Glenn Mallory C, Peterson Christine B, Howell Rebecca M, Followill David S, Pollard-Larkin Julianne M, Kry Stephen F
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
The University of Texas MD Anderson UTHealth Graduate School of Biomedical Sciences, Houston, TX, 77030, USA.
Med Phys. 2020 Oct;47(10):5250-5259. doi: 10.1002/mp.14396. Epub 2020 Aug 16.
Treatment planning system (TPS) dose calculations have previously been shown to be sensitive to modeling errors, especially when treating with complex strategies like intensity-modulated radiation therapy (IMRT). This work investigates the dosimetric impact of several dosimetric and nondosimetric beam modeling parameters, based on their distribution in the radiotherapy community, in two commercial TPSs in order to understand the realistic potential for dose deviations and their clinical effects.
Beam models representing standard 120-leaf Varian Clinac-type machines were developed in Eclipse 13.5 (AAA algorithm) and RayStation 9A (v8.99, collapsed-cone algorithm) based upon median values of dosimetric measurements from Imaging and Radiation Oncology Core (IROC) Houston site visit data and community beam modeling parameter survey data in order to represent a baseline linear accelerator. Five clinically acceptable treatment plans (three IMRT, two VMAT) were developed for the IROC head and neck phantom. Dose distributions for each plan were recalculated after individually modifying parameters of interest (e.g., MLC transmission, percent depth doses [PDDs], and output factors) according to the 2.5th to 97.5 percentiles of community survey and machine performance data to encompass the realistic extent of variance in the radiotherapy community. The resultant dose distributions were evaluated by examining relative changes in average dose for thermoluminescent dosimeter (TLD) locations across the two target volumes and organ at risk (OAR). Interplay was also examined for parameters generating changes in target dose greater than 1%.
For Eclipse, dose calculations were sensitive to changes in the dosimetric leaf gap (DLG), which resulted in differences from -5% to +3% to the targets relative to the baseline beam model. Modifying the MLC transmission factor introduced differences up to ± 1%. For RayStation, parameters determining MLC behaviors likewise contributed substantially; the MLC offset introduced changes in dose from -4% to +7%, and the MLC transmission caused changes of -4% to +2%. Among the dosimetric qualities examined, changes in PDD implementation resulted in the most substantial changes, but these were only up to ±1%. Other dosimetric factors had <1% impact on dose accuracy. Interplay between impactful parameters was found to be minimal.
Factors related to the modeling of the MLC, particularly relating to the leaf offset, can cause clinically significant changes in the calculated dose for IMRT and VMAT plans. This should be of concern to the radiotherapy community because the clinical effects of poor TPS commissioning were based on reported data from clinically implemented beam models. These results further reinforce that dose errors caused by poor TPS calculations are often involved in IROC phantom failures.
先前已表明治疗计划系统(TPS)剂量计算对建模误差敏感,尤其是在采用如调强放射治疗(IMRT)等复杂策略进行治疗时。这项工作基于两个商用TPS中放射治疗界的剂量学和非剂量学射束建模参数分布,研究了这些参数对剂量学的影响,以便了解剂量偏差的实际可能性及其临床效果。
基于来自休斯顿成像与放射肿瘤学核心(IROC)站点访问数据的剂量学测量中值以及放射治疗界射束建模参数调查数据,在Eclipse 13.5(AAA算法)和RayStation 9A(v8.99,坍缩圆锥算法)中开发了代表标准120叶Varian Clinac型机器的射束模型,以代表基线直线加速器。为IROC头颈部体模制定了五个临床可接受的治疗计划(三个IMRT,两个VMAT)。根据放射治疗界调查和机器性能数据的第2.5百分位数至第97.5百分位数,在单独修改感兴趣的参数(例如,多叶准直器(MLC)透射率、百分深度剂量[PDD]和输出因子)后,重新计算每个计划的剂量分布,以涵盖放射治疗界实际的变化范围。通过检查两个靶区和危及器官(OAR)内热释光剂量计(TLD)位置的平均剂量的相对变化来评估所得的剂量分布。还检查了对靶区剂量产生大于1%变化的参数之间的相互作用。
对于Eclipse,剂量计算对剂量学叶间距(DLG)的变化敏感,相对于基线射束模型,这导致靶区剂量有-5%至+3%的差异。修改MLC透射因子引入的差异高达±1%。对于RayStation,确定MLC行为的参数同样有很大影响;MLC偏移导致剂量变化从-4%至+7%,MLC透射导致变化从-4%至+2%。在所检查的剂量学质量中PDD实施的变化导致的变化最为显著,但也仅高达±1%。其他剂量学因素对剂量准确性的影响<1%。发现有影响的参数之间的相互作用最小。
与MLC建模相关的因素,特别是与叶片偏移有关的因素,可导致IMRT和VMAT计划计算剂量出现临床上显著的变化。这应引起放射治疗界的关注,因为TPS调试不佳的临床影响是基于临床实施的射束模型的报告数据。这些结果进一步强化了TPS计算不佳导致的剂量误差常与IROC体模失败有关。