NEW METHOD OF COLLECTING OUTPUT FACTORS FOR COMMISSIONING LINEAR ACCELERATORS WITH SPECIAL EMPHASIS

Transcription

1 NEW METHOD OF COLLECTING OUTPUT FACTORS FOR COMMISSIONING LINEAR ACCELERATORS WITH SPECIAL EMPHASIS ON SMALL FIELDS AND INTENSITY MODULATED RADIATION THERAPY by Cindy D. Smith A Thesis Submitted to the Faculty of The Charles E. Schmidt College of Science in Partial Fulfillment of the Requirements for the Degree of Professional Science Master Florida Atlantic University Boca Raton, Florida May 2014

2 Copyright by Cindy D. Smith 2014 ii

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4 ACKNOWLEDGMENTS I would like to express my sincere appreciation and thankfulness to Siliva Pella, Ph.D, who mentored me through this program and into my new life as a medical physicist, and Theodora Leventouri, Ph.D, who encouraged me to pursue this degree and provided much help and guidance along the way. I offer a very special thank you to Angelina Bacala, Ph.D who was by my side though so much of this research and offered a helping hand in countless ways. In addition, I must give love and acknowledgement to my family and friends who have cheered me on and offered support when I needed it most. Most of all, I must thank my son, Jacob Denton, who has been on the frontlines through my entire college career. I hope I make you as proud as you have made me. iv

5 ABSTRACT Author: Title: Institution: Thesis Advisor: Degree: Cindy D. Smith New Method of Collecting Output Factors for Commissioning Linear Accelerators with Special Emphasis on Small Fields and Intensity Modulated Radiation Therapy Florida Atlantic University Silvia Pella, Ph.D., DABR Master of Science Year: 2014 Common methods for commissioning linear accelerators often neglect beam data for small fields. Examining the methods of beam data collection and modeling for commissioning linear accelerators revealed little to no discussion of the protocols for fields smaller than 4 cm x 4 cm. This leads to decreased confidence levels in the dose calculations and associated monitor units (MUs) for Intensity Modulated Radiation Therapy (IMRT). The parameters of commissioning the Novalis linear accelerator (linac) on the Eclipse Treatment Planning System (TPS) led to the study of challenges collecting data for very small fields. The focus of this thesis is the examination of the protocols for output factor collection and their impact on dose calculations by the TPS for IMRT treatment plans. Improving output factor collection methods, led to significant improvement in absolute dose calculations which correlated with the complexity of the plans. v

6 NEW METHODS OF COLLECTING OUTPUT FACTORS FOR COMMISSIONING LINEAR ACCELERATORS WITH SPECIAL EMPHASIS ON SMALL FIELDS AND INTENSITY MODULATED RADIATION THERAPY LIST OF TABLES... x LIST OF FIGURES... xii 1. INTRODUCTION Purpose Linear Accelerators External Beam Radiation Therapy Planned Target Volume (PTV) Organs at Risk (OARs) Radiation Absorbed Dose Monitor Units Isodose Curves Dose Volume Histograms (DVHs) D Conformal Radiation Therapy IMRT Treatment Planning System (TPS) Forward Planning Inverse Planning Commissioning Percentage Depth Doses (PDDs) Profiles Output Factors Detector Selection Volume Averaging Effect Perturbation vi

7 Spatial Resolution Multiple Detectors Ionization Chambers Solid State Detectors Quality Assurance Verification Dose Rate and Tumor Response MATERIALS AND METHODS The Procedure Protocols and Limitations Current Method Interpolation Equivalent Squares Alignment New Method Full Matrix Alignment Multiple Detectors Novalis Linear Accelerator Micro-Multi-Leaf-Collimators Field Sizes Eclipse Algorithm Detectors PTW Pinpoint Detector PTW Small Field Diode Detector Water Tanks One Dimensional Water Tank Three Dimensional Water Tank Set Up TPS Beam Data Input Verification Plan Parameters vii

8 Anterior Posterior (AP) 3D Conformal Plan Multi-Target Plan Mock Prostate Plan Head and Neck Plan C Shape Easy Plan C Shape Hard Plan Completed Plans Multi-Target Plan Mock Prostate Plan Head and Neck Plan C-Shape Easy Plan C-Shape Hard Plan Mapcheck RESULTS Percent Difference New Method using Pinpoint vs. Diode Detectors Current Method Using Pinpoint Detector vs. New Method Using Pinpoint Detector Current Method Using Pinpoint Detector vs. New Method Using Diode Detector Percent Difference Summary Absolute Dose Comparison Anterior Posterior Plan Multi-Target Plan Mock Prostate Plan Head and Neck Plan C Shape Easy Plan C Shape Hard Plan Absolute Dose Comparison Summary DISCUSSION viii

9 4.1. IMRT Treatment Plans Multiple detectors Alignment Interpolation and Equivalent Squares Machine Specific Reference Field (MSRF) Brainlab TPS SRS and SBRT CONCLUSIONS REFERENCES ix

10 LIST OF TABLES Table 1. Multi-target treatment plan dose goals Table 2: Multi Target Plan Optimization Objectives Table 3: Mock Prostate Plan Dose Goals Table 4: Mock Prostate Plan Optimization Objectives Table 5: Head and Neck Plan Dose Goals Table 6: Head and Neck Plan Optimization Goals Table 7: C Shape Easy Plan Dose Goals Table 8: C Shape Easy Plan Optimization Objectives Table 9: C Shape Hard Plan Dose Goals Table 10: C Shape Hard Plan Dose Goals Table 11. Output factors using the current method and pinpoint detector Table 12. Output factors using the new method and pinpoint detector Table 13. Output factors using the new method and diode detector Table 14. Percent differences between output factors using the current and new methods with pinpoint detector Table 15. Percent differences between output factors using the current and new methods with the pinpoint detector Table 16. Percent differences between output factors using the current method with the pinpoint detector and using the new method with the diode detector x

11 Table 17. Multi-target treatment plan Mapcheck % pass results Table 18. Mock prostate treatment plan Mapcheck % pass results Table 19. Head and neck treatment plan Mapcheck % pass results Table 20. C-shape easy treatment plan Mapcheck % pass results Table 21. C-shape hard treatment plan Mapcheck % pass results Table 22. Summary of the average Mapcheck % pass results for each type of plan xi

12 LIST OF FIGURES Figure 1. Isodose curves of C-Shape Easy treatment plan... 6 Figure 2. Isodose curves of Anterior-Posterior (AP) beam with an SSD setup that is normalized to Dmax Figure 3. Dose Volume Histogram Figure 4. Percentage Depth Doses, SSD = 100, field sizes from 1cm x 1cm to 10cm x 10cm Figure 5. Profiles Figure 6. Output factors Figure 7. Tumor control probability curve Figure 8. Output factor matrix with fields to be interpolated by TPS are indicated by X Figure 9. Output factor matrix highlighting fields measured with the equivalent square method Figure 10. SSD Setup Figure 11. Anterior-Posterior 3D Conformal treatment plan Figure 12. Coronal view of the multi-target plan structures Figure 13. Transverse view of multi-target treatment plan Figure 14. Transverse view of mock prostate treatment plan structures Figure 15. Coronal view of mock prostate treatment plan structures Figure 16. Transverse view of mock prostate treatment plan xii

13 Figure 17. Transverse view of head and neck treatment plan structures Figure 18. Coronal view of head and neck treatment plan structures Figure 19. Transverse view of head and neck treatment plan Figure 20. Transverse view of C-shape easy treatment plan structures Figure 21. Transverse view of C-shape easy treatment plan Figure 22. Transverse view of the C-shape hard treatment plan Figure 23. DVH for multi-target treatment plan Figure 24. Transverse view of multi-target treatment plan isodose curves Figure 25. Coronal view of multi-target treatment plan isodose curves Figure 26. Sagital view of multi-target treatment plan isodose curves Figure 27. DVH of mock prostate treatment plan Figure 28. Transverse view of mock prostate treatment plan isodose curves Figure 29. Coronal view of mock prostate treatment plan isodose curves Figure 30. Sagittal view of mock prostate treatment plan isodose curves Figure 31. DVH for head and neck treatment plan Figure 32. Transverse view of head and neck treatment plan isodose curves Figure 33. Coronal view of head and neck treatment plan isodose curves Figure 34. Sagittal view of head and neck treatment plan isodose curves Figure 35. DVH for C-shape easy treatment plan Figure 36. Transverse view of C-shape easy treatment plan isodose curves Figure 37. Coronal view of C-shape easy treatment plan isodose curves Figure 38. Sagittal view of C-shape easy treatment plan xiii

