Department of Radiation Oncology, Netherlands Cancer Institute, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.
Med Phys. 2020 Jan;47(1):171-180. doi: 10.1002/mp.13893. Epub 2019 Nov 14.
In vivo EPID dosimetry is meant to trigger on relevant differences between delivered and planned dose distributions and should therefore be sensitive to changes in patient position and patient anatomy. Three-dimensional (3D) EPID back-projection algorithms can use either the planning computed tomography (CT) or the daily patient anatomy as patient model for dose reconstruction. The purpose of this study is to quantify the effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect patient-related variations.
Variations in patient position and patient anatomy were simulated by transforming the reference planning CT images (pCT) into synthetic daily CT images (dCT) representing a variation of a given magnitude in patient position or in patient anatomy. For each variation, synthetic in vivo EPID data were also generated to simulate the reconstruction of in vivo EPID dose distributions. Both the planning CT images and the synthetic daily CT images could be used as patient model in the reconstructions yielding and EPID reconstructed dose distributions respectively. The accuracy of and reconstructions was evaluated against absolute dose measurements made in different phantom setups, and against dose distributions calculated by the treatment planning system (TPS). The comparison was performed by γ-analysis (3% local dose/2 mm). The difference in sensitivity between and reconstructions to detect variations in patient position and in patient anatomy was investigated using receiver operating characteristic analysis and the number of triggered alerts for 100 volumetric modulated arc therapy plans and 12 variations.
showed good agreement with both absolute point dose measurements (<0.5%) and TPS data (γ-mean = 0.52 ± 0.11). The agreement degraded with , with the magnitude of the deviation varying with each specific case. readily detected combined 3 mm translation setup errors in all directions (AUC = 1.0) and combined 3° rotation setup errors around all axes (AUC = 0.86) whereas showed good detectability only for 12 mm translations (AUC = 0.85) and 9° rotations (AUC = 0.80). Conversely, manifested a higher sensitivity to patient anatomical changes resulting in AUC values of 0.92/0.95 for a 6 mm patient contour expansion/contraction compared to 0.70/0.64 with . Using |ΔPTV | > 3% as clinical tolerance level, the percentage of alerts for 6 mm changes in patient contour were 85%/27% with .
With planning CT images as patient model, EPID dose reconstructions underestimate the dosimetric effects caused by errors in patient positioning and overestimate the dosimetric effects caused by changes in patient anatomy. The use of the daily patient position and anatomy as patient model for in vivo 3D EPID transit dosimetry improves the ability of the system to detect uncorrected errors in patient position and it reduces the likelihood of false positives due to patient anatomical changes.
体内 EPID 剂量测定旨在触发交付剂量分布与计划剂量分布之间的相关差异，因此应能敏感地反映患者体位和患者解剖结构的变化。三维（3D）EPID 反向投影算法可以使用计划 CT（CT）或每日患者解剖结构作为患者模型进行剂量重建。本研究的目的是量化患者模型选择对体内 3D EPID 剂量测定检测患者相关变化的性能的影响。
通过将参考计划 CT 图像（pCT）转换为代表患者位置或患者解剖结构给定变化的合成每日 CT 图像（dCT）来模拟患者位置和患者解剖结构的变化。对于每种变化，还生成了合成体内 EPID 数据来模拟体内 EPID 剂量分布的重建。计划 CT 图像和合成每日 CT 图像均可用于重建，分别产生和 EPID 重建剂量分布。和重建的准确性通过在不同的体模设置中进行绝对剂量测量以及通过治疗计划系统（TPS）计算的剂量分布进行评估。通过γ分析（3%局部剂量/2mm）进行比较。通过接收者操作特征分析和 100 个容积调制弧形治疗计划和 12 个变化的触发警报数量，研究了和重建检测患者体位和患者解剖结构变化的敏感性差异。
与绝对点剂量测量（<0.5%）和 TPS 数据（γ-均值=0.52±0.11）具有良好的一致性。随着的使用，一致性降低，每个特定病例的偏差幅度不同。能够可靠地检测到所有方向上的 3mm 平移设置误差（AUC=1.0）和所有轴上的 3°旋转设置误差（AUC=0.86），而仅能很好地检测到 12mm 平移（AUC=0.85）和 9°旋转（AUC=0.80）。相反，在检测患者解剖结构变化方面表现出更高的敏感性，导致 6mm 患者轮廓膨胀/收缩时 AUC 值为 0.92/0.95，而 AUC 值为 0.70/0.64。使用|ΔPTV|>3%作为临床耐受水平，6mm 患者轮廓变化的警报百分比分别为 85%/27%和。
使用计划 CT 图像作为患者模型，EPID 剂量重建低估了由患者定位误差引起的剂量效应，高估了由患者解剖结构变化引起的剂量效应。使用每日患者位置和解剖结构作为体内 3D EPID 瞬态剂量测定的患者模型，可以提高系统检测未校正的患者位置误差的能力，并降低因患者解剖结构变化而产生假阳性的可能性。
