# Quantitative Analysis of Instrument Motion Paths in Cataract Surgery across a Resident’s Training

**Authors:** David Mikhail, Shuting Xie, Michael Balas, Jason M. Kwok, Ana Miguel, Amrit Rai, Amandeep Rai, Peter J. Kertes, Iqbal Ike K. Ahmed, Matthew B. Schlenker

PMC · DOI: 10.1016/j.xops.2025.101014 · 2025-11-26

## TL;DR

This study tracks surgical instrument movements during cataract surgeries to show how a resident's skills improve over time.

## Contribution

It introduces a detailed, video-based motion tracking method to quantify skill progression in cataract surgery training.

## Key findings

- All 11 instruments showed significant improvements in motion metrics as the resident gained experience.
- A major shift in surgical efficiency occurred around the 300th case for most instruments.
- Advanced tasks like lens implantation showed later improvements in motion efficiency.

## Abstract

To objectively quantify the motion paths of surgical instruments during cataract surgery across a resident’s training, identifying patterns of skill acquisition and proficiency development.

An n = 1 panel study.

One ophthalmology resident performing cataract surgery.

One hundred cataract surgery videos performed by a single resident from their sixth to 760th case were collected. Advanced motion tracking software (Computer Vision Annotation Tool) was utilized to annotate and track the trajectories of 11 surgical instruments on a frame-by-frame basis. Monotonic trends were assessed using the Mann–Kendall test and Theil–Sen slope estimation, with Spearman correlation measuring the association between case number and performance metric values. Pettitt change-point analysis identified significant transitions in the resident’s skill progression.

Six key motion parameters, including total path length, average velocity, average acceleration, root mean square jerk, average angular change, and workspace coverage, were extracted for each instrument in each video.

All 11 instruments demonstrated statistically significant reductions in ≥1 motion parameter. Path length consistently decreased across training, with the largest reductions seen in the cannula (–11.8%; 95% confidence interval [CI], –17.4% to –6.8%; P < 0.001), phacoemulsification handpiece (–11.5%; 95% CI, –14.1% to –8.7%; P < 0.001), and cystotome (–8.9%; 95% CI, –11.8% to –5.9%; P < 0.001). The intraocular lens inserter showed the greatest reduction in average angular change of 3.0% (–1.70°) (95% CI, –3.9% to –2.0%; P < 0.001). Pettitt analysis demonstrated significant shifts in surgical efficiency at around case 300 for most instruments, although improvements in certain advanced tasks (e.g., lens implantation) emerged later.

This large-scale, frame-by-frame motion tracking study revealed distinct instrument- and task-specific learning curves in cataract surgery, highlighting progressive changes in motion metrics over time. A significant shift at approximately case 300 marked a milestone in the resident’s instrument use patterns. These findings underscore the potential of objective, video-based motion tracking analytics to provide data-driven resident feedback, guiding targeted instruction and standardizing cataract surgery training.

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

## Full-text entities

- **Diseases:** Cataract (MESH:D002386)

## Figures

3 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12805020/full.md

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Source: https://tomesphere.com/paper/PMC12805020