14 Figure 39. DVH for C-shape hard treatment plan Figure 40. Transverse view of C-shape hard treatment plan Figure 41. Coronal view of C-shape hard treatment plan Figure 42. Sagittal view of C-shape hard treatment plan Figure D view of the planned dose of multi-target treatment plan imported into Mapcheck Figure 44. Measured dose distributions of multi-target treatment plan by Mapcheck device Figure 45. Comparison of planned and measured absolute dose on Mapcheck Figure 46. Graphical representation of percent differences of output factors (as a function of field size) using the new method with pinpoint and diode detectors Figure 47. Graphical representation of percent differences between output factors (as a function of field size) using the current method with the pinpoint detector and the new method with the pinpoint detector Figure 48. Graphical representation of percent differences between output factors (as a function of field size) using the current method with the pinpoint detector and the new method with the diode detector Figure 49. Graphical representation of the output factors using the old method with pinpoint detector Figure 50. Graphical representation of output factors, as a function of field size, using the new method with the pinpoint detector xiv

15 Figure 51. Graphical representation of output factors, as a function of field size, using new method with diode detector xv

16 1. INTRODUCTION 1.1. Purpose The purpose of this Thesis research is to compare current and new methods of collecting output factors for commissioning the Novalis linear accelerator (Linac) on the Eclipse Treatment Planning System (TPS) by examining their impact on the calculated dose for five types of Intensity Modulated Radiation Therapy (IMRT) treatment plans. New methods in the collection of output factors for small fields can prevent one source of errors commonly found in the commissioning process, and improve the accurate dose and MU calculations associated with the IMRT modality. AAPM TG-155 is making several recommendations to improve the measuring process. These include replacing the use of the one dimensional TG 51 tank with a three dimensional (3D) scanning tank to increase the central alignment of the detectors, and using multiple detection systems to confirm the accuracy of the measurements. Another area of improvement addressed is the common use of equivalent square measurements and interpolations to complete the output factor matrix. Output factors represent just one of the many aspects of commissioning. It is common practice to assume it is unnecessary to take direct measurements to complete a set of output factors. However, we are advised that the accuracy improves with the increase in direct measurements taken to complete the grid. 1 This point becomes more relevant as the field sizes decrease. As the 1

17 largest field size taken for this research is 10 cm x 10 cm (in lieu of the typical 40 cm x 40 cm available on most linacs), no equivalent square measurements or interpolations were used. The matrices representing the new method were completed by direct measurements only. To summarize, three areas are addressed: (1) detector alignment, (2) confirmation of the accuracy of measurements using a second, different, type of detector and (3) the use of direct measurements in lieu of equivalent square measurements or interpolation. These new methods in the measurement taking process exhibit a marked improvement in the accuracy of the absolute dose calculated by the TPS. Accuracy in the calculations of the TPS is the foundation of high quality external beam radiation therapy outcome and improved patient care. In order to understand the impact of measurements taken during the commissioning of linear accelerators on a treatment planning system, and how they affect the treatment output, it is important to be familiar with the equipment, treatment modalities, and terminology Linear Accelerators The development of the linear accelerator changed the world of cancer treatment more than half a century ago. In 1952, the collaboration between a physician and a physicist, Henry Kaplan and Edward Ginzton, initiated the construction of the first linear accelerator. 2 They configured a particle accelerator into a device appropriate for delivery of radiation to specific locations within a patient. 2

18 The device utilizes electromagnetic fields to propel charged particles to high energies. At the treatment head, the charged particles are directed to a target consisting of a high Z number (such as tungsten), and the subsequent radiation is directed through a series of collimators to deliver a precise dose to the target volume. The modern device is based upon the same underlying principles, but the implementation of advanced computer technology and imaging techniques make the treatment process vastly different from what Kaplan and Ginzton would recognize. Every day new developments evolve making the delivery of radiation to patients safer and more effective. Millions of people have benefited from this cancer treatment device External Beam Radiation Therapy External Beam Radiation Therapy uses a linear accelerator (Linac), CT scans, and a treatment planning system (TPS) to aim photons, electrons, or protons to the specific location of the cancer and spare normal tissue from receiving unnecessary irradiation. Over two thirds of all cancer patients receive some type of radiation therapy. 3 Of all of the patients receiving some type of radiation therapy about 88% will receive external beam radiation therapy. 4 There are background information and a number of commonly used terms regarding external beam therapy treatments that will be discussed and/or explained further Planned Target Volume (PTV) The PTV encompasses the treatment target and allow for uncertainties associated with planning and treatment. It consists of the clinical target volume (CTV) which is 3

19 defined by the physician, plus a margin which will compensate for internal organ motion, patient motion, and setup uncertainties Organs at Risk (OARs) It is critical that normal tissue be identified and contoured during the treatment planning process. These OARs cannot receive a higher-than-safe dose to function properly. By contouring the OARs we are able to use various tools available in the TPS such as isodose curves and Dose Volume Histograms (DVHs) to evaluate the dose received by the organs and work to keep the dose well below known limits and as low as reasonably achievable (ALARA) Radiation Absorbed Dose Dose calculations are the most important aspect of any external beam radiation therapy treatment. All the protocols for dose calibrations of the linear accelerator and quality assurance are a means to an end in accurately determining the dose absorbed in the patient. Small changes in absorbed dose, can lead to significant changes in treatment outcome. 5 Absorbed dose is defined as the energy absorbed (de) per unit mass (dm). 6 The SI unit is the Gray (Gy), which is defined as 1 Joule per kilogram. Dose is calculated by the TPS using a complex algorithm which models the beam s path through the linac collimators and patient tissue. The calculated dose is then multiplied by machine output factors to determine the quantity of monitor units (MUs) required to deliver the radiation to the target. 4

20 Monitor Units A monitor unit is a measure of machine output. The monitor units are measured by the linac ionization chambers. The chambers are built into the head of the linac and measure the dose delivered by the beam. They are typically defined as the monitor ionization chamber reads 1 MU when an absorbed dose of 1 cgy is delivered to reference depth in a water phantom, for a reference field size of 10 cm x 10 cm, where the phantom is positioned at a source-to-calibration-distance (SCD), 7 This is an important measurement as the output of the linear accelerator can only be read by the charge in the monitor ionization chambers. (1) MU = Dose / (CF x OF x TPR x WF) (SAD technique) Where Dose is the dose desired, CF is the calibration factor, OF is the output factor, TPR is the tissue-phantom-ratio and WF is the wedge factor. All of these factors vary from machine to machine. One MU is used to standardize treatment machines within each radiation center Isodose Curves Isodose curves give a visual representation of the radiation dose distribution in a phantom or tissue. Overlaid on the target, they are one tool to allow the physicist, physician and dosimetrist to analyze the quality of their treatment plan. Each curve represents a specified range of dose. Below are two examples of isodose curves. One represents the distribution of dose in sample complex treatment plan. (Fig. 1). 5

21 Figure 1. Isodose curves of C-Shape Easy treatment plan. The other represents the distribution of dose from a single 9 cm x 9 cm beam into a 30 cm x 30 cm x 30 cm water phantom created in the TPS for verifications. 6

22 Figure 2. Isodose curves of Anterior-Posterior (AP) beam with an SSD setup that is normalized to Dmax Dose Volume Histograms (DVHs) DVHs were introduced by Dr. Michael Goitein to graphically represent 3D dose distributions in a two dimensional (2D) format. They are another valuable tool allowing us to evaluate the quality of a treatment plan. The primary line is colored red and represents the dose delivered to the PTV. (Fig. 4). Other lines of interest represent the dose to volumes of OARs. Here we have specific parameters we strive to achieve to protect specific organs which fall close to our target. Heart, lung, eyes, spine, rectum, glands and other sensitive tissue each have different tolerances to radiation. These tolerances are represented by the ratio of dose to volume. The DVH is invaluable in helping us quickly determine these parameters are safely met. 7

