Michael Speiser, Ph.D.

Transcription

1 IMPROVED CT-BASED VOXEL PHANTOM GENERATION FOR MCNP MONTE CARLO Michael Speiser, Ph.D. Department of Radiation Oncology UT Southwestern Medical Center Dallas, TX September 1 st, 2012 CMPWG Workshop

2 Medical Physics Investigations and Monte Carlo Patient + Source = Dose Source Modeling Patient Modeling Accurate Efficient Simulation pre- and post-processing Radiotherapy analysis

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5 Patient Modeling RTMCNP Preprocessor (DeMarco et al. 1997)

6 CT Information RESCALING Hounsfield Units

7 MCNP Use nested lattice feature Bounding cell Lattice element Bounding cell origin

8 Creating a Lattice Structure z-dimension / voxel height y-dimension / slice thickness x-dimension / voxel width lattice element Cell comprised of repeating identical shapes

9 Creating a Lattice Structure Hounsfield Units to Tissues 1. Air ELEMENT WEIGHT % 2. Lung H (Z=1) 10.3 HU HU C (Z=6) range 10.5 ρ (g/cm 3. Fat ) N (Z=7) O to (Z=8) Water -824 Na (Z=11) to Muscle -674 Mg (Z=12) to Bone -524 P (Z=15) to S (Z=16) Cl (Z=17) to K (Z=19) Ca (Z=20) Alfidi et al. (Radiology, 1975) ICRP 23 (Reference Man, 1975) ICRU 44 (1989)

10 Hounsfield Units to Materials LOOKUP TABLE (DeMarco et al. 1997)

11 Hounsfield Units to Materials LOOKUP TABLE HU=0 HU=0 0, material definition is H ρ=1 0g/cm 3 2 O, 1.0

12 RTMCNP, DeMarco et al. 1. Read CT Geometry Hounsfield Units 2. Sub-sample CT Lattice of 128x128 or 64x64 3. HU s into materials (%Z, ρ) 4. Fill lattice with materials 5. Add modified pulse height tally (MeV / g)

13 Improving CT-Based Model Generation Flexible geometry modifications Sub-sampling Lattice trimming Isocenter positioning Mesh tally definition Pre- and post-processing Material definitions for physical phantoms Normalization criteria Radiotherapy analysis (gamma)

14 Efficiency: Sub-Sampling Sampling the CT 512x x x256 64x64 Fewer surfaces, faster simulations Less patient t resolution

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16 Efficiency: Voxel Trimming ~60% reduction in time required (Speiser et al. 2007)

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18 Original lattice: 512 x 512 x 160 Sub-sampled lattice:256 x 256 x 160 Trimmed lattice: 208 x 132 x 100 Trimmed lattice < 6.6% 6% of the original scan

19 Isocenter / Source Positioning

20 Energy Deposition Mesh Tally Scores energy deposition from all particles Independent of problem geometry MeV / cm 3 / source_particle Rectangular format (RMESH3)

21 Efficient Tally Definition TALLY OUTPUT Uncertainty matrix Energy matrix MeV / cm 3 / sp voxel height PREPROCESSOR voxel width OUTPUT Density matrix slice thickness Filled Lattice 1. ID the sub-volume of interest g / cm 2. Define 3 MESH tally elements as (Mgeometrically V / 3 ) identical ( / to 3 lattice ) elements (d ) 3. Further define MESH to occupy the same Less space MESH = more efficient i tally (MeV / cm 3 ) i,j,k (g / cm 3 ) i,j,k = (dose) i,j,k

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23 Simulation Results Processing Post-processing software linked with voxelized phantom creation Preprocessor generates: MCNP-formatted input file Density matrix CT underlay images MCNP simulation creates: Energy deposition matrix Uncertainty matrix Dose matrix

24 Post Processing Compare simulation results with something Film Measurement Treatment Planning System Calculation Water Phantom profile Gamma Analysis (Low, et al.) ) Usually 2D, can be 3D

25 10x10 cm 2 Dose Uncertainty

26 Normalization This voxel has relatively high low energy deposited? equivalent low density density med-high low dose dose low high uncertainty

27 Normalization Method MESH tally (energy) xyz x,y,z (density) xyz x,y,z (uncertainty) x,y,z (dose) x,y,z Max dose with sufficient uncertainty

28 Source Model Development Develop a clinically accurate Monte Carlo source model of the Novalis Compare Monte Carlo simulation results against Measurements TPS calculations

29 Gamma Analysis Low et al., Med Phys, 1998 Quantitative comparison of two dose distributions Measured dose point (M) Measured Dose Distribution (M) Calculated Dose Overlay Distribution Data Sets (C) Calculated dose point (C) z z Subset of both x x data sets IF the minimum Γ(r m,r c ) > 1, THEN GREEN overlay

30 Comparative Analysis Gamma analysis 2D or 3D capability CT image import and registration for isodose underlay MCNP simulation compared with: Film measurements TPS calculations

31 Voxelized Models of Real Phantoms Source benchmarking Monte Carlo Measurement

32 Lookup Tables MATERIAL & HU RANGE MATERIAL DENSITY (g/cm ) CIRS BONE AVG BONE MUSCLE CIRS PLASTIC WATER WATER FAT CIRS LUNG LUNG AIR AIR

33 Validate Source and Phantom Models Against Measurement Solid water slabs Kodak EDR-2 Film AP fields

34 Source Model vs. Measurements 24x24 mm 2 field Red line: film Black line: MC simulation

35 Source Model vs. Measurements IMRT segment Red line: film Black line: MC simulation

36 Source Model vs. Measurements Composite IMRT field Red line: film Black line: MC simulation

37 Source Model vs. Measurements Solid water slabs Lung slabs

38 Source Model vs. Measurements Composite IMRT field Red line: film Black line: MC simulation

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40 Analysis Monte Carlo Patient Model Monte Carlo Virtual Source Model TPS Calculation Film Measurement Simulation Results Γ analysis (Low et al.)

41 Analysis Monte Carlo Patient Model Monte Carlo Virtual Source Model TPS Calculation Film Measurement Simulation Results

42 Lung Target water lung water lung water

43 Patient Simulations

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46 Conclusions Improvements in CT-based voxelized phantom generation Flexible geometry modifications Sub-sampling Lattice trimming Isocenter positioning Mesh tally definition Pre- and post-processing Radiotherapy analysis (gamma)

47 Conclusions All models are wrong some are useful. -George Box CT-based phantoms can be used for validating radiotherapy source models in preparation for and in addition to investigations. It s easy to make a model but the model needs to be accurate.

48 Ongoing / Future Modeling techniques used to supplement small animal SBRT research Validate brachytherapy treatment planning system for heterogeneous dose calculations

49 Thank You John DeMarco, Ph.D. Adam Kesner, Ph.D.