Work

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

Year: 2026

Type: article

Abstract: : 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.

Source: Nuclear Engineering and Technology

DOI: 10.1016/j.net.2026.104254

Authors: Bojin Zhao, Qi Zheng, Qingming He, Liangzhi Cao, Tiejun Zu, Yongping Wang

Institutions: First Affiliated Hospital of Xi'an Jiaotong University, Xi'an Jiaotong University

Language: English

Topic: Boron Compounds in Chemistry

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $200