Ouellet Samuel, Lemaréchal Yannick, Berumen-Murillo Francisco, Lavallée Marie-Claude, Vigneault Éric, Martin André-Guy, Foster William, Thomson Rowan M, Després Philippe, Beaulieu Luc
Département de physique, de génie physique et d'optique, et Centre de recherche sur le cancer, Université Laval, Québec, Québec, Canada.
Service de radio-oncologie et Axe Oncologie du CRCHU de Québec, CHU de Québec-Université Laval, Quebec, QC, Canada.
Phys Med Biol. 2023 Nov 20;68(23). doi: 10.1088/1361-6560/ad058b.
Monte Carlo (MC) dose datasets are valuable for large-scale dosimetric studies. This work aims to build and validate a DICOM-compliant automated MC dose recalculation pipeline with an application to the production of I-125 low dose-rate prostate brachytherapy MC datasets. Built as a self-contained application, the recalculation pipeline ingested clinical DICOM-RT studies, reproduced the treatment into the Monte Carlo simulation, and outputted a traceable and durable dose distribution in the DICOM dose format. MC simulations with TG43-equivalent conditions using both TOPAS andegs_brachyMC codes were compared to TG43 calculations to validate the pipeline. The consistency of the pipeline when generating TG186 simulations was measured by comparing simulations made with both MC codes. Finally,egs_brachysimulations were run on a 240-patient cohort to simulate a large-scale application of the pipeline. Compared to line source TG43 calculations, simulations with both MC codes had more than 90% of voxels with a global difference under ±1%. Differences of 2.1% and less were seen in dosimetric indices when comparing TG186 simulations from both MC codes. The large-scale comparison ofegs_brachysimulations with treatment planning system dose calculation seen the same dose overestimation of TG43 calculations showed in previous studies. The MC dose recalculation pipeline built and validated against TG43 calculations in this work efficiently produced durable MC dose datasets. Since the dataset could reproduce previous dosimetric studies within 15 h at a rate of 20 cases per 25 min, the pipeline is a promising tool for future large-scale dosimetric studies.
蒙特卡罗(MC)剂量数据集对于大规模剂量学研究具有重要价值。本研究旨在构建并验证一个符合DICOM标准的自动化MC剂量重新计算流程,并将其应用于I-125低剂量率前列腺近距离放射治疗MC数据集的生成。该重新计算流程作为一个独立的应用程序构建,它摄取临床DICOM-RT研究,将治疗过程重现到蒙特卡罗模拟中,并以DICOM剂量格式输出可追溯且持久的剂量分布。使用TOPAS和egs_brachyMC代码在TG43等效条件下进行的MC模拟与TG43计算结果进行比较,以验证该流程。通过比较使用两种MC代码进行的模拟,来测量生成TG186模拟时该流程的一致性。最后,在一个240名患者的队列上运行egs_brachy模拟,以模拟该流程的大规模应用。与线源TG43计算结果相比,两种MC代码的模拟结果中,超过90%的体素全局差异在±1%以内。比较两种MC代码的TG186模拟时,剂量学指标的差异在2.1%及以下。在egs_brachy模拟与治疗计划系统剂量计算的大规模比较中,发现了与先前研究中相同的TG43计算剂量高估情况。本研究构建并针对TG43计算进行验证的MC剂量重新计算流程有效地生成了持久的MC剂量数据集。由于该数据集能够以每25分钟20例的速度在15小时内重现先前的剂量学研究,因此该流程是未来大规模剂量学研究的一个有前景的工具。