实时硼剂量测量是制约硼中子俘获治疗（BNCT）发展的难题之一，利用中子与B-10俘获产生的瞬发γ射线推算硼剂量是目前最有潜力实现在线硼剂量测量的技术手段之一。然而这一技术手段的实现必须寻求更高探测效率、更高空间分辨率的探测技术和更快速重建能力的数据分析技术。基于前期研究基础，本项目创新提出“单层康普顿相机+人工智能快速重建算法”的技术思路，以期实现0.478 MeV瞬发γ的实时精准测量，进而得到实时硼剂量分布。针对此目标，研究基于条形阵列CdZnTe的单层康普顿相机在n/γ辐射场探测0.478 MeV瞬发γ射线的结构性能优化以提高探测效率；结合FPGA电路获取γ射线三维位置信息提升单层康普顿相机空间分辨率；发展基于人工智能算法的优化重建技术实现硼剂量实时快速重建；结合真实束流环境评估在线硼剂量测量的稳定性。本项目研究将有助于进一步推动BNCT实时剂量精确测量技术的发展。

Real-time boron dose measurement is one of the challenges that restricts the development of boron neutron capture therapy (BNCT). Using the prompt γ rays from the neutron boron capture reaction to estimate the boron dose is one of the most promising techniques for online boron dose measurement. However, the implementation of this technology must seek for detection techniques with higher detection efficiency, higher spatial resolution, and faster reconstruction algorithms. On the basis of previous researches, this project proposes the idea of ​“single-stage Compton camera + artificial intelligence fast reconstruction algorithm”, for achieving real-time accurate measurement of 0.478 MeV prompt γ rays, which thereby can be used to obtain real-time boron dose distribution. To realize the specific purpose, the single-stage Compton camera based on drift strip CdZnTe detector will be used to detect the 0.478 MeV prompt gamma in the complex n/γ radiation field to improve the detection efficiency. The FPGA circuit will be used to obtain the three-dimensional position information to improve the spatial resolution. And optimized reconstruction algorithm based on artificial intelligence will be developed to achieve real-time rapid reconstruction of boron dose. Furthermore, the accuracy and robustness of the method will be evaluated in the real BNCT clinical environment. This project will help to further promote the development of real-time dose measurement technology for BNCT.