23 PTV OAR Figure 3. Dose Volume Histogram D Conformal Radiation Therapy Three Dimensional Conformal Radiation Therapy (3D CRT) is a treatment modality which uses Computed Tomography (CT), a TPS, and multi-leaf-collimators (MLCs) to shape the radiation beam to fit the tumor and spare normal tissue. Typical plans include static fields with static MLCs during treatment. Three dimensional static external beam dose and MUs are significantly easier for the TPS to calculate IMRT The IMRT modality is an extension of 3D CRT in the initial planning stages. 8 It, too, uses the MLCs to shape the radiation beam to the shape of the tumor. However, set up has multiple beams, and the MLCs are dynamic. Creating a treatment plan involves an 8

24 inverse planning technique utilizing a dose volume optimization algorithm to calculate the dose fluence of each beam, for the resulting total dose to cover the entire primary target volume (PTV) while minimizing the dose to the OAR. Unlike 3D CRT, the radiation intensities are non-uniform. The control of the fluence using advanced computer optimization techniques to determine the MLC motion modulates the intensity of the radiation allowing for a more controlled distribution of dose. The continuous motion of the MLCs leads to very small field sizes, which make the TPS commissioning process more critical. Inaccurate data during the commissioning process can result in TPS miscalculations of the MLC positions, absolute dose and associated MUs resulting in hot or cold spots in the target volume Treatment Planning System (TPS) Modern radiation therapy takes advantage of the development of imaging modalities such as computed tomography (CT) and the computing power available to calculate complex algorithms to deliver accurate doses to the target. Paired together, they make the TPS an essential tool in any radiation therapy treatment. The specific capabilities of one TPS to another may differ, but the fundamentals are the same. A CT image (along with any other diagnostic images such as MRI or PET scans) are imported, and registered as needed to better delineate the tumor. The target volume is contoured and a dose prescribed by the physician. Critical structures such as PTVs and OARs are contoured. Beams are placed. The goals to the PTV and constraints to the OARs are entered and the optimization is performed to generate the energy fluence, 9

25 then the leaves motion is configured to obtain the desired absorbed dose and then will be proceeding to MU calculations. Analysis tools, such as isodose curves and DVHs allow in-depth evaluation of the dose delivered. If necessary, changes to a plan such as beam arrangements, field sizes, optimizations and energies can be made quickly and easily Forward Planning In the 3D CRT modality, treatment planning is completed using the forward planning technique. CT images are acquired and volumes of interest are contoured. The energy, field sizes and beam arrangements are selected to deliver sufficient dose to the tumor while sparing critical organs. Once these parameters selections are complete, the dose is calculated. Then, the plan is evaluated and (no iterations in forward planning; can be fluence editing or creation of multiple fields in an initial field) until the desired goals are obtained. When the desired dose distribution is obtained the fields are merged into the initial field. The time needed to develop a forward plan is highly dependent upon the experience of the team and the complexity of the case. The optimal result will be a plan where the radiation beams are of uniform intensity across the PTV. The jaws for each individual beam are static. This is a common treatment technique and it works well depending on the tumor shape, location (especially in relation to critical structures), and prescription parameters. 10

26 Inverse Planning For certain clinical cases, dynamic external beam therapy, such as IMRT, is the appropriate treatment modality. In this modality, a more complex combination of hardware and software is required to calculate and create non-uniform fluence maps across beams projected from multiple directions. 10 The fluence profiles are optimized then translated to the motion of the MLCs to deliver a high dose to the target volume while projecting an acceptable low dose to the surrounding normal tissue. The initial parameters are the same as for forward planning: energy, field sizes and beam arrangements. But, the process diverges at optimization. Plan criteria (maximum and minimum dose) are entered for each target volume. Limiting dose parameters are entered for critical structures. The optimization algorithm then attempts to match the criteria. Methods and algorithms differ from one TPS to another, but generally, the TPS divides each beam into numerous beamlets. A Leaf Motion Calculator algorithm optimizes the location of the MLCs to change the intensity of each beamlet and satisfy the dose distribution objectives Commissioning Commissioning is the process of collecting, importing, modeling, calculating and verifying beam data from the linac into the TPS so it accurately represents beam behavior in the dose calculation algorithms. The more meticulous the methods used to collect data, then the more accurate the resulting radiation therapy dose calculations. 11

27 The TPS will require a set of scanned and point dose beam data Scanned data include the Percentage Depth Doses (PDDs), Cross-beam and Diagonal Profiles. Point dose beam data are Output Factors. Other linac specific parameters are entered and/or obtained from a database. Once all the data have been imported, they are analyzed, modeled, calculated and calibrated to support multiple calculation algorithms. Numerous verification methods are applied to confirm the data. The outcome of radiation treatment is directly related to the accuracy of the beam data used by the TPS algorithms to model the behavior of the radiation beam(s) Percentage Depth Doses (PDDs) PDDs are a way of characterizing the central axis (CAX) dose at every point up to 30 cm depth. Areas of interest for PDD curves are the build-up region, peak absorbed dose (Dmax) and rate of decrease as the radiation penetrates the phantom. (Fig. 4). The PDD is defined as a ratio between (Dd) is the absorbed dose at a certain depth, and the dose at the depth of maximum dose (Dmax) and expressed as a percentage. (2) PDD = (Dd/Dmax) x 100% 12

28 Dmax Build-Up Region Rate of Decrease Figure 4. Percentage Depth Doses, SSD = 100, field sizes from 1cm x 1cm to 10cm x 10cm Profiles Profiles of beam data are measurements performed at varying depths and 100 cm SSD. Beam profiles are performed for the same field sizes as those used for the PDDs and scanned in the X (transverse or cross-plane) and Y (longitudinal or in-plane) directions. Diagonal scans are performed at the reference field size of 10 cm x 10 cm from one corner to the diametrically opposed corner. Areas of interest include symmetry of the distribution, the flatness along the central axes, the penumbra region along the beam edge and the dose outside the field. A collection of profiles provide an isodose chart allowing us to examine the beam quality and dose distribution. 13

29 Penumbra Region Flatness and Symmetry Dose Outside Field Figure 5. Profiles Output Factors Output factors are measurements of intensities at different field sizes in relation to the measurement at a specified reference field (10 cm x 10 cm). They are part of the total collimator and phantom beam scatter factors and used to calculate the necessary monitor units from the linac needed to achieve the prescribed dose. Output factors are highly dependent upon field size. A completed matrix (Fig. 6) of all factors for squares and rectangles from the smallest to largest sizes available for that linac are used by the TPS to evaluate the MUs delivered to achieve the desired dose. 14

30 Figure 6. Output factors Detector Selection When measuring beam data for small fields, the correct selection of a proper detector is central to collecting accurate data. Devices designed for large fields will not perform optimally in small fields. This is especially true in the IMRT modality where the radiation field is comprised of many small field segments. Different considerations need to be addressed for scan and point dose data. In small field output factor measurements, the measurement is taken from a static position within a beam comprised of overlapping penumbra resulting in non-uniform fluence across the field. This puts detectors in an area with no uniform dose to measure compared to broad reference fields and scanned data conditions. Certain effects and parameters must be well understood and addressed in selecting the detectors to be used to measure output in small fields. The most significant of these are: (1) dose volume averaging, (2) perturbation, and (3) spatial resolution. 15

31 Volume Averaging Effect Each detector averages the dose over the volume. In small fields where there is a high gradient in dose intensity, the average over a volume can lead to a significant change in the reading inside the detector. Using a detector with volume sensitivity too large for the field size will result in an under estimation of the central axis (CAX) dose. This phenomenon is called the Volume Averaging Effect or Dose Averaging. This effect can be especially important for output factor measurements Perturbation Unless the material of the detector has perfect tissue equivalence, its presence within the field will perturb the photon fluence. In broad fields, this perturbation is negligible and forms the basis of the Bragg Cavity Theory. 12 However, within small fields the physical parameters for the Bragg Cavity Theory fail as the presence of the detector interferes with the measurements Spatial Resolution As field sizes decrease, there are spectral changes in standard linacs due to increased scatter contribution from collimators. Non-uniform fluence across the field becomes increasingly significant for small radiation field sizes becoming entirely comprised of overlapping penumbrae. If the sensitive volume of the detector is too large, the measured output factor will be smaller than the real output factor resulting in radiation overdoses to the patients. 16

