Program Information

Modeling of a Compact Proton Therapy System Using TOPAS Monte Carlo Code

M Prusator*, S Ahmad, Y Chen, Oklahoma Univ. Health Science Ctr., Oklahoma City, OK

SU-E-T-526 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Purpose: To demonstrate the potential of using a newly innovated Monte Carlo platform TOPAS based on GEANT4 toolkits for proton therapy simulation is the primary purpose of this study.

Methods: Based on preliminary geometry and material information provided by Mevion Medical system for a compact 250 MeV proton therapy machine planned to be delivered at our institution,
a scattering foil, a secondary scatter filter, a range modulator wheel and a treatment nozzle were created using TOPAS. Beams of 250 MeV incident protons with energy spread of 0.75 MeV, shaped as point sources were used to interact in the phantom for the simulation. The beam angular spread in the X and Y directions were 0.0032 radians. Six hundred scoring detectors each with 1 mm thickness were placed in a water phantom (15 cm x 15 cm x 60 cm) created in the beam path. A default modular physics list was used in the simulation that included standard electromagnetic, nuclear elastic (G4Elastic) and inelastic (binary cascade) processes for protons and all secondary particles. Range modulator wheel in the simulation was rotating with a constant speed (using time feature function) to produce spread out Bragg peak (SOBP). Total 1 million incident particles were used in the simulation.

Results: A complete model of beam components from a compact proton therapy system planned to be used in our facility has been achieved. A normalized single Bragg peak and a modulated spread out Bragg peak of 10 cm width for 250 MeV incident proton beam generated in this study will be presented.

Conclusion: A compact double scattered proton therapy system was effectively modeled with TOPAS where the build-in features dedicated for particle therapy were used. Further validation on beam parameters and physics settings are needed before utilizing this to patient specific applications.

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