RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY

Transcription

1 ICRU REPORT No. 87 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY THE INTERNATIONAL COMMISSION ON RADIATION UNITS AND MEASUREMENTS Journal of the ICRU Volume 12 No Published by Oxford University Press

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3 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Report Committee J. M. Boone (Chair), University of California Davis, Sacramento, California, USA J. A. Brink, Massachusetts General Hospital, Boston, Massachusetts, USA S. Edyvean, Public Health England, Oxfordshire, UK W. Huda, Medical University of South Carolina, Charleston, South Carolina, USA W. Leitz, Swedish Radiation Protection Authority, Stockholm, Sweden C. H. McCollough, Mayo Clinic, Rochester, Minnesota, USA M. F. McNitt-Gray, University of California Los Angeles, Los Angeles, California, USA ICRU Sponsors P. Dawson, UCL Hospitals, London, UK P. L. M. DeLuca, University of Wisconsin, Madison, Wisconsin, USA S. M. Seltzer, National Institute of Standards and Technology, Gaithersburg, Maryland, USA Consultants to the Report Committee J. A. Brunberg, University of California Davis, Sacramento, California, USA G. W. Burkett, University of California Davis, Sacramento, California, USA R. L. Dixon, Wake Forest University, South Carolina, USA J. Geleijns, Leiden University Medical Center, Leiden, The Netherlands J. P. McGahan, University of California Davis, Sacramento, California, USA S. E. McKenney, University of California Davis, Sacramento, California, USA N. J. Pelc, Stanford University, Palo Alto, California, USA J. H. Siewerdsen, Johns Hopkins University, Baltimore, Maryland, USA J. A. Seibert, University of California Davis, Sacramento, California, USA H. Winer-Muram, University of Indiana, Indianapolis, Indiana, USA S. Wootton-Gorges, University of California Davis, Sacramento, California, USA The Commission wishes to express its appreciation to the individuals involved in the preparation of this Report for the time and efforts that they devoted to this task and to express its appreciation to the organizations with which they are affiliated. All rights reserved. No part of this book may be reproduced, stored in retrieval systems or transmitted in any form by any means, electronic, electrostatic, magnetic, mechanical photocopying, recording or otherwise, without the permission in writing from the publishers. British Library Cataloguing in Publication Data. A Catalogue record of this book is available at the British Library.

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5 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndt006 The International Commission on Radiation Units and Measurements Introduction The International Commission on Radiation Units and Measurements (ICRU), since its inception in 1925, has had as its principal objective the development of internationally acceptable recommendations regarding: (1) quantities and units of radiation and radioactivity, (2) procedures suitable for the measurement and application of these quantities in clinical radiology and radiobiology, and (3) physical data needed in the application of these procedures, the use of which tends to assure uniformity in reporting. The Commission also considers and makes similar types of recommendations for the radiation protection field. In this connection, its work is carried out in close cooperation with the International Commission on Radiological Protection (ICRP). Policy The ICRU endeavors to collect and evaluate the latest data and information pertinent to the problems of radiation measurement and dosimetry and to recommend the most acceptable values and techniques for current use. The Commission s recommendations are kept under continual review in order to keep abreast of the rapidly expanding uses of radiation. The ICRU feels that it is the responsibility of national organizations to introduce their own detailed technical procedures for the development and maintenance of standards. However, it urges that all countries adhere as closely as possible to the internationally recommended basic concepts of radiation quantities and units. The Commission feels that its responsibility lies in developing a system of quantities and units having the widest possible range of applicability. Situations can arise from time to time for which an expedient solution of a current problem might seem advisable. Generally speaking, however, the Commission feels that action based on expediency is inadvisable from a long-term viewpoint; it endeavors to base its decisions on the long-range advantages to be expected. The ICRU invites and welcomes constructive comments and suggestions regarding its recommendations and reports. These may be transmitted to the Chairman. Current Program The Commission recognizes its obligation to provide guidance and recommendations in the areas of radiation therapy, radiation protection, and the compilation of data important to these fields, and to scientific research and industrial applications of radiation. Increasingly, the Commission is focusing on the problems of protection of the patient and evaluation of image quality in diagnostic radiology. These activities do not diminish the ICRU s commitment to the provision of a rigorously defined set of quantities and units useful in a very broad range of scientific endeavors. The Commission is currently engaged in the formulation of ICRU Reports treating the following subjects: Bioeffect Modeling and Biologically Equivalent Dose Concepts in Radiation Therapy Concepts and Terms for Recording and Reporting Gynecologic Brachytherapy Key Data for Measurement Standards in the Dosimetry of Ionizing Radiation Measurement and Reporting of Radon Exposure Operational Radiation Protection Quantities for External Radiation Prescribing, Recording, and Reporting Ion-Beam Therapy Small-Field Photon Dosimetry and Applications in Radiotherapy The Commission continually reviews radiation science with the aim of identifying areas in which # International Commission on Radiation Units and Measurements 2013

6 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY the development of guidance and recommendations can make an important contribution. The ICRU s Relationship with Other Organizations In addition to its close relationship with the ICRP, the ICRU has developed relationships with national and international agencies and organizations. In these relationships, the ICRU is looked to for primary guidance in matters relating to quantities, units, and measurements for ionizing radiation, and their applications in the radiological sciences. In 1960, through a special liaison agreement, the ICRU entered into consultative status with the International Atomic Energy Agency (IAEA). The Commission has a formal relationship with the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), whereby ICRU observers are invited to attend annual UNSCEAR meetings. The Commission and the International Organization for Standardization (ISO) informally exchange notifications of meetings, and the ICRU is formally designated for liaison with two of the ISO technical committees. The ICRU also enjoys a strong relationship with its sister organization, the National Council on Radiation Protection and Measurements (NCRP). In essence, these organizations were founded concurrently by the same individuals. Presently, this long-standing relationship is formally acknowledged by a special liaison agreement. The ICRU also exchanges reports with the following organizations: Bureau International de Métrologie Légale Bureau International des Poids et Mesures European Commission Council for International Organizations of Medical Sciences Food and Agriculture Organization of the United Nations International Council for Science International Electrotechnical Commission International Labour Office International Organization for Medical Physics International Radiation Protection Association International Union of Pure and Applied Physics United Nations Educational, Scientific and Cultural Organization The Commission has found its relationship with all of these organizations fruitful and of substantial benefit to the ICRU program. Operating Funds In recent years, principal financial support has been provided by the European Commission, the National Cancer Institute of the US Department of Health and Human Services, and the International Atomic Energy Agency. In addition, during the last 10 years, financial support has been received from the following organizations: American Association of Physicists in Medicine Belgian Nuclear Research Centre Canadian Nuclear Safety Commission Electricité de France Helmholtz Zentrum München Hitachi, Ltd. International Radiation Protection Association International Society of Radiology Ion Beam Applications, S.A. Japanese Society of Radiological Technology MDS Nordion National Institute of Standards and Technology Nederlandse Vereniging voor Radiologie Philips Medical Systems, Incorporated Radiological Society of North America Siemens Medical Solutions US Department of Energy Varian Medical Systems In addition to the direct monetary support provided by these organizations, many organizations provide indirect support for the Commission s program. This support is provided in many forms, including, among others, subsidies for (1) the time of individuals participating in ICRU activities, (2) travel costs involved in ICRU meetings, and (3) meeting facilities and services. In recognition of the fact that its work is made possible by the generous support provided by all of the organizations supporting its program, the Commission expresses its deep appreciation. Hans-Georg Menzel Chairman, ICRU Geneva, Switzerland

7 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndsxxx Radiation Dose and Image-Quality Assessment in Computed Tomography Preface... 1 Glossary Abstract Introduction CT Manufacturers and Model Names Basics of Computed-Tomography Technology CT-Scanner Design Scan-Acquisition Modes Axial CT Scanning Helical (Spiral) Scan Mode Repeated Scanning at the Same Table Position Dual-Energy CT Cardiac CT Scan-Acquisition Parameters and Their Effects on Image Quality Dose-Reduction Techniques Fixed Tube Current (Technique Charts) and Patient Size Automatic Exposure Control Angular and Longitudinal X-Ray-Tube-Current Modulation Adjusting X-Ray-Tube Potential Based on Patient Size Beam-Shaping Filters Image-Reconstruction and Noise-Reduction Algorithms Summary Computed Tomography in Clinical Use Introduction CT in Neuroradiology CT in Thoracic Radiology CT in Abdominal Imaging CT in Pediatric Radiology CT in Clinical Use: Summary Overview of Existing CT-Dosimetry Methods Goals of CT Dosimetry CTDI-Based Metrics Basic Tools CTDI # International Commission on Radiation Units and Measurements 2013

8 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY CTDI FDA The nt Term CTDI Weighted CTDI, CTDI w Volume CTDI, CTDI vol Limitations of CTDI vol Dose Length Product Limitations of CTDI Methods Estimation of Effective Dose CT X-Ray-Spectrum Characterization Introduction Methods for HVL Measurement Conventional HVL Assessment in CT Aluminum-Cylinder Method Real-Time Probes Aluminum Cage with Real-Time Probe Method Spectrum Assessment Using the Tube Potential and the HVL Off-Angle HVL Assessment Typical HVL Values in CT CT Output Characteristics Measured in Air Introduction Theoretical Methods for Predicting f air (z) Measurement of f air (z) Optically Stimulated Luminescence Systems TLD Measurements Film Computed-Radiography Detectors Real-Time Radiation Detectors Summary of f air (z) Measurements Measurement of f L (x) orf A (u) Measurement of f L (x) Measurement of f A (u) Planar Measurements of the CT Beam Profile Summary CT Dosimetry in Phantoms Axial Dose Profiles in Phantoms Cumulative Absorbed-Dose Distributions for Helical Scans Equilibrium Dose, D eq Dose Profile for a Single Axial Rotation Cumulative Absorbed-Dose Distribution, D L (z), for Multiple Rotations Covering a Scan Length L Phantom Design and Usage AAPM Report 111 Recommendations for Assessment of H(L) The Role of the Real-Time Radiation Meter in Measuring H(L) Measurement of h(l) in the Clinical Environment Rise to Equilibrium in 160 mm and 320 mm PMMA phantoms The Radial Dose Profile Summary Patient Size-Specific Dose Estimation

9 Contents 8.1 Introduction Absorbed Dose versus Patient Size Size Metrics Size-Specific Dose Estimates Summary Automatic Exposure Control in CT Introduction Automatic Exposure Control Angular Tube-Current Modulation Patient Dose Assessment with TCM Examples of Slice-by-Slice CT Dose Calculation Organ-Dose Estimation Summary Spatial Resolution in CT Introduction Basic Spatial-Resolution Metrics Assessment of Axial-Plane Resolution in CT Limitations and Concerns in Axial-MTF Assessment Resolution Along the z Axis Modern Resolution Metrics in CT Axial-Plane Resolution z-axis Resolution Summary Noise Assessment in CT Introduction Basic Noise Metrics The Noise-Power Spectrum, NPS(f) Demonstration of NPS Utility Noise-Equivalent Quanta, NEQ Dose-Normalized NPS(f) Summary Summary of Recommendations Radiation-Dose Assessment in CT Existing CT-Dosimetry Methods CT X-Ray-Spectrum Characterization CT Output-Related Parameters Measured in Air CT Dosimetry in Phantoms Patient SSDE Automatic Exposure Control in CT Other Considerations in Patient Dosimetry in CT Image-Quality Metrics Spatial Resolution in CT Noise Assessment in CT Future Directions Real-Time Probe Rise-to-Equilibrium Curve, H(L) Incorporation of Scan-Length Corrections to the SSDE References

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11 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndt007 Preface For nearly three decades, the ICRU has developed authoritative Reports dealing directly with radiological imaging. These include: Report 41, Modulation Transfer Function of Screen-Film Systems (1986); Report 54, Medical Imaging The Assessment of Image Quality (1995); Report 70, Image Quality in Chest Radiography (2003); Report 74, Patient Dosimetry of X Rays Used in Medical Imaging (2005); Report 79, Receiver Operating Characteristic Analysis in Medical Imaging (2008); and Report 82, Mammography Assessment of Image Quality (2009). This Report on computed tomography (CT) continues that series and is intended to advance dosimetry and image-quality evaluation in this important application. Computed tomography has experienced rapid growth in technological sophistication, and with these advancements there has been a commensurate increase in the types of clinical questions that can be addressed. In addition to profound improvements in image quality, the acquisition times for routine CT examinations have dropped from several minutes in the early era to a few tens of seconds today, opening up new clinical uses, including pediatric, cardiac, and thoracic imaging, for which organ or patient motion preclude the use of other imaging modalities. The improvement in the diagnostic information that CT provides has led to a large increase in utilization, with well over 100 million studies performed worldwide annually. CT scans involve radiation exposure, and the radiation dose levels in most cases are higher than with other radiographic examinations. The higher dose levels, coupled with the very large number of CT scans performed annually, has led to concerns about the associated radiation risks. The National Council on Radiation Protection and Measurements has reported that 48 % of the average total dose to citizens in the U.S. is from medical-imaging procedures, and of this about 49 % is due to CT. Thus, approximately 24 % of the radiation burden to the U.S. population is from CT examinations. There have been a number of dosimetric quantities used for CT since the early 1980s, and these have undergone incremental changes over the past 3 decades. It has been recognized that in light of the large population doses associated with CT, and given the improved features of modern scanners, that current radiation-dosimetry methods are out of date. Therefore, there is a need to make more accurate measurements of more relevant parameters, including those that take into consideration scanspecific parameters such as patient size and the length of the scan. One of the principal driving forces for the increased use of CT for clinical diagnosis is the phenomenal improvement in image quality that has occurred over the past 15 years. In addition to increased spatial resolution, improvements in detectors, x-ray tubes, and reconstruction algorithms have led to significant improvements in the signal-to-noise properties in CT images. These improvements challenge traditional measures of image quality. This Report seeks to amend, improve, and update the methods for both dosimetry and image-quality evaluation in CT. After reviewing current CT-dose metrics, a number of updated measurement procedures are recommended that capitalize on faster systems and on new phantom designs that allow more accurate assessment of dose in patients. Measurement procedures are introduced that allow rapid measurement of the x-ray beam in terms of both its quality and the spatial distribution of the air kerma. Updated methods for characterizing image quality, including both spatial resolution and noise performance are recommended. Overall, this Report capitalizes on recent developments in CT metrology combined with new measurement technology, with the intent of providing more accurate characterization of the dose and image-quality from modern, high-performance CT systems. John M. Boone Stephen M. Seltzer # International Commission on Radiation Units and Measurements 2013

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13 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndt004 Glossary Artifact Acquisition Acquisition channel Attenuation Automatic exposure control Axial CT the appearance in the CT image of details not present in the scanned object. process of acquiring raw data by measuring the transmission of the x-ray beam through an object. one or more electronically coupled detector arrays yielding one transmission profile. reduction in the number of photons in an x-ray beam upon passage through matter. automatic adjustment of the tube current, depending on the attenuation of the patient, to achieve a pre-determined level of image quality. the standard step-and-shoot acquisition mode of CT scanners. Also called sequential by some manufacturers. Axis of rotation axis about which the x-ray tube rotates, coincident with the isocenter. Back projection a mathematical procedure for CT reconstruction, based on projecting the detected x-ray signal back along the measurement trajectory between detector element and focal spot. Beam filtration Beam hardening Beam-shaping filter Bow-tie filter Breast computed tomography Collimation material, usually metal or plastic, placed in the x-ray-tube port that filters the x-ray beam and preferentially removes lower-energy photons, sparing some dose to the patient. the result of filtration of a polychromatic beam by the absorption of lowerenergy photons in a patient or material, with a subsequent increase in effective energy. Beam hardening can cause artifacts in CT images, so the x-ray spectrum is pre-hardened in CT to reduce beam-hardening artifacts. same as bow-tie filter. a metal filter that is placed in the x-ray-tube assembly, which is thicker at the periphery and tapers gradually to a thin filter at the center of the beam. The bow-tie filter reduces x-ray intensity incident peripherally upon the patient, and compensates for the typically round contours of the patient s body to deliver a more homogeneous beam intensity to the detector arrays. a method of examining the breast utilizing a specially designed CT scanner, where the breast hangs pendant into the field of view with the woman lying prone on the table. geometrical limitation of the extent of the radiation beam in the z direction. # International Commission on Radiation Units and Measurements 2013

14 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Computed-tomography dose index (CTDI) integral along a line parallel to the axis of rotation (z) of the air-kerma profile; CTDI 1 ¼ 1 ð 1 KðzÞdz; nt 1 Computed tomography (CT) Computed-tomography angiography (CTA) CT generation CT number Contrast Contrast agent Contrast resolution CT fluoroscopy CT number CTDI CTDI 100 where K(z) is the air kerma as a function of z, n is the number of sections, T is the nominal section thickness. a process to image anatomical information in a cross-sectional plane of the body from a computed synthesis of x-ray transmission data. a method of examining blood vessels utilizing a CT scanner and injection of iodine-containing contrast medium. indicates place in the evolution of CT technology. First- and secondgeneration CT geometry used rotate-translate motions, but all modern MDCT systems use a third-generation motion: rotate-rotate, for which the x-ray tube and detector arrays are mounted rigidly on a rotating gantry. Fourth-generation CT uses a rotating x-ray source with a full 2p ring of detectors. equivalent to Hounsfield Unit (HU). the difference in HU between adjacent regions or structures within an image, for example, HU a HU b for regions a and b. a liquid injected intravascularly prior to imaging that contains a high atomic number compound, usually iodine, to enhance vessels and vascular tissues. the ability to detect objects that are only subtly different in contrast from the background. Contrast resolution is related to the signal-to-noise ratio of the object to be detected. continuous real-time imaging by CT to guide a diagnostic or therapeutic intervention, often used for CT-guided needle biopsy. see Hounsfield Unit. abbreviation for computed-tomography dose index. CTDI calculated by integrating the air-kerma profile K(z) over 100 mm: CTDI x 100 ¼ 1 nt ð þ50 mm 50 mm KðzÞ dz; CTDI air CTDI w CTDI vol Detector Detector array where x refers to either the center or peripheral position in a standard cylindrical phantom. value of CTDI determined free-in-air, at the isocenter of the scanner. the weighted CTDI. the volume CTDI. on the CT scanner, a device that responds to ionizing radiation, converting this response to an electronic signal for subsequent digitization. More generally, a meter used to measure radiation levels. a collection of individual detectors that are typically located in an arc along the fan angle of a CT scanner. A single-detector array collects enough information during an axial (sequential) CT scan to produce one CT image. 4

15 Glossary Detector efficiency Detector element (del) Detector row Dose length product (DLP) the fraction of x-ray energy incident upon a detector that contributes to the electronic signal. a single element of a detector array. a row of detector elements, including their interspace material, arranged along an arc centered on the axis of rotation; same as detector array. a parameter used as a surrogate measure for energy imparted to the patient in a CT scan of length L: Dose profile DLP ¼ CTDI vol L: By convention, the DLP is reported in the units of mgy cm. representation of the absorbed dose or air kerma as a function of position, e.g., usually along the z axis. Effective dose risk-related quantity defined by the International Commission on Radiological Protection in Publication 60 (ICRP, 1991) as the sum of the weighted absorbed doses in all tissues and organs of the body: E ¼ X X w R w T D T ; R T Field of view (FOV) Filtered back projection Focal spot Full width at half maximum (FWHM) Gantry Helical CT where D T is the absorbed dose in tissue T due to radiation of type R, w R is the weighting factor for radiation type R, and w T is the weighting factor for tissue T. For x-rays, w R is equal to unity. The tissue weighting factors have been revised in ICRP Publication 103 (ICRP, 2007). the maximum diameter of the scanned area or reconstructed image (SFOV, scanned field of view; DFOV, displayed field of view). a mathematical procedure that reconstructs the CT images from the measured profile data in a CT scanner. The profile data are convolved with a filter function (usually performed in the spatial-frequency domain), and the entire projected data set is then backprojected to produce the CT image. the effective area on the x-ray-tube anode from which x rays are emitted. The size of the focal spot affects the spatial resolution in the CT image. interval parallel to the abscissa between the points on a curve with the value of one-half of the maximum of the curve. part of the CT scanner that, for modern third-generation systems, supports the x-ray tube, x-ray generator, collimators, and detector arrays. technique of scanning in which there is continuous rotation of the x-ray tube coupled with continuous linear translation of the patient through the gantry aperture in order to achieve volumetric data acquisition. Also known as spiral or volume CT. Hounsfield Unit the gray-scale values in a CT image, named after inventor Godfrey Hounsfield (also called CT number). The HU of a voxel m is defined as: HU m ¼ 1000 m m m w m w ; where m m and m w are the effective linear attenuation coefficients of the voxel material and water, respectively. 5

16 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Iterative-reconstruction algorithms Kernel Linear attenuation coefficient Line-spread function (LSF) Modulation-transfer function (MTF) Monte Carlo technique Multi-detector CT (MDCT) Multi-slice CT (MSCT) Noise Noise-power spectrum (NPS) Nyquist frequency Over-beaming Over-ranging Pitch a reconstruction algorithm that uses a series of successive iterations, each one becoming closer to the appearance of the object scanned. Iterative reconstruction is usually more computer intensive than filtered-backprojection reconstruction, and is thought to produce CT images with lower noise levels. see reconstruction filter. the fractional reduction in intensity per thickness of material as an x-ray beam passes through the material. the LSF is evaluated by imaging a slit in radiography or a plane of material parallel to the z axis in CT, both of which result in a line on the resulting images. The LSF is then given by image intensity (HU in CT) versus position orthogonal to the line. the MTF is the classical approach to characterizing the spatial resolution of an imaging system. It is generally computed by taking the Fourier transform of the line-spread function. a method for computing the distribution of x-ray energy deposition (other applications exist also) in objects, based on realistic simulations of photon transport using known interaction probabilities. A state-of-the-art method for estimating absorbed dose in patients or phantoms in CT procedures. a CT scanner that has multiple detector arrays; also called multi-slice CT. MDCT systems, with between 64 and 320 detector arrays, are the current state of the art in CT systems. same as multi-detector CT. variation of CT numbers from a mean value in a defined area in the image of a uniform substance, indicated by the standard deviation of the CT numbers in that region of interest. the NPS is used to characterize the noise variance as a function of spatial frequency in an imaging system. the maximum frequency, f N, that can be described by a sampled system with a sampling spacing of a, where f N ¼ (2a) 21. in multiple-detector-array CT scanners (MDCT), the effect whereby the FWHM, a, of the dose profile along the z axis exceeds the active detector width, i.e., for n detectors of width T, over-beaming is the situation for which a. nt. Over-beaming is considered necessary in MDCT systems in order to prevent artifacts. in helical (spiral) scanning, over-ranging occurs because it is necessary to scan beyond the edges of the reconstructed CT volume to produce the required images. For a scanner with a nominal beam width of nt, overranging of approximately 1 2 nt on each side of the volume is required. Over-ranging can be reduced by the use of adaptive beam collimation. for helical (or spiral) CT, the pitch, p, is the quotient of the table advance per 2p rotation of the x-ray tube, b, by the product of the number of simultaneously acquired sections, n, and the section thickness, T, i.e., p ¼ b nt : Pixel picture element of a digital image. 6

17 Post-patient collimation Profile Projection Quantitative computed tomography (QCT) Ray Reconstruction algorithm Reconstruction filter Region of interest (ROI) Rotation period Scan range Scan time Scattered radiation Section geometrical limitation of the extent of the radiation beam in the z direction by a slit device positioned between the patient and the detector. Infrequently used for thin-section imaging. a profile is a collection of rays acquired at a specific gantry angle using the detector array. The term profile is synonymous with projection or view. same as profile. the use of CT images and the corresponding HU values for quantitative characterization of organs or tissues. QCT is most widely used in the determination of bone-mineral content, lung density, and treatment planning in radiotherapy. the schematization of a narrow beam of x rays from the x-ray-tube focal spot to a single detector element, giving rise to a detector-element reading. Each view or projection is composed of numerous rays. precisely defined computational procedure to produce CT images from the acquired projection data. Filtered back projection has been used for most image reconstruction in CT; however, in recent years, iterativereconstruction algorithms have been used as well. for filtered back projection, the reconstruction filter is used to mathematically filter the projection data prior to back projection. Typically, the reconstruction filter is described in the frequency domain and consists of a ramp component combined with an apodization filter to reduce the impact of quantum noise at higher spatial frequencies. Reconstruction filters have names that vary among CT-scanner manufacturers. a region that is part of an image. The ROI is typically square or rectangular, but can be of any arbitrary shape. time duration of a single 3608 rotation of the x-ray tube and detector array (in third-generation CT geometry). Typical rotation periods for modern CT scanners range from 0.25 s to 1.0 s. the length of the body that is visualized, measured along the z axis for one volume acquisition or for a series in sequential (axial) acquisition (step-and-shoot mode). the time interval between the beginning and the end of the acquisition of data, i.e., time for either a complete spiral acquisition or for a single tube rotation in the step-and-shoot mode. x rays whose trajectories have been redirected due to a scattering event in the patient or CT hardware. Generally, scattered radiation can deposit energy inside the patient but outside of the primary x-ray beam, can be emitted into the CT scanner room, and can reach detector elements and cause artifacts or increased noise in the reconstructed CT images. in multi-slice scanning, the tomographic volume corresponding to a single image in the reconstructed CT data set. Sections can be of different thickness, usually ranging from 0.5 mm to 5 mm, and sometimes to 10 mm. CT sections are also called CT slices. Section thickness the thickness of a CT image, measured at the scanner isocenter. Thicknesses range from 0.5 mm to 10 mm on most CT systems. Also called slice thickness. Sequential (axial) CT Glossary CT-scanning technique in which images are acquired at fixed z positions interspersed by translation of the patient in the z direction. During translation, the x-ray beam is turned off. Sequential or axial CT imaging is the basic step-and-shoot acquisition method of CT scanners. 7

18 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Shaped x-ray filter Single-slice scanner Slice Slice-sensitivity profile (SSP) Slice thickness Spatial resolution Spiral CT Spread function Table feed Uniformity View Volume CTDI (CTDI vol ) same as bow-tie filter. CT scanner with a single row of detector elements, i.e., only one acquisition channel. tomographic volume corresponding to the reconstructed image; a single CT image is often called a slice. The thickness of this volume is defined by the slice thickness. relative response of a CT system along the z axis. The SSP is essentially the line-spread function of the CT scanner along z. same as section thickness. the ability to resolve fine detail in an image. see helical CT. spread functions are used to measure the spatial resolution of imaging systems, and include the point-spread function (PSF), the line-spread function (LSF), and the edge-spread function (ESF). for helical (spiral) CT scans, the distance that the patient table moves longitudinally during a 2p rotation of the CT gantry. consistency of the CT numbers in the image of an homogeneous material across the scan field. Synonymous with homogeneity. a collection of rays acquired at a specific angle by the detector array. Same as projection or profile. the weighted CTDI, CTDI w, normalized by the helical pitch, p, i.e., CTDI vol ¼ CTDI w : p Voxel Weighted CTDI (CTDI w ) volume element. an estimate of the average dose over a single slice in a CT dosimetry phantom, defined as: CTDI w ¼ 1 3 CTDIcenter 100 þ 2 3 CTDIperi 100 ; z axis where CTDI100 center or CTDI peri 100 refer to measurements of CTDI 100 at the center (center) or periphery (peri) of the head or body phantom. axis parallel to the axis of rotation. 8

19 Abstract Computed tomography has experienced a number of significant technological advances over the past decade, and these have had pronounced impacts on the accuracy of radiation dosimetry and the assessment of image quality. After reviewing CT technology and clinical applications, this Report describes and discusses existing dosimetry methods and then presents new methods for radiation dosimetry, including the evaluation of beam quality, and measurement of CT-scanner output in air and in phantoms. Many of the proposed dosemetric quantities can be measured quickly using a real-time ionization chamber, which is introduced here. Traditional measurements of image quality for computed tomography rely upon simple and subjective observations. A more rigorous approach is proposed, including routine use of the modulationtransfer function for describing spatial resolution along all axes, and of the noise-power spectrum for describing the noise amplitude and texture properties of CT images. This Report focuses on new but practical methods for the assessment of radiation dose and image quality for CT scanners. 9

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21 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds Introduction This Report centers on computed tomography (CT) scanners, which are used widely in diagnostic medicine around the world. The Report focuses on dose assessment, as well as the characterization of image quality in CT. A description of the basic technology underlying CT is provided in Section 2. The early systems, which used simple acquisition geometries requiring several seconds per slice, have evolved into modern axial (sequential) and spiral (helical) acquisition platforms that can acquire a large number of slices in one-third of a second or less. A number of different dose-reduction features have been added to CT scanners in recent years, and these are also discussed in Section 2. Section 3 describes the clinical utility of CT, described by radiologists specializing in neuroradiology, body CT, thoracic imaging, and pediatric radiology. This Section introduces the reader to a sampling of clinical applications of CT, demonstrating why this modality is used so widely and so frequently in diagnostic medicine. Absorbed-dose levels have been an emerging issue in regard to CT for the past decade or more. Sections 4 through 9 of the Report focus on various aspects of radiation dose and dose assessment, recognizing recent advancements in CT scanner design, new perspectives on the radiation dose distribution in CT, and the important issue of patient size and length of the CT scan. Section 4 describes the conventional measurements of CT-radiation dose, and is intended to familiarize the reader with traditional methods of radiation-dose assessment in CT. This Section highlights the technological baseline, and provides a context from which the many CT-dosimetry recommendations contained in this Report can be understood. This Report also introduces the use of a real-time dosimeter for evaluation of the air-kerma rate. The use of a real-time dosimeter provides capabilities in CT dosimetry that cannot be achieved using integration-mode radiation meters, and simplifies several of the proposed measurements. These new dosimeters are first discussed in Section 5. Section 5 mainly addresses measurement of the spectral properties of CT scanners, including use of the new technology of real-time ionization-chamber systems. Although the measurement of the half-value layer (HVL) in CT is generally performed infrequently, x-ray beam quality is an important property that relates to both image quality and absorbed dose in the patient. Proposed methods for HVL assessment considerably streamline previous approaches. Section 6 discusses the assessment of the x-ray output (air kerma or air-kerma rate) of a CT scanner as measured free-in-air in the absence of a phantom. Although a dosimetry phantom is an important tool in the assessment of dose in CT, the x-ray output (air kerma) is a fundamental quantity that impacts the dose in the patient during CT. In this Section, it is recognized that measuring the output characteristics of the CT scanner in the absence of a phantom can be a practical method for routine quality assurance. This Section focuses on the dose distributions in both the z dimension and along the axial or x y dimensions of the CT system. The real-time dosimeter has an important role to play in these measurements. Section 7 introduces a newly designed phantom that is long enough (600 mm) to capture the majority of the absorbed dose due to x-ray scatter that occurs in a phantom. This Section is harmonized with AAPM Report 111 (AAPM, 2010), and the phantom was designed in close collaboration with AAPM Task Group 200. With a phantom and realtime dosimeter, an asymptotic curve that represents the air kerma or absorbed dose at the center plane of the CT scan can be determined as a function of the scan length in a single measurement. This rise-to-equilibrium curve can be used to describe, in general, the dose distribution in CT under the simplified conditions of a homogeneous phantom. In all x-ray imaging modalities, including CT, the size of the patient plays an important role in x-ray dosimetry. Section 8 discusses methods by which patient size, defined as the water-equivalent diameter, can be used to adjust the value of CTDI vol reported by the CT scanner to produce a more accurate dose estimate. A quantity is introduced in this # International Commission on Radiation Units and Measurements 2013

22 RADIATION DOSE AND IMAGE QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Section called the size-specific dose estimate. This Section is well aligned with AAPM Report 204 (AAPM, 2011a), which has been endorsed by the AAPM, the ICRU, and the Image Gently campaign. Modern CT systems dynamically adjust the x-raytube current depending upon the dimensions of the patient along the length of the scan, in a procedure called automatic exposure control or x-ray-tube current modulation. In order to compute dose when x-ray-tube-current modulation is used, an imageby-image assessment of both patient size and tube current becomes necessary to achieve good accuracy. Section 9 describes the algorithms necessary for this, together with a computer program developed to illustrate the trends in dose estimates as a function of patient size and CT technical parameters. Image quality is an important characteristic of any imaging system, and is related to the associated absorbed-dose levels. In Section 10, characterization of the spatial resolution of CT scanners is discussed. Historical methods have utilized the point-spread function, line-spread function, and edge-spread function to compute the modulation transfer function (MTF). This Section also discusses the use of the MTF to characterize the spatial resolution in the z dimension, moving away from the historical use of the slice-sensitivity profile. Section 11 addresses the measurement of noise texture and amplitude in CT images. The 3D noisepower spectrum (NPS) is proposed to characterize the noise properties of CT images. The dependencies of the NPS on CT parameters such as x-raytube potential, the product of gantry rotation time and x-ray-tube current, the reconstruction kernel used, and other technical parameters are discussed. The assessment of both spatial resolution and contrast resolution is described in some cases using the CT phantom recommended in Section 7. The Report concludes with Section 12, which makes specific recommendations with respect to the characterization of both dose and image quality in CT. 1.1 CT Manufacturers and Model Names There are only a few large manufacturers of CT scanners, and there are some differences in the fundamental technology offered by these companies. In some cases, the makes and models available differ, depending on country of placement. In this Report when discussing CT characteristics, in many cases, the type of scanner (manufacturer and model) is mentioned. In doing so, there is no intent for endorsement, but rather to allow readers to understand the type of scanner that produced a specific set of data. In general, this knowledge will be more useful to readers who work in the CT field, and who are familiar with the subtle differences in the capabilities of various CT-scanner types. The manufacturers of the CT scanners mentioned in this report are listed here alphabetically: General Electric Medical Systems, Waukesha, Wisconsin. Philips Healthcare, DA Best, The Netherlands. Siemens Medical Systems, Erlangen, Germany. Toshiba Medical Systems, Irvine, California, USA. 12

23 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds Basics of Computed-Tomography Technology For the first 75 years of x-ray imaging, the detectors used in diagnostic radiology, such as radiographic film or image intensifiers, provided reasonably good visualization of high-contrast objects. However, their ability to record small differences in transmitted x-ray signals was limited. Several factors contributed to the inability to resolve low-contrast signals. First, large-area detectors record a large amount of scattered radiation, making small differences in x-ray transmission difficult to resolve. Second, the superposition of the patient s three-dimensional information onto a two-dimensional detector obscures low-contrast information. Geometrical tomography provided some separation of overlapping structures, but its utility was limited to high-contrast structures such as bones, airways, and iodinated vessels. Finally, radiographic film, intensifying (scintillation) screens, and image intensifiers can exhibit non-linearities and/or non-uniformities that are large compared with the small differences in x-ray transmission of low-contrast objects. Introduced clinically in the early 1970s, x-ray computed tomography (CT) overcame many of the difficulties encountered in using large-area detectors. First, the sequential irradiation of slabs of tissues and collimation at the detector markedly reduced the amount of scattered radiation measured. Second, the reconstruction of a tomographic image eliminated much of the problem of overlapping anatomy. X-ray CT was the first imaging modality that allowed physicians to see the internal structure of a three-dimensional object in crosssection (see Figure 2.1). With CT, the use of highefficiency, low-noise detectors that could respond linearly over a wide range of transmission values provided uniform sensitivity over a wide dynamic range, producing excellent CT images across a wide variety of clinical applications. The Radon transform introduced the concept of mathematically reconstructing the internal structure of an object from multiple projections through the object (Radon, 1917). The techniques of image reconstruction were pursued in a variety of disciplines including Bracewell s work in the 1950s in radio astronomy (Bracewell, 1956; Bracewell and Riddle, 1967). In the early 1960s, several independent investigations into the medical applications of image-reconstruction techniques were carried out (Cormack, 1963; Kuhl and Edwards, 1968; Oldendorf, 1961). However, it was not until the late 1960s and the work of Hounsfield that the first clinically useful x-ray CT scanner was developed (Hounsfield, 1973). Despite its relatively low spatial resolution, 1 CT was rapidly accepted into clinical practice because of its tomographic nature and superior contrast resolution (0.5 %) when compared with existing radiographic images (approximately 5 %). In 1979, the Nobel Prize in Medicine was awarded to Hounsfield and Cormack for their contributions to the development of x-ray CT (Hounsfield, 1980). 2.1 CT-Scanner Design CT-scanner hardware is designed to determine effective x-ray attenuation coefficients at each point within a volume of interest from transmission measurements acquired at multiple angles through the object. A set of transmission measurements through the object at a given angle is known as a projection, or view. These projection measurements are mathematically combined to form a twodimensional representation of a three-dimensional object. Figure 2.2 illustrates a single projection, which contains multiple rays (representing line integrals) through the patient, acquired as the x-ray tube rotates around the patient. The x-ray tube is used to irradiate the patient with a diverging beam of x-rays, and transmission measurements are acquired using a detector array on the opposite side of the patient. At each angular position, approximately transmission measurements (rays) are acquired (with each detector array), with a spacing of approximately 1 mm. The x-ray tube and detector array(s) rotate continuously, and the data-collection process is 1 Current spatial resolution limits are 1.0 cycle/mm for CT compared with 3.5 cycle/mm for digital radiography and 7.0 cycles/mm for digital mammography. # International Commission on Radiation Units and Measurements 2013

24 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 2.1. Sample CT images. High-spatial-resolution images can be generated in all the axial, coronal, and sagittal planes from a single data acquisition. gantry angle u, which can be described mathematically as mðx; uþ ¼ I 0 e m eff tðx;uþ ; ð2:1aþ where m eff is the effective x-ray linear attenuation coefficient for the tissues in the patient, and t is the thickness of those tissues through a path in the patient defined by the geometrical parameters x and u. It is noted that the use of the variables x and u in this Section is general, and other assignments of these terms are made in later Sections of this Report. All CT scanners also have a reference detector, which measures the x-ray-tube output when there is no anatomy in the beam path: m ref ¼ I 0 : ð2:1bþ Figure 2.2. Schematic of the transmission measurements acquired in a single projection measurement as the tube rotates around the patient. repeated (usually for the complete 3608) until a predetermined number of views of the subject are gathered to allow mathematical reconstruction of the object. Typically, data from about 1000 view angles are acquired, and this is performed by repeatedly sampling the detector arrays as the gantry rotates. The CT-scanner hardware shown in Figure 2.2 acquires a large number of transmission measurements, m, along the detector at position x and at a Basic signal processing in CT produces a projection value, P, from the measured detector information: Pðx; uþ ¼ ln m ref ¼ m mðx; uþ eff tðx; uþ : ð2:2þ The projection values P(x,u) are used in various image-reconstruction algorithms to compute the CT image. A key observation from Eq. (2.2) is that the intensity of the x-ray beam, I o, has been factored out of the equation. This means that the gray-scale value in CT images is not dependent on the intensity settings used for acquisition; however, the statistical noise in the CT image is dependent upon I 0. Another important normalization is applied to CT images after the reconstruction process. In honor of Godfrey Hounsfield s pioneering work, 14

25 Basics of Computed-Tomography Technology the Hounsfield Unit, 2 HU, is the name given to the gray-scale values in CT images. The HU is defined as: HU x;y;z ¼ 1000 m x;y;z m w ; ð2:3þ m w where the HU for a voxel located at position (x,y,z), HU x,y,z, corresponds to the measured effective linear attenuation coefficient for that voxel, m x,y,z, rescaled after being normalized to the effective linear attenuation coefficient of water, m w. Thus, the gray-scale values (CT numbers) in CT images have physical meaning and are essentially rescaled linear attenuation coefficients. With the definition given in Eq. (2.3), the HU of water is 0.0 and that of air is These are the only two materials for which the Hounsfield scale is defined and calibrated against. Since the early days of CT, a number of different CT-scanner designs have been developed. Currently, all commercial systems use a geometry in which the x-ray tube and opposing detector array are mounted onto a common frame (gantry) that rotates on a mechanical slip-ring system, which passes electrical signals across sliding metal contacts (Crawford and King, 1990; Kalender et al., 1990; Rigauts et al., 1990). Slip-ring designs eliminated inter-scan delays that were once necessary to unwind cables between successive rotations of the gantry; this development enabled the continuous gantry rotation and patient-table motion necessary for helical (spiral) CT data acquisition. The axis of rotation of the CT gantry is called the isocenter. The rotational plane of the CT gantry is perpendicular to the z axis of the system, which is typically the cranial caudal direction of the patient. In the late 1990s, a new CT design emerged for clinical use. Instead of acquiring a single ring of transmission data with each rotation of the x-ray tube, the new CT scanners were able to acquire four separate rings of data with each rotation. This was made possible by the use of multiple rows of x-ray detector arrays positioned side by side along the z axis. The most important clinical advantage of these scanners is the considerable decrease in routine scanning time while simultaneously producing thinner image sections (higher z-axis resolution), i.e., faster scans with better spatial resolution. Since the late 1990s, CT scanners have been designed with an increasing number of detector channelsorarrays.ctscannerswith4,6,8,10,16, 20, 32, 40, 64, 128, and 320 detector channels are 2 The Hounsfield Unit is not a unit in the usual sense. As it is so basic to CT imaging, this nomenclature will be retained in this Report. now in clinical use. Some scanners rapidly toggle the position of the x-ray source (by magnetically deflecting the electron beam inside the tube), forming two channels from one physical detector. It is also possible to add the signal from adjacent detector arrays together, for instance, a 64-detector array scanner with mm detector widths can be configured to acquire mm, mm, or mm channels. These systems are referred to as multiple-detector-row CT (MDCT) scanners. Although the design details become more complicated as the number of channels increases, the basic idea behind MDCT imaging remains the same. Scanners with more data channels generally offer more coverage in the z-axis direction for each rotation of the CT gantry, which results in even greater scanning speed. However, this scanner geometry also requires more divergence of the x-rays along the z-axis direction (forming a cone angle), and allows more x-rays scattered within the patient to reach the detectors, potentially creating anomalous signal information. Algorithms that take into account the cone-beam geometry and increased scatter are required on these newer CT-scanner types. In addition to the development of more numerous detector arrays with thinner detector elements, gantry rotation periods have continued to decrease. Current state-of-the-art systems have rotation periods in the range of from 0.27 s to 0.35 s per rotation. With the use of partial-scan reconstruction techniques (rotation of approximately 1808 plus the fan angle in the scan plane), this has allowed temporal resolutions per image in the range of from 130 ms to 175 ms. Application of this technology to cardiac CT is now well established. For patients with high heart rates (.70 beats/min) or irregular heart rhythms, further improvements in temporal resolution are required. One approach to this problem has been the development of a CT system equipped with two x-ray tubes and two detector arrays, placed at approximately right angles to one another. Temporal resolutions as short as 75 ms are possible on such systems, which are referred to as dual-source CT scanners. 2.2 Scan-Acquisition Modes There are two basic scan modes in CT, axial (sequential) scanning and helical (spiral) scanning. Building on these are specialized modes of scanning for perfusion, fluoroscopy, cardiac, and dualenergy imaging Axial CT Scanning In the axial scan mode, the patient table remains stationary while the tube and detector array rotate 15

26 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 2.3. Illustration of the differences between axial (a) and helical (b) scan modes. once around the patient, collecting the necessary data for image reconstruction. After one rotation, the patient table is moved along the z axis to the next position, and another set of scan data are acquired (see Figure 2.3a). This mode is also referred to as step-and-shoot scanning. If projections through the entire organ of interest (e.g., the heart or brain) can be acquired in one rotation, such as with 16 cm wide detector arrays, then no table translation is required. In single-detector row CT systems, the image thickness is determined primarily by the collimation of the x-ray beam along the z axis, and one wide detector array (e.g., 13 mm) was used to acquire different slice thicknesses such as 1 mm, 3 mm, 5 mm, 7 mm, and 10 mm thick CT slices, but not simultaneously. In MDCT scanners, the image thickness is determined by the detector-element dimensions, which on modern systems are approximately from 0.50 mm to mm along the z axis, as measured at isocenter (the physical detectors are about two times wider, the difference being the geometric magnification from isocenter to the physical detectors). In MDCT, the data from adjacent detector rows can be added together to give wider image thicknesses. This provides the flexibility to reconstruct narrow and/or wider image thicknesses from the same measured projection data set, so a range of different slice thicknesses can be acquired simultaneously Helical (Spiral) Scan Mode Helical (spiral) scanning involves continuous translation of the patient table with continuous x-ray rotation and data collection (see Figure 2.3b). This decreases overall scan time, and can allow scanning of the entire adult torso within a breath hold. Helical scanning also allows for reconstructions of overlapping slices at any z-axis position. For an MDCT scanner with n arrays that have a thickness T (at isocenter), the beam width a as measured at the isocenter is given by a ¼ nt þ z; ð2:4þ where z is the over-beaming that is necessary in MDCT systems. The z portion of the beam corresponds to the width of the penumbra on both sides of the active beam, which extends beyond the edges of the active detector arrays (nt) to reduce artifacts in helical scanning. With a helical CT scanner, the ratio of the table feed b (a distance) per full gantry rotation (i.e., 3608) to the beam width is defined as the pitch, p, thus p ¼ b nt : ð2:5þ In helical scanning, extra rotations of data acquisition are required at the beginning and end of the helical scan in order to provide sufficient data for image reconstruction at the edges of the prescribed scan range. This is referred to as over-ranging. For CT scanners with wider detector arrays (40 mm to 160 mm), a significant amount of extra irradiation beyond the prescribed scan volume can occur. Scanner manufacturers have addressed this by using adaptive z-axis collimators (see Figure 2.4), which open and close at the beginning and end of the scan to shield the patient from unnecessary radiation (Christner et al., 2010; Deak et al., 2010). With all other technique factors held constant, the use of larger pitch values in helical scanning will reduce patient dose; the average absorbed dose for a given scan volume can be shown to be inversely proportional to pitch. Although the dose is decreased, there is a penalty in terms of loss of image quality (see Table 2.1). The penalty depends on whether the scanner has a single detector row or is a MDCT system. In single-detector-row CT, as the pitch is increased, the data sampling along z is more sparse, and the resultant image is wider ( poorer z-axis resolution). Image noise is not affected, however, as the same number of projections is always used to form an image. MDCT scanners use spiral interpolation algorithms that are different than those in single-detector-row CT and take advantage of the multiple rings of transmission data. For MDCT scanners, the width of the section 16

