Clinical implementation of a GPU-based simplified Monte Carlo method for a treatment planning system of proton beam therapy
Clinical implementation of a GPU-based simplified Monte Carlo method for a treatment planning system of proton beam therapy
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DOI：
10.1088/0031-9155/56/22/n03
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发表时间：
2011-11-21
影响因子：
3.5
通讯作者：
Suzuki, T.
中科院分区：
文献类型：
--
作者：
Kohno, R.;Hotta, K.;Suzuki, T.
在NVIDIA开发的计算机统一设备架构平台上，在图形处理单元（GPU）架构上实现了简化的蒙特卡罗（SMC）方法。基于gpu的SMC临床应用于4例头颈癌、肺癌或前列腺癌患者。在计算时间和误差方面与传统的基于cpu的SMC进行了比较。在基于cpu和gpu的SMC计算中，计算剂量在规划目标体积区域的估计平均统计误差在0.5% rms以内。基于gpu和cpu的SMCs计算的剂量分布相似，但在统计误差范围内。基于gpu的SMC性能比基于cpu的SMC快12.30-16.00倍。临床病例采用基于gpu的SMC计算每束排列时间为9 ~ 67 s。结果表明基于gpu的SMC成功应用于临床质子治疗计划。
We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU-and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU-and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.