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首页> 外文期刊>Physics in medicine and biology. >GPU-based fast Monte Carlo simulation for radiotherapy dose calculation.
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GPU-based fast Monte Carlo simulation for radiotherapy dose calculation.

机译：基于GPU的快速蒙特卡洛模拟，用于放射治疗剂量计算。

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摘要

Monte Carlo (MC) simulation is commonly considered to be the most accurate dose calculation method in radiotherapy. However, its efficiency still requires improvement for many routine clinical applications. In this paper, we present our recent progress toward the development of a graphics processing unit (GPU)-based MC dose calculation package, gDPM v2.0. It utilizes the parallel computation ability of a GPU to achieve high efficiency, while maintaining the same particle transport physics as in the original dose planning method (DPM) code and hence the same level of simulation accuracy. In GPU computing, divergence of execution paths between threads can considerably reduce the efficiency. Since photons and electrons undergo different physics and hence attain different execution paths, we use a simulation scheme where photon transport and electron transport are separated to partially relieve the thread divergence issue. A high-performance random number generator and a hardware linear interpolation are also utilized. We have also developed various components to handle the fluence map and linac geometry, so that gDPM can be used to compute dose distributions for realistic IMRT or VMAT treatment plans. Our gDPM package is tested for its accuracy and efficiency in both phantoms and realistic patient cases. In all cases, the average relative uncertainties are less than 1%. A statistical t-test is performed and the dose difference between the CPU and the GPU results is not found to be statistically significant in over 96% of the high dose region and over 97% of the entire region. Speed-up factors of 69.1 approximately 87.2 have been observed using an NVIDIA Tesla C2050 GPU card against a 2.27 GHz Intel Xeon CPU processor. For realistic IMRT and VMAT plans, MC dose calculation can be completed with less than 1% standard deviation in 36.1 approximately 39.6 s using gDPM.
机译：蒙特卡洛（MC）模拟通常被认为是放射治疗中最准确的剂量计算方法。但是，对于许多常规临床应用，其效率仍然需要改进。在本文中，我们介绍了基于图形处理单元（GPU）的MC剂量计算软件包gDPM v2.0的开发最新进展。它利用GPU的并行计算能力来实现高效率，同时保持与原始剂量计划方法（DPM）代码相同的粒子传输物理特性，因此具有相同水平的仿真精度。在GPU计算中，线程之间执行路径的差异会大大降低效率。由于光子和电子经历不同的物理过程，因此获得不同的执行路径，因此我们使用一种模拟方案，其中将光子传输和电子传输分开以部分缓解线散度问题。还使用了高性能随机数发生器和硬件线性插值。我们还开发了各种组件来处理注量图和直线加速器几何形状，因此gDPM可用于计算实际IMRT或VMAT治疗计划的剂量分布。我们的gDPM软件包在幻像和实际患者案例中均经过了准确性和效率测试。在所有情况下，平均相对不确定度均小于1％。进行了统计t检验，并且在超过96％的高剂量区域和超过97％的整个区域中，未发现CPU和GPU结果之间的剂量差异具有统计学意义。使用NVIDIA Tesla C2050 GPU卡与2.27 GHz Intel Xeon CPU处理器相比，观察到加速因子为69.1约87.2。对于现实的IMRT和VMAT计划，使用gDPM可以在36.1约39.6 s内以不到1％的标准偏差完成MC剂量计算。

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