Evaluation of dose calculation method with a combination of Monte Carlo method and removal-diffusion equation in heterogeneous geometry for boron neutron capture therapy

Mai Nojiri, Takushi Takata, Akinori Sasaki, Yuki Tamari, Nishiki Matsubayashi, Naonori Hu, Yoshinori Sakurai, Minoru Suzuki, Hiroki Tanaka

Research output: Contribution to journalArticlepeer-review

Abstract

Clinical research in boron neutron capture therapy (BNCT) has been conducted worldwide. Currently, the Monte Carlo (MC) method is the only dose calculation algorithm implemented in the treatment planning system for the clinical treatment of BNCT. We previously developed the MC-RD calculation method, which combines the MC method and the removal-diffusion (RD) equation, for fast dose calculation in BNCT. This study aimed to verify the partial-MC-RD calculation method, which utilizes the MC-RD calculation method for a portion of the entire neutron energy range, in terms of calculation accuracy and time as the dose calculation method. We applied the partial-MC-RD calculation method to calculate the total dose for head phantom, comprising soft tissue, brain tissue, and bone. The calculation time and accuracy were evaluated based on the full-MC method. Our accuracy verifications indicated that the partial-MC-RD calculation was mostly comparable with full-MC calculation in the accuracy. However, the assumptions and approximation used in the RD calculation mainly occurred the discrepancy from the full-MC calculation result. Additionally, the partial-MC-RD calculation reduced the time required to approximately 45% for the irradiation to the top and cheek region of head phantom, compared to the full-MC calculation. In conclusion, the MC-RD calculation method can be the basis of a fast dose calculation method in BNCT.

Original languageEnglish
Article number025045
JournalBiomedical Physics and Engineering Express
Volume11
Issue number2
DOIs
Publication statusPublished - 31-03-2025
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • General Nursing

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