Operator experience determines performance in a simulated computer-based brain tumor resection task.
Academic Article
Overview
abstract
PURPOSE: Develop measures to differentiate between experienced and inexperienced neurosurgeons in a virtual reality brain surgery simulator environment. METHODS: Medical students (n = 71) and neurosurgery residents (n = 12) completed four simulated Glioblastoma multiforme resections. Simulated surgeries took place over four days with intermittent spacing in between (average time between surgeries of 4.77 ± 0.73 days). The volume of tumor removed (cc), volume of healthy brain removed (cc), and instrument path length (mm) were recorded. Additionally, surgical effectiveness (% tumor removed divided by % healthy brain removed) and efficiency (% tumor removed divided by instrument movement in mm) were calculated. Performance was compared (1) between groups, and (2) for each participant over time to assess the learning curve. In addition, the effect of real-time instruction ("coaching") was assessed with a randomly selected group of medical students. RESULTS: Neurosurgery residents removed less healthy brain, were more effective in removing tumor and sparing healthy brain tissue, required less instrument movement, and were more efficient in removing tumor tissue than medical students. Medical students approached the resident level of performance over serial sessions. Coached medical students showed more conservative surgical behavior, removing both less tumor and less healthy brain. In sum, neurosurgery residents removed more tumor, removed less healthy brain, and required less instrument movement than medical students. Coaching modified medical student performance. CONCLUSIONS: Virtual Reality brain surgery can differentiate operators based on both recent and long-term experience and may be useful in the acquisition and assessment of neurosurgical skills. Coaching alters the learning curve of naïve inexperienced individuals.
