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Evaluation of a GPU-Based Fast Monte Carlo Code for Proton Therapy Biological Optimization

R Taleei

R Taleei1*, C Peeler2 , N Qin3 , S Jiang4 , X Jia5 , (1) UT Southwestern Medical Center, Dallas, TX, (2) UT MD Anderson Cancer Center, Houston, TX, (3) UT Southwestern Medical Center, Dallas, TX, (4) UT Southwestern Medical Center, Dallas, TX, (5) The University of Texas Southwestern Medical Ctr, Dallas, TX


SU-F-T-193 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall

Purpose: Biological treatment plan optimization is of great interest for proton therapy. It requires extensive Monte Carlo (MC) simulations to compute physical dose and biological quantities. Recently, a gPMC package was developed for rapid MC dose calculations on a GPU platform. This work investigated its suitability for proton therapy biological optimization in terms of accuracy and efficiency.

Methods: We performed simulations of a proton pencil beam with energies of 75, 150 and 225 MeV in a homogeneous water phantom using gPMC and FLUKA. Physical dose and energy spectra for each ion type on the central beam axis were scored. Relative Biological Effectiveness (RBE) was calculated using repair-misrepair-fixation model. Microdosimetry calculations were performed using Monte Carlo Damage Simulation (MCDS).

Results: Ranges computed by the two codes agreed within 1 mm. Physical dose difference was less than 2.5 % at the Bragg peak. RBE-weighted dose agreed within 5 % at the Bragg peak. Differences in microdosimetric quantities such as dose average lineal energy transfer and specific energy were < 10%. The simulation time per source particle with FLUKA was 0.0018 sec, while gPMC was ~ 600 times faster.

Conclusion: Physical dose computed by FLUKA and gPMC were in a good agreement. The RBE differences along the central axis were small, and RBE-weighted dose difference was found to be acceptable. The combined accuracy and efficiency makes gPMC suitable for proton therapy biological optimization.

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