representing range compensators in the topas monte carlo
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Representing Range Compensators in the TOPAS Monte Carlo System Forrest Iandola, Jan Schuemann, Jungwook Shin, Bruce Faddegon, Harald Paganetti, and Joseph Perl SLAC National Accelerator Laboratory University of Illinois at Urbana-Champaign


  1. Representing Range Compensators in the TOPAS Monte Carlo System Forrest Iandola, Jan Schuemann, Jungwook Shin, Bruce Faddegon, Harald Paganetti, and Joseph Perl SLAC National Accelerator Laboratory University of Illinois at Urbana-Champaign Massachusetts General Hospital & Harvard Medical School UCSF Department of Radiation Oncology

  2. Overview • Introduction to Tool for Particle Simulation (TOPAS) • Range compensator overview • Boolean Solid geometry • Modeling compensators with Boolean Solids • Approximation using Hexagonal Prisms for faster performance • Comparison of Boolean Solids and Hexagonal Prisms – Performance results (computation time) – Accuracy Forrest Iandola 2 Modeling Range Compensators

  3. Introduction to TOPAS TOPAS (Tool for Particle Simulation) • TOPAS aims at making proton Monte Carlo particle transport simulation easier to use • User can easily customize beamline for specific treatment facilities • TOPAS uses Geant4 for the underlying physics processes Forrest Iandola 3 Modeling Range Compensators

  4. Introduction to TOPAS TOPAS (Tool for Particle Simulation) • TOPAS provides numerous pre-built and customizable components. For example: – Propeller wheel for double scattering – Ion chamber – Range compensators Forrest Iandola 4 Modeling Range Compensators

  5. Overview of Range Compensators • Range compensator produces a patient-specific energy spread • Often designed in treatment planning software – Varian Eclipse – Elekta XiO • Construction: drill a number of holes out of a cylinder of lucite • Each drill hole may have a unique depth Forrest Iandola 5 Modeling Range Compensators

  6. Boolean Solids • Geant4 supports boolean solid combinatorial geometry – Subtraction solids – Union solids • It � s as simple as newSolid = Solid1 union Solid2 or, newSolid = Solid1 minus Solid2 • Overlap among boolean solids is acceptable Forrest Iandola 6 Modeling Range Compensators

  7. Compensator with Union Solids Forrest Iandola 7 Modeling Range Compensators

  8. Compensator with Union Solids Compensator comprised of a bigCylinder with n holes unioned: newSolid_1 = smallCylinder_1 union smallCylinder_2 newSolid_2 = newSolid_1 union smallCylinder_3 … newSolid_(n-1) = newSolid_(n-2) union smallCylinder_(n-1) Compensator = bigCylinder minus newSolid_(n-1) Forrest Iandola 8 Modeling Range Compensators

  9. Approximation for Performance Gains • Goal: reduce computation time – Want to exploit Geant4’s navigation optimizations; this requires solids not to overlap • Solution: Approximate the drill holes with hexagonal prisms – Easy to “nest” hexagons without overlap Forrest Iandola 9 Modeling Range Compensators

  10. Approximation for Performance Gains Union Solids Hexagonal Prisms Forrest Iandola 10 Modeling Range Compensators

  11. Performance results • Fixed number of particles; vary the number of drill holes • With hexagonal prisms, navigation only looks at nearby boundaries in geometry • With UnionSolids (boolean solids), navigation system traverses entire set of unioned cylinders System specifications • 2.6 GhZ AMD Opteron • Used one core • 8GB RAM Forrest Iandola 11 Modeling Range Compensators

  12. Accuracy results Simulation setup: • Real compensator from a treatment – Drill hole size: 0.475 cm • 200 million protons • Simulated in MGH FHBPTC beamline – 169.23 MeV • Scored inside a volume of water – Water is placed 2cm beyond end of beamline Forrest Iandola 12 Modeling Range Compensators

  13. Accuracy results UnionSolids vs. Hexagonal Prisms Simulation setup: • Real compensator from a treatment • 200 million protons • Simulated in MGH FHBPTC beamline • Scored inside a volume of water • Results: within 3 percent difference Forrest Iandola 13 Modeling Range Compensators

  14. Conclusions • Geant4 UnionSolids enable a precise model of patient-specific range compensators • Approximation with Hexagonal Prisms provides significant performance gains • The work discussed in this talk is implemented in Tool for Particle Simulation (TOPAS) Forrest Iandola 14 Modeling Range Compensators

  15. Acknowledgements • United States National Institutes of Health • The TOPAS team (my co-authors) • Geant4 developers and architects: – Makoto Asai (SLAC) – Gabriele Cosmo (CERN) Contact: forrest@slac.stanford.edu Forrest Iandola 15 Modeling Range Compensators

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