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Optimization of GATE and PHITS Monte Carlo Code Parameters for Uniform Scanning Proton Beam Based On Simulation with FLUKA General-Purpose Code

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K Kurosu

K Kurosu1,2*, M Takashina2 , M Koizumi2 , I Das3 , V Moskvin3 , (1) Department of Radiation Oncology, Osaka University Graduate School of Medicine, Osaka, Japan, (2) Department of Medical Physics & Engineering, Osaka University Graduate School of Medicine, Osaka, Japan, (3) Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, USA,


SU-E-T-254 Sunday 3:00PM - 6:00PM Room: Exhibit Hall

Monte Carlo codes are becoming important tools for proton beam dosimetry. However, the relationships between the customizing parameters and percentage depth dose (PDD) of GATE and PHITS codes have not been reported which are studied for PDD and proton range compared to the FLUKA code and the experimental data.

The beam delivery system of the Indiana University Health Proton Therapy Center was modeled for the uniform scanning beam in FLUKA and transferred identically into GATE and PHITS. This computational model was built from the blue print and validated with the commissioning data. Three parameters evaluated are the maximum step size, cut off energy and physical and transport model. The dependence of the PDDs on the customizing parameters was compared with the published results of previous studies.

The optimal parameters for the simulation of the whole beam delivery system were defined by referring to the calculation results obtained with each parameter. Although the PDDs from FLUKA and the experimental data show a good agreement, those of GATE and PHITS obtained with our optimal parameters show a minor discrepancy. The measured proton range R90 was 269.37 mm, compared to the calculated range of 269.63 mm, 268.96 mm, and 270.85 mm with FLUKA, GATE and PHITS, respectively.

We evaluated the dependence of the results for PDDs obtained with GATE and PHITS Monte Carlo general-purpose codes on the customizing parameters by using the whole computational model of the treatment nozzle. The optimal parameters for the simulation were then defined by referring to the calculation results. The physical model, particle transport mechanics and the different geometry-based descriptions need accurate customization in three simulation codes to agree with experimental data for artifact-free Monte Carlo simulation.

Funding Support, Disclosures, and Conflict of Interest: This study was supported by Grants-in Aid for Cancer Research (H22-3rd Term Cancer Control-General-043) from the Ministry of Health, Labor and Welfare of Japan, Grants-in-Aid for Scientific Research (No. 23791419), and JSPS Core-to-Core program (No. 23003). The authors have no conflict of interest.

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