27 Basics of Computed-Tomography Technology Figure 2.4. Adaptive collimation in helical CT. For helical CT scanning without adaptive z-axis beam collimation (left), half of the x-ray beam width at both ends of the scan is not used because those projections do not have sufficient angular sampling for image reconstruction, resulting in unnecessary absorbed dose in the patient. With adaptive beam collimation, collimators are used to eliminate patient exposure at the edges of the scan, reducing the absorbed dose in the helical scan mode, especially for short scan ranges or wide beam widths. sensitivity profile (i.e., image thickness) remains relatively constant as the pitch changes. However, with all other technique factors held constant, such as occurs using a constant value of the product of tube current, J, and tube-on time per rotation, t, corresponding to a constant mas -setting, 3 image noise will increase as pitch increases. This is because the number of projections that can be used while still maintaining the prescribed image thickness decreases as pitch increases. However, some MDCT scanners automatically adjust the photon fluence, that is, Jt, to compensate for changes in the pitch setting, and therefore image thickness, noise, and absorbed dose remain constant as pitch is varied. This approach allows the scanner operator to adjust pitch as needed, without having to calculate and make the compensatory changes in Jt to maintain image-noise levels. The ratio of Jt to pitch is referred to as the effective mas or mas /slice, depending on the scanner manufacturer (AAPM, 2011b). 3 During the development of CT scanners, certain jargon has been established in which the product of the tube current, J, and the tube-on time per rotation, t, is referred to as the mas. Although such a variable as this product should not be named using unit symbols (which symbols, in this case, should correctly be written as ma s), the use of mas appears to be so entrenched that it will occasionally be used in this Report to avoid terms that might be obscure to the practitioner. A similar issue concerns using kv to indicate the value of the accelerating potential, V, for the x-ray tube (which is commonly expressed in units of kv). When needed, these quantities will be termed mas setting and kv setting, which correspond to displays on most scanners. Table 2.1. Effect of increased pitch. Scanner type Tube current Dose a Image noise Repeated Scanning at the Same Table Position Image thickness Single-detector Constant Reduced Constant Larger row Multi-detector Constant Reduced Increased Constant row Multi-detector Increased Constant Constant Constant row b a As represented by the volume CT dose index (AAPM, 2008; IEC, 2009; McNitt-Gray, 2002). b Tube current, J (ma setting), adjusted as pitch, p, is changed to yield the same effective photon fluence, Jt ( mas setting), where the effective fluence is defined as Jt/p. CT fluoroscopy is used to guide interventional procedures, such as the placement of biopsy needles to extract tissue samples for the assessment of pathology. This near-real-time procedure is useful for providing visual feedback for needle guidance. The CT perfusion study is used with an intravascular injection of an iodine-based contrast agent, and a quantitative assessment of contrast kinetics is made by scanning the same region for a relatively long period of time, which depends on the organ or tissue of interest. Scan times of about 40 s are typical for brain perfusion imaging, although scans up to 3 min in duration can be necessary in abdominal organs. In both of these scan modes, the 17

28 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY table is stationary and the same region of the patient is repeatedly scanned, resulting in the buildup of absorbed dose in the tissues within and around the scanned volume. In these acquisition modes, it is typical to operate the scanner with a lower tube current, as very high absorbed doses can result from these repetitive scanning procedures Dual-Energy CT Dual-energy CT scanning more easily allows the delineation of regions in the patient corresponding to different densities and mean atomic number, such as bone, iodine, or soft tissue. The acquired dual-energy CT images are processed such that subsequent computer-based enhancement or elimination of certain tissue types is accomplished. An example would be subtracting out the bones in a neck CT angiogram to allow the physician to better evaluate the vasculature without having it obscured by overriding boney anatomy. Equation (2.3) defines the relationship between the CT number and the effective linear attenuation coefficient, and it is the differences in how m eff decreases for higher-energy x-ray spectra that allows discrimination of materials of different atomic number. Dual-energy scanning requires the acquisition of two sets of projection data, each of which contain a sufficient number of projections for image reconstruction. One set is acquired at a high x-ray-tube potential, V, (e.g., 140 kv) and the other at a lower x-ray-tube potential (e.g., V ¼ 80 kv). From either the reconstructed images or the raw projection data, the effective atomic number of the tissue composition can be differentiated from the material density. The reason for this is that the CT number of any voxel is a rescaled measure of the linear x-ray attenuation coefficient [Eq. (2.3)]. Thus, the same amount of x-ray attenuation (i.e., the same CT number) can be obtained for two different materials (e.g., iodine and bone) in typical single-energy CT scanning, if the densities of the materials compensate for the differences in atomic number. In dual-energy CT, the projection data acquired at the two x-ray tube potentials provide the information needed to assess what fraction of the x-ray attenuation is due to the material composition (atomic number) and what fraction is due to mass density. The dual-energy concept was initially described by Godfrey Hounsfield in 1973 (Hounsfield, 1973), and was subsequently explored by several investigators (Alvarez and Macovski, 1976; Kalender et al., 1986) decades ago. Widespread clinical applications of dual-energy CT did not emerge until approximately 2007 (Johnson et al., 2007; Primak et al., 2007). Some models of Siemens CT scanners have two x-ray tubes and detector arrays, and these allow simultaneous acquisition of low- and high-v data. Other manufacturers have developed single x-ray tube systems that are capable of rapidly switching the tube potential in order to acquire low- and high-v data in one rotation of the gantry. In switched-potential systems, the x-ray pulse duration can be adjusted to balance the x-ray intensity levels between the low- and high-v pulses. In the future, it is anticipated that photoncounting detector systems will be developed for CT; such systems will differentiate detected photon energy into several energy channels, and thus dualenergy scanning can be performed without switching x-ray-tube potential. Dual-energy CT scanning can be used also to estimate so-called monoenergetic images, which are mathematical combinations of the high- and low-v scans that approximate the CT image that would be produced with a monoenergetic x-ray beam (instead of the polyenergetic spectra that were actually used). Dual-energy CT imaging also allows the correction for beam-hardening artifacts. Beam hardening occurs as a polyenergetic x-ray spectrum passes through a thick, dense structure such as the bones in the skull (see Figure 2.5). As the x-ray beam traverses the tissue, the overall x-ray fluence is of course reduced, but there is also a shift in the shape of the x-ray spectrum as lower-energy x-ray photons are absorbed preferentially as a function of depth relative to higher-energy photons. This occurs because, in general, the effective linear Figure 2.5. Beam hardening. Three x-ray spectra, all produced at 120 kv, are shown, corresponding to the spectra at different points along the x-ray beam path in CT. These spectra are interpolated measured data, and the energy resolution was not sufficient to resolve the individual characteristic x-ray peaks. Beam-hardening artifacts occur if the reconstruction algorithm does not take beam hardening into consideration (see inset, arrows point to a dark region in the brain resulting from beam hardening). 18

29 Basics of Computed-Tomography Technology attenuation coefficient is higher at lower x-ray energies. This process causes m eff in Eq. (2.1a) to vary as the x-ray beam passes through the patient, creating slight errors in the CT numbers on the reconstructed CT images. Artifacts that occur in the image, often adjacent to highly attenuating structures, are referred to as beam-hardening artifacts Cardiac CT Initially, CT imaging of the coronary arteries was accomplished with unique CT scanner designs, for example, electron-beam CT. These systems were not, however, widely available. Cardiac CT became more feasible clinically with the advent of four-detector-row CT scanners. The technique required that the CT scan continuously throughout the cardiac cycle and the table be translated slowly along the z axis, such that every z-axis position was imaged during every phase of the cardiac cycle. The ECG trace was recorded simultaneously with the CT projections. This data redundancy was required because the reconstruction algorithm sorted through the acquired data to determine which projection data were appropriate to reconstruct a CT image at a given z position at a given phase in the cardiac cycle. This approach, referred to as retrospective gating (see Figure 2.6a), was very dose inefficient compared with non-cardiac CT exams. With 16- and 64-detector-row scanner technology, the use of ECG-based tube-current modulation became common, whereby the tube current was reduced by a factor of 5 or more during those phases of the cardiac cycle in which image reconstruction was not anticipated (Jakobs et al., 2002). In this manner, ventricular and valve function could still be assessed over the entire cardiac cycle using the Figure 2.6. In retrospective gating (a), the x-ray beam is continuously on throughout the cardiac cycle, irradiating the patient much longer than with prospective triggering (b), in which the x-ray beam is turned on only for short periods of time during the phase of interest within the cardiac cycle. noisier, reduced-dose projection data, while the quality of the coronary angiogram was maintained during the full-dose portion of the cardiac cycle. This strategy evolved further to eliminate the constant motion of the patient (and table) through the gantry, using axial prospectively triggered acquisitions (see Figure 2.6b), in which the tube current was shut off in synchrony with the ECG signal during the scan, and also between table movements (Hsieh et al., 2006;Stolzmann et al., 2008).Wider detector coverage, up to 160 mm for some systems, also became available, such that the entire heart could be imaged in one beat (Einstein et al., 2010; Goma et al., 2011; Rybicki et al., 2008). With dual-source CT scanner technology, a highpitch mode (so-called flash scan mode, pitch of 3.4, Siemens Healthcare) was developed to image the entire heart in one beat using approximately 40 mm detector coverage (Achenbach et al., 2010; Flohr et al., 2009; Lell et al., 2009; McCollough et al., 2009). For stable heart rates below approximately 65 beats/min, high-pitch scanning enabled a reduction in the estimated effective dose from approximately 12 msv using 64-detector-row technology (Hausleiter et al., 2009) to below 1 msv (Achenbach et al., 2010; Raff et al., 2009; Stolzmann et al., 2008). 2.3 Scan-Acquisition Parameters and Their Effects on Image Quality CT image quality can be predictably affected by several scan-acquisition parameters. These parameters include x-ray-tube potential, V (typically in units of kv), tube current, J (typically in units of ma), rotation time, t (typically in units of s), pitch, p, reconstructed CT image thickness, beam and detector collimation, and scan mode. The typical range of x-ray-tube potentials provided in CT systems is approximately from 80 kv to 140 kv. Within this range, the effective linear attenuation coefficient for many tissues changes substantially. Although the use of lower V settings to improve soft-tissue contrast has been recommended (Huda et al., 2000a; 2000b), this approach can lead to fairly severe beam-hardening artifacts, even in small children (Cody et al., 2004). Higher V (130 kv to 140 kv) is often used in CT imaging of the bodies of very large patients. Contrast resolution (i.e., the ability to distinguish lesions differing only slightly in HU values) is strongly dependent on CT-image noise. Noise is the pseudo-random visual pattern of CT numbers observed in a CT image of a uniform object such as a water-filled cylinder. The so-called root-mean-square 19

30 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY (RMS) noise can be determined on a CT image by computing s ¼ sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi P n 2 i¼1 HU i HU ; ð2:6þ n 1 where s is the RMS noise, and HU i corresponds to the CT number in each of n voxels in a region with a mean voxel value of HU (mean CT number). A simple software tool to calculate RMS noise in a user-defined region of interest is commonly available on all current CT scanners and on image-review workstations. Image noise cannot be measured accurately in patient images (due to the presence of tissue heterogeneity) unless regions of known homogeneous tissue composition are present, such as urine in the bladder or blood in large arteries with no contrast agent present. Noise is routinely measured on phantoms of uniform composition. The image noise in a CT image is affected by the reconstruction methods used for computing the CT image from the raw projection data, and in general the reconstruction process tends to add noise correlation to the reconstructed image. The correlation structure of CT image noise can be characterized by computing the noise-power spectrum, and this will be discussed in more detail in Section 11. Despite the influences of reconstruction methods in CT images, image noise is principally a function of the photon counting statistics of the individual transmission measurements, which are a function of the photon fluence measured at the detector elements during the scan. Thus, in CT scanning, anything done to increase the number of photons reaching the detector will in general result in lower image noise and better contrast resolution. Another factor that directly affects image noise, and thus affects contrast resolution, is the thickness of the reconstructed CT image t. If the image thickness is reduced by a factor of 2, (e.g., from 5 mm to 2.5 mm), then p ffiffiffi the CT image noise increases by a factor of 2 (or about 40 %), because only half of the x-ray photons contribute to the image in that case. In MDCT scanners, the detector configuration implemented during the scan acquisition will define the range of CT image-thickness values that are available for retrospective CT image reconstruction. For example, if a CT scan protocol on a 64-slice MDCT system calls for the acquisition of 64 rings of transmission data, mm thick, then this finely sampled data can be used (after the scan) to retrospectively reconstruct thicker images such as 1.25 mm, 2.5 mm, or 5.0 mm thick images. Thus, several sets of image data can be reconstructed having different image thicknesses with no additional scanning necessary, and hence no additional absorbed dose in the patient. If, however, the CT-acquisition protocol is set to acquire eight 5.0 mm thick rings of transmission data, retrospective generation of thinner CT images would not be possible. Although the thinner 1.25 mm images convey more spatial resolution along the z axis, they are substantially noisier than corresponding 5.0 mm thick images for the same acquisition parameters. 2.4 Dose-Reduction Techniques Modern dose-management strategies in CT imaging recommend that the appropriate radiation fluence level be used for the specific patient thickness and the specific diagnostic task for which the scan was ordered. Unlike film-based radiographic imaging, a CT image never appears over-exposed or underexposed in the sense of being too dark or too light. The normalization of the acquired CT projection data [Eq. (2.2)] factors out the incident beam intensity used during acquisition, resulting in uniform gray scale images for low-dose and high-dose images alike. As a consequence, CT technologists do not receive the feedback on technique selection that was available in radiography during the screen-film era. Therefore, the CT operator needs to consider patient size when selecting parameters that affect absorbed dose and image quality, the most basic factor being the photon fluence used to acquire the scan, which is most commonly adapted by adjusting the tube-current time product, Jt (ma s) (FDA, 2002; Linton and Mettler, 2003) Fixed Tube Current (Technique Charts) and Patient Size For most CT applications, it is common to standardize the tube potential and gantry rotation time: the fastest rotation time is typically used to reduce motion artifacts and the lowest plausible tube potential is selected to maximize image contrast, provided that the tube-current limits are adequate to provide sufficient photon fluence (Funama et al., 2005; Huda et al., 2002a; McCollough et al., 2006; Nakayama et al., 2005; Siegel et al., 2004). Thus, x-ray tube current, J, is the primary parameter used to account for patient size (see Section 8). When all other parameters are kept constant, I has a linear relationship with detected x-ray fluence rate, i.e., _mðx; uþ ¼k 1 J, and the product of tube current, J, and exposure time, t has a linear relationship with detected x-ray fluence; mðx; uþ ¼k 2 Jt, where k 1 and k 2 are constants of proportionality 20

31 Basics of Computed-Tomography Technology that depend on numerous scanner and technique factors. Tube current is typically adjusted to patient dimensions based on the overall attenuation of the anatomy of interest. Weight is used in some settings to adjust tube current, although weight is less useful than actual physical dimensions as a quantity to adjust for x-ray attenuation (Boone et al., 2003; McCollough et al., 2002; Wilting et al., 2001). Importantly, when considering CT images acquired across a range of patient sizes, it has been shown that radiologists do not find the same image-noise level acceptable for all patient sizes (Wilting et al., 2001). Radiologists tend to require lower image noise in children relative to larger patients because children often lack adipose tissue between organs and tissue planes and have smaller anatomic dimensions (Boone et al., 2003; Kalra et al., 2004; McCollough et al., 2002; Wilting et al., 2001). For body CT imaging, it has been found that a reduction in Jt by a factor of from 4 to 5 from adult techniques is generally acceptable in infants, although for obese patients, an increase of at least a factor of two is required (McCollough et al., 2002). To achieve sufficient exposure levels for obese patients, the tube current can be increased, the gantry rotation period can be increased, or the pitch can be decreased (at constant Jt setting) Automatic Exposure Control Modern CT systems have the capability to adjust the x-ray-tube current in response to variations in patient attenuation (Gies et al., 1999; Haaga et al., 1981; Kalender et al., 1999; McCollough, 2005). Methods of adapting the tube current to patient attenuation, known generically as automatic exposure control (AEC), are analogous to AEC methods (also called photo-timing) in general radiography, and in CT have demonstrated substantial reductions in absorbed dose when image quality is appropriately specified. An exception to this trend occurs with obese patients, in which the radiation output of the system is increased under most AEC system scenarios to ensure adequate image quality. In obese patients, much of the additional x-ray energy is absorbed by excess adipose tissue, a relatively radio-insensitive tissue. In obese patients due to x-ray attenuation by peripheral adipose tissues, absorbed doses in internal organs are slightly reduced at the same tube current time product compared with thinner patients (Schmidt and Kalender, 2002). AEC is a broad term that encompasses not only tube-current modulation (see Section 3), but also refers to overall technique selection according to patient size in order to achieve appropriate image quality for the diagnostic task. The specific implementations of AEC differ by the manufacturer. Practically speaking, acceptable noise levels can change across patient-size ranges, and so sizebased technique charts are sometimes used to prescribe the AEC parameters (Kalra et al., 2004; 2005; McCollough et al., 2006; Nyman et al., 2005; Wilting et al., 2001) Angular and Longitudinal X-Ray- Tube-Current Modulation Angular tube-current modulation addresses (see Section 9) variation in the x-ray attenuation path within a scan plane, for example, the differences in the anterioposterior (AP) and lateral dimensions of the patient at a particular location along the z axis of the patient. The tube current is varied as the x-ray tube rotates around to the patient, with higher current used for thicker projections and lower current for thinner projections through the patient s anatomy. Attenuation information is determined from the previously acquired CT localizer view, or on some systems the projection measurement acquired 1808 before the currently acquired projection is used to modulate the tube current level; for a 0.30 s gantry rotation period, that requires dynamic (150 ms) modulation hardware. X-ray-tube-current modulation along the z axis of the patient takes into account variations in attenuation among different regions (e.g., shoulders versus abdomen) by varying the average Jt along the patient s long axis. To achieve the right compromise between image quality and absorbed dose, the parameters that influence tube-current modulation, which are scanner-manufacturer dependent, must be clearly communicated by the manufacturer and properly chosen by the user. Both angular and z-axis tube-current modulation are effective methods of achieving CT dose reduction Adjusting X-Ray-Tube Potential Based on Patient Size Several investigators have studied the use of lower-tube-potential CT imaging to improve image quality or reduce absorbed dose. The principle behind lower-energy imaging is that the attenuation coefficient of iodine increases as photon energy decreases toward the iodine K-edge energy of 33 kev. In CT exams involving the use of iodinated contrast media, the superior enhancement of iodine at lower tube potentials improves the conspicuity of hypervascular or hypovascular pathologies. However, images obtained using lower tube potentials tend to be much noisier, mainly due to the higher absorption of low-energy photons by the 21

32 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY patient, unless the tube current is adequately adjusted (FDA, 2002; Funama et al., 2005; Haaga et al., 1981; Huda et al., 2000a; Kalender et al., 1999; McCollough, 2005; Nakayama et al., 2005; Siegel et al., 2004). The x-ray tube output (for instance, the measured air kerma at isocenter) changes non-linearly as a function of V, when other parametersareheldconstant(seefigure2.7).ingeneral, there is a power-law function that describes x-ray tube output as a function of x-ray-tube potential, V: K air ¼ aðvþ b ; ð2:7þ where K air is the air kerma at isocenter, a a coefficient, and b the parameter of interest here. As seen in Figure 2.7 for four CT scanners from different manufacturers, the exponent b ranges from 1.8 to 2.6. As a generalization, b increases with increasing added filtration in the x-ray beam, and that is why the curves in Figure 2.7 have decreasing overall output levels as the value of b increases. The optimal and most dose-efficient tube potential is dependent on the patient size and diagnostic task (McCollough, 2005), considering the contrast-to-noise ratio in tissues with and without contrast agent (Yu et al., 2010) Beam-Shaping Filters CT scanners generally use a greater amount of beam filtration than x-ray systems used for radiography or fluoroscopy in order to reduce the beam hardening that occurs as the beam passes through the patient. The tube assembly for modern CT scanners usually has between 1 mm and 3 mm aluminum filtration with an additional flat filter of 0.1 mm copper, giving a total filtration of between 6 mm and 9 mm of aluminum equivalent. As x-ray tube and generator technology has advanced, allowing higher peak power levels, additional filtration can be used without limiting the ability of the system to achieve the necessary x-ray fluence rates forfastctscanningprotocols.mdctscannersalso make much more efficient use of the x rays that are produced because of the larger beam widths that are used. Compared with a single-detector-row CT scanner with a 5 mm beam width, an MDCT system with a 40 mm beam width (i.e., nt ¼ 40) is eight times more efficient in terms of usable photon fluence rate per x-ray-tube power. Because most body regions that are scanned in clinical CT are approximately cylindrical, the x-ray path length is smaller at the periphery of the patient relative to the center. If uncompensated, the x-ray fluence reaching the detectors corresponding to the periphery of the patient would be much greater than at the center of the patient. To compensate for this, the x-ray beam in CT scanners is attenuated more at the periphery and less at the center. These bow-tie or wedge filters reduce unnecessary patient absorbed dose by matching the filter shape to the patient size and clinical application. Most CT systems have two or three different bow-tie filters, which are selected based on patient size. In cardiac CT, the region of interest is centered within the thorax, and therefore the x-ray fluence can be substantially reduced outside the cardiac volume of interest using an appropriately designed bow-tie filter, with no loss of diagnostic information. The use of beam-shaping filters on CT scanners heightens the importance of properly centering the patient in the scan field. Figure 2.7. The x-ray tube output [expressed as the air kerma (mgy) measured at the isocenter of the scanner per Jt (ma s) as a function of tube potential, V (kv)] for four manufacturers. Curve A: General Electric VCT; curve B: Siemens Definition; curve C: Toshiba Aquilion 16; and curve D: Philips Brilliance 16. The value of the exponent b is shown with each curve, ranging from 1.8 to 2.6. These curves illustrate the non-linear relationship between tube potential and x-ray tube output in CT systems Image-Reconstruction and Noise-Reduction Algorithms Iterative reconstruction and algorithms such as projection- or image-based noise reduction are currently being introduced to help users reduce absorbed doses in CT. In iterative reconstruction, an initial estimate of the truth (i.e., the object being imaged) is generated from the acquired projection data. This is typically done using conventional filtered-back-projection reconstruction methods, which are very fast. From this initial estimate, the system performs a forward projection mathematically from the initial estimate of truth. This step can address scanner-specific geometrical and x-ray properties such as detector spacing and 22

33 Basics of Computed-Tomography Technology focal-spot distribution. The algorithm might also include a model of the quantum noise (i.e., Poisson distribution). The forward projection data are compared with the originally measured projections, and the differences are used to update the estimate of the truth. This process is repeated (iterated) until the differences between the actual and simulated projections are acceptably small. This technique can produce images that more closely resemble the scanned object, and, in particular, noise and artifacts can be reduced substantially and spatial resolution improved, leading to the potential for absorbed-dose reduction. Iterative-reconstruction methods or other image noise-reduction techniques do not, by themselves, reduce absorbed dose in CT scanning. Rather, by improving the image quality through noise reduction, the technical factors that affect absorbed dose (tube potential and current, pitch, etc.) can be adjusted to realize excellent image quality at reduced dose levels. In contrast to iterative-reconstruction methods, which form an image from the projection data, noise-reduction techniques can be used to reduce noise levels in the projection data (Funama et al., 2011; La Riviere, 2005; La Riviere et al., 2006; Li et al., 2004; Manduca et al., 2009; Silva et al., 2010; Wang et al., 2006) or on the reconstructed CT images (Bittencourt et al., 2011; Tipnis et al., 2010). These approaches can reduce noise, but do not in themselves reconstruct an image and do not reduce artifacts or improve spatial resolution. 2.5 Summary CT technology has evolved over four decades to the point at which CT is one of the most widely used diagnostic imaging examinations performed. Its rapid scan time and isotropic resolution provides excellent anatomical detail, and - with the use of dynamic imaging and contrast-medium injection - functional physiological information such as regional blood volume and tissue perfusion can be assessed. Because CT entails more absorbed dose than radiography, there have been a number of recent efforts to reduce the radiation levels in clinical CT scanning. 23

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35 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds Computed Tomography in Clinical Use 3.1 Introduction Since its introduction in 1972, computed tomography (CT) has become an integral diagnostic tool of modern medicine. According to national surveys of CT use, it is estimated that approximately 70 million CT examinations are performed per year in the USA (Brenner and Hall, 2007), and the use of CT in Europe and Asia has experienced large increases as well. Current scanners are capable of rendering sub-millimeter-resolution images of the entire body in a matter of seconds. With the increasing use of picture archiving and communication systems, teleradiology, and voice-recognition software that facilitate rapid image dissemination and interpretation, CT has become an especially vital component of patient evaluation for a large number of diagnostic settings. In this Section, some of the clinical applications of CT in the several sub-specialty fields of radiological imaging are presented. The development of multi-detector CT in 1998 was a major step forward in CT technology. The sub-second rotation time of the scanners, the slip-ring technology that enabled helical (spiral) acquisition, coupled with the ability to produce a set of CT images in a single rotation has made it possible to scan large areas of the body in a single breath hold. Multi-planar reconstructions and three-dimensional (3D) images of excellent quality can be produced, which can be of great benefit in many clinical situations (Hu, 1999). 3.2 CT in Neuroradiology The first clinically available CT scanners were head CT scanners only. The introduction of clinical CT brain imaging led to an immediate and permanent transformation of the clinician s approach to adults and children with suspected neurologic disorders. With this tool, physicians could, for the first time, obtain an accurate structural image of the brain, demonstrating not only its contour, but also differentiating regions of normal and abnormal attenuation within the brain parenchyma itself. And, importantly, the imaging process could be accomplished in a manner that was rapid, entirely noninvasive, relatively low in cost, and eventually, widely available. The tool was also free of immediate risk, and was entirely pain-free. In the four decades since 1972, technological developments relating to CT-beam generation, detector technology, image-reconstruction algorithms, and computer-processing capabilities have dramatically improved image resolution and the utility of brain CT imaging. These improvements have resulted in greater spatial resolution and improved attenuation-related differentiation of brain structural components, both for normal and for abnormal brain tissue. In a separate manner, the development of intravenously administered iodinated contrast agents has enabled even more precise tissue-differentiation capabilities during CT imaging, based on differential contrast penetration through the vascular endothelial wall (see Figure 3.1). In the past decade, the dramatically increased speed of current CT-image acquisition, in association with contrast administration, has enabled the dynamic acquisition of image data that enables the quantification of normal or abnormal vascular perfusion of brain tissue. The combination of imaging speed and contrast administration has also allowed for CT angiography, enabling a precise anatomic depiction of the arterial and venous vascular structures of the head and neck. For patients with suspected brain dysfunction relating to trauma, stroke, tumors, infectious processes, or developmental abnormality, CT imaging is usually the first and most useful imaging tool. This same imaging technology is generally preferred for the characterization of soft tissues and osseous structures of the facial region, and for imaging of osseous components of the cervical, thoracic, and lumbar spine. In an emergency-room setting, brain CT imaging can generally be completed within from 2 min to 3 min, providing the physician with critical information regarding the presence or absence of trauma-related intracranial hemorrhage or mass effect (see Figure 3.2). Skull and facial fractures # International Commission on Radiation Units and Measurements 2013

36 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 3.1. Images from a 42-year-old with the new onset of seizures. Axial CT slices without contrast (left) could be interpreted as normal. Following contrast administration (right), there are enhancing foci due to metastatic melanoma (arrows). Figure 3.2. Images from a 27-year-old with head trauma. Axial images demonstrate an epidural hematoma over the surface of the brain (double white arrows) with mass effect manifest by a shift of the midline septum pellucidum from right to left (single white arrow). A hemorrhagic cerebral contusion is deep to the hematoma (double black arrows), and scalp hematoma is present (single black arrow) outside of the skull. are identified immediately. In patients with suspected stroke, early subarachnoid hemorrhage can be identified. Areas of early ischemic stroke, not associated with hemorrhage, might not be demonstrable on routine axial CT images during the first several hours, but can be identified on CT brainperfusion studies performed with a few extra minutes of workstation-based processing of dynamic brain CT images obtained following the intravenous administration of iodinated contrast. Magnetic resonance diffusion imaging is often correlated with initial CT imaging for the rapid clinical characterization of potential areas of early non-hemorrhagic stroke. In patients with more prolonged or recurring symptoms of abnormal neurologic function, CT imaging can be performed both prior to and/or following the intravenous administration of iodinated contrast agents. In these situations, the radiologist and referring physician might be concerned with the potential presence of an extremely broad number of disorders, such as an underlying primary or metastatic tumor (see Figure 3.1), a degenerative disorder such as Alzheimer s disease, or the presence of a chronic brain alteration associated with prior trauma or stroke. CT imaging of the spine is useful when there has been significant trauma, or when there are symptoms of suspected spinal-cord or nerve-root dysfunction. Although cross-sectional images of the spine provide excellent anatomic detail, contiguous thin-cut axial slices can be reformatted almost 26

37 Computed Tomography in Clinical Use Figure 3.3. Images from a 44-year-old with upper and lower extremity paralysis following trauma. (a) Axial CT images demonstrate a burst fracture of the C6 vertebral body (black arrow) with spinal-canal narrowing (white arrow). (b) These findings are more clearly demonstrated on reformatted sagittal images. instantaneously into coronal, sagittal, oblique, or 3D images, which provide an optimal anatomic characterization for referring physicians (see Figure 3.3). Lumbar-spine CT imaging is often used to demonstrate the presence or absence of disc protrusion (see Figure 3.4), to show narrowing of the spinal canal that can be associated with degenerative or congenital disorders of the spinal column, or to characterize congenital or acquired disorders of the spinal cord. Such imaging can be accomplished without or with the injection of a contrast agent into the cerebrospinal fluid space that normally surrounds the nerve roots and spinal cord within the spinal canal. In patients with suspected skull-base lesions, and in those with suspected tumors or infections involving the neck or facial region, CT imaging is generally performed with intravenous contrast administration. Its purpose is to characterize the site of origin, the presence of regional extension, and the presence or absence of regional lymphatic or other metastatic involvement. Thin-slice, highresolution CT imaging allows a precise characterization of regional anatomy, including fascial planes. The value of coronal and sagittal reformatted images is often additive. On the basis of patient age, regional soft tissue, and/or bone extension, tissue attenuation, and the pattern of tissue and lymph-node enhancement, a relatively narrow Figure 3.4. Images from a 35-year-old with back and left-lower extremity pain. Axial CT image from a lumbar-spine CT study shows a left paramedian disc protrusion at the L4 L5 disc space. The disc margin (double arrows) is indenting the spinal canal and the originating left L5 nerve-root sleeve. The normal originating right L5 nerve-root sleeve is unaffected (single arrow). differential diagnosis of the underlying pathological process can generally be established. For mass lesions involving the skull base, face, or neck, CT imaging is an indispensable complement to the 27

38 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 3.5. Images from a 58-year-old with a lump in his neck. Axial images through the lower facial region demonstrate a poorly marginated right-sided oropharyngeal squamous-cell carcinoma (double arrows) with extensive regional lymph-node metastases (single black arrow). Figure 3.6. Axial chest CT scan with contrast on a 62-year-old male following a motor-vehicle accident. The image shows rupture of the aorta (arrow) in the most common location, at the aortic arch. There is a substantial collection of blood in the mediastinum. physical examination, which is generally constrained to an inspection or palpation of regional cutaneous and mucosal surfaces (see Figure 3.5). 3.3 CT in Thoracic Radiology In the emergency department, the most common indications for obtaining a chest CT include trauma and chest pain (Larson et al., 2011a; 2011b). In patients with trauma, CT imaging can show significant critical injuries such as aortic rupture, tension pneumothorax, pulmonary laceration, hemorrhage, and airway and esophageal injury (see Figure 3.6). All of these findings require immediate intervention. In patients with chest pain and shortness of breath, the scope of diagnoses is vast. CT can pinpoint the cause to be pulmonary embolism, pneumonia, or pulmonary edema (see Figure 3.7). In some instances, pleural or pericardial disease, for example empyema (infected pleura) or pericarditis, can be the cause of the chest pain. Cardiac CT for coronary-artery disease in many medical centers is performed on a non-emergent basis, and not in the emergency department. Various pulmonary fungal infections are endemic in certain geographic regions of the world. For example, histoplasmosis is endemic in the mid-south and Midwest of the USA. Approximately 50 % of chest CT scans will show lung nodules, half Figure 3.7. Images from a 62-year-old male complaining of shortness of breath and chest pain. Axial chest CT scan with contrast shows a massive saddle embolus (arrow) in the right and left main pulmonary arteries. of which are not calcified. In high-risk patients who smoke, differentiating these nodules from lung cancer is of utmost importance. Solid nodules that are less than 1 cm in diameter and are not calcified are typically followed with serial CT scans for 2 y. Stability over a 2 y period in most cases indicates benign nodules. Nodules that increase in size or indeterminate nodules that are greater than 1 cm in diameter are often imaged with a PET-CT examination or are surgically removed (Winer-Muram, 2006) (see Figure 3.8). Patients who present with a mass on chest radiography are commonly referred for CT as the next 28

39 Computed Tomography in Clinical Use Figure 3.8. Axial chest CT scan without contrast in an asymptomatic 73-year-old man. This image shows a 1.4 cm nodule in the left upper lobe. Comparison with a prior chest CT performed 4 y earlier showed interval growth of the nodule. study. CT can elucidate if a mass is present and show the extent of disease spread (see Figure 3.9). Enlarged hilar and mediastinal lymph nodes, pleural masses and fluid, rib erosion, and chestwall invasion are very suggestive of advanced disease. CT is one of the best diagnostic tools to evaluate for tumor response to chemotherapy. Protocoldriven studies are routinely requested by oncologists to assess the efficacy of the chemotherapy or radiation-therapy regimen they have chosen. Recently, chest CT was determined to be useful in screening of patients at high risk for lung cancer, which is the leading cause of cancer-related death in the developed world. A large multicenter study, the National Lung Screening Trial (NLST), compared low-dose helical CT with chest radiography in the screening of older, current, and former heavy smokers, for early detection of lung cancer. Starting in August 2002, the NLST enrolled about men and women: all had a smoking history of at least 30 pack-years and were either current or former smokers without signs, symptoms, or history of lung cancer. They were randomly assigned to receive three annual screens with either low-dose helical CT or standard chest radiography, and were then followed for another 5 y. At the conclusion of the study, a total of 354 deaths from lung cancer had occurred among participants in the CT arm of the study, whereas a significantly larger 442 lung-cancer deaths had occurred among those in the chest-radiography group (Aberle et al., 2011). How this information will be implemented in clinical practice is not yet clear, as the cost benefit Figure 3.9. A 64-year-old male presented with chronic cough and an abnormal chest radiograph. Chest CT without contrast shows a heterogeneous mass-like opacity (arrow) in the right upper lobe. Further clinical evaluation led to a diagnosis of lung cancer. analysis is still ongoing and the infrastructure necessary to launch such a large-scale screening program currently does not exist in any country. CT has been shown to be very useful in patients with diffuse lung disease. Thin-section CT (1 mm to 2 mm thick) reconstructed images with a bone kernel show exquisite detail of the lung parenchyma. A diagnosis of pulmonary fibrosis with honeycombing is so reliable with imaging that open-lung biopsy need not be performed in most cases. If surgery is needed, the scan can be used as a guide for the best biopsy site. Distinguishing emphysema, cystic lung disease, and cavities can be difficult with chest radiography. There are a variety of diseases that cause lucent lung lesions, and chest CT images can delineate vanishing lung from emphysema, thin-walled cystic lung disease, and thick-walled cavities (see Figure 3.10). In many cases, the CT findings can provide the diagnosis, or a short list of possibilities. It is a powerful tool that has played a crucial role in the diagnosis and management of diseases of the thorax. 3.4 CT in Abdominal Imaging Worldwide, ultrasound imaging is the most commonly used cross-sectional imaging modality to evaluate potential abnormalities of the abdomen and pelvis. Advantages of ultrasound over CT include a much lower cost, better delineation of cystic versus solid masses, and absence of ionizing 29

40 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Chest CT, coronal reconstruction in a 52-year-old male smoker. The patient complained of increasing shortness of breath. This CT image shows abnormal lung parenchyma, especially at the apices (arrows) representing bullous emphysema, a smoking-related lung disease. Figure Images from a 35-year-old male with right-lowerquadrant pain. Coronal CT reformatted image demonstrates the liver (L) and the kidney (K). There is a tubular structure seen in the right lower quadrant of the abdomen (arrow), which represents an inflamed appendix in this patient. radiation. However, in many parts of the world, ultrasound is often used as a screening exam, and CT is used for definitive diagnosis, particularly in situations in which ultrasound visualization is obscured by overlying structures in the abdomen such as loops of air-filled bowel. With the rising number of obese individuals in many countries, CT is often used as the first-choice imaging modality owing to the difficulty of obtaining diagnosticquality ultrasound images of internal organs in obese individuals. CT gives a quick and comprehensive view of the abdomen and pelvis, and is the imaging method of choice in a number of clinical situations. Situations in which CT is helpful are described below. There are numerous etiologies of abdominal pain, for which CT is an ideal tool (Rao et al., 1997). CT can evaluate inflammatory conditions in solid organs or hollow viscous regions within the abdomen. These can include evaluation of pancreatitis or diverticulitis and related complications. CT can evaluate other inflammatory conditions such as acute appendicitis (see Figure 3.11). With this condition, the appendix becomes inflamed and enlarged, usually due to a small appendicolith (small stone-like structure) obstructing the appendix. This can be seen as a fluid-filled enlarged appendix in the right lower quadrant of the abdomen (Figure 3.11). In some situations in which appendicitis is suspected, there can be other etiologies of the patient s pain. Figure 3.12 shows CT images of a patient with right-sided pain due to a renal stone, which has lodged in the ureter. The stone imposes an obstruction, which causes kidney swelling due to the back-up of urine, with associated intense flank pain. CT is well suited for the examination of the patient with acute blunt or penetrating abdominal trauma (Federle et al., 1981). In these situations, the patient is often unstable, and it is essential to rapidly diagnose any potential abnormality for immediate surgery or other interventional therapy. This can include injuries to arteries causing internal bleeding, injuries to hollow viscous tissues (e.g., bowel), or injuries to solid organs. Figure 3.13 shows a CT image of a patient with blunt trauma from a motor-vehicle accident. The patient has a severely fractured spleen with active bleeding from the spleen into the abdomen. CT is the preferred imaging modality for the detection of malignant or non-malignant abdominal masses (Freeny et al., 1988). CT can also guide biopsy or treatment of these masses. Figure 3.14 shows images of a patient with pancreatic cancer; CT can detect the cancer, determine local extension, and identify liver and other metastases, resulting in tumor staging. Tumor staging is important because it helps to guide oncologists as to what therapies should be considered. CT imaging can also be used to follow oncology patients to evaluate their response to tumor therapy. CT is well suited to guide needle-biopsy placement into abdominal masses, particularly those that are not amenable to biopsy under ultrasound guidance. Biopsy needles are placed in the 30

41 Computed Tomography in Clinical Use Figure Coronal CT image from a 45-year-old with right-sided flank pain. (a) This coronal CT image demonstrates the liver (L), right kidney (K), and the bladder (B). There is dilatation of the right renal pelvis and ureter (arrow). (b) Another reformatted coronal image demonstrating the liver (L), kidney (K), and the bladder (B). Note that there is a high-attenuation spherical structure representing a kidney stone (arrow), which is obstructing the right ureter and causing the patient s right-sided pain. Figure Images from a 22-year-old involved in a motorvehicle accident. The axial CT scan after administration of contrast demonstrates active extravasation of contrast in the region of the patient s spleen (arrow). This caused hemorrhage into the abdomen (curved arrow) surrounding the patient s liver (L). This patient required immediate operative intervention for removal of his spleen. Figure Pancreatic cancer. The axial CT scan demonstrates a low-density mass identified in the body of the pancreas (arrow). There are multiple low-density regions seen within the patient s liver corresponding to multiple metastases from the patient s pancreatic carcinoma. There is also a benign cyst noted within the left kidney (curve arrow). images of a patient with liver metastases treated by placement of three radiofrequency needles. abdomen using CT-image guidance, and small amounts of tissue are removed and sent for histopathology assessment. Invasive techniques have been developed that allow CT-guided treatment of abdominal tumors, avoiding open surgery. For example, radiofrequency ablation allows a series of small needle electrodes to be placed into a tumor, which result in intense tissue heating when electrified, killing the tumor cells by tissue coagulation (McGahan and Dodd, 2001; McGahan et al., 2011). Figure 3.15 shows 3.5 CT in Pediatric Radiology CT is a powerful tool in the diagnosis and care of pediatric patients. The development of multi-slice scanners and helical scanning allows for faster scanning in less-cooperative children. Quality imaging can now be performed without the significant risk and cost of patient sedation. Dynamic studies also add important information. CT has resulted in a beneficial change in patient management in as many as 68 % of hospitalized pediatric 31

42 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Images from a 68-year-old with metastatic colon cancer. (a) The axial CT scan shows a heterogeneous mass in the right lobe of the liver (arrow). (b) This liver lesion was treated with radiofrequency ablation (RFA), and three electrodes used to perform the RFA are seen in the liver. Figure Axial CT image from a 3-year-old boy with a Wilms tumor. The arrows point to the tumor in the left kidney. It enhances less (so is not as bright) with IV contrast than does the normal kidney tissue. RK, normal right kidney; LK, normal part of left kidney, from which the tumor arises. Figure Head CT images of a 5-year-old boy. After trauma experienced while wrestling, a large epidural hematoma (arrow) is seen and the brain is shifted to the left from the mass effect of the hemorrhage. patients (Callahan et al., 2002) and has decreased the need for exploratory surgery. As a result, CT use in children is on the rise. As many as 7 million CT scans are performed yearly in children in the USA (Frush and Applegate, 2004), and CT use in the pediatric emergency department has increased five-fold between 1995 and 2008 (Larson et al., 2011a; 2011b). Concern regarding radiation exposure from CT scans in children has been in the forefront of the medical literature and the lay press in recent years. Children are more radiosensitive than adults, and have a longer lifetime to develop radiation-induced cancer (Brenner and Hall, 2007). Organizations such as the Alliance for Radiation Safety in Pediatric Imaging, the Image Gently campaign, and the ALARA (as low as reasonably achievable) principle have focused on the need for radiation protection in children. There is increased awareness, knowledge, and communication in the efforts to optimize CT imaging in children (Newman and Callahan, 2011). Evidence-based imaging research helps guide clinicians toward the appropriate utilization of CT imaging, and when to consider alternative imaging options. Imaging the brain is one major use of CT in children. CT scans give physicians a rapid window through which to see the otherwise hidden region enclosed by the skull. For example, emergent and critical decisions for patient care are made based upon CT imaging in trauma patients. In the image shown in Figure 3.16, there is a large hemorrhage between the brain and the skull (arrow), which compresses the brain. CT imaging of the abdomen and pelvis in children is performed for a variety of reasons. CT is 32

43 Computed Tomography in Clinical Use Figure (a) Three-dimensional reconstruction of a complex (tri-plane) ankle fracture in a 14-year-old boy (arrows show multiple fracture lines). These 3D images can be viewed from various angles, and allow the surgeon to accurately plan the surgical reduction of this injury. (b) A post-operative radiograph shows anatomic bony alignment after fracture reduction and internal fixation with plates and screws. the standard imaging modality used in the evaluation of pediatric blunt abdominal trauma, usually from motor vehicle or bicycle accidents, falls, or sports injuries. CT can accurately define the extent and type of intra-abdominal and intra-pelvic injury (Wootton-Gorges, 2010). CT can also be used in the diagnosis and management of children with abdominal tumors. Figure 3.17 shows a child with Wilms tumor, the most common kidney and intra-abdominal malignant tumor in children. Although ultrasound is favored in many centers for diagnosing appendicitis in children, CT has also been useful in the diagnosis of appendicitis in children. In some centers, using CT to diagnose appendicitis has decreased the negative appendectomy rate (Callahan et al., 2002). One study also describes less delay in treatment and fewer complications with the use of CT in over 2000 patients with suspected appendicitis seen between 1997 and 2004 (Frei et al., 2008). CT scanning of the chest in the pediatric population is most frequently performed for trauma and for evaluation for metastatic tumor spread to the lungs or other tissues in the thorax. Evaluation of serious pneumonia is another common reason physicians ask for CT scans of the chest. Less-frequent reasons for scanning the chest include congenital abnormalities, such as maldevelopment of the heart or large vessels in the chest, or primary tumors in the chest. Lung disease, such as cystic fibrosis, can also be followed to assess its severity and/or response to therapy. CT scanning is very useful in evaluation of bony abnormalities. Three-dimensional reformatted images are particularly useful to the orthopedic surgeon managing spinal curvature, fractures, or bone tumors. Figure 3.18 shows a 3D reformation of a complex fracture of the ankle. Threedimensional images allow the surgeon to accurately plan the operative procedure before going to the operating room. 3.6 CT in Clinical Use: Summary CT was originally utilized for examining the head and brain only, because the head could be immobilized for long scan periods. Through four decades of technological advancement, CT scanners can now acquire high-resolution images throughout the body in a matter of a few seconds. The increased image quality and decreased scan time has led to the use of CT for many examinations for which radiography was used in the past. This has increased the utilization of CT imaging in most clinical disciplines. Although the diagnostic accuracy of CT is generally superior to radiographic (or other) imaging procedures, the increased use of CT has also increased concerns about large populations receiving higher exposures to ionizing radiation. 33

