Department of Radiation Oncology, University of California San Diego, La Jolla, CA 92037-0843, USA.
Phys Med Biol. 2009 Oct 21;54(20):6287-97. doi: 10.1088/0031-9155/54/20/017. Epub 2009 Oct 1.
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.
在线自适应放射治疗(ART)是一个很有吸引力的概念,它有望根据患者解剖结构的分次间变化,提供最佳的治疗能力。然而,由于技术限制,这一概念尚未实现。快速剂量沉积系数计算是在线计划过程的一个关键组成部分,对于强度调制放射治疗(IMRT)的计划优化是必需的。计算机图形处理单元(GPU)非常适合提供所需的快速性能,以适应剂量计算的数据并行性质。在这项工作中,我们开发了一个基于有限大小铅笔束(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。我们在水模和前列腺癌患者的情况下测试了我们的实现,改变了射束和体素的大小。在使用 NVIDIA Tesla C1060 卡与 2.27 GHz Intel Xeon CPU 相比的所有测试场景中,速度都提高了 200 到 400 倍。使用这个新框架计算九野前列腺 IMRT 计划的剂量沉积系数的计算时间不到 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计划。