Impact of manual contour editing on plan quality for online adaptive radiotherapy for head and neck cancer.

Purpose: Online adaptive radiotherapy (oART) has high resource costs especially for head-and-neck (H&N) cancer, which requires recontouring complex targets and numerous organs-at-risk (OARs). ART systems provide auto-contours to help, we aim to explore the optimal level of editing automatic contours to maintain plan quality in a cone-beam-computed-tomography (CBCT)-based oART system for H&N. In this system influencer OAR contours are generated and reviewed first, which then drives the auto-contouring of the remaining OARs and targets.

Methods and materials: Three-hundred-and-forty-nine adapted fractions of forty-four H&N patients were retrospectively analyzed, with physician-edited OARs and targets. These contours and associated online adapted plans served as the gold standard for comparison. We simulated three contour editing workflows: (1) no editing of contours, (2) only editing the influencers, (3) editing the influencers and targets. The geometric difference was quantified with Dice Similarity Coefficient (DSC) and Hausdorff Distance (HD). The dosimetric differences in target coverage and OAR doses were calculated between the gold standard and these three simulated workflows.

Results: Workflow 1 resulted in significantly inferior contour quality for all OARs (mean DSC 0.85±0.17 and HD95 3.10±5.80mm), dosimetric data was hence not calculated for workflow 1. In workflow (2), the frequency of physician editing targets and remaining OARs were 80.8%-95.7% and 2.3% (brachial plexus)-67.7% (oral cavity) respectively, where the OAR differences were geometrically minor (mean DSC>0.95 with std≤0.09). However, due to the unedited target contours of workflow 2 (mean DSC 0.86-0.92 and mean HD95 2.56-3.30mm versus the ground-truth targets), plans were inadequate with insufficient coverage. In workflow (3) when both targets and influencers were edited (non-influencer OARs were unedited), over 95.5% of the adapted plans achieved the patient-specific dosimetry goals.

Conclusion: The CBCT-based H&N oART workflow can be meaningfully accelerated by only editing the influencers and targets while omitting the remaining OARs without compromising the quality of the adaptive plans.