Monitor Unit Verification for Small Fields

Transcription

1 Monitor Unit Verification for Small Fields Patrick Higgins, Ph.D University of Minnesota Department of Radiation Oncology October 10, 2013

2 The Issues: How do we verify the monitor units calculated by the planning system are accurate when we have multiple issues of small fields and heterogeneous media? Do we have to run IMRT-like phantom tests (which avoid the problem of heterogeneity) to verify MU s? Can we do some kind of hand calculation to verify MU s? If so, how do we approximate heterogeneity effects? What level of check accuracy is reasonable to avoid catastrophe?

3 What do people do? As best as we have been able to tell, they do either: 1. Simple hand calcs for confirmation. But MuCheck and Rad Calc use deff for heterogeneous calcs. This is maybe the simplest of 1-d calculations and loses accuracy as the depth (and effective depth) increases. or, 2. Measure dose using Mapcheck or its equivalent (with or without point measurement) as is done for IMRT qa. But now we replace a hard problem with a much easier test.

4 What do we do? Historically, at Minnesota we have relied on hand calculations as being the most accurate, least biased method for monitor unit definition. The planning system MU s were considered a secondary check. Prior to Pinnacle (i.e. superposition/convolution) heterogeneity corrections were rarely done, except for lung. Even then we tried to be sure the central axis minimally overlapped lung so that simple hand calculations could still be done. Only in the last 5 or 6 years have we become comfortable with the predictive quality of Pinnacle for heterogeneous media and only after we convinced ourselves that we could do confirmative hand calculations for 6 MV to within about ±5%. Another great impacting factor on us was the introduction of SBRT which forced us to find a way to check doses in the presence of significant heterogeneity.

5 Planning System Accuracy The best we can hope for beam models is probably 2-5% accuracy when we include heterogeneities (AAPM report 85). For systems like Pinnacle that accuracy is further confounded by the subjectivity of the modeling process. Beam models (and modelers!) are further stretched in the limits of small fields where both the input data is more prone to error and heterogeneity modeling is not included. For IMRT plans we are forced to transfer heterogeneous plans to homogeneous phantoms in which we can do direct measurements to confirm monitor units and bypass the heterogeneity issue. For static field SBRT cases some places use the IMRT QA approach. We felt that, at least for static fields, we should be able to find a way to verify Pinnacle MU s without resorting to special (albeit flawed) measurements.

6 Planning system verification vs. Hand calculation As part of an M.S. project (Rishik Saxena) we measured the validity and range of application of several 1-d heterogeneity corrections that could easily be incorporated into a hand calculation for planning system MU verification. We built composite lung-soft tissue and bone-soft tissue phantoms to measure doses and compared against Pinnacle, Eclipse pencil beam and 3 1-d methods over a range of field sizes and energies: 1. Effective depth (used by MuCheck and other vendor supplied programs). 2. Effective attenuation (originally used in diagnostic applications). 3. Ratio of TMR s. All 3 methods use effective depth in some form or other. For this presentation we are going to concentrate on effective attenuation.

7 Effective Depth This is the simplest possible estimate of the effect of electron density on depth for the purpose of calculating dose in homogeneous media of density different from water. It is so primitive that it is not discussed in textbooks as a correction model. deff is the effective pathlength or depth in a medium based on the weighted electron densities of the elements in the medium. This has been used to adjust measurement depths over a small range to make up for the difference in density in water-replacement plastics for calibration purposes. It has been used in place of the physical depth in some vendor-supplied monitor unit calculation programs.

8 Effective attenuation An effective attenuation coefficient is used to estimate the correction to TERMA due to differences in physical and effective depths: ICF = exp( µ ( d eff d)) (Inhomogeneity Correction Factor) µ is the effective attenuation coefficient of water for a particular beam quality. (For this we have just used the linear attenuation coefficient for the peak photon energy.) d is the physical depth d eff is the effective depth In this method the homogeneously calculated pdd or TMR is corrected by the ICF.

9 Ratio of tissue-air ratios (RTAR) This method was one of the most commonly used methods in older commercial treatment planning systems and as a method of spot checking dose. Other names have been given to this method. The 1-d version is given by ICF = TAR( d eff, W ) TAR( d, W ) One might expect the inclusion of field size effects would be an advantage over simple attenuation differences, but as you will see we found no particular improvement in accuracy.

10 Model Evaluation In order to evaluate dose calculation accuracy for our planning systems we built a lung/soft tissue phantom. Measurements were made 1 at a number of depths (EDR2 film) and in interfaces for a range of field sizes and energies. These measurements have been used for some time for baseline testing of our planning systems. Using this data we could also evaluate the viability of different correction methods. 1 Saxena R. and Higgins PD, Measurement and Evaluation of Inhomogeneity Corrections and Monitor Unit Verification for Treatment Planning. Medical Dosimetry, 35:19-27, 2010.

