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PhacoTrainer: Automatic Artificial Intelligence-Generated Performance Ratings for Cataract Surgery.

Hsu-Hang Yeh1, Simmi Sen2, Jonathan C Chou3

  • 1Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA.

Translational Vision Science & Technology
|May 1, 2025
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Summary
This summary is machine-generated.

Artificial intelligence (AI) metrics can distinguish between trainee and faculty cataract surgeons. These AI-generated surgical skill metrics correlate with expert evaluations, offering potential for surgical education enhancement.

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Area of Science:

  • Ophthalmology
  • Surgical Education
  • Artificial Intelligence in Medicine

Background:

  • Assessing surgical skill is crucial for effective training.
  • Objective metrics can complement subjective expert evaluations in surgical education.
  • Artificial intelligence (AI) offers novel methods for analyzing surgical performance.

Purpose of the Study:

  • To determine if AI-generated metrics can differentiate between trainee and faculty cataract surgeons.
  • To assess the correlation between AI-derived surgical performance metrics and expert-rated skills.

Main Methods:

  • Deep learning models generated video-level (e.g., probe decentration) and instrument-specific (e.g., path length) metrics from routine cataract surgery videos.
  • Surgeons included residents (N=28) and attendings (N=29).
  • Expert human judges used the Objective Structured Assessment of Cataract Surgical Skill (OSACSS) for evaluation. Statistical analyses included t-tests and Pearson correlation coefficients.

Main Results:

  • AI metrics, such as phacoemulsification probe total path length and maximum velocity, were significantly lower in attending surgeon videos.
  • Attending surgeons exhibited superior phacoemulsification and eye centration based on AI analysis.
  • Most AI metrics showed a negative correlation with OSACSS scores, indicating better performance with lower AI metric values (e.g., phacoemulsification decentration: r = -0.369).

Conclusions:

  • Automatically generated AI metrics effectively differentiate between attending and trainee cataract surgeries.
  • AI metrics demonstrate a significant correlation with human expert evaluations of surgical performance.
  • AI-driven metrics hold promise for enhancing cataract surgical education and training.