Mehrens Hunter, Taylor Paige, Alvarez Paola, Kry Stephen
IROC Houston Quality Assurance Center, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Int J Part Ther. 2023 Jul 14;10(1):23-31. doi: 10.14338/IJPT-22-00043.1. eCollection 2023 Summer.
To analyze trends in institutional performance and failure modes for the Imaging and Radiation Oncology Core's (IROC's) proton liver phantom.
Results of 66 phantom irradiations from 28 institutions between 2015 and 2020 were retrospectively analyzed. Univariate analysis and random forest models were used to associate irradiation conditions with phantom results. Phantom results included pass/fail classification, average thermoluminescent dosimeter (TLD) ratio of both targets, and percentage of pixels passing gamma of both targets. The following categories were evaluated in terms of how they predicted these outcomes: irradiation year, treatment planning system (TPS), TPS algorithm, treatment machine, number of irradiations, treatment technique, motion management technique, number of isocenters, and superior-inferior extent (in cm) of the 90% TPS isodose line for primary target 1 (PTV1) and primary target 2 (PTV2). In addition, failures were categorized by failure mode.
Average pass rate was approximately 52% and average TLD ratio for both targets had slightly improved. As the treatment field increased to cover the target, the pass rate statistically significantly fell. Lower pass rates were observed for Mevion machines, scattered irradiation techniques, and gating and internal target volume (ITV) motion management techniques. Overall, the accuracy of the random forest modeling of the phantom results was approximately 73% ± 14%. The most important predictor was the superior-inferior extent for both targets and irradiation year. Three failure modes dominated the failures of the phantom: (1) systematic underdosing, (2) poor localization in the superior-inferior direction, and (3) range error. Only 44% of failures have similar failure modes between the 2 targets.
Improvement of the proton liver phantom has been observed; however, the pass rate remains the lowest among all IROC phantoms. Through various analysis techniques, range uncertainty, motion management, and underdosing are the main culprits of failures of the proton liver phantom. Clinically, careful consideration of the influences of liver proton therapy is needed to improve phantom performance and patient outcome.
分析影像与放射肿瘤学核心(IROC)质子肝脏体模的机构性能和失败模式趋势。
回顾性分析了2015年至2020年间28个机构的66次体模照射结果。采用单因素分析和随机森林模型将照射条件与体模结果相关联。体模结果包括通过/失败分类、两个靶区的平均热释光剂量计(TLD)比值以及两个靶区通过γ分析的像素百分比。从以下类别对它们如何预测这些结果进行了评估:照射年份、治疗计划系统(TPS)、TPS算法、治疗机器、照射次数、治疗技术、运动管理技术、等中心数量以及主要靶区1(PTV1)和主要靶区2(PTV2)的90%TPS等剂量线的上下范围(以厘米为单位)。此外,根据失败模式对失败情况进行了分类。
平均通过率约为52%,两个靶区的平均TLD比值略有提高。随着治疗野增大以覆盖靶区,通过率在统计学上显著下降。对于Mevion机器、散射照射技术以及门控和内部靶区体积(ITV)运动管理技术,观察到较低的通过率。总体而言,体模结果的随机森林建模准确性约为73%±14%。最重要的预测因素是两个靶区的上下范围和照射年份。三种失败模式在体模失败中占主导地位:(1)系统性剂量不足,(2)上下方向定位不佳,(3)射程误差。两个靶区之间只有44%的失败具有相似的失败模式。
已观察到质子肝脏体模有所改进;然而,其通过率在所有IROC体模中仍然是最低的。通过各种分析技术,射程不确定性、运动管理和剂量不足是质子肝脏体模失败的主要原因。临床上,需要仔细考虑肝脏质子治疗的影响,以改善体模性能和患者治疗结果。