Neurosurgery Simulation-based Skills Training: From Mannequins and Cadavers to Virtual Reality and Artificial Intelligence

Abstract

Simulation in the neurosurgical context broadly refers to systems that either create or enhance the perceivable and sometimes interactable environment of the user. Adequate resident training requires hands-on experience, but operative neurosurgery affords few such chances. Moreover, the pressure of performing well, time constraints and fear of mistakes hinder adequate learning. It may also lead to an erroneous evaluation of the residents’ surgical aptitude on the part of the supervisor. Simulation systems offer a unique solution for resident training in a safe environment as well as unbiased evaluation. Simulation-related technologies can also be used to better counsel patients, pre-operative planning and development of newer techniques and devices. Various modalities of simulation training available at present include physical (PR), virtual (VR), augmented (AR), and mixed (MR) reality. Though we have achieved significant advances in all forms of simulation models, largely we are dependent on human experts for the evaluation of the performance of trainees. Artificial Intelligence (AI) algorithms may offer an alternative to human experts with several advantages including the removal of human bias, and preserving human resources. In this manuscript, we have summarized our innovations and lessons learned from our neuro-engineering collaboration at the Neurosurgery Education and Training School (NETS): Neurosurgery Skills Training Facility (NSTF), All India Institute of Medical Sciences (AIIMS), New Delhi that will help in pushing the boundaries of the role of simulation in neurosurgery.