32 1.7. Multiple Detectors TG-155 recommends more than one type of detection system be used to cross calibrate and confirm the accuracy of the data. Because of the unique conditions when measuring small fields, the advantages and disadvantages of different types of detectors become amplified. By comparing the measurements of, at least, two different types of detectors, confidence in the accuracy of the measurements is increased. Two of the most popular and readily available types of detectors are ionization chambers and solid state detectors Ionization Chambers Ionization chambers are very popular because of their small variation in response to energy, dose, dose rate and reproducibility. 13 But measuring small or narrow fields using ionization chambers becomes a challenge because of the lack of lateral electronic equilibrium and the volume of the chamber perturbing the field. The standard chamber is comprised of a central electrode surrounded by a spherical solid shell filled with a volume of air. Irradiation causes the air to ionize. The electrons produced by the ionization are attracted to the positive electrode creating a small amount of electrical current which is measured using an electrometer. Ideally, the total electron charge is measured. However, some electrons deposit their energy outside the region of ion collection. And, some electrons produced outside the volume are deposited inside the region of ion collection. If the loss from electrons deposited outside is compensated by the gain from those deposited inside, then we reach a condition of electronic equilibrium. This condition is not reached in small field conditions. 17

33 The volume of the detector, combined with the narrowness of the field, decrease the chances of electrons produced outside the region of ion collection balancing with the electrons produced within the chamber which are not collected by the electrode. In order to increase the confidence of the measurement, selecting a chamber with a small volume is mandatory in small field dosimetry. Mini-chambers designed for small field measurements are available, but high dose gradients, uncertain energy fluence and volume averaging will result in a reduced chamber reading. However, ionization chamber readings for small fields can be considered valid where the spatial resolution is appropriate so the entire sensitive volume of the detector is encompassed by the homogeneous region of the radiation field Solid State Detectors Silicon crystals mixed (or doped) with impurities to make p- and n- type silicon are diode detectors and commonly used for small field dosimetry. When irradiated, electronhole pairs are produced. Their movement from the depletion region results in a current. As with ionization chambers, the current is measured with an electrometer to determine exposure. The energy required to produce an ion-pair in diodes is smaller than ionization chambers by an order of magnitude. This parameter, combined with the high density of the material, means solid state detectors can be designed very small. This makes diodes seem like the ideal detectors for measuring dose within small fields, but they, too, have limitations and controlling parameters such as directional dependence, energy dependency and dose volume averaging. 18

34 Directional dependence is a significant drawback for diode detectors. Typical diode detectors exhibit directional dependence about 3% in magnitude. 15 Proper orientation at set up is crucial to reducing the effect of angular response to the incident beam. Profile scans to assess the proper orientation prior to point dose measurements help create confidence in the correctness of the measurement. Silicon has a high atomic number compared to water or air. This causes diodes to demonstrate significant energy dependence, especially in photon beams of non-uniform quality as is the case in small fields. Diodes also have negative effects from volume averaging in dose gradients over the detector volume. So, as with ionization chambers, the size of the detector in relation to the size of the smallest field to be measured is a significant factor for consideration Quality Assurance Verification Verification of dose calculations for clinical use is the goal of the commissioning practice. There are a number of verifications applied throughout the process, but there is one practical procedure which most effectively reveals the effect on absolute dose from the data imported into the TPS. It is reproducing daily IMRT QA on a carefully selected set of treatment plans. This is the verification process used to analyze the effect of the improved output factor measurements. In this process, a variety of treatment plans are selected and calculated in the TPS. These plans can vary from simple geometries involving water-type phantoms, to very complex geometries meant to mimic realistic treatment cases. The selected treatment plans 19

35 should cover the types of targets, structures, dose constraints and target doses likely to be used in the clinic. 16 Once created, they are calculated, measured and analyzed. 17 The goal is to confirm the absolute dose calculated in the TPS and the actual dose delivered match within an acceptable deviation, typically +/- 2%. A separate device, a 2D diode array, is often used to verify and analyze the actual dose measured in comparison to the planned dose. Verification plans created by the TPS are used by the 2D device to simulate 3D treatment. They include the MLC placement and MU for each field which is derived from a CT study. The diode array is irradiated and the doses measured and analyzed Dose Rate and Tumor Response A tumor control probability (TCP) curve is a simple X-Y graph representing the relationship between tumor control probability and radiation dose. This relationship is represented as a sigmoid with a steep gradient. (Fig. 7). 20

36 Figure 7. Tumor control probability curve 18 In clinical use it is compared to the normal tissue complication probability (NTCP) curve, which is similar in shape, showing the increased rate in complications with increased dose. The goal is to determine the dose range, a therapeutic window, to treat the tumor and avoid complications. The curve representing the therapeutic window is a Gaussian curve with high gradients. A small change in dose can result in a significant change in tumor response. In an attempt to determine how accurate the dose needs to be in order to increase the cure rate it was determined that a 1% accuracy improvement results in a 2% increase in the cure rate 21

37 for early stage tumors. 19 At the mid-range of the steepest portion of the curve, the greatest dosimetric accuracy is required. A 5% change in dose can result in a 10% to 20% change in TCP and may result in a 20% to 30% impact on the NTCP. This relationship highlights the importance of accurate beam data collection and modeling. As we will demonstrate, small differences in the data, can lead to significant changes in the radiation therapy absolute dose delivered, which may result in large changes in the tumor response, normal tissue complications, and, ultimately, the patient care and treatment outcome. 22

38 2. MATERIALS AND METHODS 2.1. The Procedure Three separate sets of output factors were collected. One using the current protocol, and two using the new methods, all within parameters set by the TPS. Current protocol includes using a one dimensional tank, measuring equivalent squares, and letting the TPS interpolate part of the data set. The new methods include using a Multidata three dimensional scanning system to align the detector, and measure each rectangle in the data set in lieu of using equivalent squares and/or interpolation, and measuring with two different types of detectors to confirm the accuracy of the data. General parameters and scanned beam profiles were kept the same. After entering the parameters and data into the TPS, each set of output factors were calculated and calibrated in the exact same manner.. Comparison of the absolute dose was completed using an Anterior Posterior plan in 3D CRT modality and the five IMRT plans from the TG 119 Treatment Suite using dose goals contained within the accompanying report. In addition, the percent difference between each set of output factors were compared, identifying large differences in the very small field range. 23

39 2.2. Protocols and Limitations The Eclipse TPS has specific protocols for the collection of output factors. The units of the matrix were required to be integers, thus limiting our smallest field size to 1 cm x 1 cm. The set-up is required to be at an SSD of 95 cm and a depth of 5 cm. The linac we are working with has field dimensions that do not exceed 9.8 cm x 9.8 cm in treatment mode, but in service mode, we were able to set the largest field at 10 cm x 10 cm, which allowed us to use the normal reference field 10 cm x 10 cm for the output factor measurements. 20 The selection of detectors, scanning tank and 2D diode array are limited to those available at the clinic where the research was performed but are at the highest quality. The ionization chamber selected is a PTW Pinpoint N The diode selected is a PTW Small Field Diode. The scanning tank is a Multidata scanning system which includes the tank, software and electrometer. The 2D diode array used for verification is Sun Nuclear s Mapcheck Current Method The current method of collecting output factors includes procedures which shorten the process and are based upon broad field conditions. We simulated these conditions for one set of output factors. The matrix was collected using a one dimensional tank, where only visual alignment of the detector was available. A common ionization chamber was used to collect 24

40 the data. Some measurements were taken using the equivalent square methods and the TPS interpolated a random selection of field sizes. These are discussed in detail Interpolation The manual for the Eclipse TPS gives instructions to partially enter data to create a coarse grid and let the computer interpolate the missing values. 21 The method works within large fields and designed for linacs with field sizes up to 40 cm x 40 cm. However, the largest field size available on the Novalis is much smaller (10 cm x 10 cm), and the IMRT modality creates MLC configurations that are an aggregate of very small field sizes. Under these small field conditions, the dose gradients are steep, making it difficult for the algorithm to provide accurate calculations. The field sizes in the following matrix (Fig. 8) are marked with an X to indicate measurements which were interpolated by the TPS. All other measurements are grayed out for de-emphasis. X Jaw: Y Jaw: (cm) X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X Figure 8. Output factor matrix with fields interpolated by TPS are indicated by X. 25