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45 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds Overview of Existing CT-Dosimetry Methods 4.1 Goals of CT Dosimetry As pointed out in Sections 2 and 3, rapid advances in CT technology over the past decade have led to increasing clinical demand for CT examinations. Because of the increased sophistication of modern CT scanners, performing CT on patients has becomse easier and faster, and better image quality has improved diagnostic accuracy. The dramatically shorter acquisition times of multidetector-row CT (MDCT) systems have opened up a number of new clinical applications, including cardiac CT, time-domain CT perfusion, and pediatric imaging on unsedated patients. These improvements have led to a huge increase in the number of CT examinations performed around the world, and especially in developed countries in which CT scanners are more widely available. As noted in NCRP 160 (NCRP, 2009) over the last 30 y, there has been a 72%increaseintheradiationdoseintheUSA,averaged over the entire population, and a sizeable fraction of this increase is attributed to the more widespread use of CT. Modern CT scanners have more advanced capabilities, and these features affect the patient s radiation dose. It is therefore necessary to identify the requirements of CT dosimetry to better optimize dosimetry tools and metrics that are most useful for CT dose estimation in the context of modern medical practice and CT utilization. CT dose-estimation methodologies and accuracy requirements will vary depending on the specific objective. Modern CT scanners have the capacity to produce deterministic effects (tissue reactions) in addition to stochastic effects. Deterministic effects include erythema, epilation, and disruption of the normal function of implanted devices such as pacemakers and neurostimulators. In many instances, the dosimetry techniques required for the evaluation of stochastic effects differ from those necessary for evaluation of deterministic effects. For example, absorbed doses in internal organs are more pertinent to stochastic influences of radiation, and absorbed doses in the skin or eye lens are often more important in considering deterministic effects of radiation exposure. Dosimetry in CT and other x-ray procedures is complicated by the fact that there is a wide range of body shape, height, and weight distributions in the population. Adult women and men have different characteristic body types and organ sites of concern in regard to radiation risk. In addition to their smaller body habitus, pediatric patients present special concerns in terms of CT dosimetry, given their more rapidly growing tissues and greater longevity. General categories of CT dosimetry methods include (1) routine dose characterization of a CT scanner for acceptance testing and quality control; (2) the determination of dose for the generic patient to compare acquisition protocols; (3) dosimetry for a specific patient; and (4) large-scale monitoring of CT dose values across hundreds or thousands of patients to assess institutional CT practices. (1) For acceptance testing and quality control, radiation output (air kerma), or dose indices (discussed below) might be measured for a wide array of uses, including: To assure that the scanner is generating similar air-kerma levels, for a given set of technique factors, as other identical scanners, and that these values are consistent with vendor-provided specifications. To assure that the CT scanner is generating similar radiation-output levels periodically over time, after a change in the x-ray tube, or after a CT scan of a patient that requires follow-up dosimetry. To optimize technique factors using phantoms of different size, complexity, and composition. To comply with applicable regulations or accreditation procedures. (2) CT dosimetry for generic patients using specific acquisition protocols, which represent the most common use of CT dosimetry in patients, including: A general knowledge of CT doses (organ absorbed and effective doses) for various CT examinations (e.g., head, abdomen) for rapid, # International Commission on Radiation Units and Measurements 2013

46 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY routine clinical decision-making and protocol selection. The computation of CT doses for a specific examination type for a general population of patients ( pediatric patients, women undergoing CT evaluation for pulmonary embolism during pregnancy, trauma patients, etc.) for clinical practice or research studies. Estimation of peak doses in specific organs (e.g., brain, skin) to assess the potential for deterministic effects in generic patients for specific CT examinations (e.g., CT head perfusion, CT angiography). Assessment of the cumulative organ dose from CT examinations and comparison of this value with the exposures from other artificialor natural-radiation sources. Comparison of the estimated radiation risks associated with different radiological methods that are expected to provide similar medical outcomes. (3) Dosimetry performed on specific individual patients that usually (but not always) occurs after the examination has been performed, and typically includes the following situations: Estimation of the absorbed dose in specific organs associated with a particular examination. Estimation of the stochastic radiation risk associated with a specific CT examination. Assessment of the absorbed dose to a fetus when a pregnant woman is undergoing or has had a CT examination. Absorbed dose in exposed tissues when there is concern about the potential for the patient to develop deterministic effects from a highdose CT procedure. (4) The assessment of CT dosimetric quantities to evaluate large numbers of dose estimates for characterization of an institution s CT-dose practices, including: The use of dose-reporting software to characterize quantities such as the volume computed tomography dose index (CTDI vol ), dose length product (DLP), or size-specific dose estimates (SSDE) for classes of CT examinations such as the head, chest, or abdomen/ pelvis CT scans. Assessment of the DICOM object (RDSR object radiation dose structured report) for CT-dose registry programs. Increasing concern over the radiation dose associated with modern CT scanners has led to the need for more accurate methods for CT-dose assessment and for a wider range of CT-dose assessment techniques. Although CTDI-based methods have proved useful in the past when the CT function was far more limited, it is clear that CT-dosimetry methods need to advance to keep pace with the technological advances of the scanners themselves. This is discussed in detail below. Ideally, a single radiation-dose quantity in CT would be usable by all parties of interest. However, different quantities might be necessary for the needs of various stakeholders involved in CT, including patients, radiologists and other physicians, medical physicists, lawyers, and others. For example, to monitor radiation output of a CT scanner over extended periods of time, a number of different radiation measurements could be used. However, for the assessment of potential fetal risk from an extensive series of CT procedures, more specific dosimetric quantities would be required. Section 4.2 discusses existing dosimetric quantities that have been used for these various purposes for the past several decades. CT dosimetry is in a state of flux as a result of a number of recent publications, including AAPM Report 111 (AAPM, 2010). The purpose of this Section is to define the state of the art for CT dose assessment. It should be noted that the CTDI methodology is a key part of International Electrotechnical Commission regulations, and it is therefore unlikely that measurement protocols that are a part of many regulations worldwide will be changed in the short term. Therefore, a review of current methodologies for assessing dose from a CT scanner will be described below Basic Tools 4.2 CTDI-Based Metrics Figure 4.1 illustrates the basic shape of the 100 mm pencil chamber used for over 30 y for CT dose measurements. The pencil chamber has a 100 mm active length and is designed to fit within a solid phantom with holes placed at various locations as illustrated in Figure 4.2. The design of the chamber produces a uniform response along its axis. A radiation meter longer than the collimated radiation beam was required historically in CT dose assessment because it is difficult to position a small radiation meter precisely within the very narrow collimated slice thicknesses, especially in the era of single-slice scanners in which nt ranged typically from 1 mm to 10 mm. With multi-detector array (n) CT scanners with detector widths of T (in mm), the parameter nt describes the nominal beam width, and this is a very useful measure in CT acquisition protocols and dosimetry in general. 36

47 Overview of Existing CT Dosimetry Methods Figure 4.1. A schematic diagram of the 100 mm pencil chamber. The active length of this chamber is 100 mm, with a total volume of 3 cm 3. Inside the pencil chamber, a long graphite electrode runs through the center of the volume. Whereas, in a radiographic field of (for example) 30 cm 30 cm, placement of a 5 cm diameter radiation meter in the center can be performed with confidence that the dosimeter will not accidentally be placed outside of the beam (also most radiographic systems have a light field to help with guidance), the same was and is not true for the narrow beams in CT. Therefore, the approach of using a pencil chamber significantly longer than the width of the collimated beam was required, and a correction for partial-volume exposures of the chambers was also intrinsic to the measurement. Today, however, there are CT beams that are wide much wider than the 100 mm pencilchamber length, so alternative methods for Figure 4.2. Schematics of the CTDI phantom. (a) CTDI phantoms are cylinders comprised of PMMA. At a minimum, there is a through-hole at the center and at one location on the periphery of the phantom. Various manufacturers have slightly different designs, and some phantoms have several holes around the periphery. (b) The phantom is illustrated with a pencil chamber positioned in the central hole. All remaining holes are plugged with PMMA rods during measurements. With the phantom placed on the patient table, the 12 o clock and 6 o clock positions are illustrated. 37

48 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY measuring dose need to be addressed, as will be discussed later in this Report. The phantoms used for CT dosimetry over the years were defined by the report of AAPM Diagnostic Radiology Committee Task Force on CT Scanner Phantoms (AAPM, 1977). The general design of the CT dosimetry phantom is illustrated in Figures 4.2a and 4.2b. The phantoms are fabricated from polymethyl methacrylate (PMMA), or [C 5 H 2 O 8 ] n, which has a density of approximately 1.19 g/cm 3. Although the design of the phantom has several variations, in general there is a central hole and one or more peripheral holes, which are through-bored with diameters of 12 mm, large enough to allow the placement of the pencil chamber in any of the holes. When the pencil chamber is placed to make a measurement in one hole, PMMA rods are placed in all the other holes to displace the air with solid material. There are two phantoms in general usage for CT dosimetry, a body phantom that is 320 mm in diameter, and a head phantom that is 160 mm in diameter. The head phantom also doubles as a pediatric body phantom, with an equivalent cross-sectional area of the typical 2-year-old. Both of the PMMA phantoms are 150 mm in length, although some phantoms that were 140 mm in length were manufactured and used in some settings. Another parameter becomes useful in this discussion when considering the clinical reality of a series of axial CT scans that cover a length of the patient. This is the scan interval, b, defined as the table-translation distance between rotations. An interval of b ¼ nt produces contiguous scans, leaving no gaps in the acquired image data. CTDI 1 represents the average dose (i.e., air kerma) in a defined phantom over a small interval +b/2 about the center of the scan length that accumulates at z ¼ 0 from a series of N contiguous (b ¼ nt) scans covering a scan length L ¼ Nb, which is sufficient to produce scatter equilibrium at z ¼ 0 (symbolically denoted by L! 1) (AAPM, 1990; IEC, 2009; COCIR, 2000; Shope et al., 1981). The CTDI 1 is in principle measured in the axial scan mode using a single 2p rotation of the x-ray source around a stationary phantom, and allows one to estimate the average absorbed dose at the center (z axis) of the scan volume resulting from multiple gantry rotations, if the scan length is sufficiently long for the central dose to approach its asymptotic upper limit (McCrohan et al., 1987; COCIR, 2000; Shope et al., 1981). To measure CTDI 1 in one axial scan, the measurement instrument needs to be long enough to integrate the majority of the dose from scattered radiation that propagates away from the scan plane CTDI 1 In this Section, the methods to measure or calculate various traditional CT dose descriptors are described. The CTDI is currently the primary dose measurement concept in CT: CTDI 1 ¼ 1 nt ð 1 1 KðzÞdz; ð4:1þ where K(z) is the air kerma in the phantom as a function of position on the z axis. n is the number of tomographic sections imaged in a single axial scan. This is equal to the number of data channels used in a particular scan. The value of n is less than or equal to the maximum number of data channels available on the system. T is the nominal width of the tomographic section along the z axis imaged by one data channel. In MDCT scanners, several detector elements can be grouped together to form one data channel. In single-detector-row (single-slice) CT, the z-axis collimation at the isocenter determines the nominal beam width CTDI FDA The multiple-scan average dose (MSAD) represents the absorbed dose averaged over a small scan interval, b, and requires multiple exposures for its direct measurement. The CTDI approach offers a more convenient yet nominally equivalent method of predicting the MSAD, and requires only a single axial CT scan acquisition. In the early days of CT, this saved considerable time and x-ray-tube heat loading. Theoretically, the equivalence of the MSAD and the CTDI requires that all contributions from the tails of the absorbed-dose distribution be included in the CTDI measurement. The exact integration limits required to meet this criterion depend upon the width of the primary beam, the scattering medium, and the x-ray beam energy. To standardize CTDI measurements, the FDA (1984) introduced the integration limits of +7T, wheret is the nominal slice width. Interestingly, the original CT scanner, the EMI Mark I, was a dual-detector-row system. Hence, the nominal radiation-beam width was equal to twice the 38

49 Overview of Existing CT Dosimetry Methods nominal slice width (i.e., 2 T). Thus, CTDI FDA ¼ f ð 7T SI KðzÞdz: nt 7T ð4:2þ For an ionization chamber that is calibrated in terms of air kerma, the measured value is converted to absorbed dose in PMMA, using the ratio of the mass energy-absorption coefficients: f f SI ¼ m en=rg medium : ð4:3þ fm en =rg air For the typical energies used in CT, the value of f SI is 0.90 mgy/mgy to convert to absorbed dose in PMMA. Here, f SI is the value of the so-called f-factor in units consistent with the International System of Units. A value of f SI of 1.06 mgy/mgy would be appropriate to convert to absorbed dose in tissue. Conversion to absorbed dose in PMMA is unique to CTDI FDA,and the more-recently defined CTDI quantities (discussed below) are reported as air kerma, with no conversion factor necessary. The original definition of CTDI FDA was to include the f-factor such that the resultant measure was in terms of the quantity absorbed dose; however, the more modern CTDI 100 is explicitly defined as a measurement of air kerma.inthefollowing, the general term dose is kept because air kerma is closely related to absorbed dose in air at the x-ray energies used in CT. For the CTDI FDA, the limits of integration were expressed in terms of nt (such as +7nT), allowing for the potential underestimation of the MSAD by the CTDI. For modern MDCT scanners, such as a 16-slice scanner using nt ¼ mm ¼ 20 mm, the integration length of 14T ¼ 17.5 mm is smaller than the primary-beam width and clearly beyond the intent of the CTDI FDA model. As n ¼ 1 for the vast majority of CT scanners in use from 1975 to the late 1980s, the integration width was 14 times wider than the primary collimated beam, so that the measurement of all of the primary radiation was intended. The limits of integration in the CTDI FDA mean that for a 3 mm beam width (T ¼ 3 mm), the integration length of 14T was 42 mm; 98 mm for a 7 mm beam width; and 140 mm for a 10 mm beam width. However, the variation in the integration length (42 mm to 140 mm) implies that differing extents of x-ray-scatter-tail integration would be measured with changes in T, even though the propagation distances of scatter along the z axis from the center of the primary beam (at z ¼ 0) is related more to the x-ray spectrum, phantom composition, and diameter than to the beam width T (Boone, 2007). It is likely that the importance of the role of scattered radiation in CT dosimetry was not fully appreciated in the early years of CT operation. The scattering media for CTDI measurements were also standardized by the FDA (1984). As mentioned previously, these consist of the two PMMA cylinders, 160 mm and 320 mm in diameter and 150 mm in length. Figure 4.3 shows these two phantoms in the measurement position The nt Term Air kerma, K, is defined (ICRU, 2011) as K ¼ de tr dm ; ð4:4þ Figure 4.3. Photographs of the CTDI head phantom and body phantom, with the cable from the pencil chamber visible. For CTDI measurements, the cylindrical phantom is located concentrically in the gantry using laser lights for positioning. Along the z axis, the phantom is positioned so the center of the axial (sequential) scan intersects the phantom at its midpoint. The pencil chamber is also positioned so its midpoint is aligned with the center of the radiation beam (and hence with the phantom). In the photograph on the left, the head phantom is placed on the table. This is a common geometry for an emergency-room CT scanner, in which many patients are either unconscious or otherwise impaired. In most CT scanners outside of the emergency department, the head phantom is more typically placed in the CT head holder, which is used preferably for head imaging with ambulatory patients. 39

50 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY where de tr is the mean sum of the initial kinetic energies of all the charged particles liberated in a mass dm of a material by the uncharged particles incident on dm. Ionization chambers, including the long pencil chamber typically used for CT, are designed to produce accurate dosimetry readings only when they are completely and uniformly exposed, and this is the manner in which most ionization chambers are used and calibrated. When partial exposure of the pencil chamber occurs, as in CT measurements, a partial-volume correction is necessary CTDI 100 The CTDI 100 protocol calls for measurements to be made using a 2p rotation of the gantry in the axial mode, with the PMMA cylindrical phantom placed concentrically with its center coincident with the isocenter of the CT scanner s rotation, and with the center of the phantom along the z axis located at the CT scanning location (Figure 4.3) at z ¼ 0. The pencil chamber is placed on the central axis of the phantom, and subsequently at the peripheral position. The measurements made under these conditions are referred to in this document as the CTDI100 center and CTDI peri 100. Some head and body phantoms include multiple (e.g., 4) holes in the phantom at its periphery to allow assessment of CTDI peri 100 at various angles, and these values are typically averaged. Because the CTDI100 center measurement is only at the center of the phantom, and also at the center of the scanner s field of view, this measurement is relatively insensitive to the influence of the bow-tie filter, which is relatively homogeneous at the center of the field of view. However, the CTDI100 center measurement is indirectly affected by the bow-tie filter (see Section 2), because peripherally scattered photons can reach the central axis and affect the measurement. The peripheral measurement, CTDI peri 100, however, interrogates the x-ray fan beam at a wider fan angle and therefore is more sensitive to the attenuation properties of the bow-tie filter. Because some CT scanners initiate the beam-on position at an arbitrary start angle, the peripheral measurements, CTDI peri 100, are typically less reproducible than those for the center hole. It is also noted that measurement of CTDI 100 requires that the phantoms be placed on the CT table, and the measurements therefore include attenuation of the table itself. Although the table has little effect on the central measurement, it has a measurable influence on the peripheral CTDI 100 measurement; if the peripheral hole location where the pencil chamber is placed is in the 6 o clock position (nearest to the tabletop), then this measurement will be in general lower in value than with the pencil chamber placed in the 12 o clock position. Even though the measurement value is the integral of the 2p rotation of the x-ray tube around the phantom and chamber, the peripheral measurement of air kerma is highly influenced by the part of the 2p scan when the x-ray source is on the side of the phantom at which the peripheral measurement is made. When the CT table is between the x-ray source and chamber as in the 6 o clock position, it will have a greater influence on the measured air kerma than when the table is not between the source and pencil chamber as in the 12 o clock position (see Figure 4.2b). Unlike CTDI FDA, CTDI 100 values are reported in terms of air kerma, and no conversions are performed to convert the air kerma to absorbed dose in PMMA or any other medium. CTDI 100 represents the accumulated multiplescan air kerma at the center of a 100 mm scan and underestimates the accumulated air kerma for longer scan lengths. It is thus smaller than the equilibrium air kerma or MSAD for most clinical examinations, because most patient CT scans are longer than 100 mm. The CTDI 100, as does the CTDI FDA, requires integration of the radiation dose profile from a single axial scan over specific integration limits. In the case of CTDI 100, the integration limits are +50 mm, which corresponds to the 100 mm length of the commercially available pencil ionization chamber (Jucius and Kambic, 1980; AAPM, 1990; 1993; McNitt-Gray, 2002). Pencil chambers of lengths other than 100 mm have been manufactured; however, the 100 mm version is required for the CTDI 100 measurement, thus CTDI 100 ¼ 1 ð 50 mm KðzÞdz: ð4:6þ nt 50 mm We note that historically the integrand in Eq. (4.6) has been written in terms of a generalized dosimetric quantity, such as D(z), but current protocols are specified in terms of air kerma, K(z). The use of a single, constant set of integration limits avoids the problem of overestimation for narrow slice widths (e.g.,,3 mm) (AAPM, 1990) compared with CTDI FDA. It also resolves the problem of measurements for a number of different scan lengths; the +7T limits for CTDI FDA were defined when multiple thermoluminescent dosimeters (TLDs) were more commonly used, and the length of the TLD array could be varied. CTDI 100 is typically measured using a 100 mm long, 3 cm 3 active volume CT pencil ionization chamber in conjunction with the two standard CTDI PMMA phantoms (AAPM, 40

51 Overview of Existing CT Dosimetry Methods 1990; FDA, 1984), using a single rotation about a stationary patient table and phantom, i.e., in axial (or sequential) acquisition mode Weighted CTDI, CTDI w The dose in CT varies across the axial field-of-view, that is, across the plane of an individual axial CT scan. For example, for the 320 mm diameter PMMA body phantom, the CTDI 100 is typically a factor of two higher at the periphery than at the center of the field-of-view (average for 120 kv from four major manufacturers ¼ 1.99; coefficient of variation ¼ 6 %); whereas for the head phantom (160 mm diameter), the CTDI 100 is quite similar at the center and peripheral locations (average ratio 1.08; COV ¼ 2 %). The average CTDI 100 across the field-of-view at the central scan plane is estimated by the weighted CTDI (CTDI w ) (IEC, 1999; 2002; Leitz et al., 1995), where CTDI w ¼ 1 3 CTDIcenter 100 þ 2 3 CTDIperi 100 : ð4:7þ CTDI w is intended as an average value, calculated from the CTDI 100 center and peripheral measurements. The weights of 1/3 and 2/3 are from the assumption of a linear increase in CTDI 100 with radial distance from the phantom central axis, and approximates the relative areas represented by the center and edge values (Leitz et al., 1995). CTDI w is a useful indicator of a CT scanner s radiation output (air-kerma levels measured in a specific phantom) for a specific kv and mas setting. According to IEC requirements, CTDI w must use CTDI 100 as described above (IEC, 2009) Volume CTDI, CTDI vol To represent the radiation levels (air kerma) in a phantom for a specific scan protocol, which almost always involves a series of scans, it is essential to take into account any gaps or overlaps between the x-ray beams from consecutive rotations of the x-ray source. This is accomplished with the use of a dose descriptor known as the volume CTDI, orctdi vol. As CTDI w is the central plane (along the z axis) air kerma for contiguous scans (b ¼ nt), CTDI vol converts CTDI w to the central plane for an arbitrary scan interval, b, as CTDI vol ¼ nt b CTDI w ¼ 1 p CTDI w; ð4:8þ where b is the table translation increment per axial scan (IEC, 2009), and p is the pitch. The smaller the scan spacing relative to nt, the greater the overlap of the dose profiles, and the larger the CTDI vol value. Because no averaging over the scan length L has been performed, CTDI vol (and also CTDI w ) is essentially an average over the area of the central scan plane at z ¼ 0, with no appreciable z extent, namely over only a relatively small distance +b/2 about z ¼ 0 for axial scans, and is a pure planar average at z ¼ 0 for helical scanning (Dixon, 2003). Thus, its name is somewhat of a misnomer. Likewise, MSAD is a central-plane average about z ¼ 0. Pitch is defined as the ratio of the table travel per rotation, b, to the total active detector length (nt) (IEC, 2009; McCollough and Zink, 1999), as in Eq. (2.5). The CTDI vol provides a single CT dose quantity based on a directly and easily measured quantity, which approximates the average absorbed dose (in air) across the central scan plane for a 100 mm scan length in a standardized (CTDI) phantom (IEC, 2009). CTDI vol is a useful dose metric for a standardized phantom for a specific examination protocol, because it takes into account the important parameter of pitch. Its value is displayed prospectively on the console of newer CT scanners, although it might be mislabeled as CTDI w on some older systems. The IEC consensus agreement on these definitions is used on most modern scanners (IEC, 2009) Limitations of CTDI vol Although CTDI vol is an attempt, given previous CTDI quantities, to better estimate the average absorbed dose (in air) in the central CT slice for an object of attenuation similar to that of the CTDI phantom, it does not represent the average dose for most patients, which differ from the phantom in size, shape, and attenuation; moreover, the 100 mm integration limits omit a considerable fraction of the scatter tails (Boone, 2007) and underestimates the absorbed dose for typical body-scan lengths of 250 mm or more. This is discussed at length in Section 7. The CTDI vol as indicated on the scanner console remains unchanged whether the scan length is 10 mm, 100 mm, or 1000 mm. CTDI vol estimates the dose for a 100 mm scan length only, as it is derived from the CTDI 100, even though the actual central dose will increase as a function of scan length, up to an asymptotically approached equilibrium dose value (AAPM, 2010). Although CTDI vol is not an ideal direct measurement of patient dose for the reasons discussed above, it is considered to be a useful measurement of the pitch-corrected x-ray output properties (integrated air kerma for specific technique factors) of each make and model of CT scanner. As will be 41

52 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY seen later in Sections 7 and 8, CTDI vol has shown value in normalizing a number of quantities to the output characteristics of different CT scanners. The usefulness of CTDI vol is further supported by the widespread availability of tools ( phantoms and pencil chambers) for measuring it, and on more recent scanners, the IEC requires display of the CTDI vol after a CT scan technique is set up, but before it is initiated. CTDI vol is also commonly reported after the CT scan, and more recently the CTDI vol is often stored as a secondary capture image (a bitmap image) in the patient s CT image files in the Picture Archiving and Communication System (PACS) or in the DICOM (digital image communication) standard. 4.3 Dose Length Product The total energy 1 deposited in the phantom by a given scan protocol can be estimated by multiplying CTDI vol by the directly irradiated mass of the phantom pr 2 rl, where L is the scan length and r is the mass density. Thus 1 ¼ rpr 2 L CTDI vol : ð4:9þ Therefore, a surrogate measure of the total energy absorbed in the phantom is the dose length product (DLP) (IEC, 1999), where DLP ¼ CTDI vol L; ð4:10þ and where typically the units of CTDI vol are mgy, of length L are cm, and of DLP are mgy cm. The DLP is a surrogate for the total energy absorbed [formerly called the integral dose (Johns and Cunningham, 1974)] attributable to the complete scan acquisition. For example, an abdomenonly CT exam might have the same CTDI vol as an abdomen/pelvis CT exam, but the latter study would have a greater DLP, proportional to the greater z extent of the scan volume. In helical CT, the scan length L is defined as total table travel during the beam-on time (couch velocity total beam-on time), which is longer than the programmed, reconstructed image length because images at the beginning and end of a helical scan require data from z-axis projections beyond the programmed scan boundaries. The increase in dose-length product due to the additional gantry rotation(s) and table travel required for the helical interpolation algorithm is often referred to as over-ranging. For MDCT scanners, the number of additional rotations is pitch-dependent, with a typical additive increase in scan length of 1.5 times the total nominal beam width. The overall dose implications of over-ranging with regard to the dose length product, DLP, depends on the scan length. For helical scans that are relatively short (e.g., 100 mm), a scanner using a 40 mm collimated beam width can have up to 40 % of the DLP in the over-ranging region. For a scan length of 300 mm with a 20 mm collimated beam, about 7 % of the DLP is contributed by the over-ranging region. Newer models of CT scanners have independent collimator systems (adaptive dose collimation, see Section 2.2.2) that are designed to substantially reduce the over-ranging dose, and these systems perform well in terms of reducing unnecessary dose at the edges of the CT scan. Table 4.1 shows the CTDI vol and DLP for typical CT exams. The values are meant to be illustrative only; they can vary by scanner model, vendor, institution, and image-quality requirements. Because the DLP is related to the total energy absorbed, it depends only on the total number of rotations, and is indifferent as to how these rotations are distributed along z, i.e., DLP remains the same even if the table does not move (L ¼ 0). For a given tubepotential setting and bow-tie filter, the DLP depends on the product of the primary beam width, a, and the total tube-current time product used for the entire scan series. If scan length is changed by changing pitch without increasing the total mas setting, DLP remains unchanged Limitations of CTDI Methods For body scan lengths of 400 mm or more, the accumulated dose approaches the limiting equilibrium dose (see Section 7). However, CTDI 100 underestimates the equilibrium dose CTDI 1 (or the MSAD for a pitch of unity) by a factor of approximately 0.6 on the central axis and by about 0.8 on the periphery (Mori et al., 2005; Boone, 2007). In order to measure the equilibrium dose (i.e., air kerma), a phantom of almost 450 mm in length is required (Boone, 2009). This length of phantom is required in order to capture the extent of the x-ray scatter tails in both directions. Because a pencil chamber of this length is not practical, direct measurement of the MSAD using a short ion chamber (Dixon, 2003) is possible. Such a method can be utilized to emulate a virtual pencil chamber of arbitrary length up to the available phantom length using helical acquisition modes. The issue of dose estimation in longer phantoms is discussed in Section 7 of this Report. 42

53 Overview of Existing CT Dosimetry Methods Table 4.1. Illustrative values for CTDI vol and DLP for common CT exams for 4- and 16-channel MDCT. Exam Beam collimation Pitch Tube current time per rotation (ma s) Scan length (cm) CTDI vol (mgy) DLP (mgy cm) Four-channel MDCT (120 kv) Head mm Axial Chest 4 5 mm Abdomen 4 5 mm Abdomen and pelvis 4 5 mm channel MDCT (120 kv) Chest mm Abdomen mm Pelvis mm Table 4.2. Effective-dose weighting factors from ICRP Publication 103 (ICRP, 2007), combined with the example of a thoracic CT scan. Column 1 identifies the organ site of interest, and column 2 gives the tissue-weighting factors (w T ) defined in ICRP Publication 103. Column 3 represents the various organ absorbed doses from a thoracic CT examination, determined using Monte Carlo methods. Column 4 is the product of w T and the organ absorbed doses, resulting in the contribution to effective dose from that organ. Summing column 4 represents the total effective dose of 9.3 msv for this hypothetical CT examination. Organ site W T (msv/mgy) Organ dose (mgy) 4.4 Estimation of Effective Dose E (msv) Gonads Bone marrow Colon Lung Stomach Bladder Breast Liver Esophagus (thymus) Thyroid Skin Bone surface Brain Salivary glands (brain) Remainder Total 9.28 When comparing different CT scan protocols, or when comparing absorbed-dose levels between x-ray radiography and CT, methods are required that allow prorating the absorbed dose levels for a generic patient. The effective dose, E, definedin ICRP 60 (ICRP, 1991) and subsequently redefined (ICRP, 2007), can be a useful tool in such comparisons (see Table 4.2). Effective dose is not a physical dose, as its computation includes weighting factors that are derived from radiobiological Table 4.3. DLP-to-E conversion coefficients, k, for various types of CT examinations. Conversion coefficients for head-and-neck assume the use of the 16 cm diameter CT head phantom. All other conversion coefficients assume the use of the 32 cm diameter CT body phantom (Bongartz et al., 2004; Shrimpton et al., 2006). Region of body Head and neck Head Neck Chest Abdomen and pelvis Trunk considerations. Effective dose was never intended to be used for the assessment of an individual patient s radiation dose, because the radiobiological weighting factors are not pertinent to a specific patient. To minimize controversy over differences in effective-dose values that are purely the result of calculation methodology and data sources, a generic estimation method was proposed by the European Working Group for Guidelines on Quality Criteria in CT (IEC, 2009). In this method, effective-dose values are calculated from the NRPB dose-conversion coefficients derived from Monte Carlo calculations of organ absorbed doses (Jones and Shrimpton, 1991), using the ImPACT spreadsheet (ImPACT, 2011). The effective doses were compared with DLP values for the corresponding clinical exams to determine a set of coefficients, k, that are dependent only on the region of the body being scanned (head, neck, thorax, abdomen, or pelvis) (see Table 4.3). Using this methodology, E can be estimated from the DLP, which is reported on most CT systems, according to E k DLP; k/[msv/(mgy cm)] ð4:11þ 43

54 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 4.4. The relationship between dose length product, DLP, and the effective dose, E. The individual data points were gathered from 46 different CT scanners. With the line intersecting the y axis at zero, the inverse slope of the line shown is the k coefficient for abdominal CT (k ¼ msv/ (mgy cm)). Figure 4.6. The DLP versus E for head CT scans. The fit shows a k coefficient of msv/(mgy cm). Figure 4.5. The DLP versus E for thoracic CT. The inverse slope of the line (i.e., the k coefficient) is msv/(mgy cm). where E is the effective dose in msv if DLP has units of mgy cm and k has units of msv/(mgy cm). To illustrate the utility of Eq. (4.11), Figure 4.4 illustrates the relationship between DLP and E for abdominal CT scans; these data were derived from 46 different CT scanners in the European Union, with the observation that the relationship is relatively robust across this large number of scanners. Figure 4.5 shows the relationship between DLP and E for thoracic CT scans, and Figure 4.6 shows this relationship for head CT scans. The values of E predicted by DLP and the values of E estimated using more rigorous calculations methods are remarkably consistent, with a maximum relative deviation from the mean of approximately 10 % to 15 % (McCollough, 2003). Lam et al. (2011) have also demonstrated a good relationship between DLP and E (see Figure 4.7) based on observations from a single pediatric patient receiving 50 CT scans as a part of a cancersurveillance protocol. Hence, the use of DLP to estimate E is a reasonably robust method for estimating effective dose. In addition, Huda et al. (1997) have Figure 4.7. The effective dose as a function of the DLP. These data were specific to a single pediatric patient who had repetitive CT scans as a result of a cancer-screening protocol. For this one individual, the slope for these predominantly abdominal CT scans was msv/(mgy cm), with excellent correlation. compared effective dose, as calculated from the NRPB data of Jones and Shrimpton (1991), to estimates of total energy deposited in order to develop conversion coefficients with which to later estimate effective dose. The use of routinely displayed scan parameters such as mas and kv settings is marginally successful in predicting dose (Herlihy et al., 2006). Rather than relying on parameters such as the tube-current time product, the tube potential, and pitch, the use of CTDI vol provides a single dose metric by which users can benchmark the prescribed output for a given exam against national averages, having factored in the effects of pitch, detector collimation, x-ray-tube-to-isocenter distance, and other technical parameters (McCollough, 2006). The values of CTDI vol displayed on the user console prior to scan initiation can be compared with published values, such as reference values provided by the ACR and AAPM (McCollough, 44

55 Overview of Existing CT Dosimetry Methods 2006; Gray et al., 2005), and results of national surveys, such as the NEXT study (Conway et al., 1992) conducted by the Food and Drug Administration s Center for Devices and Radiological Health. Users prescribing CT protocols that result in doses above references values should have an appropriate justification (Hart et al., 1996). 45

56

57 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds CT X-Ray-Spectrum Characterization 5.1 Introduction The vast majority of x-ray tubes used in diagnostic radiology make use of tungsten anodes, and CT is no exception. Tungsten (alloyed with 5 % to 10 % rhenium) has excellent heat conductivity, a high melting point, and its relatively high atomic number (Z ¼ 74) makes for efficient bremsstrahlung x-ray production. Although bremsstrahlung represents the majority of the photons produced by CT x-ray tubes, the characteristic-radiation production from tungsten produces two peaks, at 59 kev and 68 kev (each is a doublet) when tube potential is above tungsten s K edge of 70 kev. The x-ray spectra used in CT imaging are some of the hardest used in medical radiological x-ray imaging, generally because of the typically higher tube potentials used and the greater amount of added filtration for the central ray. Toward the periphery of the fan beam, the beam-shaping filter provides even more x-ray-beam filtration, and this hardens the x-ray spectrum further. A harder beam is necessary in CT to reduce beam-hardening artifacts, which arise from differing magnitudes of spectrum hardening for different projections around a patient. Adding metallic (and sometimes plastic) filtration to the x-ray beam pre-hardens the x-ray beam and thus reduces beam-hardening artifacts, as discussed in Section The higher filtration levels also lead to relatively lower absorbed-dose levels in the patient. Although spectroscopy methods have been used to accurately measure x-ray spectra, the experimental setup for x-ray spectroscopy is complicated, the equipment is expensive, and the procedure is time-consuming and requires significant expertise to produce accurate results. Consequently, x-ray spectra have been characterized using the concept of the half-value layer (HVL) for nearly a century. The HVL of an x-ray beam is measured using an air-kerma meter, or other dosimeters calibrated to produce air-equivalent readings. The measurement of the HVL generally requires that the measurement instrument remain fixed in location, as a number (including zero) of different thicknesses of an absorber are placed between the dosimeter and the stationary x-ray source. In the context of CT, the traditional method for HVL measurement requires that the service mode of the scanner be used in order to stop gantry rotation. Aluminum is the predominant material for characterizing the HVL in diagnostic-radiology applications, including CT. 1 For an aluminum thickness t, the measurement is approximated by the polyenergetic form of the Lambert Beers law: K air ðtþ ¼ Ð E fðeþ e m FðEÞt adde m Al ðeþt E m en r de; air ð5:1þ where K air (t) is the air kerma for an aluminum thickness t, f(e) is the x-ray fluence as a function of energy, E, at the isocenter in the absence of the added filtration, and m Al (E) is the linear attenuation coefficient as a function of energy of the aluminum filters used for HVL assessment. The thickness t add of a permanent filter (F) material with an attenuation coefficient m F (E) is the (inherent þ added filtration) in the x-ray beam at the center of the field of view. Inherent filtration refers to the attenuation properties of the x-ray-tube housing itself that the x-ray beam has to penetrate in exiting the x-ray-tube port. Added filtration refers to additional filtration that is permanently and intentionally added to the x-ray tube assembly to harden the x-ray beam, i.e., to reduce the fluence of low-energy x rays relative to higher-energy x rays; it might or might not be aluminum in composition. Added filtration does not refer to the aluminum filters that are inserted in the x-ray beam only to make the HVL measurement. From the HVL measurement procedure, using additional Al filters, a relative transmission curve is produced according to AðtÞ ¼ K airðtþ K air ð0þ : ð5:2þ The HVL is the thickness, t, of aluminum such that A(t) ¼ 1/2 (for a given tube potential), which can be 1 Type 1100 Al alloy is often used, but high-purity Type 1145 is also available. # International Commission on Radiation Units and Measurements 2013

58 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY evaluated graphically, interpolated among adjacent data, or estimated by curve fitting of A(t). The HVL increases as the x-ray-tube potential increases, with constant inherent þ added filtration. It is noted that by convention, the HVL is defined in terms of air kerma, and therefore its accurate measurement requires that a properly calibrated air-ionization chamber be used. If solid-state detectors are used, then corrections are necessary to convert the measured values to air kerma. Modern CT dosimetry is substantially informed by data produced using Monte Carlo radiationtransport techniques. In order to achieve desired levels of accuracy, methods require a good model of the x-ray spectrum used. It has been shown that x-ray spectrum modeling can produce adequate spectra if both the tube potential and the HVL of the x-ray beam are known (Boone, 1986; 1988; Duan et al., 2011; Turner et al., 2009). Therefore, for accurate CT dosimetry, characterization of the HVL of the CT scanner is necessary. HVL measurement is useful for research studies of CT beam spectra, but can be a quality-control tool as well. 5.2 Methods for HVL Measurement Conventional HVL Assessment in CT The conventional assessment of the HVL in computed tomography requires that the service mode of the CT scanner be used in order to stop the rotation of the x-ray tube. In this mode, the HVL measurement is performed as it would be for any radiographic system; measurements are made in a fixed geometry as increasing thicknesses of filter material are added incrementally to determine K air (t) over a range of t [see Eq. (5.2)]. Figure 5.1 illustrates the experimental set-up for conventional HVL assessment. Although a number of different measurement configurations are possible, in Figure 5.1 the aluminum filters are placed directly on the gantry cowling, the x-ray tube is centered at the 6 o clock position, and the ionization chamber is placed in the center of the field. The patient table is retracted out of the gantry so as not to interfere with the measurements. A series of measurements are then made with different thicknesses of Al placed in the beam. Few medical physicists have the passwords necessary to enter the service mode of most CT scanners, let alone the ability to use the system in service mode in a safe and time-efficient manner. Therefore, the conventional measurement of the HVL using the service mode typically requires the presence of the service engineer during the procedure. Because of this difficulty, the characterization of a CT scanner HVL is typically performed infrequently or not at all in most settings Aluminum-Cylinder Method Kruger et al. (2000) described a method by which the HVL of a CT x-ray beam can be measured without the need for using the service mode of the system. This ring method uses a series of aluminum cylinders of slightly different diameters that can be nested in a concentric fashion to create a number of different filtration thicknesses. The 100 mm pencil chamber is aligned at the isocenter of the scanner with the aid of laser positioning, and a series of repeated axial CT scans is performed, with additional cylindrical filtration added between measurements (see Figure 5.2a). The table is positioned out of the gantry for this measurement. The ionization chamber is read out in the integration mode, and an axial CT scan with the same technique settings is repeated until all of the measurements are made. The investigators used a number of cylinders, each with 2.0 mm thickness. This approach was demonstrated to produce HVL measurements of acceptable accuracy. The HVL values for 120 kv measured with the ring method and the conventional service-mode method were not significantly different. The investigators also studied the influence of mispositioning the ionization chamber away from isocenter, and found that the ring technique was relatively insensitive to realistic positioning uncertainties in the field. Although the manual placement of the aluminum cylinders between measurements can be timeconsuming, by obviating the need for the presence of the service engineer during the measurements, this approach has clear advantages over the conventional HVL-measurement method when service engineers are not routinely available Real-Time Probes X-ray source rotation in a CT scanner creates a dynamic situation in which the radiation beam is directed toward the center from a circular trajectory. Combined with table translation along z, and depending upon the experimental setup and if a phantom is involved, the air-kerma rate can vary rapidly and appreciably. The use of a conventional thimble chamber with integration periods of 0.1 s precludes the measurement of the dynamic characteristics of the CT x-ray beam. Therefore, the use of a rapid-readout, real-time radiation meter is recommended for several classes of measurement in CT. For the purposes of characterizing the dynamically changing x-ray beam in a CT scanner, a rate of 48

59 CT X-Ray Spectrum Characterization Figure 5.1. The traditional measurement of the HVL for a CT scanner. (a) Serial measurements are made with the x-ray gantry held stationary, a process typically requiring access to the service mode of the system. (b) A photograph showing a 0.6 cm 3 ionization chamber used for HVL measurements. A sheet of aluminum is positioned directly below the ionization chamber on the plastic cowling of the scanner. Figure 5.2. Measuring the HVL using a series of Al rings. (a) Schematic illustration of the method. (b) The concentric Al rings used for this method samples per second or higher is considered necessary. There are different types of technologies that can be brought to bear to achieve a high temporal bandwidth x-ray meter: (1) solid-state x-ray meters, and (2) air-ionization chambers with real-time readout capabilities. Solid-state x-ray meters can be fabricated from a number of different detector materials. A simple approach is to couple a scintillating material to a photodiode using a fiberoptic cable, assuring that the photodiode is outside of the x-ray beam or is well shielded. A key requirement for solid-state x-ray meters is that the x-ray scintillator material has a short decay constant. Most solid-state x-ray meters demonstrate excellent linearity as a function of air-kerma rate. One of the biggest limitations of solid-state x-ray meters is that in general they have a different response than air and therefore energy-dependent corrections are necessary to provide a signal measurement that is similar or identical to air ionization chambers. Although energy corrections are plausible in a free-in-air geometry for which x-ray scatter levels are small, much of the utility of a real-time x-ray dosimeter is in phantom measurements, in which scatter levels can be quite high. A large scatteredradiation component introduces uncertainty with respect to the effective energy of the x-ray beam, confounding accurate energy-correction algorithms. Nevertheless, it seems that real-time solid-state x-ray detectors can be designed and calibrated for use in real-time CT dosimetry. A real-time thimble chamber that uses air as the x-ray detector presents a technological challenge if a small detector volume is desired. The density of air is three orders of magnitude smaller than many solidstate detectors, and therefore the electronic-signal levels generated in air-based detectors are much 49

60 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY smaller, leading to noisy signals. Nevertheless, the use of air as the detection medium is appealing due to the long history of air-ionization chambers in diagnostic radiology applications Aluminum Cage with Real-Time Probe Method Most ionization chambers read out in the integration mode, in which they integrate the charge produced over a time interval that is typically from sub-seconds to several seconds. Real-time radiation meters are only now becoming available, and these systems are capable of accurately measuring a radiation beam of varying intensity over short periods of time ranging from 100 ms to 1000 ms. Thus, 1000 or more measurements per second can be made using real-time x-ray detector systems. When a real-time radiation meter is available, an aluminum-cage method for measuring the HVL is feasible. Similar to the ring setup (see Section 5.2.2), the real-time probe is positioned at the isocenter of the CT scanner using laser positioning, with the patient table retracted out of the beam. An aluminum cage (see Figure 5.3) has been designed to have a number of aluminum filters (eight in the configuration shown) of different thicknesses placed around the center of the cage in which the real-time probe is positioned. One or more axial CT scans are acquired, and the data derived from the real-time probe can then be used to compute the HVL. The measurement geometry is shown in Figure 5.4. Data generated from the real-time probe (in this case, Radcal Chamber Model 10X6-0.6) using this technique are illustrated in Figure 5.5a. This signal trace is used to produce the attenuation measurements described in Eq. (5.2), and is plotted in Figure 5.5b. There are a number of commercially available real-time radiation meters available, including airionization chambers and solid-state systems. Solidstate, real-time radiation meters include siliconbased systems as well as scintillator-based probes. For the solid-state radiation meters used to determine the HVL, in general, energy-dependent corrections are required. Figure 5.3. The aluminum cage for HVL measurement using a real-time probe. The system presents a number of different thicknesses of aluminum, interspersed with air gaps, into the x-ray beam. As the x-ray tube rotates during the scan, the central ray passes through each of the Al filters in the cage assembly, resulting in eight (or more) measurements with each rotation of the gantry. 5.3 Spectrum Assessment using the Tube Potential and the HVL There are a number of x-ray-spectrum models that can be used to generate relatively accurate x-ray spectra using empirical or semi-empirical methods (Boone and Seibert, 1997; Duan et al., 2011; Tucker et al., 1991a; 1991b; Turner et al., 2010). Common to all the models is the selection of the x-ray tube potential. With knowledge of the tube potential and the measured HVL, the model can be used to estimate the x-ray spectrum in an iterative manner. Figure 5.4. The HVL cage illustrated in the context of a rotating CT gantry. (a) Schematic illustrating use of the cage. (b) Photograph of a prototype HVL cage. 50

