Room: AAPM ePoster Library
Purpose: Synchrotron-based proton therapy systems can produce Gaussian beams with standard deviations less than 1 mm, known as mini beams. Fast Monte Carlo (MC) codes leverage modern computational hardware architecture and shortcuts in particle transport modeling to reduce computation time. The purpose of this study is to explore the applicability of a recently developed MCsquare (MCS) fast MC code for standard and mini proton beams as a secondary dose computation engine.
Methods: We commissioned the MCS for a spot-scanning proton therapy system (PROBEAT-V, Hitachi) at energies ranging from 69.4 MeV to 221.3 MeV with standard- and mini-beam options. Commissioning data were generated by a benchmarked TOPAS model and were previously used to commission the clinical treatment planning system (Eclipse, Varian Medical Systems). The absorbed dose was calculated from treatment plans comprising standard or mini beams with the MCS and TOPAS models and measured in a water-box phantom according to the TRS 398 protocol for reference fields. The MCS was tested for potential use at a high-performance computing facility via Amdahl’s Law.
Results: The parameters of the MCS source physical model agreed with those from the TOPAS phase space files for the nozzle output. Therapeutic ranges (R90) of individual spot beams computed with MCS and TOPAS agreed with measurements within 0.1 mm. The absorbed dose from reference fields agreed between two MC codes and with measurements for both standard and mini beams within 0.7%. The test of MCS computation speed showed a high level of code parallelization and required 0.34% of the time of TOPAS computations.
Conclusion: MCsquare agreed with the output of a TOPAS-based secondary dose computation engine and with measurements. MCS is an attractive candidate for fast secondary dose calculations of proton therapy treatment plans using synchrotron-based standard and mini beams.
Not Applicable / None Entered.
TH- External Beam- Particle/high LET therapy: Proton therapy – computational dosimetry-Monte Carlo