41 Equivalent Squares A simple method was developed in the early 1960 s to equate rectangular in square field dosimetry. 22 This method states a rectangular field dose is equivalent to a square field dose if they have the same area/perimeter (A/P). The formula is as follows: (3) A/P = (a x b) / [2(a + b)] Where a is field width and b is field length. This concept is widely used in clinical practice. It is a dosimetric equivalency that works very well for relative large fields. It breaks down as electronic equilibrium is lost in the narrow beam fields, such as those prevalent in the IMRT treatment modality. 23 Inaccuracies become more significant as the field sizes decrease, especially where one dimension of the field falls below 2 cm. In order for the equivalent square measurement to be used for our research, the equivalent square field size had to equal a number to one millimeter. The field sizes in the following matrix (Fig. 9) are highlighted to indicate measurements which were measured using the equivalent square method. All other measurements are grayed out for de-emphasis. 26

42 X Jaw: Y Jaw: (cm) X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X X Figure 9. Output factor matrix highlighting fields measured with the equivalent square method Alignment As is common practice today, the output factors were collected using a one dimensional tank. Set up included aligning the detector to the cross hairs of the light field visually. No extra verifications or methods were used to confirm the accuracy (or inaccuracy) of the detector alignment New Method The focus of the improved method is to eliminate data based on assumptions and algorithms. This means eliminating short cuts which may produce quality results for large fields, but not be reliable for small fields where charged particle equilibrium and overlapping penumbrae create different physical phenomena. In addition, all measurements were taken using multiple types of detectors to further confirm their 27

43 accuracy, and a 3D scanning tank was used to align detectors to the center of the fields in the X and Y axes Full Matrix Output factors are highly dependent upon field size. In order to confirm the accuracy of the data for very small field sizes, each rectangle in the 10 cm x 10 cm matrix was taken using the jaws to shape the fields. This was more time consuming than using the current protocols, but led to a uniform dose rate table. A 10 cm x 10 cm full matrix measurement of 100 field sizes took Alignment In a large field, using a one dimensional tank and visually aligning the detectors to within 1 mm in the X and Y planes is sufficient. However, once the dimensions of the fields fall below 2 or 3 cm, the alignment of the detector to the center of the field becomes crucial to obtaining accurate measurements. It is here, in these small fields, where the overlapping penumbrae begin to eliminate an area of uniform fluence at the center of the field. In order to obtain more accurate measurements, TG 155 recommends using a three dimensional scanning tank which allows the user to digitally align the detectors to the CAX. Although many are equipped with automatic algorithms for obtaining a better alignment, it is currently good practice to use a manual method which consistently gives better results than the software algorithms. Set up included using the Multidata scanning tank for point measurements. This allowed the precise alignment of each detector prior to measurements. Using the Multidata 28

44 scanning software, we learned that a typical eyeball measurement was misaligned in a range from 0.5 to 1.0 mm. Each manual scan included a longitudinal and transverse scan at two depths (5 cm and 10 cm). The scans were analyzed and their misalignments in each direction were separately added and divided by two to obtain a correction factor for each axis. The origin was adjusted with these correction factors and the procedure repeated until the software indicated a misalignment less than 0.03 mm was obtained Multiple Detectors Although measurements from one detector may be repeatable and quantified as precise, it is essential the results be compared to the readings from a different detector in the identical setup in order to confirm their accuracy. This becomes especially important in small field conditions where physical limitations of different types of detectors come more pronounced. The results of two different types of detectors, the PTW Pinpoint N31014 ionization chamber, and a solid state diode, the PTW Small Field Diode, are presented Novalis Linear Accelerator The Novalis (Type 600C) linear accelerator has only one treatment energy of 6 MV. (Please note MV is a convention used when representing photon energies). It is typically commissioned for use with the BrainLab TPS and used for Stereotactic Radiation Surgery (SRS), in addition to 3D Conformal and IMRT. The special features of interest in our work with small fields and IMRT are the micro-multi Leaf Collimators and the limited range of field sizes. 29

45 Micro-Multi-Leaf-Collimators The micro-multi-leaf Collimators (mmlcs) available on the Novalis have a unique geometry. There are 26 leaves in each bank. The central 14 leaves are 3 mm wide and the remaining 12 leaves are 5.0 mm wide. Smaller leaves allow for very conformal shaping of the beam to the target volume. The small field sizes provide a greater challenge to the TPS to accurately calculate the absolute dose Field Sizes A typical linac has a maximum field size of 40 cm x 40 cm. However the Novalis has a maximum field size of only 9.8 cm x 9.8 cm in treatment mode. Field sizes can be shaped by the jaws or mmlcs. The jaws can create a maximum field size of 10 cm x 10 cm in service mode. The minimum field size the jaws can create is 0.5 cm x 0.5 cm. The mmlcs can create a field as small as 0.2 cm x 0.2 cm. Because the current protocol is to use the jaws to shape the fields, both sets of output factors were shaped by the jaws with the collimator rotated to 270 o Eclipse Algorithm The Eclipse TPS (Ver. 8.9) is a windows based system manufactured by Varian Medical Systems and is intended for dose and MU calculations in the planning of radiation therapy treatments of various modalities. It uses several algorithms: the Analytical Anisotropic Algorithm (AAA), Pencil Beam Convolution (PBC) algorithm, and electron Monte Carlo (emc) algorithm model 30

46 dose distribution. The Dose Volume Optimizer (DVO) algorithm is the engine which determines the optimal field shapes used in the IMRT modality. 24 The TPS uses a sophisticated algorithm to calculate the dose deposited in tissue which is divided into three phase spaces. Phase space one follows the beam from the source, through the target, primary collimator, flattening filter and ionization chambers. The electron contamination is included in the model. Phase space two follows the beam through the moveable collimators, such as the jaws and MLCs, where scatter contribution is accounted. Phase space three utilizes the patient modeled from the CT images to complete the beam path and finally calculate the dose deposited in the patient. Phase spaces one and two are referred to as the configuration algorithm where the physical parameters of the beam are derived. Phase space three is the dose calculation algorithm where the physical parameters of the beam are used to calculate the dose deposition in the patient. The accuracy of the calculated dose is highly dependent upon the quality of beam data collected during the commissioning process to model the fundamental physical parameters of the radiation as it exits the linac. AAA is a pencil beam convolution/superposition algorithm that uses a separate Monte Carlo model for the primary photons. The beam is divided into finite size beamlets, β, with photon intensity Φβ. The photon intensity is assumed to be uniform across each beamlet. The initial energy distribution is defined as: (4) x, y, x I x, k u x, v y z E ph,, Where (u,v) is the area of β and kβ is the scatter kernel. dudv 31

47 The energy deposition function is composed of, where Iβ(z ) represents the area integral of deposited energy over the spherical surface of the pencil beam, and ρ is the electron density: (5) In this case z represents the radiological depth and is defined as: z (6) 0 And the scatter kernel, composed of the sum of six exponential functions, is defined as follows: 5 (7) kr k x, y, z ck z' e k 0 r At this point in the calculations, they are assuming a homogeneous environment, with the exception of z (introduced in Eq. 4), which takes into account the heterogeneity between the calculation point and the beamlet entry point. In Eq. 6, The factor ck defines the weights for the exponent kernels, and µk defines the decay constants. A density scaling is performed, heterogeneity is accounted, and then the convolution energy distribution at (x,y,z) is defined as: (8) density: (9) Where kz(z) represents the one dimension scattering kernel. Scaled by the local The de-convolution of the energy deposition will take the following form: (10) I z, I z' z' (0,0, t) k E z I 0,0, z water 1 x, y, z E x, y, z k z ' ph, ph, z ' 2 z i water 1 c e i i z' z I z inv k z 32 i z z

48 Where inv(kz(z)) is the de-convolution kernel derived from Eq. 8. Contaminating electrons are modeled by a Gaussian distribution function. The contaminating electron fluence is determined by the convolving photon fluence with a sumof-gaussians kernel. The separate energy contributions from the primary photons, extra-focal photons, and contaminating electrons within each beamlet are super-positioned at a calculation point and converted to dose using electron densities (ρ): (11) D x, y, z E x, y, z water x, y, z The conversion from dose to MU is based upon the output factors measured during the commissioning process MU D calib ref 1 (12) MU ref CBSF x, y D D x, y WCF x, y Where the collimator backscatter factor (CBSF) is the ratio of the output factors at reference conditions (OFref) and point of dose calculations multiplied by the ratio of the dose calculated at (x,y) and the dose at the reference conditions (D ref) (13) calib OFref D' x, y CBSF x, y OF x, y D' ref The output factors play a direct role in the last calculation performed to determine norm the MUs. This allows us to easily examine the impact they play in the absolute dose distribution. 33

