Measurement of Skin Dose

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Transcription:

Measurement of Skin Dose Sources of Uncertainty Kenneth A. Fetterly, Ph.D. William Pavlicek, Ph.D. Dan Bednarek, PhD 2014 AAPM Annual Meeting, Austin Texas 2013 MFMER slide-1

Purpose 1. Present a framework to recognize and minimize error associated with peak skin dose calculation. 2. Reduce known and substantial bias error to acceptable random error. 3. Suggest a real-world estimate of precision for reporting calculated skin dose. 2013 MFMER slide-2

Outline 1. Types of error 2. Reducing bias error to random error 3. Estimate a likely range of skin dose values 2013 MFMER slide-3

A tiered approach Single exposure event (foot pedal event) Single procedure (multiple exposure events) Multiple procedures Incorporate tissue repair processes First order correction factors MUST HAVE! Higher order correction factors Even better! Improve precision of correction factors 2013 MFMER slide-4

Types of error Bias Unknown constant offset from actual value Can lead to substantial error and must be corrected Remedy by measured correction factor with acceptable random error 2013 MFMER slide-5

Types of error Random Random offset from actual value Instrumentation error Intra and inter-observer variability Unavoidable in physical systems For relative uncertainties, combine by summation of the variances Minimize individual error sources to minimize net uncertainty 2013 MFMER slide-6

TG246 Patient Dose with Diagnostic Radiations - Fluoroscopy 2013 MFMER slide-7

Manufacturers AK tolerance is noted in the Owners Manual! Physicist s Values FIX: AK Calibration 2013 MFMER slide-8

Table and Pad Attenuation Physicist s Exposure Corrections Table and Pad Table and Pad Attn values From Dan Bednarek 2013 MFMER slide-9

C-Arm Angulation Table Movement Chugh K, Dinu P, Bednarek DR, et al, Proc of SPIE 5367, 2013 464 MFMER (2004). slide-10

Peak Skin Exposure Exposure LOCATIONS Exposure OVERLAP At IRP Incident AK Mapping From Clemence Bordier 2013 MFMER slide-11

Relative Forward Scatter 1.15 1.13 1.11 1.09 1.07 1.05 1.03 1.01 0.99 0.97 0.95 40 60 80 100 120 kvp 1.8 mm Al filter 0.2 mm Cu filter 0.3 mm Cu filter Exposure to Dose Forward Scatter From Table - Pad Forward Scatter values From Dan Bednarek 2013 MFMER slide-12

Backscatter Factor Exposure to Dose Back Scatter 1.45 1.4 1.35 1.3 1.25 1.2 1.15 1.1 1.05 1 0 10 20 30 40 Square Field Dimension (cm) Back Scatter values From Dan Bednarek 4 3 2. 5 2 2013 MFMER slide-13

Exposure to Dose f Factor f Factor graph From Dan Bednarek 2013 MFMER slide-14

Well known bias errors Air kerma (as reported by the system) Table and pad attenuation Spectral effects Angular incidence Table and pad forward scatter Tissue backscatter Soft-tissue f-factor Homogeneity effects 2013 MFMER slide-15

Less well known bias errors X-ray source to skin distance Lateral x-ray tube Non-target anatomy (arms) Patient position on table Mismatch between virtual phantom and real patient 2013 MFMER slide-16

Even Less well known bias errors Overlapping fields Same procedure Subsequent procedure X-ray field shape Secondary collimators Area is known, width and length not in DSR Wedge filter Heel effect Imaging during system or patient movement 2013 MFMER slide-17

Strategy to manage bias error Apply correction factors for known sources of bias Investigate and address less known sources of bias Review the images, including DICOM headers Review the DICOM Dose Structured Report Interview staff Assign realistic error estimates to correction factors Calculate overall error estimate Report a likely range of skin dose values 2013 MFMER slide-18

Example: Error mitigation 2013 MFMER slide-19

Modeling error as a normal distribution Approximation for unknown actual probability function. Provides a convenient mathematical foundation for combining sources of uncertainty. P μ, σ, x = σ 1 2π e (x μ) 2 2σ 2 = mean (correction factor) 2013 MFMER slide-20

Estimating error as normal distribution = 0.8, = 0.1 ± If standard deviation, is known, use it. If range of possible values is known, then approximate 2 = ½ range ±2 range Assigns probability of actual value Example For range = 0.4, = 0.1 2013 MFMER slide-21

Approximating source to skin distance (SSD) uncertainty as a normal distribution Assigned SSD (cm) Estimated range of error Estimated range of correction factors Estimated range of relative uncertainty Estimated 60 (AP) ±2 cm 0.93 to 1.07 ± 0.07 0.035 60 (AP) ±5 cm 0.85 to 1.15 ± 0.15 0.075 60 (Lat) ±10 cm 0.7 to 1.3 ± 0.30 0.15 2013 MFMER slide-22

Propagation of normalized error For a composite correction factor, μ c = i μ i, assume that the normalized errors are uncorrelated and then combine variances by the delta method I i J j i σ c 2 = σ i 2 [ μ j ] I i J j i σ c = σ i 2 [ μ j ] 2 2 1/2 Partial derivative of μ c with respect to μ j, where μ c is the composite correction factor I 2013 MFMER slide-23

Propagation of normalized error Assign an a reasonable normalized error to each correction factor. Measured error Range estimate Calculate the estimated composite error. The largest 1 or 2 single sources of error will dictate the magnitude of the composite error. Identify and correct the largest sources of uncertainty to improve the precision of the skin dose estimate. 2013 MFMER slide-24

Single exposure error estimate For every estimate of skin dose, D f (x, y, z) I D f x, y, z = K f i μ f,i J j i f = K f σ c = K f σ i 2 [ μ j ] I i 2 1/2 where f is the exposure event and K is the air-kerma 2013 MFMER slide-25

Multiple exposure error propagation The same (or similarly derived) correction factors are used to calculate dose (D) for each exposure event (f). Therefore, the dose events are assumed to be highly correlated. Traditional square root of the sum of the squares error propagation assumes measurements are independent and is therefore incorrect. 2013 MFMER slide-26

Multiple exposure error propagation Sum the dose (D) from all exposures. F D x, y, z = f D f Propagate error from all exposures. σ 2 F D = ±σ 2 D,f + σ 2 2 D,fi σ 1/2 D,fj f F fi f j Covariance matrix diagonal elements Covariance matrix off-diagonal elements The composite variance is the sum of the elements of the auto-covariance matrix of the individual dose error estimates. 2013 MFMER slide-27

Peak skin dose reporting For every estimate of skin dose, D(x, y, z) Report a nominal expectation value D Report the 95% CI associated with D 95% CI = D ± 1.96 2013 MFMER slide-28

Sample statement for patient record The interventional procedure performed on patient Austin Texas on 7-23-2014 had an estimated peak skin dose of 4.5 Gy (95% CI: 3.4 to 5.6 Gy). 2013 MFMER slide-29

Summary Recognize sources of error associated with skin dose estimates. Reduce bias errors to random errors. Assign realistic error estimates to all correction factors. Report the expected skin dose and an estimated range of possible values. 2013 MFMER slide-30