Real-world analysis of manual editing of deep learning contouring in the thorax region

•Deep-learning contouring for radiotherapy is evaluated in the thorax region.•Specific regions-of-adjustment and variability in editing per organ were found.•The consistency and accuracy of training data remains crucial to model performance.•Separate models for specific indications or acquisition protocols may be necessary.•Subsampling and post-processing make the clinical workflow more efficient.