Continuous Instrument Tracking in a Cerebral Corticectomy Ex Vivo Calf Brain Simulation Model: Face and Content Validation

Abstract

BACKGROUND AND OBJECTIVES: Subpial corticectomy involving complete lesion resection while preserving pial membranes and avoiding injury to adjacent normal tissues is an essential bimanual task necessary for neurosurgical trainees to master. We sought to develop an ex vivo calf brain corticectomy simulation model with continuous assessment of surgical instrument movement during the simulation. A case series study of skilled participants was performed to assess face and content validity to gain insights into the utility of this training platform, along with determining if skilled and less skilled participants had statistical differences in validity assessment. METHODS: An ex vivo calf brain simulation model was developed in which trainees performed a subpial corticectomy of three defined areas. A case series study assessed face and content validity of the model using 7-point Likert scale questionnaires. RESULTS: Twelve skilled and 11 less skilled participants were included in this investigation. Overall median scores of 6.0 (range 4.0-6.0) for face validity and 6.0 (range 3.5-7.0) for content validity were determined on the 7-point Likert scale, with no statistical differences between skilled and less skilled groups identified. CONCLUSION: A novel ex vivo calf brain simulator was developed to replicate the subpial resection procedure and demonstrated face and content validity.

Real-Time multifaceted artificial intelligence vs In-Person instruction in teaching surgical technical skills: a randomized controlled trial

“…Methodologies are being developed to accurately identify surgical steps, potentially assess intraoperative performance during surgery, and provide feedback using artificial intelligence 48 , 49 . Obtaining performance data during surgery in realistic operating settings using real surgical instruments may enable transitioning intelligent feedback systems to the real operating room to mitigate errors during surgery 50 – 52 . Currently, computer vision systems are being implemented in the real-operating room to track information similar to the performance metrics that the ICEMS uses to make its decisions.…”