Abstract

Introduction: Bile duct injury is the main serious complication of laparoscopic cholecystectomy. This study uses eye-tracking technology to identify distinct visual gaze patterns employed by surgeons able to promptly detect bile duct injury risk during laparoscopic cholecystectomy. Methods: Gaze tracking was performed using a remote eye-tracking system. Subjects were shown 3-minute videos of a laparoscopic cholecystectomy that led to a serious bile duct injury (Video A) and of an uneventful procedure (Video B), while logging if they perceived errors in surgical approach that could result in bile duct injury. Outcome parameters include fixation sequences on anatomical structures and eye tracking metrics. Participants were stratified based on performance and compared using conventional statistical and machine learning approaches. Results: 29 surgeons were recruited. There was no relationship between experience and speed of risk identification. The group with early-detection of the risk of injury displayed reduced dwell time [ms] on the common bile duct (6632.50 [IQR 3600.3] vs 9249.30 [IQR 3924.8]; p = 0.041) in the first half of video A. They also displayed increased cystic duct dwell time [ms] (15665.30 [IQR 7999.5] vs 12715.65 [8348.7]; p= 0.026) and increased Calot's triangle glances count (3.00 [IQR 2] vs 1.50 [IQR 1]; p = 0.018) viewing the dissection of Calot's triangle in video B. Hidden Markov Model based classification of fixation sequences demonstrated clear separability between early and late identifier groups. Conclusions: There are discernible differences in visual gaze patterns of surgeons during laparoscopic cholecystectomy associated with early recognition of impending bile duct injury.

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