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基于 GPU 的相位空间源蒙特卡罗放射治疗剂量计算。

GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources.

机构信息

Department of Physics and Astronomy, University of Victoria, PO Box 3055, STN CSC, Victoria, British Columbia V8W 3P6, Canada.

出版信息

Phys Med Biol. 2013 Jun 21;58(12):4341-56. doi: 10.1088/0031-9155/58/12/4341. Epub 2013 Jun 4.

Abstract

A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm(2) in water resulted in gamma passing rates of 99.96%, 99.92% and 98.66%, respectively. Relative output factors agreed within 1%. An intensity modulated radiation therapy patient plan using the PSL method resulted in a passing rate of 97%, and was calculated in 50 s (per GPU) compared to 8.4 h (per CPU) for BEAMnrc/DOSXYZnrc.

摘要

一种新的相空间源实现已被设计用于基于图形处理单元(GPU)的蒙特卡罗剂量计算引擎。在剂量计算中,要对临床射束进行建模,除了完整模拟直线加速器机头外,使用相空间源是最准确的方法。然而,在基于 GPU 的蒙特卡罗剂量计算中,由于计算效率非常高,读取和处理大型相空间文件所需的时间与粒子输运时间相当。此外,由于 GPU 硬件的并行化特性,同时传输相同类型和相似能量但空间上分离的粒子以提高效率是至关重要的。我们提出了三种相空间实现方法,这些方法已被整合到最新版本的基于 GPU 的蒙特卡罗放射治疗剂量计算包 gDPM v3.0 中。第一种方法是顺序读取来自患者相关相空间的粒子,并根据粒子类型和能量对其进行实时排序。第二种方法通过添加简单的次级准直器模型和通量图实现来补充这一点,以便使用患者独立的相空间源。最后,作为第三种方法(称为相空间束,或 PSL 方法),我们引入了一种新颖的源实现方法,该方法利用按粒子类型、能量和位置排序的预处理患者独立相空间。位于包含治疗场的矩形感兴趣区域之外的位置箱将被忽略,这大大减少了模拟时间,对最终剂量分布几乎没有影响。这三种方法都通过与 BEAMnrc/DOSXYZnrc 的绝对剂量进行了验证,并通过伽马指数测试(10%等剂量线以上 2%/2 毫米)进行了比较。结果发现,PSL 方法在准确性和效率之间具有最佳的平衡,因此在 gDPM v3.0 中被用作默认方法。使用 PSL 方法,在水中的 4×4、10×10 和 30×30cm2 的开放野分别产生了 99.96%、99.92%和 98.66%的伽马通过率。相对输出因子的差异在 1%以内。使用 PSL 方法的调强放射治疗患者计划产生了 97%的通过率,而使用 PSL 方法计算需要 50 秒(每个 GPU),而使用 BEAMnrc/DOSXYZnrc 计算则需要 8.4 小时(每个 CPU)。

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