11 Lung Phantom for Testing Solid Water 3 cm Cork Solid Water Cork Solid Water 3.0 cm 5.0 cm 7.0 cm 7.5 cm 8.5 cm 10.5 cm 11.5 cm 13.5 cm 15.5 cm 17.5 cm 4 cm 4.5 cm 4 cm 5 cm

12 4x D-effective %-difference Depth (cm) Attenuation corr Eclipse Eq. TAR Pinnacle 6 MV Pdd calculation vs. 10x10 measurement %-difference D-effective Attenuation corr Eclipse Eq. TAR Pinnacle Depth (cm)

13 4x %-difference Attenuation corr Eclipse Eq. TAR Pinnacle 10 MV Depth (cm) 10x10 Pdd calculation vs. measurement %-difference Attenuation corr Eclipse Eq. TAR Pinnacle Depth (cm)

14 25.0 4x4 %-difference Depth (cm) x10 Attenuation corr Eclipse Eq. TAR Pinnacle 18 MV Pdd calculation vs. measurement 10.0 %-difference Attenuation corr Eclipse Eq. TAR Pinnacle Depth (cm)

15 How good can Pinnacle be? Pdd vs. Depth, Varian 25 MV, field size 2x Pdd (%) Measured Pinnacle Depth (cm)

16 Measurement Summary 1. All of the 1-d correction errors are in the direction of overestimating doses. 2. Pinnacle appears accurate to within 5% for field sizes as small as 2x2 for energies of 6-25 MV. 3. For large field sizes (>10x10) all of the simple 1-d correction methods work fairly well (within 5%). 4. For small fields (4x4) and low energy (6 MV) the attenuation correction appeared promising, at least in a simple phantom setting.

17 Clinical Small Field MU Evaluation Phantom tests confirmed the accuracy of Pinnacle. The next step was to apply the simple 1-d corrections for real test cases. For our first 26 SBRT lung cases, we compared Pinnacle MU settings with hand monitor unit calculations, based on the physical depth, but corrected using the effective attenuation ICF factor. 2 2 Higgins PD, Adolfson T, Cho LC and Saxena R. Monitor Unit Checking in Heterogeneous SBRT Treatment Planning; Medical Dosimetry, Vol. 36 (3): , 2011

18 SBRT #19 Comparison of Pinnacle with ICFcorrected Point calc. Field d deff FS Eff FS ICF Pinnacle MU Point MU Point/ICF Delta a % b % c % d % e % f % g % h % I % j % ICF = exp{ µ w ( d eff d )} µ water ( 6 x ) = / cm

19 MU comparison with Pinnacle vs. ICF ICF Pinnacle Calculation Comparison: Attenuation Correction Most outliers are correlated with very low lung density % -15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0% % Diff calc vs Pinnacle MU n Ave ICF St Dev Max Min Ave St Dev Max Min 1.80% 4.10% 14.70% % Pass number % 15% % 10% % 5% %

20 MU comparison with Pinnacle vs. Field Size Pinnacle Calculation Comparison: Field Size Effective Field Size % -15.0% -10.0% -5.0% 0.0% 5.0% 10.0% 15.0% 20.0% % Diff calc vs Pinnacle MU

21 Ratio of TMR Comparison of MU s with Pinnacle vs. ICF Pinnacle Calculation Comparison: Ratio of TMR's ICF % -5.0% 0.0% 5.0% 10.0% 15.0% 20.0% 25.0% 30.0% 35.0% 40.0% % Diff calc vs Pinnacle MU

22 SBRT Test Summary 1. Check calculations using effective attenuation to approximate the effect of heterogeneities on lung plans appear to be accurate to ±5% for 6 MV and field sizes 3x3 and larger. 2. For those fields where the check is more than 10% different from Pinnacle, we review the planned fields for potential problems, increasing the field size, if needed, to obtain better agreement. Even though we have the highest confidence in Pinnacle, we may not know if the discrepancy is due to the lousy 1-d test, or to modeling error in small field extrapolation. So it is better to err on the cautious side.

23 SBRT Test Summary 3. We have found that conditions where the point calculation disagrees the most with Pinnacle are for the situation of very low density lung tissue (COPD) and in areas of bone-lung interfaces where Pinnacle is less accurate. This led us to do the following study of density effects, relative to this simple point calculation check.

