A physically constrained Monte Carlo-Neural Network coupling algorithm for BNCT dose calculation.

Journal: Medical physics
PMID: 38299670

Abstract

BACKGROUND: In boron neutron capture therapy (BNCT)-a form of binary radiotherapy-the primary challenge in treatment planning systems for dose calculations arises from the time-consuming nature of the Monte Carlo (MC) method. Recent progress, including the use of neural networks (NN), has been made to accelerate BNCT dose calculations. However, this approach may result in significant dose errors in both the tumor and the skin, with the latter being a critical organ in BNCT. Furthermore, owing to the lack of physical processes in purely NN-based approaches, their reliability for clinical dose calculations in BNCT is questionable.

Authors

  • Yongquan Wang
    Department of Urology, Southwest Hospital, Third Military Medical University (Army Medical University), Chongqing, 400038, China. wyq@tmmu.edu.cn.
  • Junliang Du
    School of Business, Jiangnan University, Wuxi, 214122, Jiangsu, China.
  • Huan Lin
    Department of Radiology, Zhujiang Hospital of Southern Medical University, No. 253, Gong Ye Da Dao Zhong, Guangzhou, Guangdong, 510280, People's Republic of China.
  • Xingcai Guan
    School of Nuclear Science and Technology, Lanzhou University, Lanzhou, China.
  • Lu Zhang
    Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX, United States.
  • Jinyang Li
    Engineering College, Heilongjiang Bayi Agricultural University, Daqing 163319, China.
  • Long Gu
    School of Nuclear Science and Technology, Lanzhou University, Lanzhou, China.

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