49 All data imported for beam modeling had to be for field sizes which were integers and no smaller than 1 cm. This is a notable difference from the BrainLab TPS which accepted data at 0.5 cm Detectors When measuring beam data for small fields the correct selection of a proper detector is crucial. Certain parameters must be considered when selecting the appropriate detectors: (1) Dose Volume Effects, (2) Directional Effects, and (4) Detector Volume Each detector averages the dose over its volume. In small fields where there is a high gradient in dose intensity, the average over a volume can lead to a significant change in the average reading by the detector. Using a detector with volume sensitivity too large for the field size will result in an underestimation of the central axis (CAX) dose. As previously explained, this phenomenon is called the Dose Volume Effect or Dose Averaging. 25 The guideline is to have a sensitive volume less than half the size of the smallest field, in this case, < 0.05 cm x 0.05 cm. 26 Setting up the detector with minimum uncertainty is crucial. Directional dependence adds another level of uncertainty to the measurement. Chambers generally have minimal directional dependence given their cylindrical nature. Diodes, on the other hand, have significant directional dependence and require extra care for an accurate setup. As part of the new methods, it is recommended more than one type of detector be used to cross-calibrate and confirm the accuracy of the data. The same PTW Pinpoint ionization chamber was used to collect a set of data using the current method and new 34

50 methods. The PTW Small Field Diode was used to collect a set of data using the new method PTW Pinpoint Detector The PTW Pinpoint Model N31014 has a sensitive volume of cm 3 and an energy sensitivity of nc/cgy. It is specially designed for beam profile measurements and evaluation of stereotactic and IMRT small radiation fields. The angular dependence is +/- 1% for up to a 20 o rotation. It is recommended for field sizes from 10 cm to 2 cm. As previously stated, this detector was used to collect two sets of output factors PTW Small Field Diode Detector PTW Small Field Diode has a sensitive volume of 0.03 cm 3 and an energy sensitivity of 9 nc/gy. It is shielded to filter low energy response. This detector was used in the new method to confirm the measurements taken with the PTW Pinpoint Water Tanks Two different types of water phantoms were used to measure the output factors. The original measurements were taken in a one dimensional water tank that is typically used for TG-51 calibrations and point dose measurements. The second and third sets of data were taken using the three dimensional Multidata scanning system. The scanning system is recommended when taking measurements for small fields because it has mechanisms which allow greater alignment accuracy on the longitudinal and transverse axes. As field size decreases, the accurate alignment of the detector becomes more crucial 35

51 to obtain a true measurement because of non-uniform fluence of the beam created by overlapping penumbrae, One Dimensional Water Tank The one dimensional water tank is designed to take point data and was used for the original set of output factors taken using the current method. The dimensions are 40.0 cm x 40 cm x 40 cm. The maximum scanning depth (Z-Axis) is 25.0 cm. It has a positioning accuracy in the Z axis of 0.05 mm Three Dimensional Water Tank The three dimensional Multidata scanning system includes a water tank, electrometer and software designed to measure PDDs and Profiles. It was used to take the new output factors for the improved methods protocol. The tank dimensions are 60.0 cm x 60.0 cm x 60.0 cm. The scanning speed is 5 cm/sec in each axis. It has a mechanical sampling resolution of 0.25 mm and an electronic sampling resolution of mm Set Up An excel spread sheet was created to input the measurement for each rectangle from 1 cm x 1 cm to 10 cm x 10 cm. The tanks were filled, centered and leveled beneath the gantry. The SSD was positioned at 95 cm and the center of the measuring volume of each detector was positioned at a depth of 5 cm. (Fig. 10). 36

52 Figure 10. SSD Setup. The electrometer was set with a bias of 300 V for the measurements taken by the PTW Pinpoint, and no bias for the PTW Small Field Diode. Each detector set up was checked for redundancy and linearity prior to use. Annual readings, mechanical checks, and calibrations were performed on the linac within sixty days prior to measurements. The gantry rotation was set at 0 o and the collimator rotation at 270 o. Original readings were taken using the one dimensional water tank and alignments of the X and Y axis were done visually. The new method measurements were taken using the Multidata scanning system. Detectors were aligned to within 0.03 mm or less along each axis as determined by the RTD Multidata software at each set up. 37

53 The raw readings were taken for 100 MUs. At least three readings were taken for each field size. Each set of readings was averaged for each field size and divided by the measurement taken for the reference field size of 10 cm x 10 cm. Each complete matrix was measured in one sitting. Temperature and pressure readings were taken at the beginning and ending of each sitting. No significant changes in temperature or pressure were identified TPS Beam Data Input The beam data for the profiles were smoothed, centered and imported into the TPS and used with all three sets of output factors. The primary General Parameters were set as follows: (a) Reference depth: Dmax 1.5 cm (b) Energy: 6 MV (c) Profile depths: 1.5, 5, 10, 20 and 30 cm (d) MLC transmission factor: (e) Dosimetric Leaf Gap: 0.11 cm Calculated dose was calibrated in the TPS using a 9 cm x 9 cm beam on a 30 cm cube phantom. As were the Tissue-to-Mass-Ratios (TMRs) Verification Plan Parameters A simple Anterior Posterior (AP) plan with a field size of 9 cm x 9 cm on a 30 cm x 30 cm x 30 cm phantom was created as a control for the 3D CRT modality. Five IMRT 38

54 verification plans were created by importing the TG 119 Treatment Suite and using the parameters outlined in the accompanying instructions. 27 Each plan was created and optimized using one of three sets of output factors: (1) Current Methods with PTW Pinpoint, (2) New Method with PTW Pinpoint, and (3) New Method with PTW Diode. Each time a set of output factors were input to the TPS, the beam data were recalculated and calibrated. Then each plan had the dose recalculated using the new set of data. No other parameters were changed. The process was repeated a total of three times for each set of output factors Anterior Posterior (AP) 3D Conformal Plan The AP plan was created as a control and confirmed that without the use of the Dose Volume Optimizer algorithm, in a broad field treatment plan, each set of output factors had the exact same absolute dose calculations planned and measured. The plan consists of a 30 cm x 30 cm x 30 cm phantom with a target volume at the center. A 9 cm x 9 cm beam was directed from the anterior to the posterior of the phantom, and the dose normalized at the center of the target volume. All plans calculated 183 MUs, and were identical in every measurable parameter. 39

55 Figure 11. Anterior-Posterior 3D Conformal treatment plan Multi-Target Plan The Multi target consisted of three cylinders stacked upon each other. The object of this plan is to test the ability of the TPS to achieve goals set at multiple targets adjacent to each other. Each cylinder had a diameter of 4 cm. The height of each cylinder was adjusted from approximately 4 cm to 2 cm to accommodate the field size limitations of the Novalis (i.e., < 9.8 cm x 9.8 cm). (Fig. 12). 40

56 Superior PTV Inferior Figure 12. Coronal view of the multi-target plan structures. Seven beams were positioned at 50 o intervals from the vertical. (Fig. 13). The dose prescription is 200 cgy in 25 fractions for a total of 5000 cgy. The Plan Normalization Value is

57 Figure 13. Transverse view of multi-target treatment plan. The plan dose goals were as prescribed in TG 119. (Table 1). Table 1. Multi-target treatment plan dose goals. Structure Lower Objectives Upper Objectives Central Superior Inferior 99% of volume to receive at least 5000 cgy 99% of volume to receive at least 2500 cgy 99% of volume to receive at least 1250 cgy 10% of volume to receive no more than 5300 cgy 10% of volume to receive no more than 3500 cgy 10% of volume to receive no more than 2500 cgy The optimization objectives (Table 2) were kept the same for each plan. Objectives were only adjusted to meet the goals. No fluence editing or additional techniques were used to modify the plans. 42

58 Table 2: Multi Target Plan Optimization Objectives. Structure Objective Volume (%) Dose (cgy) Priority Central Upper Central Upper Central Lower Central Lower Superior Upper Superior Upper Superior Lower Superior Lower Inferior Upper Inferior Upper Inferior Lower Inferior Lower Mock Prostate Plan The Mock Prostate plan consists of an ellipsoidal with dimensions of approximately 4.0 cm laterally, 2.6 cm from anterior to posterior, and 6.5 cm from superior to inferior. The PTV is expanded 0.6 cm around the CTV. The rectum is a cylinder with a diameter of 1.5 cm located posterior to the prostate. (Fig. 14). Bladder PTV Rectum Figure 14. Transverse view of mock prostate treatment plan structures. 43

