Concurrent validity of augmented reality metrics applied to the fundamentals of laparoscopic surgery (FLS)

Abstract

Current skills assessment in the Fundamentals of Laparoscopic Surgery (FLS) program is labor intensive, requiring one proctor for every 1-2 subjects. The ProMIS Augmented Reality (AR) simulator (Haptica, Dublin IR) allows for objective assessment of physical tasks through instrument tracking technology. We hypothesized that the ProMIS metrics could differentiate between ability groups as well as standard FLS scoring with fewer personnel requirements We recruited 60 volunteer subjects. Subjects were stratified based on their laparoscopic surgical experience. Those who had performed more than 100 laparoscopic procedures were considered experienced (n = 8). Those with fewer than 10 laparoscopic procedures were considered novices (n = 44). The rest were intermediates (n = 8). All subjects performed up to five trials of the peg transfer task from FLS in the ProMIS simulator. The FLS score, instrument path length, and instrument smoothness assessment were generated for each trial. For each of the five trials, experienced surgeons outperformed intermediates, who in turn outperformed novices. Statistically significant differences were seen between the groups across all trials for FLS score (p < 0.001), ProMIS path length (p < 0.001), and ProMIS smoothness (p < 0.001). When the FLS score was compared to the path length and smoothness metrics, a strong relationship between the scores was apparent for novices (r = 0.78, r = 0.94, p < 0.001) respectively), intermediates (r = 0.5, p = 0.2, r = 0.98, p < 0.001), and experienced surgeons (r = 0.86, p = 0.006, r = 0.99, p < 0.001). The construct that the standard scoring of the FLS peg transfer task can discriminate between experienced, intermediate, and novice surgeons is validated. The same construct is valid when the task is assessed using the metrics of the ProMIS. The high correlation between these scores establishes the concurrent validity of the ProMIS metrics. The use of AR for objective assessment of FLS tasks could reduce the personnel requirements of assessing these skills while maintaining the objectivity.