Department of Medical Physics, Ludwig Maximilian University of Munich, Garching, Germany.
Irving K. Barber Faculty of Science, University of British Columbia, Okanagan Campus, Kelowna, BC, Canada.
J Appl Clin Med Phys. 2021 Jun;22(6):35-44. doi: 10.1002/acm2.13276. Epub 2021 May 21.
Institutions use a range of different detector systems for patient-specific quality assurance (QA) measurements conducted to assure that the dose delivered by a patient's radiotherapy treatment plan matches the calculated dose distribution. However, the ability of different detectors to detect errors from different sources is often unreported. This study contains a systematic evaluation of Sun Nuclear's ArcCHECK in terms of the detectability of potential machine-related treatment errors. The five investigated sources of error were multileaf collimator (MLC) leaf positions, gantry angle, collimator angle, jaw positions, and dose output. The study encompassed the clinical treatment plans of 29 brain cancer patients who received stereotactic ablative radiotherapy (SABR). Six error magnitudes were investigated per source of error. In addition, the Eclipse AAA beam model dosimetric leaf gap (DLG) parameter was varied with four error magnitudes. Error detectability was determined based on the area under the receiver operating characteristic (ROC) curve (AUC). Detectability of DLG errors was good or excellent (AUC >0.8) at an error magnitude of at least ±0.4 mm, while MLC leaf position and gantry angle errors reached good or excellent detectability at error magnitudes of at least 1.0 mm and 0.6°, respectively. Ideal thresholds, that is, gamma passing rates, to maximize sensitivity and specificity ranged from 79.1% to 98.7%. The detectability of collimator angle, jaw position, and dose output errors was poor for all investigated error magnitudes, with an AUC between 0.5 and 0.6. The ArcCHECK device's ability to detect errors from treatment machine-related sources was evaluated, and ideal gamma passing rate thresholds were determined for each source of error. The ArcCHECK was able to detect errors in DLG value, MLC leaf positions, and gantry angle. The ArcCHECK was unable to detect the studied errors in collimator angle, jaw positions, and dose output.
医疗机构使用各种不同的探测器系统对患者特定的质量保证(QA)测量进行检测,以确保患者放射治疗计划所给予的剂量与计算的剂量分布相匹配。然而,不同探测器检测不同来源误差的能力往往没有报道。本研究对 Sun Nuclear 的 ArcCHECK 进行了系统评估,以评估其检测潜在机器相关治疗误差的能力。研究中考察了五个误差源,包括多叶准直器(MLC)叶片位置、机架角度、准直器角度、机架位置和剂量输出。研究涵盖了 29 名接受立体定向消融放疗(SABR)的脑癌患者的临床治疗计划。每个误差源都考察了六种误差幅度。此外,还研究了 Eclipse AAA 光束模型剂量学叶片间隙(DLG)参数随四种误差幅度的变化。根据受试者工作特征(ROC)曲线下面积(AUC)来确定误差检测能力。当误差幅度至少为±0.4mm 时,DLG 误差的检测能力较好或极好(AUC>0.8),而 MLC 叶片位置和机架角度误差的检测能力较好或极好的幅度至少为 1.0mm 和 0.6°。为了最大化敏感性和特异性,理想的阈值(即伽马通过率)范围为 79.1%至 98.7%。当误差幅度较小时,准直器角度、机架位置和剂量输出误差的检测能力较差,AUC 在 0.5 到 0.6 之间。评估了 ArcCHECK 设备检测与治疗机器相关源的误差的能力,并为每个误差源确定了理想的伽马通过率阈值。ArcCHECK 能够检测 DLG 值、MLC 叶片位置和机架角度的误差。ArcCHECK 无法检测到研究中的准直器角度、机架位置和剂量输出误差。