24 Effects of Lung and Target Density The amount of heterogeneity in the scattering environment certainly contributes to the treatment planning problem. Low density lungs require larger PTV volumes or block margins to achieve the same coverage as higher density lungs. We set up a water phantom model in Pinnacle with a spherical lung insert and varied the size and density of a target as well as the lung density. We then exercised our simple correction by calculating MU s vs. Pinnacle MU s for a single field ranging in size to just matching the target to a few cm larger.

25 Effects of Lung and Target Density 6 MV Field Unit density 3.5 cm Lung 15 cm PTV

26 Effects of Lung and Target Density cm Target Density 1.0 MuCalc MU/Pinnacle MU Lung density 0.25 Lung density 0.2 Lung density 0.15 Lung density 0.1 Lung density 0.05 Lung density Field Size ICF-corrected MU vs. Pinnacle MU Single Small Field of Different Widths: 5-10% overestimates.

27 Effects of Lung and Target Density cm Target Density 0.6 MuCalc MU/Pinnacle MU Field Size Lung density 0.25 Lung density 0.2 Lung density 0.15 Lung density 0.1 Lung density 0.05 Lung density 0.0 ICF-Corrected MU vs. Pinnacle for Typical Target Density: ±5% Range.

28 Effects of Lung and Target Density cm Target Density 0.3 MuCalc MU/Pinnacle MU Field Size Lung density 0.25 Lung density 0.2 Lung density 0.15 Lung density 0.1 Lung density 0.05 Lung density 0.0 ICF-Corrected MU vs. Pinnacle for Typical Target Density: 10+% underestimate depending on field size.

29 Effects of Lung and Target Density cm Target Density 0.3 MuCalc MU/Pinnacle MU Field Size Lung density 0.25 Lung density 0.2 Lung density 0.15 Lung density 0.1 Lung density 0.05 Lung density 0.0 ICF-Corrected MU vs. Pinnacle for Typical Target Density: Match improves with target and field size.

30 Conclusions 1. For low energy (6 MV) a 1-d attenuation-based correction can be used to verify the planned MU s for a well-tested planning system, avoiding the need for phantom test measurements and giving us some level of confidence that there is no catastrophic problem in the plan. 2. Small targets in SBRT lung cases pose additional problems for planning systems depending on how diffuse the targets are and on the surrounding lung density. It is better to increase the field margin to satisfy a simple 1-d test than use very tight margins and prescribe to low isodose lines. 3. Even though it may be argued that hand calculations are much inferior to a full, well-tested beam model, experience has shown that the risk of not performing some independent test is not worth taking.

31 Thank you!

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33 1.6 cm Target Density Ratio 0.8 cm Lat:to:Center Dose Lung density 0.25 Lung density 0.2 Lung density 0.15 Lung density 0.1 Lung density 0.05 Lung density 0.0 Dose homogeneity: Ratio of dose at lateral edges of targets to the dose at the center. Field Size Ratio 1.5 cm Lat:to:Center Dose 3 cm Target Density Lung density 0.25 Lung density 0.15 Lung density 0.1 Lung density 0.05 Lung density 0.0 Effect of field size and densities of target and lungs on dose coverage. Field Size

34 Estimates of Uncertainty (in terms of one standard deviation) in absolute dose in the patient for megavoltage photons (AAPM Report 85). Source of Uncertainties Uncertainty at Uncertainty in Present (%) Future (%) Dose at the calibration point in water Additional uncertainty for other points Beam Monitor stability Beam flatness Patient data Patient set up and organ motion Overall (excluding dose calculation) Dose calculation algorithm 1.0 / 2.0 / 3.0 / / 2.0 / 3.0 TOTAL 4.4 / 4.7 / 5.2 / / 3.2 / 3.9

35 Table 7. Categorization of different inhomogeneity correction algorithms according to the level of anatomy sampled (1D or 3D) and the inclusion or exclusion of electron transport (AAPM Report #85) TERMA Local energy deposition (No electron transport) DOSE Non-local energy deposition(electron transport) 1d Category Linear attenuation 1.2 Ratio of TAR (RTAR) (Equivalent path length, effective SSD, isodose shift) 1.3 Power law (Batho) 3d Category Equivalent TAR (ETAR) 2.2 Differential SAR (DSAR) 2.3 Delta volume (DVOL) 2.5 3D Beam Subtraction Method Category Convolution (pencil beam) 3.2 FFT techniques Category Superposition/Convolution 4.2 Monte Carlo 2.4 Differential TAR (dtar)

36 1-d Methods for Evaluating Monitor Units 6 MV 2300cd pdd pdd (uncorrected) pdd (deff) Measured ICF-corrected pdd Pinnacle depth (cm)