61 CT X-Ray Spectrum Characterization Figure 5.5. Results from an Al-cage measurement. (a) The signal trace generated by the real-time probe in the cage geometry for HVL assessment. This trace illustrates attenuated regions labeled a h, with the interspersed unattenuated measurements. These data were acquired on a General Electric VCT scanner for a tube potential of 120 kv, and with the medium bow-tie filter, using a prototype airionization chamber (Radcal, Monrovia, CA, USA). (b) The attenuation curve computed from the data shown in (a). The attenuation values corresponding to the specific signal components a h are labeled. The dashed line corresponds to the conventional measurement of HVL, and the solid line is that measured using the real-time air-ionization chamber and the Al cage. In a computer program that starts with an unfiltered x-ray spectrum, f(e), from tabulations, incremental thicknesses, t add, of absorber with linear attenuation coefficient m F (E) are added. The absorber material can be aluminum, or other materials that are known to be used by CT manufacturers to harden the beam. Other materials might include PMMA, copper, tantalum, or combinations of these. The x-ray spectrum is thus hardened by adding the thickness t add of a material with attenuation coefficient m F (E), and the computer program then iterates using the necessary added Al thicknesses to compute the HVL. This process of adding absorbers and then computing the HVL, is repeated until the thickness of added filtration t add results in a computed HVL that matches the measured HVL. Figure 5.6 illustrates the results of a least-squares approach for determining the modeled spectrum that most closely matches a measured spectrum of known tube potential and measured HVL. The value of t add at which the minimum squared difference between the measured and modeled HVL occurs is accepted, and the estimated x-ray spectrum f 0 (E) is defined as f 0 ðeþ ¼ fðeþe m FðEÞt add: ð5:3þ Figure 5.7 illustrates two different spectra, both generated with a tube potential of 120 kv but with substantially different inherent-plus-added filtration and hence different HVLs; Figure 5.7a shows a 120 kv spectrum with 2 mm of added Al filtration intrinsic to the beam, whereas Figure 5.7b shows Figure 5.6. Illustrative results of the iterative procedure used to estimate the inherent-plus-added filtration. As the amount of inherent-plus-added aluminum thickness is added, the calculated HVL using a spectrum model (Boone and Seibert, 1997) computed for a tube potential of 120 kv increases as shown by the curve with diamond symbols (left vertical axis). The squared differences between the calculated and measured HVLs are shown as the dashed curve (right vertical axis). The minimum in that curve corresponds to the best-fit spectrum parameters, in this example having a total of 9.5 mm Al of inherent-plus-added filtration, giving the measured HVL of 8.0 mm Al. also a 120 kv spectrum but with 15 mm of added Al filtration. Figure 5.7 underscores the importance of knowing the HVL in addition to the x-ray tube potential. It is noted that if the spectrum model used to produce f 0 (E) was capable of exactly matching the actual x-ray spectrum emitted by the x-ray tube 51

62 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY anode, then the m F (E)t add term should be the same at all x-ray tube potentials because the inherent filtration does not change within the x-ray tube assembly when the x-ray tube potential is changed. However, due to inherent inaccuracies of the spectrum model, the optimal estimated spectra f 0 (E) will have slightly different thicknesses t add for different tube potentials. Differences between actual and estimated inherent þ added filtration also will occur when the precise elemental composition of the filtration is not known Off-Angle HVL Assessment The HVL described so far corresponds only to the HVL along the central ray of the scanner, i.e., where the fan angle is zero (u ¼ 0). Thus, the influence of the bow-tie filter is not included in the HVL assessment, as the bow-tie filter is conventionally defined as having zero thickness at u ¼ 0. Because the bow-tie filter adds additional x-ray absorber material gradually toward the periphery of the fan angle, the beam will be increasingly hardened by this additional filter, and the HVL will increase. If there were interest in measuring the off-angle HVL, then the only direct method would be the conventional method outlined earlier. Both the Al-ring and the Al-cage methods outlined above are designed to measure the HVL along the central ray of the scanner, and they cannot measure the off-angle HVL. An indirect method for estimating the off-angle HVL is to perform the assessment at the center of the field as described above, to use the known bow-tie filter-thickness distribution to further harden the beam using appropriate attenuation coefficients, and then to compute the HVL. Estimation of the bow-tie thickness as a function of angle will be described in Section Typical HVL Values in CT The HVLs typical in conventional radiography are compared with those typical in CT in Figure 5.8; measured HVLs from two scanner types are shown. Measured HVLs as a function of tube potentials for several CT models are provided in Table 5.1. It is clear from Figure 5.8 that the typical HVL in CT is considerably larger than that generally used in conventional radiographic imaging. The primary purpose for the harder beam (i.e., higher HVL) in CT is to reduce the absorbed dose in the patient, and to reduce the impact of beam-hardening artifacts in CT images (see Section 2.4.5). HVL measurement in the clinical CTenvironment can be useful as a quality-assurance tool, and is Figure 5.8. Typical values of the HVLs used in CT and radiography. Measured HVL values for two commercial CT scanners are shown. For the radiography curve, the HVLs were modeled (Boone and Seibert, 1997) using a total of 2.0 mm of added filtration (lower solid line), and for the CT curve a total added filtration of 10.0 mm (upper solid line). Figure 5.7. X-ray spectra generated using a spectrum model, the known tube potential, and the measured HVL. (a) A 120 kv spectrum, which has a small amount of inherent filtration, resulting in a measured HVL of 5.1 mm of Al. (b) A 120 kv spectrum for an x-ray system with more inherent filtration, resulting in a harder x-ray spectrum with a measured HVL of 9.0 mm of Al. 52

63 CT X-Ray Spectrum Characterization Table 5.1 Typical values of the HVL in mm AL for several commercially available CT scanners (Mathieu et al., 2010). These were measured at the isocenter for the large or body bow-tie filter X-ray tube potential GE VCT GE Lightspeed-16 Siemens Sensation kv kv kv kv kv a Premier One models. Toshiba Aquillion a likely to be of value as a parameter during scanner acceptance-testing. The value of the HVL for a given tube potential is an indicator of beam quality (often used a surrogate for effective energy), which should remain relatively stable over time and after x-ray-tube changes. Thus, if the HVL can be measured in a relatively easy and rapid manner, it can and should become a useful parameter for monitoring beam quality as a part of a quality-assurance program in CT, just as it is in radiography, fluoroscopy, and mammography settings. In a research setting, the estimated spectrum f 0 (E) determined for a given tube potential and measured HVL canbeusedinmontecarlosimulations to estimate organ dose or other dosimetric quantities. For CT dosimetry, and in particular in Monte Carlo based dosimetry studies, the use of accurate x-ray-beam spectra is an important consideration in the assessment of absorbed dose in patients, phantoms, and in air. Moreover, as the number of scanner models, typical tube potentials, and acquisition protocols continue to increase, it might become necessary to generate dosimetry tables based on generic beam-quality parameters, e.g., tube potential and HVL. This approach is common in mammography but not yet in CT. 53

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65 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds CT-Output Characteristics Measured in Air 6.1 Introduction Section 5 discussed methods to evaluate the x-ray spectrum at the isocenter of the scanner. In this Section, the distribution of air kerma in both the lateral (x, y) and z dimensions is discussed in detail. Although the use of a physical phantom is considered necessary for the measurement of absorbed dose in objects approximating patients, in most cases such measurements reveal more about the phantom s attenuation and scattering properties than about a specific CT scanner s x-ray-tube airkerma (output) characteristics. Therefore, characterizing the air-kerma distribution as a function of both the fan angle u and longitudinal spatial variable z is a valid, useful, and rigorous method for quality assurance and reproducibility assessment. Additionally, given the important reliance of CT dosimetry on Monte Carlo simulations, the distributions f air (z) and f A (u) are key inputs for accurate Monte Carlo modeling of energy deposition. The function f air (z) is defined as the air-kerma distribution along the z axis at the isocenter of the scanner, in air. The function f A (u) is defined as the angular measurement of air kerma along the center of the fan beam as a function of fan angle, u. Most commercial x-ray CT scanners use the same basic components in the tube assembly, which include: (a) an x-ray tube that is operated between 70 kv and 140 kv, (b) inherent filtration as part of the x-ray tube port and related structures, (c) permanently installed added filtration to harden the entire x-ray beam, (d) a compensating bow-tie filter that partially equalizes air kerma to the patient and detectors, and (e) collimators to control the longitudinal (z-axis) extent of the beam. This is illustrated schematically in Figure 6.1b. Additional collimators to reduce overranging (Section 2.2.2) during helical acquisitions are a part of newer CT scanners. Each CTscanner manufacturer will have different implementations of these components, and therefore individual one-dimensional measurements in both directions, or simultaneous two-dimensional measurements, made free-in-air, are necessary to characterize each CT scanner s specific output distribution. 6.2 Theoretical Methods for Predicting f air (z) The air-kerma distribution along the z axis of a CT scanner, f air (z), is fundamentally related to the geometry of the scanner and the intensity distribution of x-ray emission from the x-ray-tube focal spot. The x-ray tube rotates around the CT gantry at very high rotation speeds. For scanners with a rotation period of 0.33 s, assuming a 1.4 m gantry diameter, components at the outer edge of the gantry experience a speed of 48 km/h, and a centripetal acceleration of almost 26 g. The x-ray-tube anode rotates in the same plane as the rotating gantry (see Figure 6.2a), which is necessary to reduce gyroscopic effects, and this orientation is also desirable from a beam-coverage consideration. Hence, the anode cathode dimension is parallel to the z axis of the scanner, and thus the heel effect runs along the z axis. A simplified geometry showing some of the critical geometrical parameters in the x-ray source assembly is illustrated in Figure 6.2. Dixon et al. (2005) used a geometrical construct similar to that shown in Figure 6.2b, and derived the profile of the x-ray beam in the z direction from first principles. A comparison of the analytical result to the measured air-kerma distribution from a General Electric Lightspeed-8 system is shown in Figure 6.3. The air-kerma profile was measured using film (Kodak EDR2), correcting for the characteristic curve. In the derivation, Dixon and colleagues assumed a Gaussian focal-spot intensity distribution, and thus the penumbra on either side of the x-ray beam was modeled as a cumulative normal distribution. Due to parallax differences on either side of the beam resulting from the anode angle, slightly different focal-spot dimensions were used to optimize the analytical fit to the measured curve. The Dixon derivation extends earlier work (Gagne, 1989) and demonstrates that the relative air-kerma profile of the x-ray beam along the z axis of CT scanners can be accurately # International Commission on Radiation Units and Measurements 2013

66 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY explained by straightforward physical and geometrical principles. 6.3 Measurement of f air (z) Optically Stimulated Luminescence Systems Arrays of optically stimulated luminescence (OSL) dosimeters were developed by a commercial manufacturer (CT Dosimeter, Landauer, Inc., Figure 6.1. The components of a modern CT scanner tube assembly. X rays emanating from the tungsten anode pass through inherent þ added filtration, and are then attenuated by the beam-shaping filter. Finally, collimator blades truncate the beam in the z and þ z directions. Glenwood, IL, USA) to provide for the measurement of f air (z) in CT. These OSL systems have excellent spatial resolution and are well-suited for qualitative measurement of air-kerma profiles free-in-air along the z axis. The system uses a long strip of AlO 2 film inside a light-tight plastic cylinder that is 150 mm long and 10 mm in diameter. To measure f air (z) directly, the dosimeter is placed in air at isocenter; it is also designed to fit within a phantom. The OSL dosimeter is exposed under typical CT operating conditions in the axial mode, and is then sent back to the manufacturer to be analyzed. The manufacturer s reader uses a 0.2 mm slit width that samples every 0.05 mm and uses a 20-point smoothing average to generate output values. From the resulting profiles (see Figure 6.4), one can obtain the raw values for f air (z). In addition, derived parameters such as the full-width at half-maximum can be calculated, which can be compared with the nominal x-raybeam collimation to determine the extent of overbeaming (see, e.g., Liu et al., 2005). Although the energy response of the OSL dosimeter is reasonably constant over the x-ray energies involved, it is not the same as that of ionization chambers. However, for OSL measurements made free-in-air at the isocenter of the CT scanner, the relative intensity of the x-ray-beam profile is of primary interest and not the absolute values; in this case, a Figure 6.2. X-ray-tube geometry in a CT scanner. (a) The x-ray tube in a modern CT scanner rotates in an orientation such that the plane of the anode is parallel to the plane of gantry rotation. (b) The geometry of the electron beam striking the anode. As the x-raytube potential increases, the kinetic energy of the electrons incident on the anode increases, and so does the average depth of penetration (DoP). As x rays are produced within the anode, they are attenuated by different thicknesses of anode material along the z axis of the beam, with greater thickness on the anode side of the field (giving rise to the heel effect). This basic geometry can be used to derive the theoretical shape of the air-kerma profile along the z axis. 56

67 CT Output Characteristics Measured in Air resolution available but exhibits non-linearity at higher optical density and has some over-response due to its higher average atomic number than air. In order to produce quantitative results, the developed film needs to be digitized and then corrected for non-linearities, if accurate dose profiles are desired. The absolute accuracy of film dosimetry is very much related to the consistency of the film processing conditions, including developer concentration and temperature. Figure 6.3. X-ray-beam profiles, f air (z), along the z axis. Theoretical (curve) and measured ( points) profiles are compared. The heel effect is readily seen. slight energy dependence should not be a limiting factor TLD Measurements Another type of dosimeter that provides good spatial resolution in one dimension is the thermoluminescence dosimeter (TLD). Although its spatial resolution is not as good as that for the OSL dosimeter, its lower atomic number gives a smaller overresponse at low photon energies. An array of TLDs allows for measurement of absolute absorbed-dose profiles with a spatial resolution of about from 1 mm to 5 mm. Figure 6.5 shows the f air (z) measured using TLDs at 3 mm intervals. These data were measured on a General Electric Lightspeed 4 CT scanner with a nominal beam width of 20 mm. Because TLDs need to be read out individually, there is a practical limit on the spatial sampling that can be achieved using these dosimeters (McNitt-Gray, 2002; Ogden and Huda, 2008) Film Figure 6.6 shows the f air (z) measured using XV film (Eastman Kodak, Rochester, NY, USA) placed in the CT field of view. After exposure and development, the film was digitized, and the measured sensitometric curve was used to convert the optical density to relative exposure (i.e., air kerma) (Liu et al., 2005). Film has perhaps the best spatial Computed-Radiography Detectors The f air (z) measured using a computed radiography (CR) plate is shown in Figure 6.7. CR plates typically comprise a BaFBr compound and thus exhibit an energy sensitivity different from airionization chambers. Nevertheless, as a relative measurement of the beam profile with excellent spatial resolution, CR represents a modern solution compared to film, as film and the necessary film processors are becoming increasingly rare in the modern clinical environment. Although CR systems are used at many facilities, they are not ubiquitous, so availability will be an issue in some settings. Furthermore, one needs to use the raw CR image read-out in the high-dynamic-range mode, and no processing should be applied (other than basic corrections for inactive detector elements and for differential collection efficiency of the read-out optics and electronics). The so-called for display images should not be used because they have been subjected to processing that alters the quantitative integrity of the gray scale in the image. Therefore, experience with CR readers and their modes of operation is required to use these systems successfully for assessment of the dose distribution in CT Real-Time Radiation Detectors A radiation probe with real-time (1 khz) readout (see Section 5.2.3) can be translated through the x-ray beam at isocenter, and the temporal readout will give a trace as a function of z in the beam. Assuming constant velocity, the relationship between time and position is given by z ¼ z start þ vt, where z start is the (arbitrary) starting position of the x-ray detector. A real-time x-ray probe (Radcal Accugold, Monrovia, CA, USA) was used to demonstrate the potential of this approach. Figure 6.8 illustrates the measurement geometry using the real-time probe, and Figure 6.9 shows measured beam profiles, f air (z), for a commercially available CT system (General Electric VCT). These data were acquired using the CT table for translation of the probe through the beam. The probe was 57

68 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 6.4. Relative profiles, f air (z), measured for a Toshiba CT scanner operating at 120 kv using OSL detectors. The one-dimensional view of the x-ray beam intensity distribution along the z axis is shown for: (a) a 32 mm nominal collimation setting, and (b) a 128 mm nominal collimation setting. Figure 6.5. Relative profiles, f air (z), measured using TLDs. Profiles are for both the head and body bow-tie filters on a General Electric Lightspeed-16 scanner. Figure 6.6. Relative profiles, f air (z), measured using x-ray film. The optical density is shown as solid circles. The characteristic curve of the film was measured and used to correct the optical density to air-kerma units (right axis). extended out in front of the table, so the table provided mechanical translation but was not in the x-ray beam. The f air (z) measured with the real-time probe relies on stable table velocity. The raw measurement of f air (z) using this approach also includes the influence of the length (and sensitivity profile) of the real-time probe. Let the true profile be f air (z) and the response function of the real-time probe be q(z), then the measured profile fair m ðzþis given by f m air ðzþ ¼Ð 1 1 f airðz 0 Þ qðz z 0 Þ dz 0 : ð6:1þ If q(z) is small in z extent in comparison to f air (z), then f m air ðzþ ffif airðzþ. In the special but realistic case that q(z) is a rect function, the influence of the probe length, l probe, can be removed by deconvolution in the frequency domain: f air ðzþ ¼FT 1 FT½ fair m ðzþš ; ð6:2þ sincðl probe =nþ where FT is the Fourier transform, FT 21 is the inverse Fourier transform, sinc(l probe /n) is the Fourier transform of a rect function of length l probe, and n is the frequency. Here the length, l probe,is the active length of the chamber. When the same real-time instrument is used, e.g., in annual x-ray beam comparisons, serial comparisons among the uncorrected profiles, fair m ðzþ, would be adequate for consistency checking Summary of f air (z) Measurements The f air (z) in CT can be measured using a number of different technologies with adequate-toexcellent results. There are tradeoffs with each method, and it is ultimately up to the CT scientist or medical physicist to determine which approach is most appropriate for their specific application and institution. It is observed that with film processors rapidly becoming less available in the hospital setting, the film-sensitometric approach will be more difficult to implement in coming years. CR is 58

69 CT Output Characteristics Measured in Air Figure 6.7. Relative profile, f air (z), measured for a General Electric VCT scanner at 120 kv using a CR detector system. An image of the profile is shown in the left panel, and the profile taken through this is plotted in the right panel. These data were not corrected for the response of the CR plate. Figure 6.9. Probe output from f air (z) measurements for the 20 mm and the 40 mm beam collimation in a GE VCT scanner. The probe sensitivity function has not been deconvolved. Figure 6.8. The geometry for measuring f air (z) along the z axis using a small ionization chamber. The ionization chamber is mounted in front of the CT table and translated through the x-ray beam at the isocenter by table translation with the scanner in the helical acquisition mode. The resulting profile is the convolution of the beam profile and the ionization chamber response function in the z direction. a viable approach only if the institution has CR plates and reader systems available, and even then special processing modes are required and nonlinear correction methods are necessary to produce accurate results. The TLD approach is appealing, but is time-consuming and requires a large number of TLD readings to make high-resolution measurements of f air (z). The OSL approach is nearly ideal if one is willing to wait for the physical transportation of the OSL dosimeter (usually by mail) to a commercial laboratory to obtain the results. The translated thimble chamber (or other radiation detector) requires a real-time readout system, and some subsequent processing is required to deconvolve the detector response function. This latter approach is appealing because it provides prompt results, is performed with portable instrumentation, 59

70 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY and the necessary signal processing can be implemented using pre-programmed spreadsheet software. Although real-time radiation detectors are not widely available at this time, it is anticipated that as CT dosimetry progresses the use of real-time dosimeters will become commonplace. 6.4 Measurement of f L (x) orf A (u) Measurement of f L (x) The function f L (x) represents a linear measurement of air kerma across the field of view, and the function f A (u) represents an angular measurement of air kerma. The angle u is defined here as the angle from the central ray of the beam in the transverse x y plane, such that at the center of the field u ¼ 0. This angle is called the fan angle. Evaluation of the beam profile as a function of the fan angle essentially characterizes the angledependent attenuation of the bow-tie filter that the scanner employs. This can also be called the bowtie filter function. Beam-profile data are useful for two primary reasons: (1) accurate CT dosimetry is increasingly dependent upon Monte Carlo computations of dose-conversation coefficients, and the characterization of the bow-tie-filter function is essential for accurate computer modeling in CT. For users of CT Monte Carlo approaches, the data derived from a measurement of the air kerma as a function of fan angle for a variety of CT scanners are extremely useful. (2) For the clinical practitioner, the f L (x) and f A (u) provide characterization of one of the two dimensions of the air-kerma distribution from x rays incident upon the patient. Combined with f air (z), characterization of f A (u) (or f L (x)) provides a two-dimensional understanding of the x-ray output properties. Because at least two bow-tie filters (body and head) are used on most CT scanners and because of the different beam spectra that are possible, the measurement of all combinations can require 8, 12, or more measurements for each CT scanner. Thus, a simple method for performing the beam profile measurement is desirable. The profile f A (u) requires that the air kerma (or air-kerma rate) be measured on a radius of curvature centered at the x-ray source, such that beam divergence due to the inverse-square law and solid-angle effects are factored out. That is, f A (u) should represent the angular dependence of the air-kerma profile; f A (u) profiles measured at different radii from the x-ray source should vary only by a scalar constant, and thus f A (u) profiles normalized to unity at u ¼ 0 will be independent of the distance from the x-ray source. Note that at the center of the fan beam (where u ¼ 0) the bow-tie filter has no effect on f A (u), but there is still considerable x-ray beam filtration material in the tube assembly. Measuring f A (u) can be difficult, however, because the location of the x-ray source is not obvious due to the CT-scanner cowling and because physical positioning of the detector along a radius of curvature is challenging. For most experimental settings, therefore, a measurement of the airkerma profile along a line running through the isocenter is more convenient. The results of such measurements are related to f A (u), and are referred to here as f L (x), where the (horizontal) x axis is orthogonal to the central ray (where u ¼ 0) and generally runs through isocenter. Due to the rotational symmetry in CT, it is recognized that measurements along the (vertical) y axis are the same as those made along the (horizontal) x axis, as long as the measurement is made orthogonal to the central ray. In all cases, however, this profile will be referred to here as f L (x). Turner et al. (2009) described a method for using the vertical adjustment capabilities of the CT couch (with an additional vertical stand) to make measurements along a line running through the isocenter of the CT system, and this technique is illustrated in Figure Ideally, this measurement of f L (x) would be performed with a relatively small device (such as a small-diameter thimble chamber). In practice, Turner et al. (2009) used a 100 mm pencil ionization chamber placed in air and positioned perpendicular to the scan plane so that only a portion of the chamber s length was irradiated. This method also requires that the CT gantry be in a fixed, non-rotating position; a 3 o clock position was used with the central ray of Figure The experimental geometry used to characterize the beam profile in the x direction. The position of the ionization chamber is moved vertically using the CT tabletop, with the stationary x-ray source positioned in the 3 o clock position. 60

71 CT Output Characteristics Measured in Air Figure Linear profiles for small and large bow-tie filters. These results for f L (x) indicate the shape of the bow-tie filter function as a function of linear distance across the field of view, and these data include the 1/r fall-off as discussed in the text. Figure The x-ray-beam profile, f L (x), for a General Electric Lightspeed 16 scanner measured with a pencil chamber. The bow-tie filter function for both the head and body filters is shown, along with no filter (Huda, personal communication). The use of the pencil chamber results in a 1/r fall-off. the x-ray beam aligned horizontally across the top of the CT couch. Measurements were made at a series of positions starting from the central ray and extending to the edge of the fan beam. This allowed the entire extent of the bow-tie filter to be characterized. These measurements were obtained using vertical table motion, with a test stand of known height to extend the range of measurements beyond the range of table movement. The use of the table-height adjustment simplified the measurement procedure as this was controlled electronically and the table height position is accurately reported by the CT-scanner hardware. Air kerma was recorded as a function of table height. Figure 6.11 shows the measured f L (x) values and illustrates the differences in attenuation between the head and body bow-tie filters. Ogden and Huda (2008) also made use of a 100 mm pencil chamber to measure f L (x), although their experimental setup was performed with the x-ray tube parked at the 12 o clock position, and repositioning of the ionization chamber was performed manually. Figure 6.12 shows the measured data, including measurements for the head and body bow-tie filters, as well as the case when the bow-tie filters were retracted. For the geometries used in both the Turner et al. (2009) and the Ogden and Huda data, the source-to-probe distance increased for the more peripheral measurements, resulting in intensity reductions at the periphery. If a small detector (fully contained within the beam) is used, then the dependence on distance would be 1/r 2, i.e., the familiar inverse-square law. However, a 100 mm long pencil chamber extending beyond the limits of the x-ray beam was used to collect both the Ogden and Huda and the Turner et al. data. In this geometry, the dependence on Figure Uncorrected linear profiles, f L (x), from measurements with a CR plate of a 40 mm wide beam from a General Electric VCT scanner. An example image is shown at the top of the figure. Results are shown for the body, medium, and head bow-tie filters. These profiles were not corrected for the response of the CR plate. distance is 1/r, as will be discussed in Section The curvature that is visible in the Ogden and Huda measurements in the case of no bow-tie filter (see Figure 6.12) demonstrates this influence, which affects the other measurements (those with bow-tie filters) as well. Seibert ( personal communication) used CR plates to characterize f L (x). Figure 6.13 shows such results for f L (x) associated with three different bow-tie filters on a General Electric VCT scanner. 61

72 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY This approach uses CR plates that are commonly available at many medical centers. The gray scale produced by CR systems is not a linear function of the air kerma, and therefore a calibration procedure is necessary if absolute values are required. Evaluation of the characteristic curve of the CR plate is a straightforward process (Lui et al., 2005) Measurement of f A (u) McKenney et al. (2011) report a method that uses a single radiation detector with real-time readout to measure f A (u) directly. The real-time detector was placed in air, near the periphery of the CT field of view, as shown in Figure No other object was placed in the x-ray beam, and the table was retracted. The air-kerma rates were recorded in real time (1 khz) during CT acquisitions at specified technique factors (tube potential, tubecurrent time product, etc.) over several gantry rotations; the results are shown in Figure In this method, as the gantry rotates, the air-kerma rate is recorded at the location of the probe. The air-kerma rate changes due to the varying angle u through the bow-tie filter, and also because the distance between the probe and the x-ray tube changes, resulting in a change of intensity due to the inverse-square law. Referring to the geometry shown in Figure 6.14, there are two points in the 2p rotation of the gantry at which the bow-tie filter has no effect (i.e., at a fan angle, u ¼ 0), and in both cases this occurs when the x-ray tube, the isocenter, and the x-ray probe are co-linear. The first point corresponds to the maxima in the signal train, at u ¼ 0, 2p, 4p,..., at which the x-ray tube is closest to the probe, maximizing the intensity in regard to the inverse-square law and minimizing the influence of the bow-tie filter. The other point in the rotation of the gantry at which the bow-tie filter has no effect is when u ¼ p, 3p, 5p,..., at which the x-ray tube is on the opposite side of isocenter from the x-ray probe. Image-processing techniques are used (McKenney et al., 2011) to identify the peaks at even multiples of p in the signal trace (gray line in Figure 6.15), and the odd multiples of p are identified as they are midway between adjacent maxima. From these two values of the signal amplitude (averaged over several gantry rotations), the effect of the inverse-square law in the absence of the bow-tie filter s influence can be deduced, and this is shown as the black line in Figure The alignment of the odd-p and even-p locations along the time-domain signal train allows the gantry angle and the fan angle to be deduced as a function of time as well. Using the data given in Figure 6.15 along with a well-defined mathematical construct (McKenney et al., 2011), the bow-tie filter function can be determined. The resultant bow-tie filter function, f A (u), is shown in Figure 6.16 for four x-ray-tube potentials. This procedure does not require precise probe positioning because the distance between the x-ray probe and the isocenter can be determined mathematically from the measured data. Thus, probe positioning does not require careful physical alignment; the probe can simply be placed at a convenient location near the edge of the scanner s field of view. The probe, Figure The measurement geometry for the characterization-of-beam-relative-attenuation (COBRA) method (McKenney et al., 2011). Angles are defined in (a), and dimensions are defined in (b). A small ionization probe is placed completely within the x-ray beam on the z axis, toward the periphery of the scanner s field of view. The table is retracted from the field of view for this measurement. 62

73 CT Output Characteristics Measured in Air Figure The output of a real-time probe for the COBRA method (McKenney et al., 2011). The gray trace indicates the raw output of the real-time probe. The minima and maxima of that trace are analyzed, and from that the inverse-square law (shown as the black trace) is used to compute the x-ray beam intensity in the absence of the bow-tie filter. The ratio of these two curves allows one to calculate the bow-tie filter function. Figure Theoretically derived thickness of a bow-tie filter as a function of fan angle. Using dual-energy decomposition techniques and the data shown in Fig. 6.16, the thicknesses of bow-tie filters were computed assuming a PMMA filter (solid circles) and an Al filter (open circles). Figure The fan-beam geometry of a CT scanner, illustrating the fundamental differences between f A (u) and f L (x). Here d sic is the source-to-isocenter distance, and x ¼ 0 at the central ray of the fan beam. Figure Illustrative bow-tie filter functions from the COBRA method. Results for a Siemens ASþ CT scanner operated at four different x-ray tube potentials. The effect of the bow-tie filter is greater at lower tube potentials, as expected (McKenney et al., 2011). however, does need to be fully contained within the x-ray field of the scanner such that there is no partial-volume irradiation. If the bow-tie filter function is determined at two or more x-ray beam energies, dual-energy decomposition techniques (Lehmann et al., 1981) can be used to estimate the actual filter thickness. Figure 6.17 shows derived thicknesses of the bow-tie filter assuming a composition of either PMMA or Al. There is a straightforward difference between f L (x) and f A (u), as illustrated in Figure As described previously, conventional measurements of bow-tie-filter effects typically rely on the translation of the measurement device laterally across the field, or on the use of a linear or planar detector system, with which f L (x) is measured. For a given source-to-isocenter distance, d sic, the angular function f A (u) is given by: f A ðuþ¼g d 2 sic d 2 sic þ x2 f LðxÞ ; ð6:3þ where the relationship between the angle u and distance x is given by u ¼ tan 1 x : ð6:4þ d sic The value of g to be used in Eq. (6.3) depends on the type of measurement device that is used. For measurement systems that are spherical or cylindrical (such as a cylindrical chamber or TLD rods), the cross section of the radiation sensor is generally not angular dependent, and g ¼ 1. For a linear or planar measurement system such as film or a CR imaging plate, there is a slight change in the 63

74 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY sensitivity given by g ¼ 1 cosðuþ : ð6:5þ For a measurement made in the plane of the isocenter, the maximum angle at the periphery of the field is about 0.45 radians ( 268), corresponding to a maximum value of g of about For measurements made along a line using a pencil chamber placed orthogonal to the CT fan beam, the relationship between f A (u) and f L (x) becomes a 1/r function instead of 1/r 2, due to the one-dimensional nature of the pencil chamber: d sic f A ðuþ ¼gqffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi f L ðxþ: ð6:6þ d 2 sic þ x2 For Monte Carlo calculations, the function f A (u) is generally more useful than f L (x) in most code systems. Therefore, linear measurements should be converted to angular functions. For example, the data shown in Figures 6.11 and 6.12 should be corrected using Eqs. (6.6) and (6.4), where g ¼ 1 due to the cylindrical shape of the ionization chamber used. The curves shown in Figure 6.13, in addition to correction for the response of the CR system, should be converted to f A (u) using Eqs. ( ). Equation 6.3 is used instead of Eq. (6.6) in this case because the detector elements are fully contained within the x-ray field and therefore have a 1/r 2 dependence with distance. Because the CR plate is planar, geometrical foreshortening occurs away from the central axis and therefore the correction factor described in Eq. (6.5) is necessary. Note that the COBRA method measures f A (u) directly (see Figure 6.16), and therefore no correction factors are necessary when this approach is used. 6.5 Planar Measurements of the CT Beam Profile Dosimetry techniques that permit either qualitative or quantitative assessment of a twodimensional air-kerma profile can characterize the entire x-ray field produced by the CT-scanner source assembly. In addition to spatial changes in the air kerma (e.g., due to heel effect, penumbrae, etc.), a two-dimensional measurement will characterize the impact of the inherent and beam-shaping filters and of the collimator subsystems. The twodimensional intensity distribution can be measured using a planar detector system such as film, CR, or a solid-state system. A planar detector placed at the plane of the isocenter of the scanner will measure a field defined as f P (z,x). Gorny et al. (2005) used Gafchromic XR-QA Dosimetry Film (International Specialty Products Inc., Wayne, NJ, USA), in a General Electric CT/i scanner operated at 120 kv to record the twodimensional radiation intensity pattern orthogonal to the central beam and through the isocenter of the scanner. After exposure, this self-developing film develops over time; a photograph of the developed film is shown in Figure 6.19a. The film was digitized using a commercial color, flatbed scanner, and the so-called red-channel component was isolated digitally and mapped into a pseudo-colored image, giving the two-dimensional distribution shown in Figure 6.19b. Using data from a calibration study, the signal was properly scaled, and the resultant two-dimensional air-kerma distribution is shown in Figure 6.19c. CR can also be used to characterize the twodimensional distribution of radiation emerging from the x-ray tube assembly of a CT system. Figure 6.20 illustrates the two-dimensional intensity distribution for a General Electric VCT system. CR has a low-amplitude, long-range glare function, as reported by Liu (2005) and observed by Seibert ( personal communication). This glare is a result of the long-range (over centimeters) propagation of optical light in the collection optics of the CR system. If not corrected for, this glare can lead to artifacts. Figure 6.7 illustrates such an artifact in a one-dimensional plot. Due to this concern, CT relative intensity distributions measured using CR should be considered as qualitative estimates and not as accurate measurements. 6.6 Summary The characterization of the two-dimensional x-ray beam emerging from a CT-scanner tube assembly, using either f P (z,x) orf air (z) combined with either f L (x) orf A (u) might in some cases supplant the need for in-phantom measurements. In particular, such measurements will be extremely useful for assessment of CT air-kerma reproducibility over time, or after an x-ray tube is changed. It is unlikely that changes in the absorbed-dose distribution in the patient or in a phantom will occur if the x-ray beam emerging from the x-ray tube head is consistent both spatially and in terms of intensity over time. Although a number of different detector systems have been discussed for such measurements, including film, CR, optically stimulated luminescence, TLDs, and real-time detectors, it is expected that the radiation measurement tools that 64

75 CT Output Characteristics Measured in Air Figure Use of radiochromic self-developing film to determine the relative two-dimensional distribution. A photograph of the self-developing film exposed at the isocenter of the CT scanner is shown in (a). The analog film was digitized, and the red channel was used with appropriate characteristic-curve normalization to determine the relative two-dimensional radiation-intensity distribution, shown in (b). An isometric plot of the distribution is shown in (c). Figure The f P (z,x) profile measured using a CR plate. are most accessible will be the most useful at a given institution. The selection of detectors is large and the availability of solid-state devices is growing; however, the air-ionization chamber is still preferred when accurate, air-kerma measurements are the goal. Solid-state detectors can provide excellent relative measurements, and in many cases are accurate if conventional x-ray-beam spectra are used and energy correction factors are employed appropriately. Some caution is necessary even when using airionization chambers in terms of the measurement Figure An illustration of a f air (z) profile, with thimblechamber profiles aligned in different locations in the x-ray beam, illustrating that slight changes in the positioning of the thimble chamber can result in appreciable imprecision in the measurement. A 100 mm pencil chamber cannot make accurate air-kerma measurements in this geometry, due to the inhomogeneous air-kerma distribution incident upon it. set-up for f air (z). Figure 6.21 illustrates an ionization chamber positioned parallel to the z axis of the x-ray beam. When a short thimble chamber is used, its position along z is critical in making accurate and reproducible measurements because the x-ray beam in many scanners has significant inhomogeneities along the cathode anode axis due to the heel effect. Small placement errors along z can therefore lead to slightly different output results among measurements. Long ionization chambers, such as the 100 mm pencil chamber, can interrogate the entire beam width, but the partial-volume correction factor used to convert the meter reading to an 65

76 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY accurate air-kerma value is ambiguous because the edges of the beam are ill-defined, and also because the x-ray beam is inhomogeneous along z. Both of these effects make the 100 mm pencil chamber an ill-suited tool for characterizing the absolute air kerma for a CT x-ray tube head. Given the above considerations, long-term recommendations assume that real-time airionization chambers will eventually become routine measurement instruments in the CT environment. Using a small ionization chamber that is translated through the beam, as illustrated in Figure 6.8, both the spatial profile and the absolute air kerma can be determined using a minimum of hardware: just a laptop computer, electrometer, and the real-time ionization chamber. The f air (z) measurement using this hardware is a robust characterization of the x-ray-tube output, and is likely to be all that is required for CT-scanner output consistency measurements over time. Of course, complete measurement would include evaluation at all tube potentials, for all bow-tie filters, and for all clinically useful beamcollimation settings. 66

77 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds CT Dosimetry in Phantoms The standard 160 mm and 320 mm diameter, 150 mm long PMMA phantoms have been used for 40 y in CT dosimetry, and serve as the basis of CT dosimetric quantities such as CTDI vol, as discussed in Section 4. With the increasing sophistication of CT acquisition modes, as well as an interest in better characterizing the absorbed dose arising from the long scatter paths in CT, there is a need for a longer phantom. In the previous Section, characterization of the x-ray beam in air was discussed. When a phantom is introduced into the x-ray beam in CT, it becomes a major source of scattered radiation that is responsible for absorbed dose in parts of the phantom (and patient) away from the collimated primary beam. Hence, phantoms are an essential tool in understanding the distribution of absorbed dose in CT. 7.1 Axial Dose Profiles in Phantoms The axial or sequential CT scan involves the rotation of the x-ray-tube head around the patient or phantom with no table motion during rotation. In this basic mode of operation, it is instructive to understand the extent and shape of the absorbeddose profile along the z axis. It is realized that for axial scanning, the absorbed dose in the patient is essentially a summation of the absorbed-dose distributions from individual axial scans spaced at equal intervals along z. Those profiles, which can be measured as air kerma or absorbed dose, can be computed using Monte Carlo techniques or can be measured in physical phantoms using a number of different detector systems. In many cases, only the relative shape of the absorbed-dose profile is of interest, and the amplitude is arbitrarily normalized. In such cases, the quantity used to describe the profile shape can be either air kerma or absorbed dose, and the generic term profile is used. For the purpose of absolute dose assessment, either the quantities of air kerma or absorbed dose are reported. The shape, size, and anatomical complexity of the patient tend to complicate an understanding of the absorbed-dose distribution; therefore, it is routine to use simpler phantom shapes for this assessment. In most circumstances, a cylindrical phantom is used because it has rotational symmetry and is easier to fabricate than more complicated shapes. Figure 7.1 illustrates the basic geometry of a cylindrical phantom with a diameter d phantom and a length L phantom. Different investigators have studied CT scanners with a large number of beam widths in the z dimension, and the parameter L in Figure 7.1 represents the length of the phantom irradiated directly by the primary beam (scan length for axial or helical scans). Even though a number of custom CT phantoms have been described in the literature, it is a common to incorporate holes that allow the insertion of a radiation meter at the center or the periphery of the phantom. Figure 7.2 illustrates a single x-ray projection through a 300 mm diameter cylindrical water phantom, involving no x-ray-tube rotation around the phantom. In this numerical simulation, the x-ray beam from the General Electric VCT scanner was modeled mathematically. The inset in Figure 7.2 shows the primary x-ray beam in the axial plane, and the individual profiles run along the z axis at the points marked a through e in the figure. These data are useful to better understand what happens to the primary x-ray beam as it is attenuated by the phantom. The simulation involves primary radiation only; the entrance-beam profile (curve a) is narrow because it strikes the phantom at a position between the isocenter and the x-ray source where there is less beam divergence. As the x-ray beam penetrates the phantom, it is both attenuated and diverging, hence the subsequent profiles are lower in amplitude and wider. These data are from a single projection, but the x-ray beam profile along the z dimension in an axial CT scan represents the rotational summation of the data illustrated in Figure 7.2. At the isocenter (curve c), the dose distribution integrated over a 2p rotation of the gantry will have a shape identical to curve c, but away from isocenter the dose profiles will be the integral over angle (and hence depth of interaction) of the different x-ray-beam profiles. Monte Carlo simulations were performed using a number of cylindrical phantoms with different # International Commission on Radiation Units and Measurements 2013

78 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 7.1. A cylindrical phantom typically used in CT dosimetry. The generic cylindrical phantom has a length L phantom, a diameter d phantom, and can be scanned over a scan length of L. Two holes are illustrated, indicating locations where radiation detectors can be positioned. Figure 7.2. Absorbed-dose profile along the z axis for a single CT stationary projection (inset picture) from the 12 o clock position. The asymmetry in the curves is a result of the heel effect (see Section 6.2), in which the cathode anode direction runs left to right in the figure. These data were computed for a 40 mm wide CT beam modeled for a General Electric VCT scanner, and the truncation of the beam intensity (shown as gray to white) at the edges of the inset photograph is due to the body bow-tie filter. diameters, composition, and beam spectra (Boone, 2009). For these simulations, a very narrow (0.01 mm) primary x-ray beam was assumed incident upon the phantom, approximating a deltafunction input. Therefore, the dose distributions in the z dimension are considered dose-spread functions (DSF), similar to the concept of the line-spread function in imaging. Figure 7.3a shows the DSF at three different depths within a 300 mm diameter cylindrical water phantom for a 120 kv beam. The central region (R1) has the same area as the other regions, R2 and R3. Figure 7.3b illustrates the DSF for a 400 mm diameter cylinder using a Siemens body bow-tie filter, for three different phantom materials: polyethylene, PMMA, and water. As seen on these semi-log arithmic plots, after some initial curvature near z ¼ 0 the DSFs are approximately exponential along distances away from the center, which is not surprising. Figure 7.3c illustrates the DSF at the center of the phantom (R1) for different phantom diameters. The DSFs fall off more rapidly for smaller-diameter phantoms. This is understandable given solid-angle considerations of scattered radiation: smaller-diameter phantoms lose more scatter due to escape from the edges than do largerdiameter phantoms. Figure 7.3d illustrates DSFs at two different x-ray-tube potentials. Here, the higher-energy spectrum (140 kv) produces a broader DSF than does the lower-energy spectrum (80 kv). It is evident from these DSFs that the shape of the long-range exponential tails is related to the x-ray attenuation of scattered radiation, away from the very narrow central x-ray beam. This is why the DSF for low-density and lower effectiveatomic-number polyethylene is broader than those for water or PMMA in Figure 7.3b, and also why the higher-tube-potential DSF is broader (see Figure 7.3d). In both cases, the effective linear attenuation coefficient is smaller, leading to a larger tail in the DSF. It is observed from Figure 7.3a that the DSF in the center region (R1) of the 300 mm diameter phantom reaches a 10 % value at an axial distance of approximately 80 mm, for a full width at 10 % of the maximum of about 160 mm. Nakonechny et al. (2005) used a Phillips PQ-5000 system running at a tube potential of 130 kv, as well as a Phillips MX-8000 Quad system at 120 kv, both with bow-tie filters, to study the axial absorbed-dose profiles in a water-equivalent plastic phantom and in the standard CTDI body phantom. These investigators used a small-volume air-ionization chamber as well as TLDs, but their primary tool was a diamonddetector array for measuring the absorbed dose along the z axis in the phantom. The water-equivalent phantom was elliptical, 200 mm 300 mm in crosssection, with a length of 300 mm. The absorbed-dose profiles for the PQ 5000 are shown in Figure 7.4a. The PQ-5000 single-detector-array scanner was used in the measurement, with primary beams ranging from 3 mm to 10 mm in width. The MX 8000 scanner is a four-slice system, and the absorbed-dose profiles are shown in Figure 7.4b for nominal slice widths ranging from 4 mm to 20 mm. It is observed from these profiles that the full width at 10 % of maximum is approximately 140 mm for the 10 mm nominal beam widths, and thus the scatter tails extend a total of 140 mm 10 mm ¼ 130 mm. For the MX8000 scanner, the tails reached a total width of about 180 mm for the nominal 20 mm beam width. Subtracting the primary-beam width as a crude correction for the width of the primary beam, the scatter tails reach a full width at 10 % amplitude of about 160 mm. 68

