A systematic review of virtual reality for the assessment of technical skills in neurosurgery

Author:

Chan Justin1,Pangal Dhiraj J.1,Cardinal Tyler1,Kugener Guillaume1,Zhu Yichao1,Roshannai Arman1,Markarian Nicholas1,Sinha Aditya1,Anandkumar Anima2,Hung Andrew3,Zada Gabriel1,Donoho Daniel A.4

Affiliation:

1. USC Department of Neurosurgery, Keck School of Medicine of the University of Southern California, Los Angeles, California;

2. Computing + Mathematical Sciences, California Institute of Technology, Pasadena, California;

3. USC Department of Urology, Keck School of Medicine of the University of Southern California, Los Angeles, California; and

4. Texas Children's Hospital, Baylor College of Medicine, Houston, Texas

Abstract

OBJECTIVE Virtual reality (VR) and augmented reality (AR) systems are increasingly available to neurosurgeons. These systems may provide opportunities for technical rehearsal and assessments of surgeon performance. The assessment of neurosurgeon skill in VR and AR environments and the validity of VR and AR feedback has not been systematically reviewed. METHODS A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted through MEDLINE and PubMed. Studies published in English between January 1990 and February 2021 describing the use of VR or AR to quantify surgical technical performance of neurosurgeons without the use of human raters were included. The types and categories of automated performance metrics (APMs) from each of these studies were recorded. RESULTS Thirty-three VR studies were included in the review; no AR studies met inclusion criteria. VR APMs were categorized as either distance to target, force, kinematics, time, blood loss, or volume of resection. Distance and time were the most well-studied APM domains, although all domains were effective at differentiating surgeon experience levels. Distance was successfully used to track improvements with practice. Examining volume of resection demonstrated that attending surgeons removed less simulated tumor but preserved more normal tissue than trainees. More recently, APMs have been used in machine learning algorithms to predict level of training with a high degree of accuracy. Key limitations to enhanced-reality systems include limited AR usage for automated surgical assessment and lack of external and longitudinal validation of VR systems. CONCLUSIONS VR has been used to assess surgeon performance across a wide spectrum of domains. The VR environment can be used to quantify surgeon performance, assess surgeon proficiency, and track training progression. AR systems have not yet been used to provide metrics for surgeon performance assessment despite potential for intraoperative integration. VR-based APMs may be especially useful for metrics that are difficult to assess intraoperatively, including blood loss and extent of resection.

Publisher

Journal of Neurosurgery Publishing Group (JNSPG)

Subject

Neurology (clinical),General Medicine,Surgery

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