59 About a third of the rectal diameter is within the PTV at the widest PTV slice. (Fig. 15). The bladder is a rough ellipsoid which is 5.0 cm laterally, 4.0 cm from anterior to posterior, and 5.0 cm from superior to inferior. It is centered on the superior aspect of the prostate. Bladder PTV Rectum Figure 15. Coronal view of mock prostate treatment plan structures. Seven beams were positioned at 50 o intervals from the vertical. The prescription is 270 cgy in 28 fractions for a total of 7560 cgy. There is no plan normalization. 44

60 Figure 16. Transverse view of mock prostate treatment plan The plan dose goals were as prescribed in TG 119. (Table 3). Table 3: Mock Prostate Plan Dose Goals. Structure Lower Objectives Upper Objectives Prostate 95% of volume to receive at least 7560 cgy 5% of volume to receive no more than 8300 cgy Rectum 30% of volume to receive no more than 7000 cgy 10% of volume to receive no more than 7500 cgy Bladder 30% of volume to receive no more than 7000 cgy 10% of volume to receive no more than 7500 cgy The optimization objectives were kept the same for each plan. (Table 4). Objectives were only adjusted to meet the goals. No fluence editing or additional techniques were used to modify the plans. 45

61 Table 4: Mock Prostate Plan Optimization Objectives. Structure Objective Volume (%) Dose (cgy) Priority PTV Upper PTV Upper PTV Lower PTV Lower PTV Lower Rectum Upper Rectum Upper Rectum Lower Rectum Lower Urinary Bladder Upper Urinary Bladder Upper Urinary Bladder Upper Urinary Bladder Lower Head and Neck Plan The Head and Neck PTV is all the anterior volume from the base of the skull to the upper neck, including the posterior neck nodes. 46

62 PTV R Parotid L Parotid Cord Figure 17. Transverse view of head and neck treatment plan structures. It is retracted from the skin by 0.6 cm. A gap of about 1.5 cm lies between the PTV and the cord. (Fig. 18). 47

63 R Parotid L Parotid PTV Figure 18. Coronal view of head and neck treatment plan structures. Nine beams are positioned at 40 o intervals from the vertical. The dose prescription is 25 fractions of 200 cgy each for a total of 5000 cgy. 48

64 Figure 19. Transverse view of head and neck treatment plan. The plan dose goals were as prescribed in TG 119. (Table 5). Table 5: Head and Neck Plan Dose Goals. Structure Lower Objectives Upper Objectives PTV 90% of volume to receive at least cgy PTV 99% of volume to receive at least 4650 cgy No more than 20% of volume to receive more than 5500 cgy Cord - No part of volume to receive more than 4000 cgy Parotids - 50% of volume to receive less than 2000 cgy The optimization objectives were kept the same for each plan. (Table 6). Objectives were only adjusted to meet the goals. No fluence editing or additional techniques were used to modify the plans. 49

65 Table 6: Head and Neck Plan Optimization Goals. Structure Objective Volume (%) Dose (cgy) Priority PTV Upper PTV Upper PTV Lower PTV Lower PTV Lower PTV Lower Cord Upper Lt Parotid Upper Lt Parotid Upper Lt Parotid Lower Lt Parotid Lower Rt Parotid Upper Rt Parotid Upper Rt Parotid Power Rt Parotid Power C Shape Easy Plan The target is a C-Shape which surrounds a central avoidance structure. (Fig. 20). The avoidance structure is a cylinder (core) with a 2 cm diameter. There is a gap between the core and the PTV of about 0.5 cm. The inner arc of the PTV is about 3.0 cm in diameter. The outer arc of the PTV has a 3.7 cm radius. The length from superior to inferior of the PTV is 8.0 cm and the central core has a length of 10.0 cm. 50

66 PTV Core Figure 20. Transverse view of C-shape easy treatment plan structures. Nine beams are positioned at 40 o intervals from the vertical. (Fig. 21). The dose prescription is 25 fractions of 200 cgy each for a total of 5000 cgy. No plan normalization is necessary. 51

67 Figure 21. Transverse view of C-shape easy treatment plan. The plan dose goals were as prescribed in TG 119. (Table 7.) Table 7: C Shape Easy Plan Dose Goals. Structure Lower Objectives Upper Objectives PTV 95% of volume to receive at least 5000 cgy 10% of volume to receive no more than 5500 cgy Core - 5% of volume to receive no more than 2500 cgy The optimization objectives were kept the same for each plan. (Table 8.) Objectives were only adjusted to meet the goals. No fluence editing or additional techniques were used to modify the plans. 52

68 Table 8: C Shape Easy Plan Optimization Objectives. Structure Objective Volume (%) Dose (cgy) Priority Core Upper Core Upper Core Upper Outer Target Upper Outer Target Upper Outer Target Upper Outer Target Lower Outer Target Lower Outer Target Lower Outer Target Lower C Shape Hard Plan The C Shape Hard plan has the exact same physical dimensions (Fig. 20), beam arrangement (Fig. 23), and dose prescription as the C Shape easy treatment plan. Figure 22. Transverse view of the C-shape hard treatment plan. 53

69 The only difference between the C-shape easy and hard treatment plans are the dose goal to the core and the associated optimizations. The plan dose goals were as prescribed in TG 119. (Table 9). Table 9: C Shape Hard Plan Dose Goals. Structure Lower Objectives Upper Objectives C Shape PTV 95% of volume to receive at least 5000 cgy 10% of volume to receive no more than 5500 cgy Core - 5% of volume to receive no more than 1000 cgy The optimization objectives were kept the same for each plan. Objectives were only adjusted to meet the goals. (Table 10). No fluence editing or additional techniques were used to modify the plans. Table 10: C Shape Hard Plan Dose Goals. Structure Objective Volume (%) Dose (cgy) Priority Core Upper Core Upper Core Upper Outer Target Upper Outer Target Upper Outer Target Upper Outer Target Lower Outer Target Lower Outer Target Lower Outer Target Lower

70 2.12. Completed Plans Each type of treatment plan had DVHs and isodose curves which were indistinguishable. A DVH, transverse, coronal, and sagittal view of the isodose curves for each of the completed plans are presented. The DVH illustrates the goals established in TG 119 are met. Isodose curves illustrate the dose distribution covers the target(s). The images presented are typical for all sets of plans Multi-Target Plan The DVH (Fig. 23) shows the PTV, superior, and inferior structures meet the dose objectives. > 1250 cgy > 2500 cgy > 5000 cgy Inferior Superior PTV < 2500 cgy < 3500 cgy < 5300 cgy Figure 23. DVH for multi-target treatment plan. The calculated isodose curves are presented from the transverse (Fig. 24), sagittal (Fig. 25) and coronal planes (Fig. 26) showing the uniform coverage of the target structures. 55

71 Figure 24. Transverse view of multi-target treatment plan isodose curves. Figure 25. Coronal view of multi-target treatment plan isodose curves. 56

72 Figure 26. Sagital view of multi-target treatment plan isodose curves. objectives Mock Prostate Plan The DVH shows that the PTV, rectum and bladder structures meet the dose 57

73 Rectum > 7560 cgy Bladder PTV < 7000 cgy < 8300 cgy < 7500 cgy Figure 27. DVH of mock prostate treatment plan. The calculated isodose curves are presented from the transverse (Fig. 28), sagittal (Fig. 29) and coronal (Fig. 30) planes showing the uniform coverage of the target structures. Figure 28. Transverse view of mock prostate treatment plan isodose curves. 58

74 Figure 29. Coronal view of mock prostate treatment plan isodose curves. Figure 30. Sagittal view of mock prostate treatment plan isodose curves. 59

75 Head and Neck Plan The DVH (Fig. 31) shows the PTV, cord, left and right parotid structures meet the dose objectives. > 4650 cgy > 5000 cgy Cord PTV < 2000 cgy Parotids < 5500 cgy < 4000 cgy Figure 31. DVH for head and neck treatment plan. The calculated isodose curves are presented from the transverse (Fig. 32), sagittal (Fig. 33) and coronal (Fig. 34) planes showing the uniform coverage of the target structures. 60

76 Figure 32. Transverse view of head and neck treatment plan isodose curves. Figure 33. Coronal view of head and neck treatment plan isodose curves. 61