79 CT Dosimetry in Phantoms Figure 7.3. The DSF for infinitely long phantoms and a very narrow primary incident x-ray beam (0.01 mm). (a) DSFs for three regions in the phantom, R1, R2, and R3, illustrated in the inset. These data are for a tube potential of 120 kv and a 30 cm diameter water phantom using a General Electric body bow-tie filter. (b) The influence on DSF of phantom composition is illustrated for a 120 kv scan in a 40 cm diameter phantom with a Siemens body bow-tie filter. The profile data are for region R1. (c) DSF profiles are illustrated for phantoms of different diameter, for a 120 kv scan in a water phantom using a General Electric body bow-tie filter. The data show the profiles for region R1. (d) DSFs are shown for two different beam spectra, showing greater scattering for higher-energy spectra. These data are for region R1, using a General Electric body bow-tie filter, and a 30 cm diameter water phantom. Figure 7.4. Axial absorbed-dose profiles measured by Nakonechny et al. (2005). Profiles at various primary-beam scan widths are shown for (a) a Philips PQ5000 system, a single-detector array fourth-generation scanner, and (b) a Philips MX8000 Quad system, a four-detector-array, third-generation CT scanner. The profiles were measured using a diamond-detector system (PTW, Freiberg, Germany). A Siemens Sensation 64 CT scanner was used to produce the absorbed-dose profiles given in Figure 7.5. Absorbed-dose profiles for the PMMA head phantom (160 mm diameter) are shown in Figure 7.5a for both the central and peripheral regions. Absorbed-dose profiles for the PMMA body 69

80 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 7.5. Absorbed-dose profiles for a Siemens Sensation 64 scanner. (a) for the 160 mm head, and (b) the 320 mm body PMMA phantoms. The center and peripheral profiles are shown in both cases. These measurements were performed using a commercially available array of optically stimulated luminescence detectors (McNitt-Gray et al., 2008). The curves were normalized to a maximum of unity for the periphery measurement. phantom (320 mm diameter) are shown in Figure 7.5b. These investigators used OSL dosimeters for the evaluation of the profile. The nominal beam width of 19.2 mm ( mm) was used for these measurements. For the body phantom in the central region, it is observed that the full width at 10 % corresponds to about 150 mm, and subtracting the 20 mm primary-beam width the scatter tails extend to a full width at 10 % of about 130 mm. Gorny et al. (2005) used strips of self-developing GafChromic film to measure the absorbed-dose profiles from a Siemens scanner, and their results are shown in Figure 7.6. For this experiment, the standard 320 mm diameter PMMA phantom was used. In this case, the limited horizontal extent of the profiles does not allow the estimation of the full width at 10 % maximum. Although the use of the selfdeveloping film and the necessary correction for its characteristic curve can be tedious, the profile itself has extremely high spatial resolution. Nevertheless, in general, self-developing film has low dosimetric accuracy even when corrected for its non-linear response. Mori et al. (2005) investigated the absorbed-dose profiles for a CT scanner with a very wide axial beam, the Toshiba Extech CT scanner, using PIN photodiodes. These investigators corrected for the x-ray-energy response and the directional dependence of the PIN photodiodes. Measurements were made in 320 mm diameter, 900 mm long PMMA phantoms, at from 1 mm to 10 mm intervals along z. Figure 7.7a shows absorbed-dose profiles at the center of the phantom for nominal beam widths ranging from 20 mm to 138 mm. The full width of the scatter tails at 10 % maximum for the 20 mm nominal beam is approximately 125 mm, and that for the 138 mm nominal beam is approximately Figure 7.6. Absorbed-dose profiles measured using commercially available self-developing film (GafChromic film) strips, placed at the center and edge of the phantom. After development, the film was digitized using the red channel of a color document scanner, and corrected for dose response using a calibration procedure (Gorny et al., 2005). 220 mm, after correction for the primary-beam width. The profiles measured at the periphery of the phantom are shown in Figure 7.7b for the same range of beam widths. The widths of the peripheral profiles are markedly smaller than those at the center of the phantom, and this is consistent with the notion that scatter does not propagate as far along z near the periphery of a phantom because it has a higher probability of exiting the phantom, fundamentally a solid-angle effect. Figure 7.7c shows a logarithmic plot of the same central-axis profiles as in Figure 7.7a, which are well matched by the theoretically derived analytical functions of Dixon and Boone (2011). 70

81 CT Dosimetry in Phantoms Figure 7.7. Absorbed-dose profiles for a number of different CT beam widths for a Toshiba 256-channel CT scanner. These profiles were measured in the axial (cone-beam) scanning mode, using PIN-photodiode sensors. (a) Profiles for a 320 mm PMMA body phantom at the center, and (b) on the peripheral axis of the phantom (Mori et al., 2005), using a 900 mm long phantom. (c) The Mori et al. data were fit using analytical methods (Dixon and Boone, 2011) with good results shown here. Geleijns et al. (2009) evaluated the absorbed-dose profiles in a wide-cone-beam CT system. Figure 7.8 gives the normalized absorbed-dose profile in a 320 mm diameter PMMA phantom for a Toshiba 320 cone-beam CT scanner, which has a nominal beam width of 160 mm. In this study, both measurements and Monte Carlo calculations were used to estimate the profile. The data shown in Figure 7.8 are from Monte Carlo simulations for the x-ray dose profiles at the center and periphery of the phantom. In the center, scatter tails at 10 % maximum approach +140 mm, for a full width of 71

82 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 7.8. Absorbed dose from Monte Carlo computations for a Toshiba 320-detector CT scanner with a body bow-tie filter. These profiles were computed (Geleijns et al., 2009) using a nominal 160 mm beam width. The periphery and center profiles are illustrated for a 320 mm diameter, 350 mm long PMMA phantom at 120 kv. 280 mm. Subtracting the primary-beam width of approximately 150 mm, the scatter tails are seen to have a full width of about 130 mm at the 10 % level. Figures 7.3 through 7.8 illustrate CT absorbed-dose profiles for a simple axial rotation from a number of different CT scanners and measurement conditions, performed by a number of different investigators. These include both measured and Monte Carlo derived profiles, using a number of different phantoms. The x-ray-primary-beam width ranged from a 0.01 mm nominal beam width (in a simulation) to a 3 mm nominal width for a single-detector-array CT system, and up to a 180 mm beam width for a fullcone-beam CT system. Despite the wide range of parameters studied in these examples, the absorbed-dose profile from scattered radiation at the center along the z axis of the phantom averaged 154 mm in width at 10 % amplitude (standard deviation of 33 mm). The primary-beam width influences the scatter-tail width in a complicated fashion (i.e., a mathematical convolution, as discussed below), and simple subtraction of the beam width does not take these influences fully into account. This approach is nevertheless useful to illustrate the significant absorbed-dose profiles that result from scattered radiation in a phantom. These observations also point to the need for a phantom longer than 150 mm if the scattered radiation dose is to be characterized accurately. 7.2 Cumulative Absorbed-Dose Distributions for Helical Scans For the typical whole-body CT scanner, helical (spiral) acquisition techniques are commonly used to scan the patient, especially in the chest, abdomen, and pelvic regions. For a helical CT scan, the accumulated absorbed-dose distribution at the center of the scan length (from L/2 to þl/2), smoothed as Figure 7.9. Normalized absorbed dose as a function of z for a number of different scan lengths: 10 mm, 50 mm, 100 mm, 150 mm, 200 mm, 300 mm, 400 mm, 500 mm, and 600 mm (from center to edge on the graph). These data were derived by convolving the DSF computed from Monte Carlo simulations with rect functions characterizing the length of the scan (i.e., L in Figure 7.1), for a 320 mm diameter PMMA phantom at 120 kv, assuming a General Electric Lightspeed-16 body bow-tie filter. necessary (Dixon, 2003), is represented by a convolution Q of the axial dose profile with a rect function, z L. When tube-current-modulation schemes are used, the convolution is invalid and a superposition of profiles of varying amplitude is required. Figure 7.9 shows normalized cumulative absorbeddose distributions for a series of helical CT scans of different scan length, produced by Monte Carlo simulation (Boone et al., 2009). These data were calculated for a General Electric Lightspeed-16 system with a tube potential of 120 kv and an infinitely long 320 mm diameter PMMA phantom. The scan lengths range from 100 mm to 600 mm in Figure 7.9. Note that the amplitude of the cumulative absorbed-dose distribution increases as the scan length increases, even though the primary-beam contribution is the same for all curves. The increase in the absorbeddose amplitude at the center of the scan length (z ¼ 0)asafunctionofscanlength,L, is due to the incremental contributions of the long-range, lowamplitude scatter tails that were seen in Figures 7.3 through 7.8, accumulating at z ¼ 0. The cumulative absorbed-dose distributions from Nakonechny et al. (2005) are shown for a number of different scan lengths, L, in Figure These profiles were produced using a computer-modeled single-scan absorbed-dose profile measured on a Picker PQ5000 CT system, in an elliptical waterequivalent phantom. The profiles were computed by convolving the axial absorbed-dose distributions, f(z), with rect functions Q z L for different scan lengths L. The mathematical description of this process is discussed in Section Nakonechny et al. note that the asymptote to the equilibrium dose, D eq, is reached in this phantom for a scan length.370 mm. 72

83 CT Dosimetry in Phantoms Figure Absorbed-dose distributions along the central axis of a 300 mm long, elliptical (200 mm 300 mm in cross-section) water-equivalent phantom for a tube potential of 120 kv. These profiles were calculated using measured f(z) axial profiles, assuming helical CT ( pitch, p ¼ 1.0) scans, and convolving with the rect function for scan length L. A range of scan lengths are indicated in the figure (Nakonechny et al., 2005). Figure A comparison between film-measured and simulated dose profiles at the periphery of a 320 mm diameter PMMA phantom (Dixon et al., 2005), for a 21-rotation helical scan with pitch, p ¼ Excellent agreement between the measured and computed profiles is observed. Figure Absorbed-dose profiles in a 320 mm PMMA phantom. (a) A Monte Carlo derived profile calculated for the center position in a helical scan (pitch, p ¼ 1) with a beam width of 34.1 mm. (b) Monte Carlo derived dose profiles for several different pitch values, at the peripheral position (Zhang et al., 2009). Zhang et al. (2009) evaluated the cumulative absorbed-dose distribution along the z axis of the scanner at both the center and the peripheral locations using Monte Carlo techniques. For a helical scan, the profile of the center of the beam is relatively smooth (see Figure 7.11a), as seen previously in Figures 7.9 and At the periphery of the beam, the cumulative absorbed-dose distribution exhibits a pattern of oscillations that are pitchdependent, e.g., for p, 1 there are peaks in the dose distribution, and for p. 1 there are valleys in the dose distribution when multiple rotations of the gantry are considered. Dixon et al. (2005) measured the cumulative absorbed-dose distribution at the surface of a 320 mm PMMA phantom for a helical scan using film densitometry, and also used an analytical model to compute the absorbed-dose profile for a nominal 10 mm beam width at a small pitch, p ¼ The absorbed-dose profiles, measured and modeled, for a 120 mm scan length were compared at the periphery of the phantom. These results were determined for a General Electric Lightspeed- 8 CT system, and are shown in Figure Excellent correspondence between the measured profile and the analytically simulated profile is seen. This approach leads to a better understanding of the small ripples in the absorbed-dose profile, which are clearly the result of the summation of primary-beam profiles of adjacent scans, which overlap for a pitch Equilibrium Dose, D eq The equilibrium dose has been discussed extensively in AAPM Report 111 (AAPM, 2010). With a 73

84 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY given DSF and a relatively narrow collimated primary beam (as in helical CT scanners), the absorbed dose at the center of the field of view along z increases as the scan length increases. Absorbed-dose profiles along the z axis for a number of different scan lengths are shown in Figure 7.9. As can be seen, the absorbed dose, D L (0), at z ¼0 along the dashed vertical line increases as the scan length L increases. As L increases, however, the absorbed dose at the center of the scan will at some point reach an asymptotic limit, and this is the so-called equilibrium dose, D eq Dose Profile for a Single Axial Rotation Consider a DSF generated using a very thin (0.010 mm) primary-beam impulse [approximating a Dirac delta function, d(z)] projected through the z collimator to the central axis giving a width a for the primary beam full width at half maximum (FWHM). Then an analytical function describing the complete absorbed-dose profile, f(z), resulting from a single axial rotation can be obtained by convolving the dose-spread function DSF ¼ d(z) þ h dsf(z) obtained from Monte Carlo simulation with the primary-beam intensity profile (Dixon and Boone, 2010; 2011). Note that the upper case dosespread function, DSF(z), includes both the primary component, d(z), and the scattered component, dsf(z), of the dose-spread function. The axial scan profile is the convolution of the DSF and a rect function of width a: f ðzþ ¼DSFðzÞA 0 P z a ¼ ½dðzÞþh dsf ðþ z ŠA 0 P z ; ð7:1þ a where, assuming a point focal spot, d(z) replicates the rectangular primary-beam profile A 0 P z ; a with A 0 the primary-beam amplitude, and h the scatter-to-primary ratio (SPR) on that axis. Replacing d(z) by the focal-spot-intensity distribution projected through the collimators produces a more realistic primary-beam function (Dixon et al., 2005) without affecting the scatter component in Eq. (7.1). Equation 7.1 can be simplified to f ðzþ ¼ Ð þa=2 a=2 DSFðz z0 Þ dz 0 : ð7:2þ This formalism includes also the simplification that the primary beam in air can be described by a rect function of width a,. Equation 7.2 simply Q z a states that the absorbed-dose profile at the center of the phantom for a single gantry rotation and no table motion is the convolution of the DSF(z) and the collimated beam width a Cumulative Absorbed-Dose Distribution, D L (z), for Multiple Rotations Covering a Scan Length L The cumulative absorbed-dose distribution, D L (z), from a helical scan of length L with a table advance per gantry rotation of b, as illustrated in Figures 7.9 and 7.10, is described by the convolution D L ðzþ ¼ 1 ð þ1 Y z 0 f ðz z 0 Þ dz 0 b 1 L ¼ 1 b f ðzþ Q z : ð7:3þ L Equation 7.3 applies only in the absence of tubecurrent modulation during the scan (i.e., is valid for constant x-ray-tube output). The convolution given in Eq. (7.3) can be reduced to a simple integration: D L ðzþ ¼ 1 b ð þl=2 L=2 f ðz z 0 Þ dz 0 : ð7:4þ Evaluating this function at z ¼ 0, Eq. (7.4) further simplifies to D L ð0þ ¼ 1 b ð þl=2 L=2 f ðz 0 Þ dz 0 ¼ p CTDI L ; ð7:5aþ where we recall that pitch is defined as p ¼ b/nt. This equation reduces further to CTDI L for a table advance of b ¼ nt (where p ¼ b/nt¼1). The dashed vertical line at z ¼ 0 in Figure 7.9 corresponds to D L (0); this maximum absorbed-dose value as a function of scan length L is shown in Figure The gradual increase in absorbed dose as a function of scan length becomes asymptotic at the larger scan lengths. This trend has been referred to as the rise-to-dose-equilibrium curve (Dixon and Boone, 2010). To express the explicit dependence of D L (0) on L, the function h(l) is defined as h(l) ¼ D L (0); thus, these functions are mathematical synonyms. Recognizing this, Eq. (7.5a) can be written as hðlþ ¼ 1 b ð þl=2 L=2 f ðz 0 Þ dz 0 : ð7:5bþ These and related curves have been reported by a number of different investigators. If the cumulative absorbed dose at z ¼ 0 is normalized to D eq,it 74

85 CT Dosimetry in Phantoms terms of absorbed dose) be h, it has been shown (Dixon and Boone, 2010) that for conventional helical or axial scans covering scan length L, the rise-to-equilibrium curve H(L) can be described as HðLÞ ¼ 1 1 þ h þ h 1 þ h ð1 lþð1 Þþlð1 e e L=d1 L=d2 Þ : ð7:9þ Figure A number of h(l) curves computed from Monte Carlo derived DSFs (Boone, 2009), for different phantom diameters (as indicated). These curves were computed for water phantoms at a tube potential of 120 kv for a Siemens body bow-tie filter. becomes the function H(L), defined (Dixon and Boone, 2010) as HðLÞ ¼ hðlþ D eq ¼ D Lð0Þ D eq : ð7:6þ Figure 7.14 gives H(L) curves derived by Nakonechny et al. (2005) for the center of a waterequivalent phantom. Figure 7.14a is for a singledetector-array scanner (Phillips PQ 5000), and Figure 7.14b is for a four-slice scanner (Phillips MX 8000). Figure 7.15 gives H(L) curves as measured by Mori et al. (2005), both at the center (Figure 7.15a) and the periphery (Figure 7.15b) of a 320 mm diameter PMMA phantom. As described in detail in Dixon and Boone (2010), the scatter component of the Monte Carlo derived DSFs shown in Figure 7.3 is well characterized by a double-exponential function such as dsf ðzþ¼ð1 lþ 1 expð 2jzj=d 1 Þþl 1 exp ð 2jzj=d 2 Þ: d 1 d 2 ð7:7þ This function has a short-range (transient) term that is weighted by l, and a longer-range term weighted by (1 2 l). The fall-off of dsf(z) with z depends on the d 1 and d 2 coefficients. The profile, f(z), can be separated into primary and scatter terms: f ðzþ¼ f p ðzþþ f s ðzþ ; ð7:8þ where f p is the primary component, and f s is the scatter component of absorbed dose obtained by convolving dsf(z) with a rect function of width a Q z representing the primary beam,, as a expressed in Eq. (7.1). Letting the SPR (in It has also been demonstrated that the same equation applies to stationary phantom, conebeam CT, with L replaced by the cone-beam width a (all other parameters remaining the same). In Eq. (7.9), the 1= ð1 þ h Þ term is the primary fraction and the h= ð1 þ h Þ term is the scatter fraction, and these terms sum to unity. It can be seen that with this normalization, H(L) ¼ 1.0 for L!1. Figure 7.16 shows a comparison between the rise-to-equilibrium data points measured by Mori et al. (as shown in Figure 7.15) and the results of Eq. (7.9), where the values of h, d 1, and d 2 were determined independently by Monte Carlo simulation (Boone, 2009). The H(L) curves shown in Figure 7.16 were not fit to the measured data points, they simply match the data well. It is noted that the value of l in Eq. (7.9) for the central axis is small (0.015), and therefore the second exponential growth term in Eq. (7.9) becomes negligible at small distances away from z ¼ 0. This leads to the simplified expression HðLÞ ¼ 1 1 þ h þ h 1 þ h ð1 e L=d 1 Þ: ð7:10þ For the central axis of the PMMA 320 mm body phantom(seefigure7.16a),theparametervalues were determined to be h ¼ 13, and d 1 ¼ 117 mm. Equation (7.10) shows that H(L) intersects the vertical axis (where L ¼ 0) at a value corresponding to the primary fraction [the first term in Eq. (7.10)], and the vertical extent of the actual equilibrium curve, i.e., [H(1) H(0)], has a value equal to the scatter fraction, h/(1 þ h). These observations are consistent with physical interpretation. A modified H(L) equation that accounts for the small dependence of H(L) on a (Dixon and Boone, 2011) can address the variation with a shown in the Mori et al. (2005) data (Figure 7.15). Earlier Monte Carlo simulations (Boone, 2007) focused on the efficiency of the CTDI 100 value, which is defined as CTDI 100 / CTDI 1. This work showed that for the center 75

86 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure H(L) curves computed by convolution with measured dose profiles (Nakonechny et al., 2005). These curves show the trend for (a) the single-detector array Philips PQ5000, and for (b) the four-detector array Philips MX8000. A 300 mm long, water-equivalent elliptical (200 mm 300 mm) phantom was used in these measurements for a tube potential of 120 kv. Figure Graphs adapted from Mori et al. (2005) showing measured H(L) curves. These data are for a 900 mm long, 320 mm diameter PMMA phantom, for a tube potential of 120 kv. Three different beam-collimation widths are shown in each plot, for (a) the center, and (b) the periphery positions. position in the 320 mm diameter PMMA phantom, the efficiency of measuring dose over a length of 100 mm (i.e., the CTDI 100 methodology) was approximately 62 % (see Figure 7.17) compared with an infinitely long measurement (or CTDI 1 ). Evaluating this in the context of the analytical development above, the ordinate value at a beam width of 100 mm is approximately 62 % in Figure 7.16a (see the dashed line with arrow), in excellent agreement with the 62 % value determined independently. 7.4 Phantom Design and Usage Mori et al. (2005) studied the dependence of the absorbed-dose profile on phantom length, in which he compared the absorbed-dose profiles in a phantom of length 140 mm with that in a 900 mm long phantom. These results are shown in Figure 7.18 for the central axis. Near the center of the scans, close to the primary beam, there is little difference between the two profiles; however, farther from the center, the relative dose profiles diverge. These data suggest that a 140 mm long 76

87 CT Dosimetry in Phantoms Figure H(a) curves for wide-cone-beam CT. The solid circles are the data from Mori et al. (2005), as seen in Figure The solid line was derived using Eq. (7.9) (Dixon and Boone, 2010), with shape parameters from Monte Carlo determined DSFs similar to those shown in Figure 7.3. (a) The H(a) curve for the center of an essentially infinitely long phantom, and (b) the corresponding curve at the periphery. There was no curve fitting per se in these comparisons; the fit parameters for the center profile correspond to a 1/e scatter length of 117 mm (d 1 ), and a scatter-to-primary ratio of 13. Figure Plots of the efficiency of CTDI 100, relative to CTDI 1 (Boone, 2007). These data are for a 320 mm diameter PMMA phantom and a tube potential of 120 kv; curves for the center, periphery, and an intermediate middle position are shown. The 62 % efficiency for a 40 mm beam width at the center position in this figure is consistent with the data shown in Figure 7.16a. phantom is too short to measure the entire absorbed-dose distribution that includes the scatter tails. Figure 7.3 also sheds light on the potential accuracy of CT dosimetry for different phantom lengths. For a clinically relevant setting and a 300 mm diameter water phantom (e.g., see Figure 7.3d), the exponential tails decrease to a relative level of 1 % at a distance of 200 mm from the center of the phantom (where z ¼ 0). Because 1 % of the cumulative absorbed dose is lost on each side, this corresponds to a 2 % loss. Therefore, it would appear that a 400 mm long, 300 mm diameter water Figure The role that phantom length plays in the measurement of the dose profile (Mori et al., 2005). The longer phantom (900 mm) contributes more absorbed dose from distant scattered radiation than does the shorter phantom (140 mm). phantom is necessary in order to measure about 98 % of the equilibrium dose. Equation (7.10) depicts an analytic approach to equilibrium with d 1 ¼ 117 mm, so to reach the 98 % of D eq, a length of 425 mm would be needed for the 320 mm diameter PMMA phantom to reach 98 % of dose equilibrium on the central axis, in good agreement with the data of Figure 7.3. Recognizing the need to establish a standard phantom capable of capturing the majority of the scattered radiation in order to measure H(L) accurately, this ICRU Report Committee collaborated with Task Group 200 of the AAPM to design such a phantom. The results of this collaborative effort led to the ICRU/AAPM phantom design shown in Figure Figure 7.19a illustrates the general design of the phantom, and Figure 7.19b shows a 77

88 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure The ICRU/AAPM phantom design. The ICRU, in collaboration with AAPM Task Group 200, defined a polyethylene phantom for the purposes of measuring the rise-to-dose-equilibrium function, h(l) or H(L). (a) The phantom design, and (b) a photograph of the phantom. Due to the large mass of this large phantom, it was designed to be modular, with three different sections. picture of an actual phantom. The phantom comprises high-density polyethylene (mass density of 0.97 g/cm 3 ) and is 300 mm in diameter. The total length of the phantom is 600 mm. Due to the large mass of the phantom ( 41 kg), it was necessary to manufacture it in three separate sections. Because a radiation detector is to be located at the center of the phantom along the z dimension, it was necessary to design the phantom without a seam at the center (z ¼ 0) to avoid the potential streaming of primary radiation that could give erroneously high readings. In order to keep the three sections aligned, alignment pegs were included in the design. The three sections of the phantom are referred to as section A, B, and C. Sections A and B are bored through with holes necessary for placement of dosimeters (e.g., small thimble chambers) at the center, periphery, and at an intermediate position between the center and edge of the phantom. Figure 7.20 shows a more complete technical drawing of the phantom. It is recognized that this phantom is too large and heavy to be practical for routine dosimetry measurements on CT scanners in the clinical environment. However, for research in CT dosimetry, and potentially for dose assessment in the testing facilities of CT-scanner manufacturers, this phantom is practical. The phantom design represents a reasonable compromise between utility and cost; it is long enough that accurate measurements of the equilibrium dose can be made, and because the stock material comes from extruded polyethylene boules it is relatively inexpensive. Several of these phantoms have been manufactured and distributed internationally, and some results measured with the phantom are reported below. 7.5 AAPM Report 111 Recommendations for Assessment of H(L) The measurement of the rise-to-dose-equilibrium curve, H(L), is discussed at length in AAPM Report 111 (AAPM, 2010) with the methodology described in that report for estimating H(L) as indicated schematically in Figure A short thimble chamber, connected to an integrating electrometer, is placed near the center of a long cylindrical phantom on the CT couch. A series of helical CT scans of different lengths are acquired, each scan centered on the thimble chamber. In Figure 7.21, three different scan lengths are shown, L a, L b, and L c. The 78

89 CT Dosimetry in Phantoms Figure Technical drawings of the ICRU/AAPM CT phantom. Figure The measurement procedure described in AAPM Report 111 (AAPM, 2010). An integrating thimble chamber is placed in the center hole (or periphery, not shown) of a long cylindrical phantom. A series of helical CT scans are performed, with the center (along z) of the scan located at the center of the phantom. Each chamber reading (in scans a, b, and c) is plotted as a function of the scan length, L. The three different scan lengths L a, L b, and L c are shown on the left, and the measured air-kerma values are plotted on the right. These data are obtained for a given scanner, tube potential, mas setting, and phantom, resulting in the h(l) profiles. When the asymptotic value D eq [or equivalently h(1)] is used for normalization, the H(L) profiles are produced. measurements for each of these scan lengths correspond to a specific point on the H(L) curve, indicated in the graph. The rise-to-dose-equilibrium curve, H(L), defined by Eqs. (7.6) and (7.10), is normalized by D eq and therefore asymptotically approaches unity whereas the unnormalized function h(l), asymptotically approaches D eq. Hence, h(l) depends on CT acquisition parameters and has the utility 79

90 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY that it retains quantitative CT-scanner air-kerma information that is lost in H(L) due to the normalization procedure. The methods of AAPM Report 111 described above and in Figure 7.21 are robust and are capable of producing accurate h(l) curves using widely available integrating radiation meters. The disadvantage of this approach is that it requires quite a few long, helical CT scans in order to fully characterize h(l). Therefore, the procedure is relatively time-consuming and can result in considerable heat loading of the x-ray tube if many points are measured. Another important observation regarding this point-by-point measurement is that the designated scan interval (at the CT console) for a given helical acquisition might not be the exact length used for the acquisition. For helical scans, the IEC definition of scan length is L ¼ vt 0, where v is the table velocity and t 0 is the total beam-on time. Thus, the length of the physical scan is slightly longer than the region in which images are prescribed on the localizer view during scan set-up. For a prescribed length for CT image acquisition of L i, the physical scan length is approximately L ¼ L i þ nt. Therefore, for helical scans on modern MDCT systems (where nt 40 mm), the integral dose efficiency (L i /L) for a 100 mm scan is 71 %, for a 200 mm scan it is 83 %, and for a 300 mm scan, it is 88 %. In state-of-the-art CT scanners, the presence of adaptive collimation (see Section 2.2.2) can substantially reduce the amount of helical overranging. An accurate method to determine the physical scan length, L, from the recorded CTDI vol and DLP values reported by the scanner is to compute L ¼ DLP/CTDI vol. AAPM Report 111 did not anticipate the existence of a real-time radiation meter (introduced in Section 5.2.3), which provides a more efficient method for measuring the h(l) and H(L) curves. These methods are discussed in the next Section. 7.6 The Role of the Real-Time Radiation Meter in Measuring H(L) A real-time radiation meter, capable of.1 khz readout rates, can be used in combination with a long phantom to determine h(l) in one long helical CT scan. Figure 7.22a illustrates the scan geometry, in which the real-time radiation detector is positioned near the center (along z) of the long phantom. A helical scan is performed covering the entire length of the phantom, and in this procedure Figure Measurement of h(l) using a real-time meter. (a) With the real-time probe positioned as shown, measurements using the ICRU/AAPM phantom or some other suitable (long) phantom are performed. The x-ray beam of width a is positioned at the end of the phantom, and, using a helical-scan acquisition, the x-ray beam is translated through the phantom and the thimble chamber contained within. (b) An idealized real-time signal from the thimble chamber is illustrated. (c) The time axis is converted to position, and the signal is integrated numerically over increasing scan length, L. (d) Plot of the integrated data derived from the procedure shown in (c), with the point corresponding to the measurement at length L 1 shown. As the integration in (c) proceeds beyond the value of L 2, the curve shown in (d) extends further. The raw measurement shown in (d) using the real-time thimble chamber results in the function h(l). 80

91 CT Dosimetry in Phantoms the x-ray beam approaches and then passes through the real-time detector (a small thimble ionization chamber), and continues toward the other edge of the phantom. An idealized real-time airkerma rate of the radiation meter is shown in Figure 7.22b. As the primary beam enters the CT phantom on the left, the x-ray probe measures the signal produced by distant x-ray scatter. As the x-ray beam approaches the detector, the measuredscatter intensity increases, due both to solid-angle effects and the shorter attenuation path length between the x-ray beam and the real-time probe. As the primary beam passes over the probe, it records not only scattered radiation but the primary radiation as well. The x-ray beam then continues toward the right edge of the phantom, producing an approximately symmetrical profile. The real-time results, measured as air kerma per time, can be converted to air kerma as a function of position using the known sampling period Dt (i.e., K air ¼ _ K air Dt) and the known velocity v of the table transport, where position ¼ t/v. After this transformation, the profile as illustrated in Figure 7.22c represents the air-kerma profile, f(z). Using Eq. (7.5b), the cumulative air kerma at the center of the phantom for scan length L can be obtained by integrating f(z) from 2L/2 to þl/2, as shown graphically in Figure 7.22c. These data are then compiled to compute h(l) as a function of L, as shown in Figure 7.22d. Despite the convenience of this method for the assessment of h(l), it is not possible to accurately assess the SPR, h, in Eq. (7.10), and therefore, there is some imprecision in the exact shape of the curve near the y axis (for L, nt), where the primary term becomes more prominent. This is more apparent in peripheral dose profiles than in center profiles. 7.7 Measurement of h(l) in the Clinical Environment Using the real-time probe located near the center (along the z axis) of the ICRU/AAPM, 600 mm long, 300 mm diameter polyethylene phantom shown in Figure 7.19, the measurement of f(z) can be determined directly. Such a measurement for a Siemens ASþ CT scanner is illustrated in Figure 7.23a. This is similar to the idealized dose profile shown in Figure 7.22c; however, there is an obvious notched pattern in this measured profile that is due to CT-couch attenuation. Although the modern CT couch is made from low-attenuation carbon-fiber components, there is still some attenuation by the patient table evident in Figure 7.23a. Although the notches in the f(z) profile appear as a distraction, the integration of this curve from 2 L/2 to þl/2 according to Eq. (7.5b) produces a monotonic function h(l) in which the influence of the table attenuation is largely eliminated (see Figure 7.23b). Thus, depending on the alignment of the notched pattern (i.e., its position relative to z ¼ 0), the integration of f(z) can result in the apparent cancellation of the notches. That is, notches on one side of z ¼ 0 will cancel out the absence of a notch on the other side. Another interesting observation in regard to Figure 7.23a is how sharp each of the notches appears, given that for most of the curve Figure Air-kerma rate from a Siemens spiral-ct scan through a phantom. (a) The signal trace from the real-time probe for a helical scan performed along the entire length of the ICRU/AAPM phantom is shown for a Siemens ASþ scanner operating at 120 kv. The thimble chamber was positioned at the center of the 300 mm diameter polyethylene phantom. (b) The rise-to-dose-equilibrium curve, h(l), is computed from the profile shown in (a) by integrating from the center out. The h(l) from the real-time trace (solid line) compares well with individual measurements using AAPM Report 111 methods (solid circles). 81

92 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Air-kerma rate from a General Electric helical CT-scan through the ICRU/AAPM phantom. (a) The real-time trace is shown for a General Electric VCT scanner operating at 120 kv. Although the notches from the table produce a trace with substantial inhomogeneities, integration from the center outwards of this profile tends to reduce the impact of the table notches. (b) The h(l) curve for the General Electric VCT scanner, determined by center-to-edge integration of the profile shown in (a). As before, the individual data points represent serial measurements using AAPM Report 111 methodology. Figure Air-kerma rate from a Philips Brilliance 16 helical-ct scan through the ICRU/AAPM phantom. These data were measured for a tube potential of 120 kv. (a) The output of the real-time x-ray meter. (b) The h(l) curve computed from the trace in (a). Individual data points using AAPM Report 111 serial measurement methods are shown. the real-time radiation meter is measuring scattered radiation only. As the x-ray tube rotates and the x-ray beam intercepts the table, the primary x-ray intensity striking the phantom is rapidly reduced, also reducing the scatter signal even at considerable distances away from the primary x-ray beam. A particularly important observation from Figure 7.23b is that the solid circles plotted are h(l) values measured using an integrating ionization chamber according to the methodology of AAPM Report 111. The agreement between these points and the solid curve measured using the real-time probe is excellent. Figure 7.24a shows a measured f(z) using the 0.6 cm 3 real-time probe through the center of the ICRU/AAPM phantom for a General Electric VCT scanner, and the corresponding h(l) curve is shown in Figure 7.24b. Again, the notches from the CT-table attenuation seen in Figure 7.24a do not appear in the h(l) curve in Figure 7.24b. The solid points measured using the AAPM Report 111 methods are shown as well, with excellent agreement between the two measurement approaches. Analogous results for a Philips Brilliance 16 CT scanner are shown in Figure 7.25a and 7.25b. The very good agreement between the two measurement methods for three different scanners as shown in 82

93 CT Dosimetry in Phantoms Figures demonstrates concordance between the AAPM Report 111 measurement methods and those using the real-time probe described here. There is a sentiment in the CT community that CTDI w can be considered as a loose measure pertaining to the relative output of the CT scanner; CTDI w is measured as air kerma in a PMMA phantom (160 mm or 320 mm in diameter) and increases with x-ray tube potential, tube current, and exposure time, and has only a slight dependence on collimation at clinically realistic settings on MDCT scanners. Because CTDI vol is Figure Three G(L) curves from three different CT scanners, normalized by CTDI vol. This figure illustrates the three central-position h(l) curves illustrated in Figs. 7.23, 7.24, and 7.25, normalized by CTDI vol corresponding to the CT scanner used. dependent on table speed, it is not an ideal measure of CT scanner output per se, as x-ray output should be independent of table speed. For measurements involving helical-ct scanning, however, CTDI vol can be considered to be a measure of pitch-normalized output (e.g., air kerma per effective mas setting, where effective mas is the tube-current time product divided by the pitch). Embracing this concept, the h(l) curves shown for three different CT models and manufacturers in Figures are normalized by the corresponding CTDI vol at the appropriate tube potential and for each machine type, and subsequently corrected to the appropriate tube-current time product, and pitch for each scan. These results are shown in Figure Given that these curves are from measurements on three different CT scanners, the normalized curves are remarkably similar. Figure 7.27a shows f(z) curves for a Siemens ASþ CT scanner measured for a number of x-ray tube potentials using the real-time probe method. As expected, at the same tube-current time value, the air kerma for the system at higher x-ray-tube potentials (and hence the area of the curves) increases. Integration of these curves leads to the h(l) curves given in Figure 7.27b. The h(l) curves can also be normalized by the tube-potential-dependent values of CTDI vol, and these results are shown in Figure 7.27c. It is evident that this normalization essentially eliminates the effects of the x-ray-tube potential, resulting in very similar normalized curves for all four x-ray-tube potentials evaluated. Figure Real-time probe data versus x-tube potential for a Siemens ASþ CT scanner using the ICRU/AAPM phantom. (a) The traces of the real-time x-ray detector for four different tube potentials. All traces were corrected to a current time product of 100 ma s. The amplitude for the higher tube potentials is greater, as anticipated. The different location of the notches in the four traces indicates that the start angle changed between measurements. (b) The resulting h(l) curves from the traces for the four tube potentials shown in (a). The asymptotic value reached at the right end of the curves corresponds to the total area of the f(z) traces shown in (a). (c) The individual h(l) curves for the x-ray tube potentials shown in (b), normalized by the measured CTDI vol, and thus are G c (L) curves per Eq. (7.13). As seen before with the different CT scanners, these normalized G(L) curves essentially fall on one another. 83

94 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Thus, it is seen that normalization by CTDI vol is an effective method for correcting for the characteristics of different CT scanners operating at different x-ray tube potentials, providing a nearly universal h(l)/ctdi vol curve. These results suggest that the parameter h(l)/ctdi vol is a useful quantitative description of the dose-distribution characteristics in CT for a cylindrical phantom of a given diameter. Although there are differences among the different manufacturer s CT scanners in terms of x-ray spectrum, beam-shaping filters, collimated-beam width, table composition, the x-ray-source-to-isocenter distance, etc., normalization by CTDI vol appears to correct for these differences. Given the likely utility of this normalized function, a function G(L) can be defined: G x ðlþ ¼ h xðlþ ¼ D Lð0Þ ; CTDI vol CTDI vol ð7:11þ where the CTDI vol is specific to the 320 mm diameter, 150 mm long PMMA phantom (or the 160 mm diameter phantom for head CT applications), and where L ¼ 100 mm, whereas h x (L) can be measured in phantoms of different diameter, length, and composition. The subscript x is meant to designate h(l) at a peripheral (x ¼ p) or center (x ¼ c) location, or the weighted average (x ¼ a) of these. It is recognized that the asymptotic value of G x (L) is D eq / CTDI vol, on a given phantom axis (central or peripheral). It is also evident that G a ð1þ is equal to CTDI 1 /CTDI vol, the inverse of the efficiency introduced in Section 7.3 regarding Figure For the 300 mm diameter polyethylene ICRU/AAPM phantom, the measured data show that for the center position, the asymptote (D eq /CTDI vol ) reaches a value of approximately 2.08 (see Figure 7.28). Figure 7.28 gives G c (L), at the center of the phantom, for two polyethylene phantoms: 180 mm and 300 mm in diameter. These data were obtained with the real-time radiation meter by integrating f(z). These G c (L) curves have both been normalized to the CTDI vol value for the scanner operating at the same tube potential and tubecurrent time product, which explains why the 180 mm diameter phantom curve is higher than that of the 300 mm diameter phantom. 7.8 Rise to Equilibrium in 160 mm and 320 mm PMMA phantoms In this Section, the focus is on the rise-todose-equilibrium functions in the 160 mm and 320 mm diameter PMMA dosimetry phantoms. The phantoms have been extended in length by using Figure The G c (L) curves for polyethylene phantoms of different diameters acquired at 120 kv. The 300 mm diameter phantom approximates an average-sized adult, whereas the 180 mm phantom corresponds to a pediatric patient of approximately 5 y old. Both curves were produced by normalizing h c (L) curves by the measured CTDI vol, which was measured using a 100 mm pencil chamber and a 140 mm long, 320 mm diameter PMMA phantom for the Siemens ASþ CT scanner. Figure H(L) curves for the center and peripheral positions in the 320 mm PMMA phantom for a tube potential of 120 kv. The solid triangles correspond to measurements (Dixon and Ballard, 2007), and the closed circles represent Monte Carlo data (Zhou and Boone, 2008). The dashed lines correspond to the analytical fits [Eq. (7.10)] to these data. several phantoms, in order to evaluate the rise-to-dose-equilibrium characteristics in PMMA. Monte Carlo data (Zhou and Boone, 2008) are compared with measured data (Dixon and Ballard, 2007) for the 320 mm diameter PMMA phantom, both for a tube potential of 120 kv, in Figure The calculated and measured data are shown as points and the analytical curves from Eq. (7.10) are plotted as dashed lines for both the center and peripheral axes. For the analytical curve on the center axis, the dashed line was computed with h ¼ 13 and d 1 ¼ 117 mm, as described previously for 84

95 CT Dosimetry in Phantoms Figure 7.16a. Figure 7.29 shows the excellent agreement among measured, simulated, and analytical results. The function h(l) represents the raw measurement (using either the integrating-probe method of AAPM Report 111 or the real-time probe measurement approach) of absorbed dose as a function of scan length in a phantom, at either the center [h c (L)] or peripheral [h p (L)] locations. The h(l) curves are dependent on output-related parameters such as tube potential, tube current, acquisition time, pitch, etc. Combining the center and peripheral measurements, the CTDI vol (L) can be derived: CTDI vol ðlþ¼ h a ðlþ ¼ 1 3 h cðlþ þ 2 3 h pðlþ: ð7:12þ Following Eq. (7.11), Eq. (7.12) can be divided by the conventional (L ¼ 100 mm) CTDI vol value, measured at (or scaled to) the same technique factors (tube potential, tube current, pitch, etc.) that were used to measure the h(l) data, to yield: CTDI vol ðlþ CTDI vol ð100 mmþ ¼ G aðlþ ¼ 1 3 G cðlþ þ 2 3 G pðlþ: ð7:13þ Figure 7.30a shows three 320 mm diameter PMMA phantoms placed end-to-end on the table of a CT scanner (Siemens ASþ). The G(L) curves acquired at 120 kv for both the center [G c (L)] and the peripheral profiles [G p (L)] were evaluated using the real-time-probe method for both the 160 mm and 320 mm diameter phantoms. The 320 mm diameter results are shown in Figure 7.30b and those for a 160 mm diameter phantom in Figure 7.30c. At the peripheral location [i.e., G p (L)], some waviness in the profile is seen (Figures 7.30b and 7.30c), which is due to the influence of both phantom attenuation and the inverse-square law. As noted previously, although the G x (L) curves are plotted starting at L ¼ 0 in Figure 7.30b and 7.30d, the data are unreliable for L, nt, which is about 40 mm for this scanner. For the 320 mm diameter phantom (see Figure 7.30b), the center measurement is nearly always lower than that of the peripheral value, as would be expected for a large-diameter phantom. For the 160 mm diameter phantom (see Figure 7.30c), however, the center and peripheral profiles intersect at a scan length of about 135 mm, with the center exceeding the peripheral beyond this scan length. This demonstrates the increasing build-up of scattered radiation at the center of the phantom as a function of scan length. Although the numerator, CTDI vol (L), in Eq. (7.13) is from a measurement using a long phantom and the denominator, CTDI vol (L ¼ 100 mm), is from a measurement in the standard 150 mm diameter PMMA phantoms, the value of G a (L) atl ¼ 100 mm is approximately 1.0 for both the 320 mm diameter (see Figure 7.30b) and the 160 mm diameter (see Figure 7.30c) phantoms. The implications of Eqs and Figures will be discussed in the Summary section. 7.9 The Radial Dose Profile Much of the focus so far has been on the airkerma or absorbed-dose distribution as a function of z in a phantom. In this Section, the radial distribution is discussed. A Monte Carlo evaluation of an infinitely long, 320 mm diameter water phantom has been performed, and the x-ray energy deposited radially at 10 mm annular thicknesses was evaluated. Figure Data from a long PMMA phantom acquired at 120 kv. (a) A photograph of three 320 mm diameter PMMA phantoms, placed end-to-end on a CT couch. (b) The center, G c (L), and peripheral, G p (L), curves are shown for the 320 mm diameter PMMA phantom. The G a (L) was computed as well, seen as the dashed line. Due to the normalization, the G a (L) curve passes through a value of 1.0 at L ¼ 100 mm. (c) The G c (L), G p (L), and G a (L) curves are shown for the 160 mm diameter head phantom. 85

96 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Radial dose profiles. (a) Monte Carlo generated profiles as a function of radial position (from center to edge) for a 320 mm diameter water phantom in a beam generated at 120 kv. The energy deposited increases from center to edge, which is consistent with basic principles of radiation attenuation. Because absorbed dose is energy deposited per mass, and the mass of an annulus of smaller radius is smaller than that of an annulus toward the periphery of the phantom, the absorbed-dose profile is different. (b) The radial absorbed-dose profiles for four different x-ray tube potentials, for a 320 mm diameter water phantom. In all cases, the absorbed dose at the center of the phantom is about from 20 % to 25 % less than the maximum absorbed doses that occur near the periphery of the phantom. The deposited energy is shown as the lower curve in Figure 7.31a. Although less energy is deposited centrally in the phantom due to attenuation, the volumes (and hence masses) of the inner annuli (and central cylinder) are also much smaller, so that the radial distribution of the equilibrium absorbed dose (top profile in Figure 7.31a) is much more uniform than the distribution of total energy deposited. Figure 7.31b illustrates the equilibrium absorbed dose as a function of radial position for four x-ray tube potentials. There is some variation in the absorbed dose as a function of radial position in CT. However, compared with x-ray projection imaging such as radiography and fluoroscopy, the radial equilibrium absorbed-dose distribution in CT is relatively uniform, the peripheral-to-central-axis ratio being about 1.4 for a tube potential of 120 kv in this 320 mm diameter phantom Summary In this Section, the body of knowledge produced by many scientists working in the field of CT dosimetry has been presented and compared. Many common themes have emerged. Collectively, this work demonstrates that CT dosimetry in phantoms has moved well beyond the traditional parameter of CTDI vol, and it also follows the developments presented in AAPM Report 111 (AAPM, 2010). The function h x (L) was defined as a raw (unnormalized) measurement of the rise-to-equilibrium curve for either the center (x ¼ c) or peripheral (x ¼ p) phantom positions, or the 1 3 and 2 3 weighted average value [x ¼ a; see Eq. (7.12)]; this is consistent with the definition h(l) ; D L (0). The amplitude of h(l) scales with the CT technique factors used, and therefore this function reflects the specific set of acquisition parameters (tube potential, tube current, acquisition time, pitch, etc.) used for the scan. In the limit of L! 1, h(l)! D eq, and the function H(L), defined as h(l)/d eq, approaches unity. The normalized value of H(L) is useful in many applications (AAPM, 2010) and is also important to the understanding of the energy deposited by scattered radiation (i.e., Eqs. 7.9 and 7.10), and the normalization process eliminates most of the dependencies on technique factors. It is recognized that the function h(l) is useful because it retains the CT scanner output characteristics that are dependent upon technique factors; however, this means that there would be a different h(l) curve for each combination of technique factors. To address this, the G x (L) was defined in Eq. (7.13), which is simply h x (L)/CTDI vol, where the definitions for x were defined previously. The utility of G x (L) is that it retains the output characteristics unique to the CT technique factors, but is normalized by a quantity that is available on the CT console (or in the DICOM header), the conventional CTDI vol. Therefore, given the G a (L) curve for a given phantom diameter and composition, the planar dose average at z ¼ 0 can be computed knowing the CTDI vol as well as the scan length L. 86

