学术文献库

Adaptive radiation therapy (ART) could protect organs at risk (OARs) while maintain high dose coverage to targets. However, there still lack efficient online patient QA methods. We aim to develop a clinically relevant online patient quality assurance (QA) solution for ART using daily CT scans and electronic portal imaging device (EPID)-based in vivo dosimetry. 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% 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. In rectal cancer, the lower and upper tolerance of the QA metric for PTV ΔD95 (%) were [-3.11%, 2.35%], and for PTV ΔD2 (%) were [-0.78%, 3.23%]. In validation, the 68% for PTV ΔD95 (%) and the 79% for PTV ΔD2 ({%)of the 28 fractions are within tolerances of the QA metrics. By using four or more out-of-tolerance QA metrics as an action level, there were 5 fractions (18%) have four or more out-of-tolerance QA metrics in validation patient dataset. The online patient QA solution using daily CT scans and EPID-based in vivo dosimetry is clinically feasible. Source of error analysis has the potential for distinguishing sources of error and guiding ART for future treatments.