Improving VMAT dose calculation accuracy and planning quality via a GPU-accelerated Fourier transform dose calculation algorithm

利用GPU加速的傅里叶变换剂量计算算法提高VMAT剂量计算精度和计划质量

阅读:1

Abstract

BACKGROUND: Inverse planning typically utilizes fast, less accurate dose calculation algorithms during the iterative optimization process, thus leading to dose calculation errors (DCEs) and suboptimal plans that often require dose normalization and/or plan re-optimization. PURPOSE: A graphic processing unit (GPU) accelerated Fourier transform dose calculation (FTDC) was recently commissioned at our institution during the Eclipse treatment planning system (Varian Medical Systems) v18.0 upgrade. We hypothesize that FTDC could reduce DCEs and planning failure rates (PFRs) compared to its predecessor, multi-resolution dose calculation (MRDC), while improving efficiency through utilization of GPUs. METHODS: Fifty lung SBRT plans were optimized with MRDC and FTDC dose calculation algorithms. Acuros XB (AXB) was then used for final dose calculations. DCEs for target and organ-at-risk (OAR) were calculated as the percent difference between AXB and dose calculated at the final optimization step. Plan quality was assessed using an in-house planning scorecard where PFRs were calculated as the percentage of plans that had a plan score less than 90% with optimal plans scored at 100%. RESULTS: FTDC showed excellent agreement with AXB in terms of planning target volume (PTV) coverage, as PTV D95% DCE(FTDC) averaged 0.8% ± 0.9%, compared to DCE(MRDC)'s -2.5% ± 3.2%. DCEs for thoracic OARs were reduced with less variation when optimizing with FTDC as compared to MRDC. FTDC had a PFR of 10% (5 out of 50) versus MRDC's 32% (16 out of 50). The subsequent re-optimization rate resulted from a plan normalization of 3% or greater was 4% for FTDC compared to MRDC's 38%. FTDC with GPU acceleration reduced optimization time by 75% on average compared to MRDC without GPU acceleration. CONCLUSIONS: FTDC shows more accurate dose calculation accuracy compared to MRDC. Its use during the optimization process improved planning quality and efficiency assisted with GPUs.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。