97 CT Dosimetry in Phantoms Because the CTDI vol and the dose length product (DLP) are reported on all modern CT scanners for each CT scan, the value of L can be computed as L ¼ DLP/CTDI vol [see Eq. (4.11)]; this means that the length-adjusted planar-dose average (at z ¼ 0) can be computed in a clinical setting when G(L) is known for the average diameter of the patient s anatomy being scanned. This would suggest that a family of G a (L) functions for different phantom diameters, G dia a ðlþ, could be useful for the clinical assessment of patient dose. 87

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99 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds Patient Size-Specific Dose Estimation 8.1 Introduction As concerns about the absorbed dose from CT examinations have grown, stakeholders, including patients, referring physicians, radiologists, medical physicists, and others, have sought to improve the accuracy of dose assessment. Nowhere has this effort been more emphasized than in pediatric CT, and indeed the well-known Image Gently campaign of the Alliance for Radiation Safety in Pediatric Imaging (Image Gently, 2011) has been a driving force calling for improved dosimetry for pediatric radiology. Two standard PMMA phantoms have been used for CT dosimetry for almost 40 y, the 160 mm diameter head phantom and the 320 mm diameter body phantom. Air kerma is measured at points both in the center and the periphery of these two phantoms, and are combined together as described in Section to form the weighted CT dose index, CTDI w. The CTDI w captures useful x-ray output information for a given CT scanner, and is dependent on a number of CT technical factors including x-ray tube potential and current, rotation time, bow-tie filter, total collimation width, as well as source-to-isocenter distance. Because CTDI w is defined only in the axial-acquisition mode; it has no dependence on pitch. The CTDI vol is the pitchcorrected CTDI w, and therefore CTDI vol is an important dosimetric quantity that pertains to helical or spiral CT scanning. The CTDI vol cannot be considered as solely an x-ray-tube-output measure because it depends upon table-feed velocity. Nevertheless, the CTDI vol has been demonstrated to be a useful parameter in normalizing for the pitch-corrected x-ray-tube output on a CT system (see Section 7.7). The CTDI vol is reported on the console of most CT scanners and is also recorded as part of the CT dose report 1 on many systems as well. The ubiquitous availability of CTDI vol makes it a useful parameter in dose assessment, but it 1 The Digital Imaging Communication in Medicine (DICOM) Radiation Dose Structured Report (RDSR) records a number of parameters in the CT image header that are pertinent for CT dosimetry. should not be considered as the patient dose per se (McCollough et al., 2011). For the same x-ray-tube potential, time current product, and primarybeam collimation width, the absorbed dose at the center of a cylindrical object in CT increases as the diameter of that object is reduced (see Figure 8.1) because of the reduction in self-attenuation. This was seen in Figure 7.28, which compares the absorbed dose in a 180 mm diameter cylinder with that in a 300 mm diameter cylinder for the same CT technique factors. For a large reduction in patient or phantom diameter, the absorbed dose increase can be substantial. Another way to understand this dependence on patient size is to recognize the larger mass of bigger patients. The vast majority of an x-ray beam incident upon a patient is attenuated by, and its energy absorbed in, the patient. Because the average absorbed dose is deposited energy divided by mass, a patient with smaller mass receives a higher average absorbed dose than a larger patient for the same x-ray beam fluence incident on the patient. The IEC (2009) requires that all modern CT scanners be capable of displaying the CTDI vol both prior to and after a CT scan, and efforts are underway to use this displayed CTDI vol as a practical parameter in estimating absorbed dose for different-sized patients. The displayed CTDI vol is available after the technique factors have been set, but prior to the actual CT scan, which enables the CT operator to use the CTDI vol to estimate patient absorbed dose prior to the exposure of the patient. However, the CTDI vol value is not by itself sufficient as it does not address the size of the patient. With appropriate compensation for patient size as described below, CTDI vol can be used to estimate more accurately the absorbed dose prior to the CT scan. This same quantity can be used after the CT scan is performed as well. A document published by the American Association of Physicists in Medicine, AAPM Report 204 (AAPM, 2011), directly addresses the issue of the size-specific dose estimate (SSDE) and has been endorsed by both the Image Gently campaign and the ICRU. This Section includes much of the information described in AAPM Report 204. # International Commission on Radiation Units and Measurements 2013

100 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 8.1. The relative absorbed dose as a function of the effective diameter of the patient. If the patient were 320 mm in diameter and composed of PMMA, CTDI vol or CTDI w would be an accurate dosimetric quantity. However, at the same technique settings (tube potential a current, time, pitch, etc.), the absorbed dose increases for patients smaller than this (i.e., most). 8.2 Absorbed Dose versus Patient Size A number of investigators have independently studied the absorbed dose in different-sized objects or patients scanned in CT. These efforts will be briefly reviewed here, and the combined data from these studies will be analyzed in Section 8.4. Nickoloff et al. (2003) reported on the influence of patient diameter for different x-ray-tube potentials and scan modes. These investigators studied a total of six different CT systems, including four single-slice and two early MDCT scanners. Given that the cylindrical PMMA phantoms are placed concentrically at the isocenter of the CT system, it was recognized that the attenuation path-length through the PMMA to the center of the phantom is constant with x-ray gantry rotation. This led Nickoloff and colleagues to assess the effective linear attenuation coefficient, m eff, for a number of CT scanners over a range of different tube potentials. Characterization of m eff allows the computation of a size-adjusted CTDI vol, and Nickoloff et al. include tables of these parameters and formulae for estimation. Huda et al. (2010) evaluated the organ doses for thoracic CT for commercial CT scanners from two different manufacturers and for different patient sizes. These investigators studied effects of the CT scan length, as well as the dependence of absorbed dose on body mass. They observed that the thoracic dimensions of most adult patients are likely to be modeled by cylinders of water with diameters that range from 200 mm to 280 mm, and they provided a polynomial relationship for relative absorbed dose in water cylinders of different diameters. A group of investigators reported on a multiinstitutional collaboration (Turner et al., 2010) that involved the Monte Carlo characterization of organ absorbed-dose estimates as a function of patient size, over a range of patient sizes, including pediatric patients, females, and males. The Monte Carlo patient models (see Figure 8.2) were developed from CT scans of actual individuals (Petoussi- Henss et al., 2002). The Monte Carlo studies evaluated the absorbed dose in a number of abdominal organs, including the liver, stomach, adrenal glands, kidneys, pancreas, spleen, and gallbladder. The investigators normalized the organ absorbed doses to the CTDI vol ; the simulations included the parameters from four major CT manufacturers, and were based on a 120 kv x-ray spectrum. A collaboration of Strauss and Toth ( personal communication) performed measurements on CT scanners from four different manufacturers using PMMA phantoms of 100 mm, 160 mm, and 320 mm diameters. The measurements were made as a function of x-ray-tube potential, and the investigators normalized the average measured air kerma to CTDI vol for the 320 mm diameter PMMA phantom. McCollough and colleagues at the Mayo Clinic ( personal communication) made dosimetry measurements in a family of commercially available phantoms, shown in Figure 8.3, that spanned a range from 100 mm to 400 mm in diameter. By adding an additional layer of simulated fat, a total of 11 different patient sizes were evaluated in these measurements. This study included CT scanners from two different manufacturers. A group of investigators at the University of California Davis used a series of six PMMA cylindrical phantoms to make image-quality assessments, including contrast and image noise (Boone et al., 2003). In this investigation, the CTDI 100 was also measured at the center and periphery of each phantom; these measurements were made for tube potentials from 80 kv to 140 kv. Monte Carlo simulations were performed for a series of mathematical cylindrical phantoms that ranged from 10 mm to 500 mm in diameter (Zhou and Boone, 2008). Several different phantom compositions were studied, including water, polyethylene, and PMMA. In these simulations, the phantoms were considered to be infinitely long, thereby including the contributions of multiply scattered x rays. These investigators also developed a spreadsheet-based tool that incorporated monoenergetic Monte Carlo data spanning 22 different phantom diameters. The spreadsheet allows the x-ray spectrum to be generated using a spectrum model, permitting flexibility in terms of x-ray-tube potential. A polynomial fit was used for interpolation of the absorbed dose across the entire range of phantom diameters from 20 mm to 500 mm. Dose estimates using this tool are provided at the 90

101 Patient Size-Specific Dose Estimation Figure 8.2. Examples of three-dimensional voxel phantoms (Turner et al., 2010). Organ boundaries were hand segmented in most cases. Figure 8.3. The eight phantoms used by McCollough and colleagues for the measurement of absorbed dose as a function of patient size. center and peripheral positions in the phantom, as well as for a planar average. 8.3 Size Metrics Figure 8.4 illustrates the concept of effective diameter, d eff. In most cases, the lateral and anterior posterior (AP) dimensions of a patient are different. When the transverse area of a patient s body in the plane of the CT image is considered, the effective diameter is defined as the diameter of a circle of equal area. Investigators have also defined a patient s water-equivalent diameter, d w. The water-equivalent diameter includes a Figure 8.4. The concept of effective diameter. For a CT scan of the cross-sectional area A, the effective diameter is defined as the diameter of a circle with equal area. Here, the AP and lateral dimensions are also illustrated. correction for the density of the patient s tissues in the CT plane of interest, as will be defined below in more detail. Kleinman et al. (2010) made comprehensive measurements of the dimensions of pediatric patients using CT images. These data characterized the AP and lateral dimensions as a function of age, from newborn to 20 y. Analysis was performed for the head, thorax, abdomen, and pelvis. The abdominal dimensions from this work are illustrated in Figure 8.5. These data can be combined to determine the AP dimension as a function of lateral dimension as well. In Boone et al. (2003), the 91

102 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 8.5. Patient sizes. (a) The anterioposterior dimension as a function of patient age. (b) The transverse or lateral dimension as a function of age (Kleinman et al., 2010). Figure 8.6. The lateral dimension (L) and AP dimension (A) as a function of effective diameter, for 87 patients (Boone et al., 2003). investigators characterized the AP and lateral dimensions for a cohort of 87 adult patients, as a function of effective diameter. The data shown in Figure 8.6 illustrate the relationships for the lateral and AP dimensions as a function of the effective diameter. For adult patients, it was found that both of the linear measurements scaled proportionately to the effective diameter, with just a scalar offset. For example, for these data, the lateral dimension, LAT ¼ d eff þ 3.8 cm, and for the AP dimension, AP ¼ d eff 4.5 cm. These investigators also found that the mean aspect ratio of the torso, that is, the ratio of the AP dimension to the lateral dimension, was (standard deviation ¼ 0.061). The investigators also evaluated the mean aspect ratio for 35 pediatric patients and found it to be (standard deviation ¼ 0.054). The data from Kleinman et al. (2010) and Boone et al. were combined, along with information provided in ICRU Report 74 (ICRU, 2005), to estimate the relationship between effective diameter and the linear dimensions (AP and lateral) of the torso. Figure 8.7a shows the relationship between effective diameter and the AP dimension; a second-order polynomial function was used to fit the relationship. Figure 8.7b illustrates the effective diameter as a function of the lateral dimension. For these data, the shape of the torso in cross-section was assumed to be elliptical, and the area was computed from the major and minor radii, which in turn are related to the AP and lateral dimensions of the patient. Figures 8.7a and 8.7b are taken from AAPM report 204 (AAPM, 2011), and these curves (with associated equations) allow the estimation of effective diameter when either the AP dimension or lateral dimension of the patient is known. Lateral and AP dimensions can be obtained from a projection image of the patient, which is routinely acquired prior to the actual CT scan. This image is used to set up the subsequent CT scan; for instance, the technologist can mark the superior and inferior edges of the CT acquisition using the patient s anatomy as a landmark. The projection image is acquired using the CT hardware, but without gantry rotation as the patient is translated through the x-ray beam on the CT couch. This projection image has many trademarked names, such as the scout view, the scanogram, or the topogram; however, generically this image is referred to as the localizer or the digital projection radiograph. The primary utility of the relationships illustrated in Figures 8.7a and 8.7b in the clinical CT setting occurs when the localizer view has been acquired, but the CT scan has not yet been 92

103 Patient Size-Specific Dose Estimation Figure 8.7. Effective diameter as a function of linear dimensions of the torso. The points represent data reported in Boone et al. (2003), Kleinman et al. (2010), and ICRU Report 74 (ICRU, 2005). A second-order polynomial provides an approximate fit (solid line). (a) The effective diameter as a function of the AP dimension. (b) The effective diameter as a function of the lateral dimension (fit is solid line). initiated. For the localizer view, the AP dimension can be measured from a lateral localizer scan, and the lateral patient dimensions can be evaluated in a PA view. By determining the AP or lateral dimension of the patient on the localizer view, the effective diameter of the patient can be estimated. As will be shown below, these values can then be used to estimate a conversion factor that in turn can be used to compute the SSDE (AAPM, 2011) for the patient prior to the commencement of the CT scan. In principle, this method would allow the technologist to predict inappropriately high patient doses prior to the CT scan, and make technique adjustments to reduce the absorbed dose. It is recognized that the localizer view on the CT scanner is a projection image produced in fan-beam geometry, and therefore some magnification in the image is present. If the patient is not properly centered in the gantry, the linear dimensions measured on the image will be less accurate because of the magnification. CT manufacturers have access to the attenuation data measured during a localizer view, and these data could also be used to compute a more accurate estimate of patient size. However, this information is proprietary to each vendor, and achieving a common metric across vendors using attenuation measurements is not likely. In most clinical settings when dose estimates are required (after the CT scan), the CT image itself should be used for the determination of patient size. Unlike the localizer images, the CT image dimensions are accurate in all three dimensions. Although the lateral and the AP linear dimensions can be measured on an axial CT image using software tools available on all modern CT scanners, the preferred approach for estimating size is to measure the area of the patient s body directly from the cross-section of the CT image. A relatively simple approach for estimating the area of a patient s cross-section is described below. The automated assessment of the effective diameter from an axial CT image is relatively straightforward. The dimensions of a given pixel (Dx, Dy) are found in the DICOM header, and the pixel area is computed: A p ¼ Dx Dy. In the CT image, the HU of water is approximately 0, and the range of HUs in most soft tissues ranges from about 2200 to þ200; however, the HU for lung tissues can be much lower, and the HU of bone is much higher. Air surrounds the body and is also present in the lung and in some body cavities. To calculate the effective diameter from a single CT image, an algorithm can be used to evaluate each HU value in the image, and tally only those pixels that exceed a certain threshold value, G. Although for air, HU ; , the HU of air in some regions of the image internal to the body can be higher than due to x-ray scatter and other artifacts, suggesting that a threshold value slightly higher than should be used to segment tissues from air. A computer algorithm that counts the number of pixels in the image exceeding a threshold value G (such as G ¼ 2800) can be used to segment body tissues from air. In this algorithm, N is first set to 93

104 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY zero, and then: Py max Px max y¼0 x¼0 ifðimageðx; yþ. GÞ; N ¼ N þ 1 ; ð8:1þ where G is the threshold value, image(x,y) is the HU value for pixel (x,y), and the summation is performed over the entire CT image. It is understood that N ¼ N þ 1 refers to indexing the counter variable N when the if condition is true. The number of pixels, N, exceeding the threshold value in the CT image is then multiplied by the area per pixel, A p, to compute the total cross-sectional area, A, of the segmented body region in that CT image, A ¼ N A p : ð8:2þ The effective diameter is then computed from the segmented body area: rffiffiffiffiffiffi 4A d eff ¼ : ð8:3þ p This procedure is relatively robust, but it tends to include the CT table as part of the body area; in practice, this results in a small positive bias in the estimate of the effective diameter. One of the limitations of this procedure is that in some cases the body area in the CT images is truncated, that is, part of the patient s anatomy is outside of the reconstructed CT image. In such cases, the method described above will underestimate the effective diameter. However, it might still be possible to evaluate either the lateral or AP dimension of the patient, which then can be used in the estimation of body size. In some CT images (e.g., chest), an appreciable amount of internal air is contained within the body dimensions; however, air does not attenuate x rays appreciably, and therefore the external dimensions of the body will overestimate the attenuation of that axial section of the body. To compensate for this, the water-equivalent patient diameter can be used. The assessment of the water-equivalent patient diameter, d w, requires an additional step in the algorithm described above for d eff. Essentially, the average density of the pixels in the image that are flagged as being tissue (when HU. G) is also tallied: Py max Px max y¼0 x¼0 if½imageðx; yþ. GŠ; 8 < N ¼ N þ 1; HU þ 1000 : : X ¼ X þ 1000 ð8:4þ In this case, for pixels other than for air, the average pixel density relative to water is P ave ¼ X N : ð8:5þ Note that if in Eq. (8.4), HU ¼ 0 for all pixels (corresponding to water), then the average density P ave would be unity. The water-equivalent patient diameter, d w, is given by rffiffiffiffiffiffi 4A d w ¼ P ave : ð8:6þ p Figure 8.8 illustrates this case for cylindrical PMMA (r ¼ 1.19 g/cm 3 ) phantoms with diameters ranging from 100 mm to 320 mm. The estimation of d eff or d w for the patient from area measurements made from the CT image is a direct measurement; however, the estimation of d eff from the lateral or AP dimensions assumes a characteristic (elliptical) shape for the human torso. The use of d w is preferred over d eff, in general, especially for the thorax. Another consideration regarding patient dimensions relates to where along z should the effective diameter be measured. To study this, data from a cohort of patients were evaluated, and the average diameter of the patient [using Eq. (8.3)] for each CT image over the entire length of the scan was compared against the diameter of one CT image at the midpoint of an abdominal-pelvis CT scan. Figure 8.9a illustrates this relationship for the most prevalent CT examination, the abdomen pelvis scan. Although good correlation exists between these two dimensions of body size, there is concern about the 4.7 cm offset seen in the data. Assuming that the average diameter is the superior quantity as it takes into consideration all of the CT images in the scan, these data suggest that the midpoint diameter for an abdomen pelvis CT scan is not the best value to use for the SSDE. Figure 8.9b illustrates the average-diameter versus midpoint-diameter relationship for the abdomenonly component of the CT scan, and here better agreement is seen, with no offset and an insignificant 2.6 % difference in slope. Figure 8.9c illustrates this relationship for the pelvis component of the CT scan, and an even better agreement is seen with no offset and a slope of essentially 1.0. The data shown in Figure 8.9a indicate that there should be some concern when using SSDE corrections that are global and are not performed on a CT slice-by-slice basis in the abdomen pelvis exam. This bias is considered significant, and further research is necessary to evaluate if the midpoint diameter of the patient is sufficiently 94

105 Patient Size-Specific Dose Estimation Figure 8.8. The assessment of the water-equivalent diameter. (a) An axial CT image of a small PMMA phantom. (b) The water-equivalent diameter as a function of actual PMMA diameter. The higher density of PMMA relative to water accounts for the slight upward bias of the data relative to the line of identity. robust for SSDE assessment in abdomen pelvis CT. 8.4 Size-Specific Dose Estimates The combined data from the numerous studies described in Section 8.2 have been evaluated to develop a relationship between a dose-conversion factor and the effective diameter of the patient. As described by Turner et al. (2010), when sizedependent scaling factors were normalized by the CTDI vol, many of the dependencies on scanner type, bow-tie filter, and x-ray-tube potential were effectively factored out. Therefore, the data used as input to this analysis were individually normalized by CTDI vol, and then combined. If the CTDI vol was specifically reported, it was used for the normalization. For the data illustrated in Figure 8.10 (for a tube potential of 120 kv), if CTDI vol data were not available, the individual curves were normalized to a value of 1.09 for a 320 mm diameter patient. This factor of 1.09 [see Eq. (4.3)] converts from air kerma to absorbed dose in water, recognizing that CTDI vol is measured in air, whereas the desired dose information is for a water-equivalent patient. The data points in Figure 8.10 show very similar trends; however, there is greater dispersion in the data at smaller effective diameters. This is in part due to the fact that the normalization point is at 320 mm. The best-fit curve of the points is the solid black line. The dashed line also plotted represents the results of AAPM Report 204 (AAPM, 2011), which was derived from 8 of the 12 data sets shown here (specifically, the top eight data sets as indicated in the key in Figure 8.10). The difference between the AAPM Report 204 trend line and that developed from this more inclusive database is very small, and given the dispersion in the data the differences are clearly insignificant. Therefore, the use of the curve as published in AAPM Report 204 is recommended. The data illustrated in Figure 8.10 are for a tube potential of 120 kv. The data shown in Figure 8.11a correspond to the average absorbed dose as a function of effective diameter for x-ray-tube potentials ranging from 80 kv to 140 kv, with each curve normalized to a setting of 100 ma s (Zhou and Boone, 2008). As expected, for the same mas setting, higher tube potential leads to higher air-kerma and absorbed-dose levels. The average absorbed dose for smaller patients is higher than for larger patients, consistent with the results of Figure Figure 8.11b shows the curves for 80 kv to 140 kv, but normalized to 1 mgy of air kerma at the isocenter of the scanner. This normalization causes the four curves to essentially collapse on one another. Figure 8.11c shows the average absorbed dose as a function of the effective diameter, but here each curve is normalized by the CTDI vol assessed for the 320 mm diameter phantom. The curves in Figure 8.11c also show significant overlap, with better overlap at larger effective diameters and more dispersion at smaller effective diameters. Based upon the plots shown in Figures 8.11b and 8.11c, normalization to the air kerma at isocenter results in the best agreement among these four curves. However, such air-kerma 95

106 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure The conversion coefficient as a function of effective diameter for a 32 cm diameter phantom. The points are from 12 different studies, as described in Section 8.2: Mc-Si, McCollough/ Siemens; Mc-GE, McCollough/General Electric; MG-Si, McNitt-Gray/Siemens; MG-Ph, McNitt-Gray/Philips; MG-GE, McNitt-Gray/General Electric; MG-To, McNitt-Gray/Toshiba; TS-Mx, Toth-Strauss/mixed scanner manufacturers; ZB-GE, Zhou-Boone/General Electric; B-G-S-G, Boone et al./general Electric; HD-cxr, Huda, General Electric Chest CT; N-GE, Nickoloff/General Electric; N-Si, Nickoloff/Siemens. The solid line represents the best fit to the data points; the dashed line is the curve reported in AAPM Report 204 (AAPM, 2011). Figure 8.9. Diameter at the midpoint versus average diameter. (a) The midpoint diameter of patients from the abdomen pelvis CT scan, as a function of the average patient diameter computed from the diameter measured for each CT slice in the scan. The solid line represents the fit, D midpoint ¼ D ave (b) The diameter at midpoint as a function of average diameter for the abdomen component of the CT scan. The solid line represents the fit D midpoint ¼ D ave. (c) The diameter at midpoint versus average diameter for the pelvic component of the CT scan. The solid line represents the fit D midpoint ¼ D ave. data are typically not available to the operators of CT scanners, except from a physicist s report. The normalization procedure using CTDI vol (Figure 8.10) is considered adequate, and the CTDI vol is more widely available. The trends shown in Figure 8.11a and 8.11c illustrate that when normalized by CTDI vol, the dose dependence on x-ray-tube potential is well accounted for. This means that one general curve corresponding to conversion coefficients as a function of d eff (or d w ) can be used for different types of CT scanners (e.g., see Figure 8.10), operating at different tube potentials (e.g., see Figure 8.11). Figure 8.12, taken from AAPM Report 204, shows dose-conversion coefficients as a function of effective diameter for the situation in which the 160 mm PMMA phantom was used for the assessment of CTDI vol. Because the small phantom is often used to assess pediatric body imaging, the ages corresponding to different effective diameters are illustrated on this figure as well. As mentioned in AAPM Report 204, d eff or preferably d w should be used to compute the dose-conversion coefficient when this value is known. In the absence of knowledge of d eff or d w,age can be used as a secondary parameter for absorbed- 96

107 Patient Size-Specific Dose Estimation Figure Average absorbed dose as a function of the effective diameter. (a) For four different tube potentials and 100 ma s on the General Electric VCT scanner (Zhou and Boone, 2008). (b) Data of Fig. 8.11a normalized by the air kerma at isocenter of the scanner. (c) Data of Fig. 8.11a normalized by the CTDI vol for the 320 mm PMMA phantom. dose estimates. The diameter-versus-age information used in Figure 8.12 was described in ICRU Report 74 (ICRU, 2005). 8.5 Summary The data from a number of investigators have been combined and show that for the same CT technique factors, the average absorbed dose is higher for smaller patients. The curves shown in Figures 8.10 and 8.12 clearly demonstrate these trends. The CTDI vol is reported for air; however, the dose-conversion coefficients to obtain SSDE include the f-factor, f SI, from air to water absorbed dose. The SSDE dose-conversion coefficients also include the fact that abdomen scans are longer (200 mm to 300 mm) than the 100 mm scan length that is the basis for CTDI vol (i.e., taking into consideration the discussion of H(L) in Section 7), at least for the eight studies that contributed to the AAPM Report 204 data that are recommended for use in this Report. The SSDE values were computed for the center of the scan field along the z axis, and the absorbed doses at the edges of the field will be slightly lower (see Figures 7.9 and 7.10). The SSDE is considered to be more accurate than CTDI vol, and allows a relatively straightforward assessment of absorbed dose in patients. The coefficients provided in Table 8.1 describe the equations to convert CTDI vol to SSDE when the d eff or d w of the patient is known. A more complete discussion of the SSDE concept is available in AAPM Report 204 (AAPM, 2011). 97

108 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Table 8.1. The mathematical relationships between the effective diameter (d eff ) and the lateral dimension (LAT) or the AP dimension of a CT image. The linear fit relating d eff to the sum of the LAT and AP dimensions is also provided d eff ¼ þ (AP)} (AP) 2 d eff ¼ þ (LAT) þ (LAT) 2 d eff ¼ þ (AP þ LAT) Note: The coefficients are given to from six to eight decimal places to maintain computational accuracy in the evaluation of these polynomials. Figure The conversion factor as a function of effective diameter for a 160 mm PMMA phantom. These data are useful when the CTDI vol is reported for a clinical study for the 160 mm phantom. The relationship between age and effective diameter is indicated by the vertical lines, with the age information data taken from ICRU Report 74 (ICRU, 2005). In some CT-scanning modes, there are limitations in the application of the SSDE using a single image for estimating patient size for a given protocol (such as chest, abdomen, or pelvis). When x-ray-tube-current modulation is used, the tube current and hence the absorbed dose in the patient can vary appreciably along the z axis of the patient, depending upon how the patient diameter varies along the z axis. In patients with large longitudinal variations in girth, a single, global estimate of effective diameter will be insufficient to compensate for the range of diameters interrogated by the x-ray beam and thus the different absorbed-dose levels that will be realized. In this case, a CT-image-by-image approach to size estimation is necessary. This will be discussed in Section 9. 98

109 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/nds Automatic Exposure Control in CT 9.1 Introduction Up until the early 2000s, whole-body CT scanners required manual selection of technique factors such as the tube potential, tube current, time, and pitch. Recognizing that the automatic-exposure control (AEC) features used so successfully in radiography could play an important role in CT, manufacturers developed a number of vendor-specific AEC techniques. AEC systems not only adjust technique factors to accommodate to the overall physical size of the patient being scanned, they also can dynamically accommodate for differences in the x-ray beam path-length through the patient during gantry rotation and while scanning along the z axis. Although the use of manually selected technique factors is still common in some circumstances, AEC with tube-current modulation (TCM) has become standard practice in CT imaging. Helical (spiral) CT, combined with the use of dynamically adjusted technique factors, adds to the complexity of dose assessment, the topic of this Section. The overall function of automatic exposure control in CT was described in Section Here, the operation is described in the context of absorbed dose in the patient. Automatic exposure control applies to two general aspects of CT technique selection: overall exposure control and tube-current modulation. These features will be discussed sequentially. 9.2 Automatic Exposure Control The basic AEC feature has the effect to increase the overall dose levels for large patients and decrease the dose levels for smaller patients, in order to deliver comparable image quality for both. As with all x-ray imaging, it is the x-ray intensity striking the detector that governs the statistics in the image. To penetrate larger patients and thicker body parts, the incident x-ray beam intensity needs to be increased for an appropriate x-ray intensity to reach the detector. For smaller patients, the x-ray beam intensity can be reduced, and for small pediatric patients, the dose levels thus can be reduced considerably. Figure 9.1a is a schematic of a phantom with five different object diameters, ranging from 10 cm to 32 cm in diameter. This phantom was used to examine the automatic adjustment of overall dose levels for two different CT scanners, a Siemens AS þ system and a General Electric VCT system. These two scanners were selected because they utilize fundamentally different concepts in TCM. Figure 9.1b illustrates the automatically selected mas levels for the Siemens system, over the range of phantom diameters. This system uses the concept of reference mas as its primary AEC control parameter. The reference mas is selected by the CT operator to deliver an expected image quality (essentially noise levels) to a standard-sized patient. For a given reference mas, if the patient diameter is larger or smaller than the reference patient diameter, the system will increase or decrease radiation levels, respectively. In both cases, the goal is to provide the same image quality (signal-to-noise ratio) over a range of different patient sizes. In Figure 9.1b, it is seen that for a given reference mas, the actual tube current selected in the AEC mode is adjusted depending upon the diameter of the phantom. The relative adjustment as a function of phantom diameter is constant across the reference mas settings. Figure 9.1c illustrates the control scheme used by General Electric scanners that make use of the noise index as their primary AEC parameter. The noise index is related to the standard deviation of CT numbers in the CT image, and therefore is a control parameter that focuses more on the noise in the image than on a technique factor per se. Itis observed that the slope of the curves in Figure 9.1c is negative, and that the slope of the curves for the Siemens scanner in Figure 9.1b is positive, as a function of their respective AEC parameters. The ramifications of this are clear: for Siemens scanners, the reference mas parameter is turned up with the result to increase the absorbed dose, and for General Electric scanners, the noise index parameter is turned down with the result also to increase the absorbed dose. The trends illustrated in Figures 9.1b and 9.1c represent the overall AEC control of the CT # International Commission on Radiation Units and Measurements 2013

110 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 9.1. Illustration of tube-current modulation. (a) The so-called wedding-cake phantom. The individual section diameters are 10 cm, 13 cm, 16 cm, 20 cm, and 32 cm. (b) The x-ray-tube-current time product resulting from the automatic exposure control on a Siemens scanner, as a function of the reference mas. (c) The x-ray-tube-current time product resulting from the automatic exposure control used by General Electric as a function of the noise index. scanner, as the phantoms used were cylindrical and homogeneous along the z axis, except for the discontinuities between sections of the phantom. The overall AEC control is essentially a oneparameter approach (either reference mas or noise index) for the overall dose levels from a given CT scanner; however, the x-ray-tube potential is an independent parameter that also plays a role in dose and image quality. 9.3 Angular Tube-Current Modulation The second component of automatic exposure control in CT is x-ray TCM. X-ray TCM changes the air-kerma rate by modulating the tube current to accommodate for the varying thickness of the body part being scanned. There are two components to tube-current modulation, an angular component that is active as the gantry rotates and affects the image-noise distribution in the x y plane, and a longitudinal component that adapts to the changing body dimensions as the patient is translated through the field of view along the z axis. Figure 9.2 illustrates both the angular and longitudinal components of tube-current modulation (see also Section 2.4.3). The cross-sectional shape of patients tends to be more elliptical than circular, and the angular TCM adjusts the x-raytube current to accommodate for the differences in x-ray path-length. Typically, the lateral dimension of the patient is greater than the anterior posterior distance, and the tube-current modulation would increase the tube current as the beam is penetrating the lateral dimension and reduce it in the AP dimension. This is a very rapid process, as the Figure 9.2. Angular TCM levels and the cumulative impact on the tube-current time product as a function of the position for a specific patient. Angular modulation of the x-ray-tube current occurs as the x-ray tube rotates around the patient, producing a high-frequency, approximately sinusoidal variation in air-kerma rate. TCM also has a lower-frequency component as the patient is translated through the x-ray beam. entire gantry rotation period is typically 0.50 s, so TCM is performed at approximately kilohertz frequencies. The modulation process leads to a relatively homogeneous distribution of x-ray photon fluence striking the detector during gantry rotation, which in turn reduces unnecessarily high absorbed-dose levels (for smaller projection pathlengths) and is an important component of dose optimization. The approximately sinusoidal modulation seen in Figure 9.2 represents the angular (i.e., x y) modulation of tube current. Along the length of the patient, the patient dimensions change depending upon the body habitus. In Figure 9.2, the patient has a relatively thin abdomen with larger 100

111 Automatic Exposure Control in CT hips, so the x-ray-tube current was increased over the hips and was slightly decreased through the torso. The x-ray-tube current was also reduced through the thoracic region due to the low density of the lungs, and increased near the patient s shoulders. Tube current is modulated to account for the average tissue path in the entire CT beam width (in z), and for scanners with wide x-ray beams this means that modulation of the tube current will be performed over wider swaths of tissue (in z). The temporal response of TCM along the z dimension of the patient will therefore be slower for wider x-ray beams (e.g., 80 mm), compared with narrower beam collimation (e.g., 20 mm). For situations in which the z-axis coverage is easily addressed (e.g., ample x-ray-tube power exists and patient motion is unlikely), CT operators might in some cases choose to reduce the x-ray-beam thickness (e.g., use 20 mm collimation on a 40 mm scanner) through protocol selection to allow tube-current modulation to be more adaptive to body contours. is estimated according to SSDE ¼ f 32D d w CTDI 32 vol : ð9:2þ Here, the average water-equivalent diameter, d w,is assessed along the length of the scan. Alternatively, the water-equivalent diameter of a representative CT slice along the scan length can be used (see Section 8.3). Equation (9.2) should be sufficiently accurate for SSDE when TCM is not used; however, it is recognized that there is a non-linear relationship between the f dw coefficient and diameter that can lead to a reduction in accuracy when significant fluctuations in diameter occur along the scan length of the patient. The use of TCM is common in CT imaging of the torso, as well as in the head and neck regions. When TCM is used, a more accurate estimate of the SSDE can be made if a slice-by-slice evaluation of d w is made and the tube-current time product for each CT image is known. In this case, the SSDE is determined using SSDE ¼ P N i¼1 f 32 d w ½iŠ C32 J i Dt pn : ð9:3þ 9.4 Patient Dose Assessment with TCM The assessment of the size-specific dose estimate (SSDE) is straightforward when TCM is not utilized and when the patient diameter is relatively uniform over the scan length. In such case, the CTDI vol can be used with the known waterequivalent diameter of the patient to compute the SSDE. In the following, data from abdomen pelvis CT scans performed on 227 patients on a single CT scanner (Siemens ASþ) will be used to illustrate the challenges of CT dosimetry when TCM is used. When constant tube current, J, is used throughout the entire CT scan and for a constant waterequivalent patient diameter, d w,thessde can be computed as SSDE ¼ f 32D d w CTDI 32 vol ; ð9:1þ where f 32D dw is the coefficient from AAPM Report 204 (AAPM, 2011) for a water-equivalent diameter of d w, derived from the tables in Report 204 (hence the D in the superscript nomenclature) for the 32 cm diameter phantom. The CTDI 32 vol is the CTDI vol reported by the CT scanner; for this adult-abdomen application, all scanner manufacturers use the 32 cm diameter phantom as reference, and that is indicated explicitly here in the superscript. For a situation in which the x-ray-tube current is constant, but the body region of the patient has variable diameter along the scan length, the SSDE Here, the summation over i includes the total number of CT slices in the scan, N; the coefficient f 32D dw[i] is determined from the water-equivalent diameter of the patient for each CT image i; the average tube current for slice i is J i, the gantry-rotation period is Dt, and the helical pitch is p. The product J i Dt is the mas, and the product J i Dt p 21 is the effective mas. The factor C 32 is the conversion coefficient that the specific CT scanner uses to compute CTDI 32 vol from the effective mas, and depends on CT manufacturer, pitch, collimation settings, x-ray-tube potential, bow-tie and other filters, and other more subtle factors. Figure 9.3 shows the linear relationship between CTDI vol and effective mas, and the slope of this curve ( in this case) is essentially the parameter C 32 in Eq. (9.3). 9.5 Examples of Slice-by-Slice CT Dose Calculation When TCM is used, and when the patient has a relatively non-uniform distribution of diameters along the scan length, Eq. (9.3) will yield a more accurate SSDE than using the simpler assumption of constant or average tube current for a scan. For implementation of Eq. (9.3) to be practical, automated software is needed to extract the pertinent information from the DICOM header on each CT 101

112 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY image, and an automatic determination of the d w is necessary for each CT image (see Section 8.3). To realize the potential of this approach, software was Figure 9.3. The CTDI vol as a function of effective mas (J Dt p 21 ) for one scanner (Siemens Definition ASþ), from 227 data sets. The slope of this curve (0.0674) determines the relationship between the CTDI vol and effective mas for this scanner, for a particular tube potential and bow-tie filter. developed to perform the SSDE calculation when current-tube modulation is used. Figure 9.4 illustrates such software. The entire series of CT images in a patient scan is read into computer memory, and the pertinent DICOM header information is extracted. The CT data itself are used to generate the PA (box 1 in Figure 9.4) and lateral data (box 2) projections, illustrated in the upper right of Figure 9.4. The effective mas is displayed in the lower left plot (box 3), and it is observed that large variations in the effective mas were used in this CT scan. The lower middle panel (box 4) illustrates the equivalent diameter assessed from CT images along the length of the scan. From this, the f dw conversion factor for the SSDE estimate was computed from the average diameter of each CT slice. Once the effective diameter is known, the f dw conversion factor is computed analytically from equations given in AAPM Report 204, which expedites this calculation. The computed SSDE is shown plotted as a function of z on the lower right panel (box 5). This software was used to evaluate parameters on 227 patients, and a number of trends can be Figure 9.4. The output of a program written to evaluate the slice-by-slice characteristics of an abdominal-pelvic CT scan. The CT images were used to generate the AP (box 1) and lateral (box 2) projection images shown. The three plots illustrate (box 3) the effective mas, (box 4) the water-equivalent patient diameter, and (box 5) the SSDE as a function of CT-slice position along the z axis. For each of the four sections A, B, C, and D on each plot, summary statistics are provided in the data box in the upper left of the display. 102

113 Automatic Exposure Control in CT identified as illustrated in Figures 9.5 through 9.9. The study involved the use of one CT scanner for one CT protocol (abdominal-pelvis examination), with automatic exposure control (including tubecurrent modulation). Figure 9.5 illustrates, as is to be expected, that the effective mas of the scan tracks reasonably well with the average patient diameter. The CTDI vol also tracks quite well with patient diameter, as shown in Figure 9.6a. This figure illustrates that under the simplified conditions of this one-scanner/one-protocol study, changes in the CTDI vol can be largely attributed to patient diameter coupled with automatic exposure control. The R 2 value of 0.77 in Figure 9.6a suggests Figure 9.5. The effective mas as a function of average patient diameter. These data were acquired using tube-current modulation. The effective mas increases non-linearly as a function of average patient diameter, typical of TCM techniques on any modern CT scanner. that 77 % of the variance can be attributed to patient diameter; the residuals between the measured data and best-fit line are illustrated in Figure 9.6b. The variance of the CTDI vol in Figure 9.6a is 55.2 mgy 2, and the variance in Figure 9.6b is mgy 2, confirming the 77 % reduction in variance ([ ]/55.2 ¼ 0.77). Relative to the CTDI vol, the SSDE tends to be larger for smaller patients, and smaller for larger patients. Figure 9.7 shows the SSDE as a function of CTDI vol ; lower values of CTDI vol correspond to smaller patient diameters (as seen in Figure 9.6a), and the lower CTDI vol values for smaller diameter patients are associated with higher SSDE conversion coefficients. The increase in SSDE relative to CTDI vol is shown as a function of average patient diameter in Figure 9.8. For patients whose diameter is smaller than 25 cm, the relative dose increase (i.e., SSDE/CTDI vol ) is from 50 % to 60 % on average, and for patients whose diameter is about 30 cm, the relative dose increase is about 20 %. Patients in the 35 cm to 45 cm range in diameter have a small dose reduction. The data were further evaluated as shown in Figure 9.9, where the ratio of the average pelvis diameter to the average abdomen diameter was assessed for male and females in the cohort of CT patients. A significant difference in the ratio is seen; women tend to have lower abdomen/pelvis diameter ratios, and men have characteristically larger ratios. These trends substantiate the very general observation that men tend to gain weight in their abdomen whereas women tend to carry weight in their hips. These trends have genderdependent ramifications on dose assessment when tube-current modulation is used. Figure 9.6. (a) The CTDI vol as a function of average patient diameter. Tracking with the effective mas (as shown in Fig. 9.5), the CTDI vol increases as a function of patient diameter. (b) The residual differences between the actual values and the curve fit (in Fig. 9.6a). The mean residual value is 0.0 mgy, and the standard deviation is 4.88 mgy. 103

114 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 9.7. The SSDE as a function of CTDI vol. The dashed line of identity is shown. As expected, the SSDE is higher than the CTDI vol (i.e., is above the line of identity) for smaller patients, and it is only slightly lower for larger patients. Figure 9.9. The ratio of the average abdomen diameter to the average pelvis diameter for two populations, males and females. A significant difference (p, 0.05) is observed, demonstrating that men and women tend to have different body-shape characteristics. Figure 9.8. The variation of the SSDE relative to CTDI vol as a function of patient average diameter. 9.6 Organ-Dose Estimation Organ-by-organ dose assessment is considered by many to be the ultimate dose assessment; a complete description of organ doses is necessary for the actual computation of effective dose, using (for example) the tissue-weighting coefficients from ICRP Publication 103 (ICRP, 2007). Although over the years, there have been many efforts using Monte Carlo calculations in three-dimensional phantoms to determine organ dose, the methods for computing SSDE on a slice-by-slice basis described above demonstrate that a practical tool for the estimation of absorbed dose on a slice-by-slice basis is presently available. It is further suggested that although Monte Carlo dose assessment is essential in CT in general, it is impractical and unnecessary to use Monte Carlo techniques on a patient-by-patient basis, especially when x-ray-tube modulation techniques have been used. It is, however, possible to extend the slice-by-slice dose-assessment approach described above (see Figure 9.4) to the estimation of organ absorbed doses, with the assumption that the relative organ position along the z axis of the patient can be characterized by a parameter Y organ. The organ positions can be scaled relative to boney anatomy, and thus the organ distributions along z would be based on a geometric rescaling of a specific patient s CT-based anatomy to a standard organ template produced by assessing organ positions over a large cohort of patients. With the assumption that such a rescaling has been performed, organ dose can be estimated using D organ ¼ PN i¼1 f 32 D w ½iŠ Yorgan z½iš C 32 J i Dtp 1 ; ð9:4þ where Y z organ is a dose-weighting function describing the contribution of organ dose at position z for each organ of interest (liver, kidney, bladder, etc.) from the average absorbed dose in the plane at the z position corresponding to the index value i. Figure 9.10 illustrates this concept. Note that z[i] need not be a linear function of i. Examples of realistic boney landmarks in the torso include the superior edge of the clavicle, the sternum, the pelvic crest, or any vertebral body. All other terms in Eq. (9.4) have been described previously. Using center and peripheral CTDI 100 values averaged over tube potential (from 100 kv to 104

