A Platform for Tracking Surgeon and Observer Gaze as a Surrogate for Attention in Ophthalmic Surgery

Abstract

Purpose: To develop and validate a platform that can extract eye gaze metrics from surgeons observing cataract and vitreoretinal procedures and to enable post hoc data analysis to assess potential discrepancies in eye movement behavior according to surgeon experience. Design: Experimental, prospective, single-center study. Participants: Eleven ophthalmic surgeons observing deidentified vitreoretinal and cataract surgical procedures performed at a single university-based medical center. Methods: An open-source platform was developed to extract gaze coordinates and metrics from ophthalmic surgeons via a computer vision algorithm in conjunction with a neural network to track and segment instruments and tissues, identifying areas of attention in the visual field of study subjects. Eleven surgeons provided validation data by watching videos of 6 heterogeneous vitreoretinal and cataract surgical phases. Main Outcome Measures: Accuracy and distance traveled by the eye gaze of participants and overlap of the participants’ eye gaze with instruments and tissues while observing surgical procedures. Results: The platform demonstrated repeatability of > 94% when acquiring the eye gaze behavior of subjects. Attending ophthalmic surgeons and clinical fellows exhibited a lower overall cartesian distance traveled in comparison to resident physicians in ophthalmology (P 0.2). The number and duration of fixations did not vary substantially among groups (P > 0.3). Conclusions: The platform proved effective in extracting gaze metrics of ophthalmic surgeons. These preliminary data suggest that surgeon gaze behavior differs according to experience. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

Keywords

• Eye movement tracking of ophthalmic surgeons
• Surgical skills assessment via artificial intelligence
• Intraoperative gaze tracking