Double-layered beam shaping assembly design based on intelligent optimization method coupling neural network and genetic algorithm for BNCT

Abstract

The beam shaping assembly (BSA) plays a crucial role in the facility of accelerator-based boron neutron capture therapy (AB-BNCT). The quality of the neutron beam utilized for treatment is directly influenced by the design of the BSA. However, conventional step-by-step optimization approaches often encounter challenges in achieving the global optimal solution, as they tend to converge towards local optima. To address this issue, this study proposed an intelligent optimization method that combines neural network and genetic algorithm. The proposed method was applied to optimize a double-layered BSA based on the neutron source resulting from a lithium target bombarding by a 2.8 MeV, 20 mA proton beam. The obtained optimal BSA solution parameters well met the IAEA-TECDOC-1223 report, while also exhibiting significantly higher epithermal neutron flux compared to alternative BSA designs. The performance of the epithermal neutron beam was assessed by calculating the dose distribution and clinical parameters in the Snyder head phantom. The findings suggest that this beam exhibits promising therapeutic potential for treating tumors.