115 Automatic Exposure Control in CT plane, and that the z-dependent Y z organ is sufficiently robust to provide a good estimate of each organ s dose when the average planar dose to each individual CT section is known. Further research is needed to evaluate if one-dimensional (i.e., along z) organ-distribution functions can produce accurate estimates of organ dose in CT. Figure A torso with boney landmarks, and with associated representative organ positions. Using an organ-weighting system (Y z organ ), determined from a large patient cohort but scaled to each individual patient, estimation of individual organ doses would be possible even when AEC is used for a patient with a non-uniform diameter distribution along z. 140 kv) and across four manufacturers systems 1 (ImPACT, 2004), the periphery-to-center CTDI 100 ratio in the 160 mm diameter head phantom is 1.08 (COV ¼ 2.8 %), and for the 320 mm diameter body phantom the ratio is 1.98 (COV ¼ 7.5 %). Thus, the weighting functions, Y organ z, would have to take into consideration the average in-plane position of the organ, from center to edge; however, this is likely to be a second-order effect relative to the organ s position along the z axis. Furthermore, most organs are positioned neither at the center nor at the extreme periphery, and so radial ( peripheryto-center) averaging is already included in the computation of CTDI w from CTDI center 100 and CTDI peri 100. These observations suggest that there might be little dependence on organ position in the (x y) 9.7 Summary CT dosimetry has had to adapt rapidly to changes in CT-scanner capabilities. Although constant-tube-current protocols are still used for some applications, AEC techniques in CT lead to dynamically adjusted x-ray-fluence rates during the entire procedure in the majority of CT protocols. Dosimetry under these conditions is most accurate when the effective mas for each CT slice generated in the image series is considered separately, and size corrections using the SSDE can then address both the specific x-ray-tube output for each CT image, as well as the waterequivalent diameter of the patient at that z position. Although simpler methods such as using one CT image at the middle of the CT scan to estimate patient size can deliver reasonable estimates for some scan protocols, or assuming that an average tube current was used over the entire scan, a slice-by-slice approach to individual patient dosimetry will likely yield the most accurate dose estimate possible at this time. Such an approach requires software that evaluates each CT image in the CT scan. If such software is not available, other methods for dose assessment when AEC modes are employed will be adequate to determine SSDE in most clinical settings. 1 General Electric VCT, Philips Brilliance, Siemens Definition AS, and Toshiba Aquilion Multi. 105

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117 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndt Spatial Resolution in CT 10.1 Introduction Spatial resolution is an important attribute of any radiological imaging system. In CT, spatial resolution depends not only upon physical parameters such as the focal-spot size and detectorelement dimensions similar to projection radiography, but because all CT images are reconstructed mathematically the resolving power of a CT image is fundamentally linked to the image-reconstruction methods as well. In addition to traditional filteredback-projection-reconstruction algorithms, which utilize a variety of reconstruction kernels that have a profound impact on spatial resolution, iterative CT image-reconstruction techniques using statistical or model-based constructs are also used clinically. These non-linear, adaptive algorithms create a challenging mathematical environment for objectively characterizing spatial resolution Basic Spatial-Resolution Metrics Spatial resolution refers to the ability of an image to convey detail; medical imaging systems produce images that are usually degraded in detail compared with the actual object being imaged. With respect to a volumetric CT data set, the imaging process can be described mathematically by the three-dimensional (3D) spatial convolution Iðx; y; zþ ¼ ð 1 z 0 ¼ 1 ð 1 y 0 ¼ 1 ð 1 x 0 ¼ 1 Vðx 0 ; y 0 ; z 0 Þ PSF 3D ðx x 0 ; y y 0 ; z z 0 Þdx 0 dy 0 dz 0 : ð10:1þ Here, the input object, V (x, y, z), is defined in three spatial coordinates, and the CT data set resulting from the imaging procedure is given here by I(x, y, z). The 3D point-spread function PSF 3D (x, y, z) describes the 3D-resolution properties of the imaging system. Because CT images are mathematically reconstructed, the spatial resolution is enhanced in some cases by the use of specific kernels used for CT-image reconstruction, which operate over a finite range of spatial frequencies. An ideal stationary imaging system is the one in which the PSF 3D is constant over the entire imaging field of view, and most medical imaging systems approximate this ideal. However, due to the acquisition geometry of whole-body CT systems, the attributes of the PSF 3D vary in the axial (x y) plane compared with the longitudinal (z) axis. To characterize the 3D PSF, consider a phantom construct of a very small metal sphere surrounded by a homogeneous material (such as water) as shown in Figure If the metal sphere has dimensions that are much smaller than the voxel dimensions, then it approximates a 3D delta function, d(x, y, z). For an image acquired of this phantom, the PSF 3D can be assessed simply as PSF 3D ðx; y; zþ ¼ ð 1 z 0 ¼ 1 ð 1 y 0 ¼ 1 ð 1 x 0 ¼ 1 dðx 0 ; y 0 ; z 0 Þ PSF 3D ðx x 0 ; y y 0 ; z z 0 Þdx 0 dy 0 dz 0 : ð10:2þ Equation 10.2 states that if a delta function (i.e., the small sphere) characterizes the object to be imaged, the image produced after acquisition represents the PSF 3D. Although a fully 3D characterization of the PSF 3D is a desirable goal for most tomographic imaging technologies, the acquisition geometry of CT suggests that separating the axial (x y) and longitudinal (z) components of spatial resolution should be useful from a practical standpoint. Figure 10.2a illustrates ideal input functions to a two-dimensional imaging system, and Figure 10.2b illustrates the degraded (blurred) output images. In addition to the point-spread function, other spatialdomain spread functions (Bushberg et al., 2012; Dainty and Shaw, 1974; Hsieh, 2003; Kalender, 2011) can be used to quantify the spatial resolution in computed tomography. Figure 10.2c illustrates the point-spread function (PSF), the line-spread function (LSF), and the edge-spread function (ESF). All of these spread functions have been used to measure spatial resolution in computed tomography. # International Commission on Radiation Units and Measurements 2013

118 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY (axial or longitudinal) using the Fourier transform: Ð 1 1 MTFð f x Þ¼ LSFðxÞe 2pifxx dx Ð 1 1 LSFðxÞ dx ; ð10:5þ Figure Measurement of the 3D MTF. A small high-contrast sphere placed in the center of a homogeneous phantom provides a 3D delta function, d(x, y, z), as a stimulus to a CT system for characterization of the PSF 3D (x, y, z). where here f x represents spatial frequency. The integral in the denominator of Eq. (10.5) normalizes the MTF to unity at f x ¼ 0. If the PSF or ESF is measured directly in CT, these functions can be transformed into the LSF using Eqs. (10.3) or (10.4b), respectively, for subsequent assessment of the MTF. Although analytical computation of the MTF from the LSF is possible in some cases, Eq. (10.5) is evaluated in most cases by a computer subroutine. There is a relationship between the point-spread function and the line-spread function. Let the x and y axes define the axial plane, and z the longitudinal or long-axis of the scan (or patient s body). The axial-plane line-spread function can be determined by integration of the point-spread function: LSF axial ðxþ¼ ð 1 z¼ 1 ð 1 y¼ 1 PSF 3D ðx; y; zþdydz: ð10:3þ Because the axial (x y) plane is rotationally symmetric, LSF(x) ¼ LSF(y), in general. However, in some cases (including CT imaging), the two dimensional PSF(x, y) can be anisotropic, and in such a case the LSF will be dependent upon the angular orientation of the two-dimensional PSF(x, y) with respect to the x y coordinate system. The edge-spread function can be determined by the integration of the axial line-spread function: ESF axial ðxþ ¼ and conversely, ð x x 0 ¼ 1 LSF axial ðx 0 Þdx 0 ; LSF axial ðxþ ¼ d dx ESF axialðxþ: ð10:4aþ ð10:4bþ Equations (10.3), (10.4a), and (10.4b) illustrate that the family of spread functions, the point-spread function, the line-spread function, and the edgespread function, are related and that any one of them can be used to assess the resolution of a CT system in the axial plane. The PSF, LSF, and ESF are functions that describe resolution in the spatial domain. However, it is common to transform these functions into the spatial-frequency domain, to obtain the modulation-transfer function, MTF. The MTF is typically computed from the line-spread function 10.3 Assessment of Axial-Plane Resolution in CT In the earliest days of computed tomography, Judy (1976) used a slanted-edge approach to determine the edge-spread function (Figure 10.3). The slanted edge provided the ability to oversample the edge-spread function, and overcome the Nyquist 1 limitations imposed by the CT-image pixel dimensions. In Report 1 of the American Association of Physicists in Medicine Report series (AAPM, 1976), it was noted that a number of established techniques for characterizing spatial resolution could be adapted to CT scanners. These approaches included (a) wedge or spoke-type modulation-transfer function phantoms, (b) edge-response functions, and (c) the impulse response (i.e., PSF) from a small wire. Although direct measurement of the line-spread function using slit images was not mentioned, this technique is a straightforward extrapolation of methods used in radiography, and will be discussed below. Point-response functions were studied (Bicshof and Ehrhardt, 1976) by scanning 0.15 mm diameter stainless-steel wires, to produce point-spread functions in reconstructed CT images. Two-dimensional-Fourier-transform techniques were used to compute the two-dimensional MTF(f x, f y ) from these point-spread functions. These investigators also studied the dependence of the MTF on the position in the field, and found virtually no dependence (see Figure 10.4a) on the parallel-beam CT scanner studied. The inverse Fourier transform of the two-dimensional MTF was computed to produce a point-spread function, and the profile through that PSF is shown in Figure 10.4b. The negative- 1 The Nyquist frequency (f N ) is the highest frequency that can be described in an image with linear pixel dimension s, and is given by f N ¼ 1/(2 s). 108

119 Spatial Resolution in CT Figure Illustration of the spread functions used in imaging. (a) Input images (left to right) defining the point-spread function (PSF), the line-spread function (LSF), and the edge-spread function (ESF). (b) Simulated degraded-output images showing raw image data used for the measurement of the PSF, LSF, and ESF. The blurring seen in these functions is due to the imperfect resolution properties of the imaging system being characterized. (c) Graphs showing the actual PSF, LSF, and ESF. The PSF(x,y) is a 2D function, and the LSF(x) and ESF(x) are 1D functions. side lobes seen in Figure 10.4b are the result of the edge-enhancement features of the convolution kernel used for filtered-back-projection reconstruction (Bushberg et al., 2012). In the early work of Schneiders and Bushong (1980), the technique of Judy was used with a custom computer program to compute the edgespread function from an image. The ESF was differentiated numerically, producing the line-spread function. Fourier transform of the LSF resulted in the (complex) optical-transform function, whose modulus is the modulation-transfer function. This study was an early demonstration of computerbased numerical methods for the calculation of spatial-resolution in CT. Other investigators (Nickoloff and Riley, 1985) developed an interesting approach toward characterizing the spatial resolution of CT. They assumed that the point-spread function could be approximated by the Gaussian distribution: PSFðrÞ ¼e a2 ðr r c Þ 2 ; ð10:6þ where r c is the center position of the PSF. Rearrangement of the above equation and substituting b ¼ 2ar c gives 1 1=2 a r þ b ¼ ln : ð10:7þ PSFðrÞ Using this approach, point-spread-function data were plotted as shown in Figure 10.5a. Data points along a straight line describe a point-spread function that is strictly Gaussian, whereas deviation from the straight line suggests non-gaussian behavior. The slope of the line shown in Figure 10.5a is the value of a in Eq. (10.7), determined by linear regression. By inserting the value of a into Eq. (10.6), the point-spread function is obtained (see Figure 10.5b). Before the existence of modern-day picture archiving and communication systems (PACS), access to the digital-image data from a CT scanner or any other digital-imaging modality was limited, and the CT-image-file format was often proprietary. 109

120 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Early MTF characterization in CT by Judy (1976). (a). By angling an edge of PMMA in water by a small angle (u) relative to the image pixel array, the sampling interval D was decreased geometrically, producing a smaller sampling interval cd. For this work, u ¼ 1.28 and c ¼ (b) The ESF computed from the oversampled edge. (c) The MTF computed from the LSF (determined by numerically differentiating the ESF). This scanner had a cut-off frequency of about 0.30 mm 21 at 5 % MTF. In many cases, the only output was a film image. However, many CT scanners had basic imageprocessing tools available at the console, such as the ability to measure the mean and standard deviation of the HU in a user-placed region of interest. Droege and Morin (1982) capitalized on the availability of these tools for the estimation of the MTF. Figure 10.6a illustrates a CT image of a line-pair phantom designed for use in CT. The modulation M 0 is determined by the expression j M 0 ¼ HU 1 HU 2 j ; ð10:8þ 2 where HU 1 and HU 2 correspond to the mean CT numbers of the bars and of the background material, respectively. The frequency-dependent MTF(f) is computed as MTFð f Þ¼ p p ffiffiffi 2 4 Mð f Þ M 0 ; ð10:8þ corresponding to the discrete frequency f of each bar pattern, where f ¼ (2B) 21 for bars of width B. Note that four different bar patterns are seen in Figure 10.6a. Figure 10.6b illustrates the excellent agreement between the Droege Morin MTF method and that using a conventional method (using the PSF from stainless-steel wires). The Droege Morin approach allowed the practical estimation of the MTF in CT in the pre-pacs era. Although the use of wires to generate PSF and edges to generate ESF profiles have been used extensively, planar layers of metallic foil can be used to measure the LSF directly (Boone, 2001). In this 110

121 Spatial Resolution in CT Figure Resolution measurements on an early CT scanner. (a) Bischof and Ehrhardt (1977) characterized the PSF in the CT field of view, and the MTFs were computed at several locations. (b) An assumed symmetrical PSF was computed from the two-dimensional MTF measurements. Figure Resolution assessment using a Gaussian model. (a) The analysis concept devised by Nickoloff and Riley (1985), as described in the text. When the PSF data plotted in this manner fall on a straight line, the CT system demonstrates a PSF that can be characterized by a Gaussian function. (b) The Gaussian PSF derived from the slope of the line in (a). procedure, a sheet of metallic foil sandwiched between two tissue-equivalent slabs for rigidity (see Figure 10.7a) was imaged at a slight angle with respect to the pixel array in the CT image. Imaging a plane on-edge produces an axial image with a line or slit running through it (see Figure 10.7b). From these slit images, a presampled line-spread function (see Figure 10.7c) can be synthesized (Boone, 2001; Bushberg et al., 2012), and the pre-sampled MTF can be computed from it. The measured LSF and MTF plots in Figures 10.7c and 10.7d are for three different kernels for a General Electric Lightspeed 16 scanner. Considerable edge enhancement is apparent for the lung kernel, where the MTF values substantially exceed unity at mid-frequencies. An alternative approach to generating a slit image is to use an air gap instead of a metallic foil, creating a negative-polarity line-spread function instead of a positive-polarity line-spread function (Uto et al., 2012). The phantom is illustrated in Figure 10.8a, and consists of two tissue-equivalent slabs separated at the edges by a thin layer of paper. The CT image of this is inverted 111

122 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure MTF analysis using a bar phantom. (a) The method described by Droege and Morin (1982) made use of the basic image analysis tools available on CT scanners in the early 1980s, with regions of interest located on a bar phantom as shown. The mean and standard deviation of the HU in each region of interest were used to compute the MTF. (b) The MTF measured using the Droege Morin method compares well with the more conventionally (i.e., wire PSF) measured MTF curve. mathematically, creating the line-spread functions, illustrated in Figures 10.8b and 10.8c, for two different reconstruction kernels. The MTFs from this method are compared with those using the aluminum foil in Figure 10.8d (standard kernel) and in Figure 10.8e (bone kernel). Although some systematic bias is apparent, the MTFs from these two phantoms are quite similar. For routine quality control in the clinical environment, bar patterns designed specifically for CT are commonly used (see Figures 10.9a and 10.9b). This technique allows the user to determine the limiting spatial resolution subjectively, by visual inspection. Although this technique is adequate for spot checking the resolution properties of a CT scanner in the field, the evaluation of the modulation-transfer function is considered to be a more rigorous assessment of the resolution properties of the CT scanner Limitations and Concerns in Axial-MTF Assessment As mentioned in Section 10.2, a stationary imaging system is one in which the point-spread function is constant over the field of view. Modern fan-beam and cone-beam CT systems are only approximately stationary, as there are differences in the PSF from the center to edge in the reconstructed image, and there is a slight angular dependence as well. Therefore, the location of the measurement of spread functions (and the subsequent calculation of the MTF) needs to be referenced and/or made in a consistent manner using similar regions in the image. All modern CT scanners make use of filtered back projection (FBP), and many also utilize iterative reconstruction techniques. There are a number of iterative algorithms in common use among the commercial CT vendors, but most of the details of these algorithms are proprietary. Nevertheless, in general, iterative algorithms can exhibit non-linear behavior that violates the measurement paradigm (i.e., a linear, stationary system) for the MTF. Specifically, iterative reconstruction methods can produce images in which the MTF exhibits a greater or lesser dependence on spatial location (in comparison to FBP) as well as a dependence on the contrast (difference in HU) of the material forming the edge. Commercial CT scanners for medical applications are designed to optimally image tissue, which spans a range in Hounsfield units from about 2200 to þ200. Tissues and non-tissue materials encountered outside this range can produce unwanted effects on image quality, chiefly high-density objects of high atomic number (Z) that produce artifacts and non-linear responses. Therefore, resolution templates and phantoms that make use of either high-z or very dense materials can drive the scanner into non-linear regions of operation. The effect of dense or high-z materials can also cause beam hardening, another source of non-linearity in the reconstructed image. These observations suggest that phantoms for the measurement of 112

123 Spatial Resolution in CT Figure MTF analysis using an aluminum slit. (a) A thin Al foil is compressed between two tissue-equivalent blocks, and is aligned parallel to the z axis, with a slight angle with respect to the x y plane. (b) The image from which the LSF is deduced. (c) The LSF synthesized using the angled-slit method, for three reconstruction kernels. (d) The corresponding MTF curves for the three kernels. spatial resolution should employ relatively low-z materials or foils thin enough to not exceed the linear operating range of the scanner. A contrary observation, however, is that high-z or dense materials produce edges or lines with a high signal-tonoise ratio, which helps to produce high-precision MTF measurements. At the very minimum, HU saturation should be avoided by not exceeding the 12-bit HU range between and þ3095. A histogram plot of Hounsfield units for the image where spatial resolution is to be measured can verify that HU saturation has not occurred. Quantum noise tends to degrade the precision and accuracy of measurements of spatial resolution. 113

124 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure An inverse-contrast slit method employing an air slit. Some results are compared with those from an aluminum slit as described in Figure 10.7 (from Boone, 2000). (a) An air gap created between two pieces of solid phantom using paper spacers. (b) The LSF determined from the air slit (AS) and the aluminum slit (Al), for the standard kernel. (c) The LSF determined from the air slit (AS) and the aluminum (Al) slit for the bone kernel. (d) The MTFs assessed for the standard kernel. (e) The MTFs assessed for the bone kernel. Figure Resolution assessment using the American College of Radiology CT phantom. (a) An image from the resolution section of the ACR Phantom, reconstructed with the standard kernel on a General Electric VCT system. (b) The same raw data as in (a) but reconstructed with the bone kernel, which has higher spatial resolution compared with that using the standard kernel. To reduce the influence of quantum noise, tubecurrent and exposure-time settings that give the flexibility to use the small and large focal spots of the x-ray tube and yet provide high-precision images are recommended, but with the following considerations. The x-ray-tube focal spot can experience blooming effects (an increase in apparent size) at very high tube-current settings, and thus the use 114

125 Spatial Resolution in CT of the highest tube-current settings is not recommended unless these settings are used clinically. Large-diameter phantoms tend to increase the noise levels in the reconstructed image due to their greater attenuation. Therefore, it is desirable to characterize spatial resolution using a relatively small-diameter phantom. When the ESF is used to measure spatial resolution, differentiation [Eq. (10.4b)] to produce the LSF (which leads to the MTF) adds considerable noise to the LSF profile, whereas integration of the PSF to produce the LSF [Eq. (10.3)] acts to reduce noise. These considerations also have an impact on the choice of methodology used for MTF characterization in CT. Historically, spatial resolution in CT has been described in units of cycles per centimeter or line pairs per centimeter (i.e., cm 21 ); however, with the improved spatial-resolution capabilities of modern scanners, it is recommended that cycles per millimeter (i.e. mm 21 ) be used instead in all forums of discussion, including the scientific literature and commercial, technical, and sales documents Resolution Along the z Axis The z-axis resolution in CT has improved significantly with the introduction of MDCT scanners. In the era of single-slice CT scanners, slice thicknesses used for clinical imaging were typically 5 mm, 7 mm, or 10 mm, depending upon the clinical application. On occasion, thinner slices, such as 1 mm or 2 mm, were used for specialty applications. As the voxel thickness dimension was on the order of from 10 to 20 times that of the in-plane pixel dimensions, the slice-sensitivity profile was used to characterize spatial resolution (essentially the line-spread function). Gagne (1989) studied the shape of the slicesensitivity profile and the air-kerma profile, both experimentally and mathematically. Samples of these profiles are shown in Figure for representative single-slice CT scanners of the late 1980s, for collimated slice thicknesses ranging from 8 mm to 10 mm. A mathematical model of the slice-sensitivity profile was also developed (solid lines in Figure 10.10a 10.10c; see also Section 6.2). With the advent of helical (spiral) CT, Hu and Fox (1996) developed analytical equations corroborated by physical experiments to describe the slicesensitivity profiles in single-slice helical scanners (see Figure 10.11a). Profiles with different collimated slice thickness are shown in Figure 10.11b. These investigators also computed the modulationtransfer function for the z-axis resolution, calling it the longitudinal MTF (see Figure 10.11c). Figure 10.12a shows a diagram of a common geometric strategy used to estimate slice thickness. A number of evenly spaced small attenuating rods are aligned diagonally in a phantom, and a CT scan is acquired of this array. Visual inspection of the CT image allows the number of rods in the image to be counted (see the drawing in Figure 10.12b). For the American College of Radiology (ACR) CTaccreditation phantom, each rod corresponds to 0.5 mm of slice thickness. For example, counting 10 rods in the image then results in an estimate of a 5.0 mm slice thickness. Figure 10.13a through 10.13d illustrates CT images from the actual ACR phantom, for different thicknesses. This determination of slice thickness allows rapid subjective assessment of slice thickness for routine quality assurance or for spot checking CT systems in the clinical environment. Although adequate for these purposes, the determination of the line-spread function along the z axis with subsequent conversion to the longitudinal MTF is considered to be a more rigorous quantitative evaluation of the longitudinal spatial resolution. Thin-section single-detector-array axial-ct acquisition provides well-sampled data for CT-image Figure Slice-sensitivity profiles. A comparison is made between a geometric model (solid line) and the measured sensitivity profile (symbols) for the z axis (see Gagne, 1989), for nominal CT slices between 8 mm and 10 mm. (a) For the General Electric 9800 scanner. (b) For the Siemens DR/H CT system. (c) For a stationary-detector CT system, the Picker

126 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Measurements of slice-sensitivity profiles and the longitudinal MTF. (a) A comparison between measured data (symbols) and model predictions (lines) for different collimations (from Hu and Fox, 1996). (b) The impact of x-ray-beam collimation on the slice-sensitivity profile, for a helical acquisition on a single-detector-row CT scanner. (c) The z-axis (or longitudinal) MTF from the slice-sensitivity profiles. Figure Phantom-based determination of CT slice thickness. (a) A standard geometry using an angled wire or series of beads or rods to estimate the effective slice (section) thickness. (b) The slice thickness is estimated by counting the number of objects seen. For example, the ACR Phantom has rods placed 0.5 mm apart (in z), and thus for M visible markers, the slice thickness T s is assessed as T s ¼ 0.5 mm M. reconstruction with a negligible cone angle (see Section 2.1 and Figure 10.14a). With the advent of multiple-detector-array CT (MDCT) scanners, the cone angle is larger for the peripheral detector arrays, and this leads to under-sampling in z, which violates the so-called Tuy data-sufficiency condition (Tuy, 1983). For example, for a 64-detector-array CT system with mm detector-array widths, a 40 mm collimated slice thickness is used. The peripheral detector arrays in this configuration (using the General Electric VCT scanner geometry as an example) are 20 mm away from the center of the Figure Images of the ACR phantom for CT scans reconstructed at several nominal slice thicknesses. Slice thickness of (a) 2.5 mm, (b) 3.75 mm, (c) 5.0 mm, and (d) 7.5 mm. detector array, and with the source-to-isocenter distanceof541mmtheconeanglefortheedgedetector arrays is or 37.6 milliradian (see Figure 10.14b). With contiguous axial scanning, the data in the central array are well sampled in z (i.e., meets Tuy s data-sufficiency condition), but the edge arrays do not fully meet this condition. This can give rise to conebeam artifacts that can distort the LSF(z). 116

127 Spatial Resolution in CT Figure CT-acquisition geometry in the z dimension. (a) A single-detector-array, axial-scan geometry has a negligible cone angle, and therefore there is complete sampling along the z dimension for contiguous SDCT scanning. (b) An MDCT system has a small half-cone angle of approximately from 18 to 48, depending on the scanner configuration, which results in a slight under-sampling in the z dimension for both axial and helical scans. (c) Full-cone-beam scanners, such as the Toshiba Aquilion 320, or flat-panel-based CT systems make use of large cone angles; the severe under-sampling in the z dimension can give rise to cone-beam artifacts. Full-cone-beam CT scanners are available that use very wide cone angles for axial acquisition; for example, the Toshiba Aquilion 320 makes use of a 160 mm wide array of detectors along z, such that the edge detectors (see Figure 10.14c) have a cone angle approaching 88. Flat-panel-based CT scanners used in dental, orthopedic, and breast-imaging applications also have very large cone angles, in some cases exceeding 208. With both MDCT and full-cone-beam CT systems, the resolution along the z axis has increased dramatically compared with what was practical with single-detector-array CT systems, and this has been accompanied by much shorter scan times as well. Nevertheless, the increased z-axis resolution has also given rise to the potential for cone-beam and other artifacts stemming from undersampling in z. Due to these considerations, CT resolution along the z axis for MDCT and cone-beam CT scanners can have substantial spatial dependence (non-stationarity) Modern Resolution Metrics in CT The voxel dimensions of a CT image are no longer measured in fractions of a centimeter, but rather in fractions of a millimeter. With this in mind, it is reasonable to use methods in CT that have been used to characterize spatial resolution in digital radiography systems, with the need to also address the 3D nature of the CT volume data set. As mentioned in Section 10.1, a fully 3D characterization of the spatial resolution of a CT scanner is possible, yielding the PSF 3D (x,y,z). One approach would be to use a large high-contrast sphere embedded in a homogeneous material as shown in Figure 10.15a. Such a phantom provides edges in all three orthogonal dimensions, which can be used to characterize the resolution in each dimension. Although there is potential utility in the computation of the 3D MTF, the parameters that influence the axial (x y) resolution in CT tend to be quite different from those that influence the longitudinal (z) resolution. For this reason, separate resolution measurements of the axial and longitudinal components are typically performed. In both cases, the line-spread function serves as a basis from which to calculate the MTF Axial-Plane Resolution It is straightforward to generate a line image in CT by scanning a high-contrast (thin foil) plane of material encompassed in a cylindrical phantom; this is illustrated in Figure 10.15b and is pictured in Figure 10.15c. This phantom comprises 100 mm diameter PMMA, and has two sections: on top, the cylinder was cut down the center and machined flat, and a thin metal foil was placed between the two halves. The bottom section is homogeneous PMMA, but placed vertically between the two cylinders is another metal foil. The upper section of the phantom is used to measure the LSF in the axial (x y) plane, and the foil separating the two cylinders vertically is used to measure the LSF in the coronal (x z) plane (effectively the same as the sagittal plane). 117

128 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Phantom for measuring MTF in both axial and azimuthal planes. (a) A high-contrast sphere embedded in a homogeneous phantom allows the edge-spread function to be evaluated in any plane: the axial (x y), the coronal (x z), and the sagittal (y z). (b) A phantom composed of a flat, thin metal foil embedded in a 100 mm PMMA cylinder has orthogonal planes of foil for measuring the MTF xy and the MTF z. (c) A photograph of the phantom schematized in (b), with a half-cylinder removed for demonstration. Figure 10.16a illustrates a CT image of the top section of the MTF phantom, showing a bright line where the metal foil was placed between the two half-cylinders. The oversampled LSF (Boone, 2000; Bushberg et al., 2012) was computed from the ROI shown in Figure 10.16a, with the result illustrated in Figure 10.16b. The Fourier transform is taken of the LSF data, and after normalization the MTFs were computed for three different reconstruction kernels, with the resultant MTFs shown in Figure 10.16c z-axis Resolution Resolution assessment along the z axis requires a point, line, or edge running nearly perpendicular to the z axis. Figure 10.15a illustrates a sphere embedded in a homogeneous phantom, and as mentioned above this approach provides edges in all dimensions. However, for MDCT or cone-beam CT systems with large cone angles used during acquisition, evaluation of the LSF(z) can be fraught with artifacts. The alternative method demonstrated in Figure 10.15b makes use of a thin metal foil placed between two cylinders of PMMA. A coronal image showing this foil as a bright line is shown in Figure 10.17a. The cylindrical phantom is slightly angled with respect to the axis of rotation in order to produce a slight angle in the vertical line of Figure 10.17a relative to the (x, z) pixel array in this coronal image. This angulation allows for the synthesis of the oversampled LSF, and these data allow the computation of the presampled MTF as shown in Figure 10.17b for three different reconstructed slice thicknesses Summary Spatial resolution is a very important component of image quality, requiring thorough and robust processes to characterize and quantify the performance of CT scanners. Although the assessment of spatial resolution in the clinical environment is qualitatively managed by visual inspection of images of bar or wedge phantoms (see Figure 10.9), scientific characterization of the spatial resolution in CT should make use of the MTF. TheMTF can be determined in a number of different ways, through the measurement of the point-spread function, the line-spread function, or the edge-spread function, with appropriate manipulation of the data as discussed in this Section. The in-plane (axial) MTF, or MTF xy, for a reconstructed image in a CT volume data set has similar resolution in the x and y dimensions, allowing for radial averaging. The longitudinal MTF, ormtf z, is computed and interpreted separately from the MTF xy. For simplicity and consistency, the oversampled line-spread function approach is preferred, as described in Sections and , and shown in Figures 10.7b, 10.16a, and 10.17a. In most cases, spatial resolution should be measured using high-dose-technique settings to achieve low-noise images. Due to the high attenuation in large diameter phantoms, small-diameter phantoms (such as the 100 mm diameter phantom pictured in Figure 10.15c) are useful to achieve higher-precision measurements of the MTF at a given technique setting. The CT-acquisition parameters described in Table 10.1 provide guidance in these respects. If the MTF with the small x-ray-tube focal spot is to be measured, the tube current should be reduced and the scan time increased to enable small-focal-spot acquisition. Most clinical CT-scanner systems now have available iterative-reconstruction techniques using statistical or model-based reconstruction algorithms. Images reconstructed using these methods, as opposed to FBP, will demonstrate adaptive smoothing in a manner that is dependent upon the specific reconstruction algorithm. The adaptive behavior of these algorithms implies that the LSF (and MTF) 118

129 Spatial Resolution in CT Figure MTFs measured in the axial plane for an MDCT system. (a) A CT image of the top section of the phantom (see Figure 10.15b) showing a line corresponding to the metal foil in the phantom. The box indicates the region of interest in which the data points for the LSF were measured. (b) An oversampled LSF synthesized from the data in the box shown in (a). (c) MTFs shown for different kernels on a General Electric 16-slice Lightspeed system. Figure Longitudinal MTFs measured on a modern MDCT system. (a) A coronal image of the phantom pictured in Figure 10.15c. The longitudinal MTF is computed from vertical profiles sampled in the box shown. (b) The longitudinal MTF z shown for three slice thicknesses. Smaller reconstruction thicknesses increase the spatial resolution in the z dimension. will change depending on the local anatomy in the patient, depending on both position (x, y, z) and contrast (signal difference) in the reconstruction. For iterative reconstruction, the spatial dependence of the MTF can be greater or less than in FBP; some iterative methods have been developed specifically to yield a PSF that does not vary in space and others allow the PSF to vary. In the latter case, the spatial variation violates basic assumptions of stationary behavior, reducing the meaningfulness of the MTF as a global metric. Similarly, iterative-reconstruction methods often involve adaptive, signal-dependent smoothing and regularization that impart a dependence of the MTF on the contrast (difference in attenuation coefficient) of the material forming a given edge. For example, 119

130 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Table 10.1 Recommended parameters for the measurement of the MTF in CT. Parameter Value Tolerance or note Tube potential 120 kv (typical) 80 kv to 140 kv Tube current 500 ma a +100 ma Time 1 s a s Display field of view 200 mm +20 mm Phantom diameter 100 mm +5mm Phantom composition PMMA or other plastic materials Number of lines in LSF (about 50 mm long) Zero padded to N ¼ 256 Angle of line to pixel matrix 18 to 58 a If the MTF for the small focal spot is being measured, the tube current will need to be decreased to allow small-focal-spot operation, and the rotation time can be increased to compensate. high-contrast edges can result in an evidently higher MTF than that with low-contrast edges. Recognizing these complexities in the spatialresolution characteristics of non-linear iterative reconstruction and the lack of a single global resolution metric, the MTF should be characterized in a manner that is explicitly local, i.e., local in both location and contrast level. Given these constraints, it is recognized that characterizing the MTF of a CT scanner using the filtered-back-projection-reconstruction mode represents a reasonable estimate of the spatial resolution of that scanner, but the local nature of the MTF should be recognized. Furthermore, in most clinical CT applications that employ iterative-reconstruction techniques, the iterative-reconstruction images are combined with filtered-back-projection images in a weighted manner (20 % iterative/80 % FBP, 30 %/70 %, etc.), which can further complicate specification and emphasizes the need for rigorous reporting of measurement conditions, reconstruction methods, and analysis techniques (including dependence on location and contrast). 120

131 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndt Noise Assessment in CT 11.1 Introduction Image noise comes from a number of sources, including structure noise due to slight pixel-to-pixel response variations in electronic-detector systems, additive electronic or shot noise from detectors and other electronic components, grain noise in film, and quantum noise that generally decreases as the x-ray fluence (and consequent patient dose) in the imaging procedure is increased. Although all noise is undesirable, some noise can be corrected for. For example, structure (or so-called fixed-pattern) noise can be easily corrected in digital-detector systems by using flat-field image-correction techniques (Bushberg et al., 2012). Grain noise in film is not an issue for digitaldetector systems, including CT. Electronic noise is usually addressed by advanced detector and circuit design, or by using detector-cooling techniques. Quantum noise is fundamentally a statistical property associated with the limited number of detected quanta that are used to form an image Basic Noise Metrics Figure 11.1 illustrates the basic concepts of signal, noise, and the signal-to-noise ratio (SNR). It has been known for many decades (Rose, 1973; Brooks and Chiro, 1976; Burgess, 1999) that the SNR plays a fundamental role in the detectability of an object on a noisy background. In Figure 11.1a, a circular signal is positioned in the center of a noisy image. Idealized distributions of the signal and background regions are illustrated in Figure 11.1b. The noise distributions within the object and in the background are characterized by normal distributions defined by their standard deviations, s, with the lateral shift between the two distributions corresponding to the signal amplitude, js 1 s 2 j. The Rose Criterion (Rose, 1973) states that when SNR 5 for an object, it will be reliably detected. This SNR concept can be extended to the frequency domain as well (see Wagner and Brown, 1982), which expands the analysis to include the noise texture (described below) and the shape of the object to be detected. The contrast-detail (CD) image (see Figure 11.2a) is a construct that allows for the subjective evaluation of contrast resolution of an imaging system, and CD diagrams have been used extensively in CT (Cohen and DiBianca, 1979). Figure 11.2b illustrates an early example of a CD diagram that shows differences in the performance of two different models of General Electric CT scanners. The CD test object presents disks that in the image vary in diameter horizontally, and vary in contrast vertically; the disk in the lower left is the smallest size and with the lowest contrast, and the upperright disk is the largest size and with the highest contrast. The SNR is maximal in the upper right and decreases to the left and downward on the diagram. The CD diagram (Figure 11.2b) shows several curves that define the line of demarcation between disks that can be seen from those that cannot. Curves that extend further to the left in the CD diagram demonstrate imaging systems that have better spatial resolution (e.g., the General Electric CT/T 8800 versus the earlier General Electric CT/T 7800 model), and lines that extend further down on this CD diagram demonstrate imaging systems that have better contrast resolution. For example, the higher dose (50 mgy) curve in Figure 11.2b extends further down than does the 12.5 mgy curve, because increasing the x- ray-fluence levels decreases the quantum noise and improves the ability to see objects that have smaller contrast levels. Although the signal-to-noise ratio is an important parameter in determining the detectability of an object, the SNR does not completely characterize noise. Figure 11.3 shows two images with exactly the same noise level as measured by the standard deviation, s; however, these two images have dramatically different appearances to the observer. The differences between Figure 11.3a and 11.3b are due to the noise texture; that is, the spatial-frequency distribution of the noise is different in these two images. In direct analogy with sound from a piano, although the volume is the same in these two # International Commission on Radiation Units and Measurements 2013

132 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Basic concepts of signal and noise. (a) A circular signal region located in the center of a noisy image. The detectability of this disk is related to its signal-to-noise ratio. (b) The concepts relevant to the signal (s 2 s 1 ) to noise (s) are illustrated. These idealized curves (measured curves would be noisier) are computed from histograms of the gray-scale values in the signal and background regions shown in (a). Figure Contrast-detail curves. (a) Image of a traditional CD phantom, for which the diameter of each disk decreases from right to left and the contrast of the disks decreases from top to bottom. (b) An early depiction of the CD diagram for two different General Electric CT scanners, the CT/T 7800 and the CT/T Adapted from Wagner et al. (1979). images, Figure 11.3a typifies noise produced by keys on the left side of the piano (low-frequency sound), and Figure 11.3b typifies noise produced by keys further to the right on the piano (higher-frequency sound). With audible sound, the frequencies are temporal frequencies measured, say, in units of s 21, whereas in images, the frequencies are spatial frequencies, in mm The Noise-Power Spectrum, NPS(f) The noise-power spectrum (NPS) is a useful measure that provides a more complete description of noise than the simple standard deviation; it describes the noise variance as a function of spatial frequency and therefore characterizes noise texture. When combined with dosimetric quantities, it can be used for comparisons among scanners and among protocols, and has been shown to be useful in translating protocols from one CT platform to another (Soloman et al., 2012). The primary source of noise correlation in CT is essentially the point-spread function, PSF 3D, discussed in Section 10. In MDCT imaging, the 3D pointspread function induces noise correlation in all three spatial dimensions. Because CT images are produced by mathematical reconstruction (e.g., 122

133 Noise Assessment in CT Figure Noise texture: the spatial-frequency distribution of the noise. Both images are from a Siemens CT scanner and have the same standard deviation (s ¼ 21.5 HU); hence, the noise is equal in the two images. The different appearance of the two images is due to the different reconstruction kernels used (Boedeker et al., 2007). (a) An image reconstructed using a B10 kernel, a low-pass kernel, producing noise texture with lower-spatial-frequency noise. (b) An image reconstructed using a B50 kernel. The B50 kernel is a high-pass kernel, producing CT images with greater spatial resolution but also with higher-frequency noise. Figure The noise-power spectrum, NPS. The solid curves represent an analytical prediction, and the open circles represent the corresponding computer simulation. Adapted from Riederer et al. (1978). (a) The noise-power spectrum for a Hanning filter, where f N is the Nyquist frequency. (b) The noise-power spectrum for a ramp filter. filtered back projection), the PSF depends not only on acquisition parameters such as focal-spot size and detector dimensions, but also on the selection of reconstruction parameters, principally the reconstruction kernel and the CT-slice thickness. The autocorrelation function describes noise correlation in the spatial domain. The Fourier transform of the autocorrelation function is the so-called Wiener spectrum (Dainty and Shaw, 1974; Faulkner and Morres, 1984), also known as the noise-power spectrum, NPS. In the context of a two-dimensional (2D) region of interest (ROI), let I i (x,y) be the signal in the i th ROI with I being the mean of I i (x, y). Then, the 2D NPS is computed as NPSð f x ; f y Þ¼ 1 N X N i¼1 DFT 2D ½I i ðx; yþ I i Š 2 D xd y N x N y ; ð11:1þ where the summation over i (and multiplication by N 21 ) refers to averaging the NPS values over N ROIs. The values of D correspond to the pixel spacing (i.e., spacing between pixel centers in x or y) ina given plane. N x and N y are the number of voxels in each dimension of the ROI used in the computation. The terms f x and f y are here the spatial frequencies in the x and y dimensions, respectively, and the DFT 2D is the discrete Fourier transform in 2D. Seminal work by early researchers studying noise properties in CT (Riederer et al., 1978) demonstrated that the NPS characterizes the noise texture of the CT image, and that in the axial plane the NPS largely reflects the CT reconstruction kernel used. Figure 11.4 illustrates analytically derived and computer-simulated NPSs for the Hanning filter (see Figure 11.4a) and the ramp filter (see Figure 11.4b). For an early single-detector-array CT scanner, these investigators used the 2D NPS 123

134 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY because the scanner could acquire only one CT image per axial scan; thus, no noise correlation occurred in the z dimension. More recent work has extended 2D NPS concepts to cone-beam CT systems (Baek and Pelc, 2010; 2011a; 2011b). An example of how the 2D NPS is measured is illustrated in Figure A homogenous phantom (e.g., water or plastic) is scanned using the desired technique factors (tube potential, tube current, rotation time, etc.), producing a relatively homogeneous image as seen in Figure 11.5a. ROIs are sampled from the homogeneous image. Typically that sampling is performed at a constant radius as shown in the figure. Each 2D ROI is extracted from the image and, after (optional) detrending (discussed below) is used (see Figure 11.5b), the 2D Fourier transform is computed [see Eq. (11.1)] for each ROI. After the considerable averaging of the N NPS data sets in the frequency domain, the mean 2D NPS is produced, and this is shown in Figure 11.5c. The f x and f y frequencies in the 2D NPS can be collapsed to a 1D radial frequency, f r, by radially averaging using qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi f r ¼ fx 2 þ f y 2 : ð11:2þ Figure The NPS computation in CT. (a) ROIs sampled at a constant radius around the center of the phantom image. (b) An example of detrending is shown. Here the raw ROI extracted from the image is fit with a low-order polynomial, which defines the background trend in the data. Only the very low frequencies in the image can be addressed by the polynomial fit, due to its low order. The background trend is subtracted from the raw ROI, resulting in the corrected ROI. (c) The two-dimensional Fourier transform is computed for the corrected regions of interest (seen in b). In the axial plane as shown here, the NPS is approximately rotationally symmetric, and typically has a shape resembling a torus. (d) The 1D NPS curve from radially averaging the 2D NPS. The initial positive slope of this curve results from the ramp filtering that is used in filtered-back-projection reconstruction, and the negative slope at higher spatial frequencies occurs due to the roll-off properties of the reconstruction kernel used to dampen high-frequency noise in the images. 124

135 Noise Assessment in CT The typical appearance of the (axial) 2D NPS is that of a torus, as shown in Figure 11.5c. Radial averaging of this 2D surface using Eq. (11.2) results in a 1D NPS (see Figure 11.5d). The positive-slope region of the NPS in Figure 11.5d is due to the ramp filtering, and the subsequent fall-off at higher frequencies is due to the (mathematical) reconstruction kernel that is used. Different kernels are used that represent different trade-offs between spatial resolution and image noise, but all clinical kernels produce some roll-off in response at high frequencies, similar to that shown in Figure 11.5d. Roll-off refers to the progressive reduction in the filter function at higher spatial frequencies, to reduce the impact of quantum noise on the image. The 2D NPS can be displayed using 3D plotting techniques, and a 2D NPS is shown in isometric format in Figure With modern MDCT and cone-beam CT systems, there are many detector arrays in the z dimension that acquire the raw data simultaneously, and these give rise to noise correlation in z. Thus, for these modern CT systems, the 3D NPS is necessary for fully characterizing the noise correlation in the image data. The 3D NPS is a straightforward extension of the 2D function (Tward and Siewerdsen, 2008), and is defined as NPSðf x ;f y ;f z Þ¼ 1 P N DFT 3D ½I i ðx;y;zþ I N i Š 2 D xd y D z ; i¼1 N x N y N z ð11:3þ where f z, D z, and N z refer to the frequency, voxel spacing, and number of voxels used in the z dimension, and DFT 3D is the discrete Fourier transform in 3D. The 3D NPS is measured as described in Figure 11.5; however, the ROIs become volumes of interest (VOIs), and the computations are performed for all three dimensions. Figure 11.7 illustrates different views of a fully 3D NPS computed from CT images acquired on an experimental cone-beam CT scanner (Siewerdsen et al., 2002). Figure 11.7a shows the 3D NPS in the axial plane, and Figure 11.7b shows the 3D NPS in the coronal or sagittal plane. Due to rotational symmetry, the sagittal and coronal 3D NPS projections are essentially identical. Figure 11.7c illustrates a 3D rendering of the 3D noise-power spectrum, with a cutout view for clarity. Figure 11.8 illustrates a 2D NPS obtained from a Siemens clinical CT system. The NPS values for four different reconstruction kernels (B10, B20, B30, and B40) are illustrated. When the NPS is computed directly from the CT scan of a homogeneous (usually cylindrical) object, some degree of cupping is usually present, and this manifests as a spike in the curve at low frequencies in the NPS (see Figure 11.8a). The cupping artifact is well known in CT, and can be from beam hardening, scattered radiation, or other phenomena. Cupping refers to a low-frequency trend in the CT image in which HU values near the center of a homogeneous object are lower than those near the periphery. To reduce the impact of cupping on the low-frequency portion of the NPS, a number of techniques can be used. The so-called detrending methods (Dobbins et al., 2006; Yang et al., 2008) can be used to subtract out low-frequency trends in the spatial domain. Figure 11.5b illustrates one type of detrending, for example, in which a low-order polynomial fit to the data is subtracted out, reducing some of the low-frequency components. Other researchers (e.g., Yang et al., 2008) have used image subtraction to reduce the impact of cupping on the NPS calculation. With this method, two separate acquisitions are made of a homogeneous (typically cylindrical) test object, and these two data sets are subtracted from one another. With this approach, inhomogeneities in the phantom are subtracted away also, and only noise remains. In 2D, the image subtraction is represented as Kðx; yþ ¼I A ðx; yþ I B ðx; yþ ; ð11:4þ where I A (x, y) and I B (x, y) are independently acquired images of the same object. In this case, the 2D NPS is then computed using NPSðf x ;f y Þ¼ 1 P N i¼1 DFT 2D½K i ðx;yþ K i Š N 2 2 D x D y N x N y ; ð11:5þ Figure An early example of the NPS as a function of spatial frequencies f x and f y. Adapted from Hansen (1979). where K i is the mean HU value in the ROI K i (x,y). The image-subtraction process results in an increase in the subtracted-image variance by a factor of 2, and therefore division by a factor of 2 in Eq. (11.5) is used to correct for this. Figure 11.8b 125

