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

摘要: Background: Boron Neutron Capture Therapy (BNCT) is a neutron-targeted radiotherapy method for treating cancer. Before radiation therapy, various dose parameters within the patient's body need to be calculated using a neutron photon dose solver based on parameters such as the patient's geometric model and neutron source terms, in order to develop an appropriate treatment plan. Purpose: Due to the complexity of neutron-material interactions, 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. Methods: Therefore, in this study, the Monte Carlo code NECP-MCX was combined with a deterministic code, and the classic hybrid method, the CADIS method was improved to meet the specific requirements of BNCT calculations. Results: 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. Conclusions: 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.