Objective skill assessment for cataract surgery from surgical microscope video

Video offers an accessible method for automated surgical skill evaluation; however, many platforms still rely on traditional six-degree-of-freedom (6-DOF) tracking systems, which can be costly, cumbersome, and challenging to apply clinically. This study aims to demonstrate that trainee skill in cataract surgery can be assessed effectively using only object detection from monocular surgical microscope video.

One ophthalmologist and four residents performed cataract surgery on a simulated eye five times each, generating 25 recordings. Recordings included both the surgical microscope video and 6-DOF instrument tracking data. Videos were graded by two expert ophthalmologists using the ICO-OSCAR:SICS rubric. We computed motion-based metrics using both object detection from video and 6-DOF tracking. We first examined correlations between each metric and expert scores for each rubric criteria. Then, using these findings, we trained an ordinal regression model to predict scores from each tracking modality and compared correlation strengths with expert scores.

Metrics from object detection generally showed stronger correlations with expert scores than 6-DOF tracking. For score prediction, 6-DOF tracking showed no significant advantage, while scores predicted from object detection achieved significantly stronger correlations with expert scores for four scoring criteria.

Our results indicate that skill assessment from monocular surgical microscope video can match, and in some cases exceed, the correlation strengths of 6-DOF tracking assessments. This finding supports the feasibility of using object detection for skill assessment without additional hardware.