Comparing Expert and Trainee Levels of Surgical Technical Skills

Background: The use of virtual reality surgical simulators has been explored as a means of providing objective assessments in surgery. The enormous data generated by simulators can provide an objective and novel insight into the technical composites of expertise. The objective of this work to form a data repository from expert and trainee levels of surgical performance data using the NeuroVR surgical simulation platform with haptic feedback, which will be used to assess face, content and construct validity of the simulated surgical tasks and develop intelligent systems in future studies. Specific Aims: 1) Construct a data repository including expert and trainee levels of surgical performance data on virtual reality simulation. 2) Outline the face and content validity of the simulated tasks. Design: 50 participants from a single university were recruited in this consecutive retrospective case series study. Setting: Neurosurgical Simulation and Artificial Intelligence Learning Centre, McGill University Participants: Neurosurgeons (14), neurosurgical fellows and neurosurgical residents (24) from Montreal Neurological Institute and Hospital along with medical studies (12). Task: Complete removal of a simulated tumor with minimal bleeding and damage to surrounding healthy brain using two surgical instruments of the NeuroVR (CAE Healthcare) surgical simulator. Intervention: A single 28-minute simulation session, including 5 practice scenarios (3 minutes per task) and one complex realistic scenario (13 minutes). Pre- and post-questionnaires to obtain participant demographics and assess face and content validity of the simulated tasks. Main Outcomes and Measures: Primary outcome are surgical performance metrics recorded during the simulated tasks including. 1. Simulated bipolar and simulated ultrasonic aspirator separation distance Mean instrument tip separation distance in mm 2. Simulated bipolar force application Mean bipolar force application in Newtons 3. Simu