Department of Radiation Oncology, University of California San Diego, La Jolla, CA 92037-0843, USA.
Phys Med Biol. 2010 Jun 7;55(11):3077-86. doi: 10.1088/0031-9155/55/11/006. Epub 2010 May 12.
Monte Carlo simulation is the most accurate method for absorbed dose calculations in radiotherapy. Its efficiency still requires improvement for routine clinical applications, especially for online adaptive radiotherapy. In this paper, we report our recent development on a GPU-based Monte Carlo dose calculation code for coupled electron-photon transport. We have implemented the dose planning method (DPM) Monte Carlo dose calculation package (Sempau et al 2000 Phys. Med. Biol. 45 2263-91) on the GPU architecture under the CUDA platform. The implementation has been tested with respect to the original sequential DPM code on the CPU in phantoms with water-lung-water or water-bone-water slab geometry. A 20 MeV mono-energetic electron point source or a 6 MV photon point source is used in our validation. The results demonstrate adequate accuracy of our GPU implementation for both electron and photon beams in the radiotherapy energy range. Speed-up factors of about 5.0-6.6 times have been observed, using an NVIDIA Tesla C1060 GPU card against a 2.27 GHz Intel Xeon CPU processor.
蒙特卡罗模拟是放射治疗中吸收剂量计算最准确的方法。但其效率仍然需要提高，特别是对于在线自适应放射治疗。在本文中，我们报告了我们最近在基于 GPU 的电子-光子耦合输运蒙特卡罗剂量计算代码方面的进展。我们已经在 CUDA 平台上的 GPU 架构上实现了剂量规划方法（DPM）蒙特卡罗剂量计算程序包（Sempau 等人，2000 年，《物理医学与生物学》，第 45 卷，第 2263-2291 页）。我们已经在水-肺-水或水-骨-水平板几何形状的体模中，针对原始的顺序 DPM 代码，对其进行了测试。在验证中，我们使用了 20 MeV 单能电子点源或 6 MV 光子点源。结果表明，我们的 GPU 实现对于放射治疗能区的电子和光子束具有足够的准确性。使用 NVIDIA Tesla C1060 GPU 卡与 2.27GHz Intel Xeon CPU 处理器相比，观察到的加速因子约为 5.0-6.6 倍。
