Do AI-based contouring algorithms influence physicians in the online adaptive radiotherapy of patients with bladder cancer?

Purpose: In this prospective cross-over study, the precision of manual correction of the clinical target volume (CTV) during online-adaptive radiotherapy (ART) of patients with bladder cancer was investigated in dependence on the input of applied computational algorithms. Methods and materials: on CBCT1. Results: of the manually adjusted segments between 16% and 50% of the errors were on average corrected by the physicians, with interindividual differences (p < 0.0001,F-test). Conclusions: The present study results reveal that the quality of AI-generated contours is of crucial importance for a proper online onboard ART, as errors may bias clinical workflow and contouring. The accuracy of supervised structures strongly depends on the accuracy of the AI generated contours before supervision.