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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Monte Carlo用于放射治疗剂量计算的仿真。

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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：蒙特卡罗（MC）模拟通常被认为是放射疗法中最准确的剂量计算方法。然而，其效率仍然需要改善许多常规临床应用。在本文中，我们展示了我们最近朝着开发图形处理单元（GPU）的MC剂量计算包，GDPM v2.0的进展。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）代码中相同的粒子传输物理学，因此相同的仿真精度。在GPU计算中，线程之间的执行路径的分歧可以显着降低效率。由于光子和电子经过不同的物理并因此获得不同的执行路径，我们使用模拟方案，其中分离光子传输和电子传输以部分地缓解螺纹发散问题。还利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流量的地图和LinaC几何形状，以便GDPM可用于计算用于现实IMRT或VMAT处理计划的剂量分布。我们的GDPM包在幽灵和现实患者案例中进行了准确性和效率测试。在所有情况下，平均相对不确定性小于1％。进行统计T检验并发现CPU与GPU结果之间的剂量差异在高剂量区域的超过96％和97％的整个区域中没有统计学意义。使用NVIDIA TESLA C2050 GPU卡针对2.27GHz Intel Xeon CPU处理器，观察到69.1的加速因子约为87.2。对于现实的ICRT和VMAT计划，MC剂量计算可以在36.1使用GDPM的36.1约39.6秒内完成小于1％的标准偏差。

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