136 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure A 3D NPS computed for a cone-beam CT scanner. (a) The axial plane (f x f y ) of the 3D NPS shown for f z ¼ 0. (b) The sagittal plane of the 3D NPS, shown for f y ¼ 0. (c) Three-dimensional rendering of the 3D NPS. Figure Two-dimensional NPS for a Siemens Somatom 64-slice CT scanner, adapted from Boedeker et al. (2007). (a) The 2D NPS for four reconstruction kernels indicated in the inset. The low-frequency spike is indicated by the arrow. (b) The 2D NPS for the same four reconstruction kernels, but using 2D image-subtraction methods [see Eq. (11.4)] to suppress the low-frequency spike. illustrates a significant reduction in the lowfrequency spike that is seen in Figure 11.8a, and this was achieved using the 2D image-subtraction method of Eqs. (11.4 and 11.5). For full 3D data sets, image subtraction is performed using Kðx; y; zþ ¼I A ðx; y; zþ I B ðx; y; zþ ; ð11:6þ where the A and B subscripts refer to independently acquired measurements of the same volume (x, y, z). The 3D NPS is then computed using NPSðf x ;f y ;f z Þ¼ 1 N P N i¼1 DFT 3D ½K i ðx;y;zþ K i Š 2 2 D x D y D z : N x N y N z ð11:7þ It is usually true for commercial CT scanners that D x ¼ D y, and hence for a square ROI N x ¼ N y. However, the voxel spacing in the z dimension (D z ) is usually not equal to that in the x or y dimension. Consequently, the value of N z can be different from N x or N y, depending upon the size of the cylinder scanned and the length (along z) of the scan itself. Figure 11.9 illustrates the influence of phantom diameter on the NPS. These NPS curves were computed using 3D data-set subtraction techniques [Eqs. (11.6 and 11.7)] to reduce artifacts in the lowfrequency regions of the NPS. For the curves shown in Figure 11.9a, the same technique factors (80 kv, 7 ma, 16.6 s) were used for polyethylene phantoms of four different diameters. In this case, the largest-diameter phantom attenuates the most x-ray photons, and hence fewer photons reach the detector compared to the smaller phantoms. 126

137 Noise Assessment in CT Figure NPS curves computed from images of four polyethylene cylinders of different diameters acquired on a prototype cone-beam breast CT scanner. Three-dimensional image-subtraction methods [see Eqs. (11.6 and 11.7)] were used to suppress low-frequency artifacts. (a) Images were acquired with constant technique settings, so that the air kerma at isocenter (in the absence of a phantom) was the same for each of the four cylinders imaged. Due to the increased attenuation of the larger-diameter cylinders, the NPS is greatest with the larger-diameter cylinder, and decreases with smaller phantom diameters. (b) For images acquired in this case, the absorbed dose at the center of the phantoms was kept approximately constant, i.e., the incident air kerma used for the larger-diameter cylinder was greater than for the smaller cylinder. With these acquisition parameters, the smallest-diameter cylinder has the largest-amplitude NPS curve, and the noise level decreases with increasing phantom diameter. Therefore, the noise variance (area of the NPS curve in this display format) is greatest for the largest-diameter phantom. In Figure 11.9b, however, the absorbed dose in each phantom was designed to be approximately equal, requiring a higher x-ray-tube current for the larger phantoms. In this case, the smallest phantom was scanned using the lowest tube current and had the highest noise levels. The integrated volume of the 3D NPS curve is equal to the overall noise variance, s 2,in the image: ððð s 2 ¼ NPSð f x ; f y ; f z Þdf x df y df z : ð11:8þ 11.4 Demonstration of NPS Utility In this Section, a number of trends that are evident from NPS analysis are discussed. The ICRU/AAPM polyethylene phantom (see Figure 7.19) was used in this work. Figure illustrates the axial (f x f y ), sagittal (f z f y ), and coronal (f x f z ) views of the 3D NPS for two different reconstruction kernels on a Siemens ASþ scanner. In the axial displays, zero frequency is at the center of the torus, and higher frequencies advance radially (see axes in Figure 11.5c). The images in Figure 11.10a correspond to a reconstruction kernel (B10s) that provides considerable smoothing, thereby reducing much of the high-frequency noise in the image data sets. The images in Figure 11.10b correspond to a high-resolution reconstruction kernel (B80s), and the NPS demonstrates noticeable higher-frequency noise characteristics, i.e., the torus has a larger diameter. The sagittal and coronal NPS curves in Figure 11.10a and 11.10b show virtually identical trends, due to the approximate radial symmetry of the NPS in these planes. These 3D functions can be condensed by radially averaging the 3D NPS in the axial plane, through the use of Eq. (11.2). After performing the radial averaging, which collapses the f x and f y axes to a single f r axis, the information illustrated in Figure can be condensed as seen in Figure This figure illustrates the (still 3D) NPS topography (f z and f r ) for two different reconstruction kernels on the Siemens CT platform. The B10s kernel (see Figure 11.11a) is a soft kernel and produces smoother images, with an NPS that has more lower-frequency content, and the B80s kernel (see Figure 11.11b) is a sharper kernel that passes more higher-frequency noise. Compared with B10s, images reconstructed with the sharper B80s kernel will have better spatial resolution (MTF) but will also have more noise at higher frequencies. The NPS plots shown in Figure contain significant amounts of information, which can be displayed more concisely as shown in Figure Figure 11.12a illustrates the radially averaged NPS for the B10s kernel; the three plots in Figure 11.12a correspond to the data regions highlighted with the horizontal bars in Figure 11.11a. The 1D NPS profiles for kernel B80s are shown in Figure 11.12b. These plots illustrate curves of the 3D NPS at f z ¼ 0, f z ¼ 1 2 f N, and f z ¼ f N, where f N is the Nyquist frequency (see Section 10.3). It is 127

138 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Full displays of the 3D NPS. (a) The 3D NPS for a B10s kernel on a Siemens scanner. These data were acquired using the ICRU/AAPM phantom. The B10s kernel produces relatively smooth images by attenuating the higher-frequency content in the images. This manifests in the 3D NPS as a small-diameter torus in the axial (f x f y ) display. The center of the torus corresponds to f x ¼ f y ¼ 0, with higher frequencies advancing away from the center. The coronal and sagittal NPS displays show the elongation of the basic torus in the orthogonal dimensions. (b) The 3D NPS for a high-pass kernel (B80s). The diameter of the torus is greater than that in (a), corresponding to the shift to higher spatial frequencies of the NPS with this kernel. recognized that the full family of curves produced from the data illustrated in Figure 11.11a would span the spaces between the curves illustrated in Figure 11.12a. It is important to note that the ordinate of Figure 11.12b is scaled differently from that in Figure 11.12a, which is necessary because the B80s kernel not only produces higherfrequency image noise than does the B10s filter (it is shifted to the right), but it also has higher noise (the variance is larger) for the same acquisition parameters. Figure gives NPS plots for the (Siemens) kernels B10s and B80s, and two others, for which the data illustrated in Figure 11.11a and 11.11b were integrated over f z, i.e., NPSð f r Þ¼ ð fn f N NPSð f r ; f z Þdf z ; ð11:9þ which converts the volumes of the 3D NPS (shown in Figure 11.11) to areas of the curves of the NPS plots shown in Figure Note that f N in Eq. (11.9) refers to the Nyquist frequency in z. A change in NPS units occurs with this integration; whereas the 3D NPS (Figures ) are in units of HU 2 volume (i.e., HU 2 mm 3 ), the integration of Eq. (11.9) converts these into units of HU 2 area (i.e., HU 2 mm 2 ) in Figure In this figure, the NPS of the B80s kernel is seen to have significantly more area compared with that with the B10s kernel, and the area of these curves is proportional to s 2 [Eq. (11.8) applies here as well, except that the integration over z has already been performed]. Figure illustrates the 3D NPS data, showing the frequency f z as a function of the radially averaged frequency f r, for three different reconstructed slice thicknesses (1 mm, 2 mm, and 5 mm). The maximum frequency computed (f N ) along the f z axis in these plots corresponds to (2t) 21, where t is the slice thickness. Figure 11.15a shows the NPS amplitude as a function of the radial frequency f r, integrated over f z. Similarly, the 3D NPS data can be integrated horizontally (see Figure 11.14) over the radial frequency f r,as NPSð f z Þ¼ ð fn f N NPSð f r ; f z Þdf r : ð11:10þ These results are illustrated in Figure 11.15b. Figure gives the 3D NPS integrated over f z, and radially averaged over f x and f y, resulting in the NPS versus spatial frequency, f r. When the 3D NPS is integrated and then displayed in this fashion, the relative noise variance is proportional to the area under each curve. In the illustrated case, the lower x-ray-tube-current time product 128

139 Noise Assessment in CT Figure Radially averaged 3D NPS plots, obtained from the symmetrical (in f x and f y )3DNPS in Fig Here the NPS amplitude is shown using a color scale. The plots extend from f ¼ 0 to the Nyquist frequency for each axis. (a) NPS data from the low-pass B10s kernel. (b) NPS of the high-pass B80s kernel. Figure NPS(f r ) for three locations along the f z axis: f z ¼ 0, f z ¼ 1 2 f N, and f z ¼ f N, where f N is the Nyquist frequency. NPS(f r ) for (a) the B10s kernel and (b) the B80s kernel. (126 ma s) produces about 25 % of the x-ray fluence compared with the higher current time product (500 ma s), and the noise variance scales inversely, as is apparent in this figure, i.e., the area under the 126 ma s curve is about four times greater than that of the 500 ma s curve. Figure compares NPS curves for axial (sequential) and helical (spiral) acquisition with the Siemens ASþ platform, using the ICRU/AAPM polyethylene phantom. Figure shows the NPS resulting from the integration of the 3D NPS over f z. These scans used the same set of technique factors [tube potential, tube current, slice thickness, etc., and with unit pitch (p ¼ 1)]; however, the noise variance in the helical scan is slightly greater than that of the axial scan. Figure shows NPS curves calculated at four different radii. These are 3D NPS data integrated over f z [Eq. (11.9)] for the four different radii. As mentioned previously, the areas under these curves are proportional to s 2. The trends in this figure show that the NPS computed from VOIs 129

140 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY near the center of the field (e.g., r ¼ 30 mm) have slightly higher noise variance than measurements at larger radii (e.g., r ¼ 97 mm). Although the radial dependence of the amplitude of the NPS is small, these results do suggest that the use of a standard radius for NPS evaluation would be more consistent for comparisons across other parameters (kernel, scanner type, tube current, etc.). As there is a need to develop more uniform interpretation of performance among CT-scanner platforms, the NPS can also serve an important role in comparing protocols (including reconstructionkernel selection) among CT scanners from different vendors. Figure gives an important comparison of NPS curves between two different vendors: General Electric shown on the top row and Siemens on the bottom row. The low-pass (softer) kernels are illustrated in the left column of plots, and the high-pass (sharper) kernels are illustrated in the right column of plots. Using the NPS, Solomon et al. (2012) performed a numerical comparison among the performances of the different reconstruction kernels of these two vendors. These data provide important information with respect to matching protocols across these two specific CT scanner platforms. Matching the reconstruction kernels between vendors as done by Solomon et al. (2012) is a practical example of the utility of the NPS(f) in the clinical environment, over and above the straightforward assessment of noise. Figure The 2D NPS(f r ) from the integral of the 3D NPS over f z. The four curves show the NPS obtained with different kernels (as labeled), and the increased noise amplitudes (areas under the curves) of the sharper kernels (e.g., B80s and B70s) are apparent Noise-Equivalent Quanta, NEQ As pointed out in Section 11.2, the signal-to-noise ratio, SNR, is a key attribute of any imaging system s performance, and the SNR provides a first-order prediction of observer performance. Section 10 described the modulation transfer function MTF(f), which essentially describes how an Figure Examples of the radially averaged 3D NPS for slice thicknesses of (a) 1 mm, (b) 2 mm, and (c) 5 mm. The plots extend from f ¼ 0 to the Nyquist frequency for each axis. 130

141 Noise Assessment in CT Figure The 2D NPS from the integral of the 3D NPS. (a) The 2D NPS computed from the 3D NPS by integration over f z. In this display, as a function of f r, the area of the NPS area is proportional to the noise variance. The results for the 1 mm slice thickness show approximately twice the noise variance compared with that for the 2 mm slice, as would be expected based upon the relative number of x-ray quanta that contribute. These curves were produced by vertically summing the data shown in Fig and then multiplying the sum by Df z. (b) The 2D NPS computed from the 3D NPS by integration over f r, as a function of f z. Curves for four different slice thicknesses are shown. Smaller slice thicknesses are capable of displaying higher spatial frequencies in the f z dimension. Figure The NPS for two products of tube current and scan time. Here, the area of the lower-dose curve (126 ma s) is approximately four times that of the higher-dose curve (500 ma s). Figure Dependence of the NPS on the radius of measurement. Four curves are given for the radii of measurement indicated. Although the differences are small, these data suggest that a consistent radius of measurement should be used to preserve NPS measurement precision. is realized that the NPS(f) relates to the noisesquared (i.e., the variance s 2 ), and the MTF(f) is not related to the signal-squared. To address this, it is customary to use the SNR 2 outð f Þ (Dainty and Shaw, 1974; Hanson, 1979; Wagner and Brown, 1982). This quantity is conventionally referred to as the noise-equivalent quanta, NEQ(f), and is defined as Figure Comparison of the 2D NPSs for axial and helical CT. NPSs were integrated over f z. For the same technique factors as with the axial scan (and with pitch, p ¼ 1), the helical (spiral) NPS has slightly greater noise variance as seen by the larger area under the curve. imaging system passes signal. The NPS(f) has been discussed at length in Section 11, and it describes how an imaging system passes noise (or, more specifically, noise variance). The concepts of MTF(f) and NPS(f) can be brought together to describe the frequency-dependent SNR(f); however, it NEQð f Þ¼SNR 2 out ð f Þ ¼ g2 MTF 2 ð f Þ ; ð11:11þ NPSð f Þ where g is used to normalize units, and is typically equal to the mean gray scale (HU in CT) of the ROIs used to compute the noise-power in the image. Equation (11.11) is general and has been used extensively in the analysis of planar radiographic and mammography systems. Investigators in CT (Wagner and Brown, 1982) measured the frequencydependent NEQ(f) for a second-generation CT system, and their result is illustrated in Figure

142 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure Comparisons of the 2D NPS from General Electric and Siemens CT systems. These measured NPS curves have utility in clinical protocol development across vendor platforms. Adapted from Soloman et al. (2012). (a) The NPS for the low-pass General Electric reconstruction kernels. (b) The NPS for the high-pass General Electric kernels. (c) The NPS for the low-pass Siemens kernels. (d) The NPS for the high-pass Siemens kernels. Figure The NEQ is shown for a (head-only) secondgeneration CT scanner (adapted from Wagner and Brown, 1982). This figure gives the SNR 2 out for the early head-only CT scanner studied. Later, researchers (Boedeker et al., 2007) evaluated the NEQ(f) for a whole-body Siemens CT scanner for numerous reconstruction kernels, with results shown in Figure Despite the substantial differences in band-pass among the various reconstruction kernels, as shown in the NPS(f) curves in Figure 11.13, the NEQ(f) isshown Figure NEQ results for an MDCT system. The NEQ is shown for a whole-body CT scanner (Siemens Somatom) for six reconstruction kernels. in Figure to be nearly independent of the bandpass differences among kernels (except for the B80 kernel). This is because the differences in the reconstruction kernel not only change the NPS as illustrated in Figure 11.13, but similar trends in band-pass occur in the MTF 2 as well (not shown). 132

143 Noise Assessment in CT The ratio, therefore, between the MTF 2 and NPS greatly mitigates the influence of the kernel, and demonstrates the fundamental NEQ(f) [i.e., SNR 2 out ] performance of the CT scanner Dose-Normalized NPS(f) Large differences are seen in the values of NPS(f) as a function of the tube-current time product; see Figure 11.16, where results for a factor of 4 difference in tube-current time product (and radiation dose) are illustrated. This observation suggests that the NPS(f), if measured at a standard dose value, might provide an excellent approach for comparing noise versus dose among CT scanner models. In radiography and other planar-imaging modalities, the detective quantum efficiency, DQE(f), is a quantity that essentially describes the dose efficiency of the detector system. That is, for a given dose, what SNR 2 outð f Þ does the imaging system produce? The DQE(f) issimplytheneq divided by the incident fluence (Dainty and Shaw, 1974): SNR 2 out ð f Þ SNR 2 in ð f Þ ¼ DQEð f Þ ¼ g2 MTF 2 ð f Þ qnpsð f Þ ; ð11:12þ where q is here the x-ray-photon fluence incident on the detector used to produce the image for which NPS(f) was measured. For Poisson noise, SNR p in ¼ ffiffiffi q, and hence SNR 2 in ð f Þ ¼ q. The incident photon fluence in CT has little spatial correlation, and hence its frequency distribution is white, meaning that the input SNR in (f) has constant amplitude as a function of spatial frequency. That is why the q term on the right side of Eq. (11.12) has no explicit frequency dependence. Despite the utility of the DQE(f) in planar x-ray imaging systems, the meaning of q is difficult to interpret for CT systems (Tapiovaara and Wagner, 1985) due to the presence of the bow-tie filter, which spatially modulates the value of q in the field of view. In addition, unlike the simple digitalimage corrections (e.g., flat-field) performed with digital radiography systems, the reconstruction algorithms used in CT include corrections for beam-hardening, x-ray scatter, and other effects that consider the presence of an object in the scanner. CT scanners are simply not designed to produce optimal images when no object is present, and therefore it would be impractical to use scans in air to characterize CT scanner performance. Given these observations, the use of the DQE(f) for CT appears to be limited at this time. An alternative to the use of the DQE(f) for the study of noise versus dose in CT is possible, however, and the phantom described in Section 7 (see Figures 7.19a and 7.19b) is an important tool for this. The phantom was designed as both a dosimetry phantom and a tool for measuring the NPS(f). For a specific set of acquisition parameters (tube potential, tube current, rotation time, pitch, field of view, bow-tie filter, reconstruction kernel, etc.), the NPS(f) is characterized at a standard air kerma at the center of the phantom. The proposed measurement procedure is as follows: (1) The center section of the ICRU/AAPM phantom, a cylinder of polyethylene 200 mm long and 300 mm in diameter, is positioned on the CT table with a thimble chamber located in the center hole of the phantom, and also at the center along the z axis of the phantom as shown in Figure 7.22a. (2) Air-kerma measurements are made for an axial or helical scan acquired throughout the entire length of the phantom, using either an integrating electrometer or an electrometer with real-time read out as described in Section The scan is performed at the desired technique factors (tube potential, rotation time, pitch, and x-ray-tube current of J 1, etc.), and the air kerma, K 1, measured at the center of the phantom during the scan is recorded. The x-ray-tube current is adjusted to a new value J 2, with the intention of producing a specific measured air kerma, K set, at the center of the phantom. Because air kerma is linearly proportional to tube current when all other technique parameters are fixed, the selected tube current J 2 can be determined using J 2 ¼ J 1 K set K 1 ; ð11:13þ where K set could be a typical value of air kerma used in body CT, such as 10 mgy. (3) After J 2 is selected, a second CT scan of the entire length of the phantom is acquired as before, and the measured air kerma, K 2, is recorded. The value of K 2 should be very close (within from 2 % to 5 %) to the desired air kerma, K set. Using this acquisition, images are then reconstructed using the desired reconstruction parameters (slice thickness, kernel, display field of view, etc.). (4)TheCTimagesproducedinstep3aboveare used to evaluate the 3D NPS(f), and after radially averaging using Eq. (11.2) and integration over f z using (Eq. 11.9) NPS curves similar to those shown in Figures 11.13, 11.15a, and are produced and used for comparative analysis. 133

144 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY With the above procedure performed on any CT manufacturer s platform, NPS(f) curves can be compared at essentially the same air-kerma levels at the center of a standard phantom. This approach allows for a direct comparison of the noise performance among two or more whole-body CT scanners Summary Contrast resolution in CT has traditionally been measured using so-called low-contrast test objects, which are widely available in commercial phantoms (see Bushberg et al., 2012). This method requires specialized phantoms and relies on subjective (human-observer) interpretation of patterns similar to the CD phantom illustrated in Figure 11.2a. Moreover, in addition to the somewhat qualitative observation used as a measure, vendors can report the measurement made under differing conditions, obscuring the ability to make meaningful comparisons among different scanners. This situation clearly needs to be updated to more modern, quantitative, and objective metrics. Thus, it is recommended that quantitative measurement of the NPS, using the middle section of the 300 mm diameter polyethylene ICRU/AAPM phantom evaluated at a radius of approximately 100 mm, be used to quantify noise in CT systems. The NPS(f r ) curves, measured from the full 3D NPS with subsequent radial averaging [Eq. (11.2)] and integration over f z [Eq. (11.9)] should be adopted for the evaluation of the noise performance of CT scanners. NPS curves, similar to those shown in Figures and , are considered to be most useful in the evaluation of the noise properties of MDCT systems. This is because, in this display format, the area under each curve is proportional to s 2. The methods described in Section 11.6 provide guidance in this manner. The 300 mm diameter polyethylene ICRU/AAPM phantom, scanned to produce an air kerma of 10 mgy at the center, is appropriate for body-imaging-protocol assessment. A 200 mm long, 180 mm diameter polyethylene phantom would be appropriate for head CT protocols, with 50 mgy air kerma as the target level. These recommendations apply not only to the clinical evaluation of CT-scanner noise-versus-dose performance, but also extend to data provided by CT manufacturers in commercial, technical, and marketing documents. It is anticipated that the measurement of NPS(f) as outlined above will supplant the use of visual assessment of low-contrast test phantoms in acceptance-testing and qualityassurance procedures for CT. 134

145 Journal of the ICRU Vol 12 No 1 (2012) Report 87 Oxford University Press doi: /jicru/ndt Summary of Recommendations This Section summarizes the most significant recommendations discussed in this Report. Sections 2 4 are introductory in nature, and were provided to acquaint those less familiar with current CT technology, clinical usage, and conventional CT dosimetry associated with this modality Radiation-Dose Assessment in CT Sections 4 9 discuss matters pertaining to radiation dosimetry, and recommendations associated with each of these Sections will be provided here in order. In the discussion below, the term acceptance testing refers to the initial measurements performed on a newly installed CT scanner, usually prior to clinical use. Quality assurance is the process of periodic evaluation of a CT scanner, and is often performed annually or after a major service event (such as an x-ray-tube change). For dosimetry in CT, many Monte Carlo and other studies describe the absorbed dose in a particular organ or site (e.g., liver, bladder, fetus) as a function of air kerma at the isocenter of the scanner. When cast in this manner, the dose coefficients take on the units of absorbed dose per air kerma, typically in units of mgy/mgy Existing CT-Dosimetry Methods Historical acceptance testing and quality-control procedures for CT systems typically involve the assessment of the CTDI vol for several standard protocols. The set of ACR quality-control recommendations is one example. In addition, based on IEC (2009) recommendations, CTDI vol is displayed on the console of all modern CT scanners. Due to its broad utility and ubiquitous availability, it is strongly recommended that the CTDI vol be measured at acceptance testing using both the 160 mm diameter and 320 mm diameter PMMA phantoms, at a clinically relevant tube-current time product (e.g., 100 ma s) over the range of tube potentials used by the CT scanner. Measurement of the CTDI vol in air CTDI air is also strongly recommended, and this measurement is made at the isocenter only. Characterization of CTDI vol on newly installed CT platforms provides continuity with measurements from previous CT scanners, even as new CT dosimetry measures are introduced and used with more frequency. The rationale for this recommendation is also found in Sections 7 and 8 of this Report, in which the CTDI vol is used to scale the size-specific dose estimate, SSDE, and to normalize rise-to-equilibrium curves. If the recommendations of Section below are followed, CTDI vol measurements performed after the initial acceptance testing become unnecessary; however, if the procedures in Section are not followed, then continued periodic evaluation of CTDI vol during quality assurance is recommended CT X-Ray-Spectrum Characterization The CT x-ray spectrum is dependent on the tube potential and its waveform, and the amount of total filtration in the x-ray beam at the center of the fan beam. All modern CT systems make use of high-frequency generators that produce very little voltage ripple in the tube potential, so this is a minor factor in today s systems. Non-invasive x-ray-tube-potential meters can be used to determine the accuracy of the tube-potential reading on the console. The total filtration can be evaluated with knowledge of both the tube potential and the measured half-value layer, HVL. In general, the current literature tends to report dose coefficients (e.g., absorbed dose in an organ or phantom location as a function of CTDI air, the air kerma at isocenter) for the specific manufacturer and model of the CT scanner (Boone et al., 2004; Zhou and Boone, 2008). However, the numbers of manufacturers and models of CT scanners are growing, and scientific reports in the future will have more impact if, in addition to reporting dosimetry values, they report dose-conversion values as a function of x-ray-tube potential and HVL of the x-ray beam for the central ray. Although different CT-scanner vendors use slightly different sourceto-isocenter distances and bow-tie filter designs, in general these influences will likely have a small impact on the dose-conversion factors. Therefore, # International Commission on Radiation Units and Measurements 2013

146 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY tabulation of dose-conversion coefficients based upon tube potential and HVL (at isocenter) will potentially be useful across a variety of CT-scanner vendors and models. This is the situation in mammography, for which the normalized glandular-dose values are not specific to a manufacturer or model. When dose-conversion coefficients are more widely available as a function of x-ray-tube potential and HVL, knowledge of the HVL for each tube potential for a CT scanner will be vital for accurate dosimetry. Hence, it is recommended for acceptance testing of a newly installed CT scanner that the HVL be measured for each tube potential that will to be used and for each of the bow-tie filters available on the scanner. Section 5 described several methods for measurement of the x-ray-beam HVL. The simplest procedure uses the real-time-probe method discussed in Section 5.2.4, but if the necessary tools are not available the conventional (manual) method described in Section is recommended CT Output-Related Parameters Measured in Air The x-ray output of the CT scanner, characterized in terms of CTDI air, is a fundamental measurement that should be performed on each CT scanner at acceptance testing and on a periodic basis, e.g., annually, and after any change or maintenance performed on the x-ray-tube head or collimators and x-ray generators. Two general approaches to measuring the x-ray-tube output as a function of spatial position are recommended below. In each case, the 2D output distribution should be measured for at least four x-ray-tube potentials (spanning the entire range of kv settings ). It is strongly recommended that at one tube potential (e.g., 120 kv), the 2D output distribution should be characterized for the three most commonly used collimation settings. For example, for a CT scanner with a maximum nominal collimation of 40 mm, collimation settings of 10 mm, 20 mm, and 40 mm should be assessed at one x-ray-tube potential. Two specific suggestions for these measurements are: (1) A two-dimensional detector system such as a computed-radiography (CR) imaging plate or a portable thin-film-transistor (TFT) system can be used to characterize the 2D distribution of x rays emanating from the x-ray-tube assembly. The measurement should be performed at the isocenter of the scanner with the gantry stationary, and therefore requires using the scanner service mode. Because CR and TFT detectors are not air-equivalent in terms of atomic number, careful calibration is required to achieve absolute air-kerma measurements. Measurements of CTDI air at isocenter (which does not require a phantom) will serve to normalize these relative measurements to measured air kerma. The 2D output distributions (or other quantities derived from the raw data, such as the collimated beam s full width at half maximum) should be compared with previous measurements performed on the same CT scanner as a consistency check. The measurement of output using a planar detector produces the function f L (x) described in Figure 6.18, which optionally could be converted to f A (u) using Eq. (6.3). (2) If a real-time probe is available, the measurement of the f(z) profile as described in Section and illustrated in Figure 6.9 is recommended. The experimental setup is relatively simple (see Figure 6.8). Optionally, for comparisons among CT scanners, the response function of the real-time probe could be deconvolved using Eq. (6.2). However, the uncorrected measured data remain useful in annual comparisons as long as the same type of real-time dosimeter is used. If the real-time probe method is used to assess f(z), then it should also be used to measure the x-ray-beam profile as a function of the fan angle, u, of the scanner, which characterizes the attenuation properties of the bow-tie filters on the system. The technique illustrated in Figures 6.15 and 6.16 for assessing the x-ray distribution as a function of u also utilizes the real-time probe (McKenney et al., 2011) CT Dosimetry in Phantoms In Section , the assessment of CTDI vol using the 160 mm diameter and 320 mm diameter PMMA phantoms combined with CTDI air and other air-kerma measurements discussed in Section was recommended for acceptance testing of a new CT scanner. It is envisioned that the CTDI vol phantoms (160 mm and 320 mm diameter PMMA) would not be necessary for subsequent routine quality assurance, as long as the air-kerma measurements performed without a phantom (i.e., CTDI air ) were consistent with those made at acceptance testing. This ICRU Report Committee worked with the AAPM Task Group 200 to develop a 600 mm long, 300 mm diameter polyethylene phantom (see Figure 7.19). This phantom was tested under realistic conditions in a clinical environment and, as anticipated, was found to be too large to be 136

147 Summary of Recommendations practical for routine testing of CT systems in the field. However, this phantom does have two important roles to play: (1) It is strongly recommended that the full 600 mm long phantom be available at manufacturer s CT-testing facilities, and that thorough measurements (at both the center and the peripheral locations) be performed using the phantom, such that H(L) and related functions [h(l), G(L), etc.] can be provided for each CT-scanner model. Comprehensive measurements should be measured at all tube-potential settings, with all appropriate bow-tie filters, and over a realistic range of collimation settings. The use of the real-time-probe measurement procedure as outlined in Section 7 will expedite these measurements. Normalization of the acquired h(l) curves by CTDI vol leads to G(L) curves that would be useful for the assessment of patient dose in the clinical setting. The large mass of the full phantom should not be an impediment for use in a factory environment. A subset of the tests with the 600 mm long phantom are strongly recommended to be made by CT manufacturers for each CT model using only the 200 mm long center section of the ICRU/AAPM phantom. For example, with a thimble chamber placed in the center hole of the phantom at the center of the hole along z, the air kerma should be measured for a helical acquisition (with pitch p 1) performed over the entire length of the phantom. This measurement should be performed for all x-ray-tube potentials at a standard tubecurrent time product (e.g., 100 ma s). In addition, at a standard tube potential (e.g., 120 kv), this measurement should be repeated for the three most commonly used collimation settings (e.g., at C max, 1 2 C max, and 1 4 C max, for a scanner with a maximum collimation of C max ). The data generated by this measurement protocol will allow for direct comparison in the field, using the same 200 mm long phantom and measurement protocol. These data also provide a means to relate the partialphantom measurements to the G(L) curves acquired in the 600 mm long phantom [e.g., G 600 (L)/G 200 (L)]. (2) For the evaluation of CT scanners in the clinical environment, it is strongly recommended that only the middle section of the ICRU/AAPM phantom be used. This phantom is 200 mm long and 300 mm in diameter, and is slightly lighter than the ubiquitous 320 mm diameter PMMA phantom. The principal function of the phantom is to measure image noise: the noise-power spectrum, NPS, at a constant air kerma at the center hole of the phantom, as described in Section This will be discussed in greater detail in Section below. An additional function of the phantom measurement is to evaluate the constancy of the tubecurrent time product required to produce a standard air-kerma value at the center of the phantom, which would serve as an additional quality-control parameter. For example, if an effective mas of Jt is required for an air kerma of 10 mgy at the center of the phantom at one time, and 0.80 Jt is required for the same air kerma at a later time, then this is cause for concern and suggests that the x-ray-tube output be further investigated Patient SSDE Section 8 describes methods that can be used to compute conversion coefficients that can be used with the known CTDI vol to estimate the average absorbed dose to patients for a scan of standard length. The SSDE provides a more accurate estimate of patient absorbed dose, and utilizes data that are available in the CT-image data set; specifically, the recorded CTDI vol and the waterequivalent diameter of the patient that can be estimated directly from the CT images. The mathematical methods pertinent to the conversion process are described in Section 9. The effective diameter of the patient was defined for quantifying patient size, when an axial CT image or set of CT images is available. The effective diameter, d eff, is appropriate for abdomen and pelvis imaging, for which only a small amount of internal air exists in body cavities. For thoracic CT scans, however, the large amount of air in the lungs needs to be accounted for, and therefore the water-equivalent diameter, d w, should be used for the thorax. Given the similarity between the calculations for d eff and d w, it is highly recommended that the water-equivalent diameter be used for computing the SSDE, for the head, neck, thorax, abdomen, and pelvis. The SSDE can also be used for estimating dose after the localizer view is acquired, but prior to the CT scan. In this case, the lateral and/or AP dimension of the patient needs to be used to compute d w. Even after the CT images become available, one or more edges of the patient in axial CT images might be cut-off (i.e., a portion of the patient s anatomy is outside of the field of view) due either to clinically appropriate use of small-display fields of view or when a very large patient is scanned. This situation prevents the accurate assessment of the area of the patient in the CT image, and hence compromises the ability to estimate of d w from the CT image. In this case, the localizer view provides the necessary data for estimating patient size using the 137

148 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY PA or lateral dimension of the patient, one of which is generally visible on the localizer image. To overcome the problem of determining d w when a small reconstructed CT field of view prevents assessment of the patient s complete anatomy, it is strongly recommended that CT manufacturers provide pre-calculated d w values for each CTsection image during the reconstruction process. The CT-scanner hardware would compute the full field-of-view (FOV) CT images, determine the d w for each axial image, and report this in the DICOM header. The full-fov images need not be stored unless this is desired by the user. This d w computation includes many elements of the standard reconstruction process for smaller-fov images, and so the additional computational burden would be light. Proprietary or vendor-specific algorithms for computation of d w are discouraged, because all aspects of patient dosimetry should be transparent and verifiable by individuals responsible for CT dose assessment at a given institution. If d w were available for each axial CT image in the DICOM header, then image cut-off due to the use of a small FOV would not be an issue, and subsequent dose assessment would be expedited considerably Automatic Exposure Control in CT The protocol for computing the SSDE is described in Section 8, and the most basic computation of SSDE is given by Eq. (9.1). This equation assumes a patient of constant diameter and a CT scan with constant tube current. Although this approach is adequate for constant-tube-current operation and for general prospective-patient dose calculations (i.e., for research or clinical CT protocols for which patient size can only be assumed), the complexities of size dependence in CT dosimetry combined with the increasing use of tubecurrent-modulation-acquisition modes require a more sophisticated approach. Furthermore, Figure 8.9a shows that for the abdomen pelvis scan, a significant difference can occur when a single value of d w is computed from a single CT image near the center of the scan (in z), when compared with the slice-by-slice determination of the average d w. Therefore, for comprehensive patientdose estimation, it is highly recommended that the average dose be computed as the average SSDE value across all images in the CT scan using the CT-image specific value of d w and the CT-image-specific effective mas or the CTDI vol [see Eq. (9.3)]. Thus, when computational capabilities are available, the SSDE should be computed on a CT-image-specific basis for a given region in the body (e.g., abdomen, pelvis, thorax, head) and an average SSDE (and standard deviation) for each region should be reported. It is recognized that the absorbed dose associated with a given CT slice along z is not only dependent on the d w and effective mas for that slice, but that the scatter tails from adjacent CT slices contribute a significant fraction of dose as well. However, d w and effective mas do not change dramatically from slice to slice along the z axis. Section 9.5 demonstrates a software-based approach for the computation of SSDE on a CT image-specific basis Other Considerations in Patient Dosimetry in CT The current state of science does not allow the estimation of the radiation risk for a specific patient, but it is known generally that the higher the absorbed dose the higher the risk of adverse health effects. The effective dose, E, defined by the ICRP (ICRP, 2007) for the purpose of radiation protection and discussed in Section 4, is based on the absorbed dose in sensitive organs and tissues. When the DLP is known, so-called k-factors can be used to estimate E [see Eq. (4.11)]. However, such information cannot be used to evaluate individual risk because effective dose applies only to a population of adults, averaged for males and females, and is intended to provide a tool for risk management (limitation and optimization) for regulatory purpose. Organ and tissue absorbed doses for individuals undergoing a radiological procedure such as CT are no doubt fundamental, but the relationships that govern the radiation response of a specific patient (depending on age, sex, size, health history, genetic nature, etc.) are still largely unknown. Although effective dose is not suitable for the assessment of the risk for individual patients, it can be useful when comparing different diagnostic modalities and techniques. The assessment of organ doses does allow, however, the use of organ-, sex-, and age-specific coefficients provided in the BEIR VII report (NAS/NRC, 2013) for the estimation of the putative risk to a smaller population and thus not all adults, but not an individual. Although Monte Carlo calculations of organ absorbed dose are useful in developing CT-dose coefficients for generic populations (Zhang et al., 2012), they are not necessary for the individual patient. A software-based approach to assessing the absorbed dose for a specific CT procedure is described in Section 9.6 and is illustrated in Figure 9.4. It is expected that the image-by-image computation of the SSDE would be useful in organ-dose estimation 138

149 Summary of Recommendations using probability-density functions (see Figure 9.10) that describe the fraction of an organ s volume that resides in each CT section. The probability-density-function concept can be developed using gender-specific organ templates ( probability of a specific organ being located along the z axis), which can be aligned (in z) with a specific patient s anatomy in the CT image using boney landmarks (e.g., vertebral bodies) Image-Quality Metrics Image quality in CT is a complex topic; in this Report the emphasis is on the development and use of more quantitative metrics for image-quality assessment rather than historical, qualitative methods. For both spatial resolution and noise assessment, proposed methods require access to the CT-image digital data as well as the ability to manipulate them with custom software. Although some of the mathematical details of these algorithms have been outlined in this Report, it is anticipated that both open-source and commercial software will eventually be available for the recommended analyses discussed here Spatial Resolution in CT A reasonable goal in characterizing spatial resolution in CT is to perform the assessment in 3D. However, there are considerable differences in the resolution properties between the in-plane MTF xy and the longitudinal MTF z, and the factors responsible for these differences are well understood. Therefore, the independent characterization of the MTF xy and MTF z is currently recommended; however, the full 3D MTF in CT can be of value in certain settings. The in-plane CT image is (in general) rotationally symmetric, in the sense that the x and y dimensions are subject to identical factors that influence spatial resolution when filtered-back-projection methods are used for image reconstruction. Therefore, the modulation-transfer function (MTF xy ) can be computed for the axial plane, and the frequency-domain variables (f x and f y ) can be described using a single variable f r. The measurement of the in-plane MTF xy is fundamentally influenced by the reconstruction kernel used, whereas the longitudinal MTF z is almost independent of the kernel and is more dependent on CT-section thickness. It is highly recommended that during acceptance testing of a newly installed CT scanner, both the in-plane and longitudinal MTFs be measured as outlined in Section 10. The in-plane MTF xy should be characterized using a few of the most commonly used reconstruction kernels for that scanner. Measurement of the in-plane MTF xy as a function of the display field of view is also strongly recommended. The longitudinal MTF z should be measured instead of the slice-sensitivity profile; in most applications the slice-sensitivity profile should be retired as a CT-resolution assessment along the z axis. To increase precision, the MTF should be measured in images produced with low noise levels. Therefore, in addition to using a high tube-current time setting for the scan, a small-diameter phantom is useful because of its lower attenuation. A smalldiameter prototype phantom is illustrated in Figure10.15b and is pictured in Figure 10.15c. The measurement of the MTF xy in CT images that are reconstructed using non-linear iterative methods needs to be performed with caution, as the MTF construct assumes a linear, stationary system. Therefore, it is highly recommended for general quality assurance that the MTF be characterized using images that are reconstructed by filtered back projection. In such cases, it is understood that these MTFs represent an upper bound on the spatial resolution of the scanner. Iterative-reconstruction techniques generally tradeoff spatial resolution to reduce noise in an adaptive (local) manner, and any attempt to quantify the MTFs when iterative-reconstruction methods are used should be considered to be valid only within a small (local) region in the image Noise Assessment in CT The noise texture in CT is well characterized by the 3D NPS. The measurement of MTF requires points, lines, or edges in the phantom for resolution measurement, but the evaluation of the NPS is performed using a homogeneous phantom with no specific structures. This makes phantom fabrication much easier than for the case of the MTF. However, the phantom for NPS assessment should approximate the size of patients because noise (and noise texture) is directly related to the size of the phantom. To address this, the ICRU Report Committee and AAPM Task Group 200 developed a 300 mm diameter, polyethylene phantom that serves as both a dosimetry phantom and a phantom for the measurement of the 3D NPS (see Figures 7.19 and 7.20). It is highly recommended that the fully 3D NPS be measured using volumes of interest [see Eq. (11.3)]; methods for radially averaging [Eq. (11.2)] and integration over f z [see Eq. (11.9)] should be used for the presentation of the axial-image NPS. Given the slight dependence of the NPS on the radius of measurement (see 139

150 RADIATION DOSE AND IMAGE-QUALITY ASSESSMENT IN COMPUTED TOMOGRAPHY Figure 11.18), it is highly recommended that a radius of approximately 100 mm be employed when the 300 mm diameter ICRU/AAPM polyethylene phantom is used. Noise and absorbed dose are intrinsically linked because they are fundamentally related to the x- ray fluence used during image acquisition; consequently, measuring the NPS in the absence of absorbed-dose information is of little value. To address this, the protocol specified in Section 11.6 is highly recommended. In that protocol, the center section of the ICRU/AAPM phantom is scanned over its entire length using helical (spiral) or axial (sequential) scanning at a fixed air-kerma level at the center of the phantom. The measurement of the NPS at standardized air-kerma levels in the phantom is meant to provide practitioners with the means to compare the NPS among different CT scanners, and to monitor a specific scanners performance periodically. For consistency testing, NPS curves similar to those shown in Figure provide a more quantitative approach for noise assessment in CT, compared with subjective visual assessment of a low-contrast test object. Comparison of NPS curves among CT scanners (see Figure 11.19) is also an important aspect in protocol development in an environment in which multiple models (and manufacturers) of CT scanners are used Future Directions Real-Time Probe The modern CT system is a dynamic platform: not only is the beam direction changing rapidly, but the beam intensity also can change rapidly. Given this dynamic environment, it is unrealistic to continue to use radiation meters that operate only in an integration mode. The dynamic nature of CT requires dynamic, real-time-measurement technology. The real-time probe, discussed in Section 5.2.3, is a necessary tool for the evaluation of CT dose in the modern era. A number of measurement protocols have been described in this Report that rely upon the use of a real-time radiation dosimeter. Such probes are certain to become an essential tool for the efficient and comprehensive characterization of CT scanners Rise-to-Equilibrium Curve, H(L) AAPM Report 111 (AAPM, 2010) describes a method for characterizing the rise-to-equilibrium curve, H(L). Section 7 of this Report extends the approach of AAPM Report 111 by introducing the use of the real-time probe for rapid singleacquisition characterization of H(L). A series of different normalizations leading to h(l) and G(L) were also discussed. What is still needed is for these metrics to be included in a practical CT-dosimetry methodology. Although characterization of H(L) is the first step toward understanding the important dosimetric consequence of scan length, a straightforward recipe for how the calculation of an individual s dose should be computed is the subject of future research. A likely correction factor, V(L), is envisioned: VðLÞ ¼ HðLÞ Hð100 mmþ : ð12:1þ It is recognized that H(L) describes the dose (at the periphery or center) at the center slice (i.e., at z ¼ 0) of a CT scan of length L. Future studies should develop methods that lead to accurate estimates of the dose along the entire length of the CT scan. The convolution method described in Eq. (7.4) gives guidance in this manner, and other investigators are studying numerical approaches to this as well (Li et al., 2012) Incorporation of Scan-Length Corrections to the SSDE The SSDE methods described in Section 8 and in AAPM Report 204 (AAPM, 2011) allow the estimation of SSDE based upon the known CTDI vol and a conversion coefficient. The conversion coefficients [see Figure 8.10 and Eq. (9.1)] were developed by combining the work of a number of investigators, and include the effect of scan length for standard studies and the conversion from air kerma to absorbed dose in tissue. Although the method is considered sufficiently accurate for current purposes, it is not robust in the case of large deviations in scan length because of the implicit assumptions. It should be recognized that both the SSDE and the H(L) provide tools that address the size of the patient over the length of their CT scan; the SSDE addresses the diameter of the patient, and the H(L) curve suggests a process [e.g., potentially using Eq. (12.1)] for adjusting patient dose based upon the length of the CT scan. Because the conversion coefficients associated with SSDE incorporate the assumption of a standard scan length, it is questionable whether or not the application of an additional scan-length correction factor would improve the accuracy of the existing SSDE methods. Furthermore, the shape of the H(L) curve is diameter-dependent [see Figure 7.28 for related G(L) curves], and the curve shape is 140

151 Summary of Recommendations also dependent upon location in the axial plane (i.e., center or peripheral positions; see Figure 7.29). Despite these complexities, future studies might prospectively develop conversion coefficients that address differences both in diameter and scan length within the same construct. 141

152

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