Real-time reconstruction and visualization system for 3D dose distribution in particle radiotherapy based on GPU acceleration
收藏中国科学数据2026-04-20 更新2026-04-25 收录
下载链接:
https://www.sciengine.com/AA/doi/10.3724/j.0253-3219.2026.hjs.49.250273
下载链接
链接失效反馈官方服务:
资源简介:
BackgroundIn particle therapy, real-time quality control and monitoring of three-dimensional (3D) dose distribution remains a significant technical challenge.PurposeThis study aims to develop a Graphics Processing Unit (GPU)-accelerated system for real-time 3D dose reconstruction and visualization of proton intensity-modulated radiotherapy.MethodsThe live data streams from a dose ionization chamber, a position ionization chamber, and the scanning control system with patient Computed Tomography (CT) images, treatment-planning data, and a precomputed beamlet matrix dijk for various positioning-error scenarios were integrated in the system. By leveraging Compute Unified Device Architecture (CUDA) acceleration, dynamic superposition of dose distributions with high efficiency was achieved. The software was implemented in a Python framework that handled data fusion and provided an interactive graphical user interface, and supported multidimensional visualization outputs such as dose images and Dose Volume Histogram (DVH). Finally, a computer equipped with an Advanced Micro Devices, Inc., (AMD) Ryzen75800 Central Processing Unit (CPU) and an NVIDIA GeForce 3060Ti GPU is used to test a TG119 abdominal single-field proton Intensity Modulated Proton Therapy (IMPT) plan consisting of 16 layers and 1 672 beam spots.ResultsTest results show that the system completes dose reconstruction and visualization for this plan in 103.7 s—faster than the plan's estimated proton delivery time of 104.21 s. In addition, for a clinical nasopharyngeal dual-field proton IMPT plan with 1 345 beam spots, the system completes dose reconstruction and visualization in 82.33 s, which is also shorter than the estimated delivery time of 83.01 s, demonstrating both real-time capability and clinical applicability.ConclusionsThis system proposed in this study provides real-time decision support for in-treatment target dose verification, dynamic organ-at-risk assessment, and adaptive adjustment of irradiation parameters, offering technical assurance to enhance quality control and clinical safety in particle therapy.
创建时间:
2026-04-20



