Artificial intelligence-generated targets and inter-observer variation in online adaptive radiotherapy of bladder...

Daily target re-delineation in online adaptive radiotherapy (oART) introduces uncertainty. The aim of this study was to evaluate artificial intelligence (AI) generated contours and inter-observer target variation among radiotherapy technicians in cone-beam CT (CBCT) guided oART of bladder cancer.

For each of 10 consecutive patients treated with oART for bladder cancer, one CBCT was randomly selected and retrospectively included. The bladder (CTV-T) was AI-segmented (CTV-T_AI). Seven radiotherapy technicians independently reviewed and edited CTV-T_AI, generating CTV-T_ADP. Contours were benchmarked against a ground truth contour (CTV-T_GT) delineated blindly from scratch. CTV-T_ADP and CTV-T_AI were compared to CTV-T_GT using volume, dice similarity coefficient, and bidirectional local distance. Dose coverage (D_99%>95 %) of CTV-T_GT was evaluated for treatment plans optimized for CTV-T_AI and CTV-T_ADP with clinical margins. Inter-observer variation among CTV-T_ADP was assessed using coefficient of variation and generalized conformity index.

CTV-T_GT ranged from 48.7 cm³ to 211.6 cm³. The median [range] volume difference was 4.5 [-17.8, 42.4] cm³ for CTV-T_ADP and -15.5 [-54.2, 4.3] cm³ for CTV-T_AI, compared to CTV-T_GT. Corresponding dice similarity coefficients were 0.87 [0.71, 0.95] and 0.84 [0.64, 0.95]. CTV-T_GT was adequately covered in 68/70 plans optimized on CTV-T_ADP and in 6/10 plans optimized on CTV-T_AI with clinical margins. The median [range] coefficient of variation was 0.08 [0.05, 0.11] and generalized conformity index was 0.78 [0.71, 0.88] among CTV-T_ADP.

Target re-delineation in CBCT-guided oART of bladder cancer demonstrated non-isotropic inter-observer variation. Manual adjustment of AI-generated contours was necessary to cover ground truth targets.