77 Figure 34. Sagittal view of head and neck treatment plan isodose curves. objectives C-Shape Easy Plan The DVH shows the PTV, cord, left and right parotid structures meet the dose > 5000 cgy Core > 2500 cgy PTV < 5500 cgy Figure 35. DVH for C-shape easy treatment plan. 62

78 The calculated isodose curves are presented from the transverse (Fig. 36), sagittal (Fig. 37) and coronal (Fig. 38) planes showing the uniform coverage of the target structures. Figure 36. Transverse view of C-shape easy treatment plan isodose curves. Figure 37. Coronal view of C-shape easy treatment plan isodose curves. 63

79 Figure 38. Sagittal view of C-shape easy treatment plan. objectives C-Shape Hard Plan The DVH (Fig. 39) shows the PTV, superior, and inferior structures meet the dose 64

80 Core > 5000 > 5000 cgy cgy > 1000 cgy PTV < 5500 cgy Figure 39. DVH for C-shape hard treatment plan. The calculated isodose curves are presented from the transverse (Fig. 40), sagittal (Fig. 41) and coronal (Fig. 42) planes showing the uniform coverage of the target structures. 65

81 Figure 40. Transverse view of C-shape hard treatment plan. Figure 41. Coronal view of C-shape hard treatment plan. 66

82 Figure 42. Sagittal view of C-shape hard treatment plan Mapcheck Using a 2D diode array, Mapcheck by Sun Nuclear Corporation, each plan was analyzed to compare the planned and measured absolute dose. This device is a common tool utilized for IMRT quality assurance (QA). It consists of 445 diodes arranged in a 22 cm octagonal grid. During exposure to radiation, each diode generates a charge proportional to the dose received at that location. The charge is integrated, converted from analog to digital and sent to the computer, giving an absolute dose for each location almost instantaneously. A 3D QA plan is created in the TPS and the coronal view of the dose array is exported to the Macpcheck (Fig. 43). 67

83 Figure D view of the planned dose of multi-target treatment plan imported into Mapcheck. The QA plan is ran delivered to the Mapcheck where the diode array measures the output and displays the dose distribution in a second display (Fig. 44). Figure 44. Measured dose distributions of multi-target treatment plan by Mapcheck device. 68

84 Before a comparison between the planned and measured dose can be analyzed, a variety of settings and parameters must be chosen. Per TG 119 guidelines, the parameters were set as follows: (1) The analysis is done in absolute dose only. (2) The dose difference threshold of 10% is used to exclude low dose points from appearing to fail due to uncertainties. (3) The Van Dyk percent difference measures the difference between any measured point and the corresponding plan point normalized to a common point. (4) When Measurement Uncertainty is On, an uncertainty factor is calculated for each diode including differences between the absolute dose calibration of the Mapcheck and the standard dose value due to temperature changes, errors in setup, fluctuations in the linac output, accuracy of array calibration and precision of electronic measurements. (5) Gamma criterion is a unitless index which relates the calculated dose distribution to within 3% of planned dose to a distance-to-agreement within 3 mm of planned location. The comparison is calculated and displayed for further analysis by the physicist (Fig. 45). Figure 45. Comparison of planned and measured absolute dose on Mapcheck. 69

85 Each set of output factors had a set of three plans analyzed, giving nine plans for each of the five types of plans for a grand total of 45 plans analyzed. Each type of plan had consistent results given the same set of output factors used in the dose calculations. 70

86 3. RESULTS 3.1. Percent Difference When comparing results, neither of which can be considered the correct value, percent difference is the absolute value of the difference over the mean. The formalism is as follows: (14) % Difference = [ M1 - M2 / (M1 + M2)/2] x 100 We applied this analysis first by comparing the measurements using the new method for the pinpoint and the diode detectors. Then, go back and look at the measurements from the pinpoint for the new and current methods. Finally, we look at the comparison of the measurements from the new method for the diode and the current method for the pinpoint. The three sets of output factors compared are listed in Tables 11, 12 and

87 Table 11. Output factors using the current method and pinpoint detector. Y Jaw: X Jaw (cm) (cm) Table 12. Output factors using the new method and pinpoint detector. Y Jaw: X Jaw (cm) (cm)

88 Table 13. Output factors using the new method and diode detector. Y Jaw: X Jaw (cm) (cm) New Method using Pinpoint vs. Diode Detectors Looking at the complete sets of output factors for the new method (Tables 12 and 13), we immediately see the under-response from the pinpoint and the over-response from the diode, as expected. 28 Calculating the percent difference, we see how the output factors diverge in small fields, with the largest differences occurring in fields where one side equals 1 cm (Table 14). 73

89 Table 14. Percent differences between output factors using the current and new methods with pinpoint detector. Y Jaw: X Jaw (cm) (cm) The graphical representation (Fig. 46) illustrates the percent difference between two sets of output factors. The x-axis represents the x-jaw field size (cm). The y-axis represents the y-jaw field size (cm). The z-axis represents the percent difference between the two sets of output factors. (This is true for all of the percent difference graphs.) This surface view allows us to easily see the wide ranges of percent differences. The striped sides show the steep gradient where the percent differences peak at 10% in the 1 cm x 1 cm field size, then quickly fall below 1% as each field side grows larger than 2 cm. 74

90 Percent Difference of Output Factors using new method with pinpoint and diode detectors output factors 10.0% y-jaw x-jaw 8.0% 6.0% 4.0% 2.0% 0.0% field sizes larger than 2 cm x 2 cm %-2.0% 2.0%-4.0% 4.0%-6.0% 6.0%-8.0% 8.0%-10.0% 10.0%-10.6% Figure 46. Graphical representation of percent differences of output factors (as a function of field size) using the new method with pinpoint and diode detectors Current Method Using Pinpoint Detector vs. New Method Using Pinpoint Detector The percent difference between the current method pinpoint measurements and new method pinpoint measurements are more difficult to analyze (Table 15). The differences are inconsistent in the small field ranges, then diminish to less than 1% as the fields sizes grow larger than 3 cm. 75

91 Table 15. Percent differences between output factors using the current and new methods with the pinpoint detector. Y Jaw: X Jaw (cm) (cm) Looking at the surface view (Fig. 47), we can see peaks and valleys where percent differences fluctuate up to 6%. These fluctuations correlate with interpolated and equivalent square measurements for field sizes less than 3 cm. It peaks at 10% for the smallest 1 cm x 1 cm field. 76

92 Percent Difference of Output Factors using new method with pinpoint detector and current method with pinpoint detector 10.0% 5.0% 0.0% x-jaw size (cm) y-jaw size (cm) 0.0%-5.0% 5.0%-10.0% 10.0%-10.6% Figure 47. Graphical representation of percent differences between output factors (as a function of field size) using the current method with the pinpoint detector and the new method with the pinpoint detector Current Method Using Pinpoint Detector vs. New Method Using Diode Detector The percent difference between the current method using the pinpoint detector and the new method using the diode detector is primarily in the small field region (Table 16). The largest percent differences also trend to correlate where interpolated and equivalent square measurements were taken. 77

93 Table 16. Percent differences between output factors using the current method with the pinpoint detector and using the new method with the diode detector. Y Jaw: X Jaw (cm) (cm) % 8.0% Percent Difference of Output Factors using new method with diode detector and current method using pinpoint detector 6.0% 4.0% 2.0% 0.0% %-2.0% 2.0%-4.0% 4.0%-6.0% 6.0%-8.0% 8.0%-10.0% 10.0%-10.6% Figure 48. Graphical representation of percent differences between output factors (as a function of field size) using the current method with the pinpoint detector and the new method with the diode detector. 78

94 Percent Difference Summary Overall, the end-to-end process revealed the significance of different methods when measuring output factors during the commissioning process. Percent differences were very large in the small field range. Understanding the outstanding areas of percent differences becomes a little easier when examining a 3D representation of each set of output factors. The x-axis represents the x-jaw field size (cm. The y-axis represents the y-jaw field size (cm). The z-axis represents the output factor normalized to the referenced field size of 10 cm x 10 cm. The current method matrix (Fig. 49) appears rocky and uneven in comparison to the two improved method matrices (Fig. 50 and 51), which are smooth, symmetrical and consistent. We can clearly see the differences in the gradients of the smallest fields. Areas where fields were interpolated in the current method matrix are especially evident. Ouput Factors using the old method with pinpoint detector Figure 49. Graphical representation of the output factors using the old method with pinpoint detector. 79