Research on hybrid methods for variance reduction in Monte Carlo dose calculation of BNCT

Boron Neutron Capture Therapy (BNCT) is a neutron-targeted radiotherapy method for treating cancer. Treatment planning requires dose calculations based on patients’ models and neutron sources. Most BNCT treatment planning systems utilize dose solvers based on the Monte Carlo method. The Monte Carlo method is a probabilistic statistical method, and thus the statistical variance exists. In BNCT dose calculations, it is necessary to obtain calculation results with as small variance as possible within a limited amount of time in order to develop better treatment plans and ensure the safety and effectiveness of the treatment process. Therefore, in this study, the Monte Carlo code NECP-MCX was combined with a deterministic code, and the classic hybrid method, the Consistent Adjoint Driven Importance Sampling (CADIS) was improved to meet the specific requirements of BNCT calculations. To evaluate the effectiveness of the improved BNCT-based Monte-Carlo–deterministic coupling variance reduction method, dose-depth curves and Dose and Volume Histogram (DVH) were calculated using a realistic head model. These results were then compared with those obtained from direct calculations. The preliminary findings demonstrate that the proposed method is effective in reducing the relative standard deviation (RSD) and enhancing the computational accuracy in BNCT simulations.