The contribution of personalized video feedback to robotic partial nephrectomy training in realistic 3D tumor kidney models: design, production and implementation.

Background: Traditional surgical training relies on a master-apprentice model, but limitations such as restricted working hours and evolving surgical techniques have led to the integration of simulation-based training. Three-dimensional (3D) printing has emerged as a valuable tool for enhancing surgical education, offering patient-specific anatomical models that improve skill acquisition. Additionally, personalized video feedback may further refine training outcomes. This study investigates the impact of 3D-printed renal models and video-based feedback on skill acquisition in robotic partial nephrectomy training. Methods: Forty urology residents without prior robotic surgery experience participated in this study. After completing a standardized theoretical and simulation-based training program, they performed partial nephrectomy on 3D-printed kidney models. The participants were randomly assigned to two groups: one received personalized video feedback based on their recorded surgical performances, while the other proceeded without feedback. Their surgical performance was evaluated based on dissection time, renorrhaphy time, total console time, and the amount of healthy renal parenchyma removed. Statistical analysis was conducted to compare improvements between the groups and assess the impact of video feedback on skill development. Results: Initial comparisons between junior and senior residents showed no significant differences in their first operations, demonstrating that e-learning and proficiency-based simulation training effectively equalized skill levels before transitioning to realistic 3D model-based training. This suggests that structured preparatory training with objective performance targets can enhance learning outcomes in surgical simulation. Additionally, 3D-printed models provide a significantly more cost-effective alternative to cadaveric and animal-based training, making high-quality surgical education more accessible and scalable. Residents who received video feedback demonstrated a greater percentage improvement in dissection time compared to the control group (46.63% vs. 23.62%, Conclusion: The integration of 3D-printed anatomical models with personalized video feedback enhances skill acquisition in robotic partial nephrectomy training. Video feedback significantly improves surgical precision by reducing unnecessary parenchymal removal and accelerating dissection time. These findings support the use of patient-specific 3D models and targeted feedback as cost-effective and scalable strategies to optimize surgical education and shorten the learning curve for complex procedures.