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基于 GPU 的放射治疗剂量计算快速蒙特卡罗模拟。

GPU-based fast Monte Carlo simulation for radiotherapy dose calculation.

机构信息

Center for Advanced Radiotherapy Technologies and Department of Radiation Oncology, University of California San Diego, La Jolla, CA 92037-0843, USA.

出版信息

Phys Med Biol. 2011 Nov 21;56(22):7017-31. doi: 10.1088/0031-9155/56/22/002. Epub 2011 Oct 21.

Abstract

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 ∼ 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 ∼ 39.6 s using gDPM.

摘要

蒙特卡罗(MC)模拟通常被认为是放射治疗中最准确的剂量计算方法。然而,对于许多常规的临床应用,其效率仍然需要提高。在本文中,我们介绍了我们在开发基于图形处理单元(GPU)的 MC 剂量计算包方面的最新进展,即 gDPM v2.0。它利用 GPU 的并行计算能力实现高效率,同时保持与原始剂量规划方法(DPM)代码相同的粒子输运物理,从而保持相同的模拟精度。在 GPU 计算中,线程之间的执行路径发散会大大降低效率。由于光子和电子经历不同的物理过程,因此会有不同的执行路径,我们使用一种模拟方案,其中将光子传输和电子传输分开,以部分缓解线程发散问题。还利用了高性能随机数生成器和硬件线性插值。我们还开发了各种组件来处理通量图和直线加速器几何形状,以便 gDPM 可以用于计算现实的 IMRT 或 VMAT 治疗计划的剂量分布。我们的 gDPM 包在体模和真实患者病例中都经过了准确性和效率的测试。在所有情况下,平均相对不确定度都小于 1%。进行了统计学 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,CPU 和 GPU 结果之间的剂量差异没有发现具有统计学意义。使用 NVIDIA Tesla C2050 GPU 卡相对于 2.27GHz Intel Xeon CPU 处理器,观察到的加速因子为 69.1∼87.2。对于现实的 IMRT 和 VMAT 计划,使用 gDPM 可以在 36.1∼39.6s 内以小于 1%的标准偏差完成 MC 剂量计算。

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