The effect of the choice of patient model on the performance of in vivo 3D EPID dosimetry to detect variations in patient position and anatomy

Purpose 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. Methods 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 e D pCTand e D dCTEPID reconstructed dose distributions respectively. The accuracy of e D pCTand e D dCTreconstructions 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 e D pCTand e D dCTreconstructions 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. Resultse D dCTshowed good agreement with both absolute point dose measurements (<0.5%) and TPS data (γ‐mean = 0.52 ± 0.11). The agreement degraded with e D pCT , with the magnitude of the deviation varying with each specific case. e D dCTreadily 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 e D pCTshowed good detectability only for 12 mm translations (AUC = 0.85) and 9° rotations (AUC = 0.80). Conversely, e D pCTmanifested 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 e D dCT . Using |ΔPTV D50 | > 3% as clinical tolerance level, the percentage of alerts for 6 mm changes in patient contour were 85%/27% with e D pCT / e D dCT . Conclusions 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.