A clinically relevant online patient QA solution with daily CT scans and EPID-based<i>in vivo</i>dosimetry: a feasibility study on rectal cancer.

<i>Objective.</i>Adaptive radiation therapy (ART) could protect organs at risk (OARs) while maintain high dose coverage to targets. However, there is still a lack of efficient online patient quality assurance (QA) methods, which is an obstacle to large-scale adoption of ART. We aim to develop a clinically relevant online patient QA solution for ART using daily CT scans and EPID-based<i>in vivo</i>dosimetry.<i>Approach.</i>Ten patients with rectal cancer at our center were included. Patients' daily CT scans and portal images were collected to generate reconstructed 3D dose distributions. Contours of targets and OARs were recontoured on these daily CT scans by a clinician or an auto-segmentation algorithm, then dose-volume indices were calculated, and the percent deviation of these indices to their original plans were determined. This deviation was regarded as the metric for clinically relevant patient QA. The tolerance level was obtained using a 95% confidence interval of the QA metric distribution. These deviations could be further divided into anatomically relevant or delivery relevant indicators for error source analysis. Finally, our QA solution was validated on an additional six clinical patients.<i>Main results.</i>In rectal cancer, the 95% confidence intervals of the QA metric for PTV Δ<i>D</i>₉₅(%) were [-3.11%, 2.35%], and for PTV Δ<i>D</i>₂(%) were [-0.78%, 3.23%]. In validation, 68% for PTV Δ<i>D</i>₉₅(%), and 79% for PTV Δ<i>D</i>₂(%) of the 28 fractions are within tolerances of the QA metrics. one patient's dosimetric impact of anatomical variations during treatment were observed through the source of error analysis.<i>Significance.</i>The online patient QA solution using daily CT scans and EPID-based<i>in vivo</i>dosimetry is clinically feasible. Source of error analysis has the potential for distinguishing sources of error and guiding ART for future treatments.