GPU-based ultra-fast dose calculation using a finite size pencil beam model
GPU-based ultra-fast dose calculation using a finite size pencil beam model
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DOI：
10.1088/0031-9155/54/20/017
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发表时间：
2009-10-21
影响因子：
3.5
通讯作者：
Jiang, Steve B.
中科院分区：
文献类型：
--
作者：
Gu, Xuejun;Choi, Dongju;Jiang, Steve B.
在线自适应放射治疗（ART）是一个有吸引力的概念，它有望针对患者解剖结构的分次间变异提供最佳治疗。但由于技术限制尚未实现。快速剂量沉积系数计算是调强放射治疗 (IMRT) 计划优化所需的在线计划流程的关键组成部分。计算机图形处理单元 (GPU) 非常适合为剂量计算的数据并行性质提供必需的快速性能。在这项工作中，我们开发了一种基于有限尺寸笔形束（FSPB）算法和GPU并行计算框架的剂量计算引擎。开发的框架可以适应任何 FSPB 模型。我们在水体模和前列腺癌患者的情况下测试我们的实现，这些患者具有不同的子束和体素尺寸。与 2.27 GHz Intel Xeon CPU 相比，使用 NVIDIA Tesla C1060 卡时，所有测试场景均实现了 200 至 400 倍的加速。使用这个新框架计算九视野前列腺 IMRT 计划的剂量沉积系数的计算时间小于 1 秒。这表明基于GPU的FSPB算法非常适合自适应放疗的在线重新规划。
Online adaptive radiation therapy (ART) is an attractive concept that promises the ability to deliver an optimal treatment in response to the inter-fraction variability in patient anatomy. However, it has yet to be realized due to technical limitations. Fast dose deposit coefficient calculation is a critical component of the online planning process that is required for plan optimization of intensity-modulated radiation therapy (IMRT). Computer graphics processing units (GPUs) are well suited to provide the requisite fast performance for the data-parallel nature of dose calculation. In this work, we develop a dose calculation engine based on a finite-size pencil beam (FSPB) algorithm and a GPU parallel computing framework. The developed framework can accommodate any FSPB model. We test our implementation in the case of a water phantom and the case of a prostate cancer patient with varying beamlet and voxel sizes. All testing scenarios achieved speedup ranging from 200 to 400 times when using a NVIDIA Tesla C1060 card in comparison with a 2.27 GHz Intel Xeon CPU. The computational time for calculating dose deposition coefficients for a nine-field prostate IMRT plan with this new framework is less than 1 s. This indicates that the GPU-based FSPB algorithm is well suited for online re-planning for adaptive radiotherapy.