RESUMEN
OBJECTIVE: To perform the first validation of a full procedural virtual reality robotic training module and analysis of novice surgeon's learning curves. DESIGN: Participants completed the bladder neck dissection task and urethrovesical anastomosis task (UVA) as part of the prostatectomy module. Surgeons completed feedback questionnaires assessing the realism, content, acceptability and feasibility of the module. Novice surgeons completed a 5.5-hour training programme using both tasks. SETTING: King's College London, London. PARTICIPANTS: 13 novice, 24 intermediate and 8 expert surgeons completed the validation study. RESULTS: Realism was scored highly for BDN (mean 3.4/5) and UVA (3.74/5), as was importance of BDN (4.32/5) and UVA (4.6/5) for training. It was rated as a feasible (3.95/5) and acceptable (4/5) tool for training. Experts performed significantly better than novice group in 6 metrics in the UVA including time (p = 0.0005), distance by camera (p = 0.0010) and instrument collisions (p = 0.0033), as well as task-specific metrics such as number of unnecessary needle piercing points (p = 0.0463). In novice surgeons, a significant improvement in performance after training was seen in many metrics for both tasks. For bladder neck dissection task, this included time (p < 0.0001), instrument collisions (p = 0.0013) and total time instruments are out of view (p = 0.0251). For UVA, this included time (p = 0.0135), instrument collisions (p = 0.0066) and task-specific metrics such as injury to the urethra (p = 0.0032) and bladder (p = 0.0189). CONCLUSIONS: Surgeons found this full procedural VR training module to be a realistic, feasible and acceptable component for a robotic surgical training programme. Construct validity was proven between expert and novice surgeons. Novice surgeons have shown a significant learning curve over 5.5 hours of training, suggesting this module could be used in a surgical curriculum for acquisition of technical skills. Further implementation of this module into the curriculum and continued analysis would be beneficial to gauge how it can be fully utilised.
