Anastasiou, Dimitrios;
Singla, Nitish;
Raja, Laxmi;
Saleh, George;
Stoyanov, Danail;
Mazomenos, Evangelos;
(2022)
Surgical knot training in ophthalmic surgery: Skill assessment with eye-tracking.
In:
Proceeding of the 11th Joint Workshop on New Technologies for Computer/Robot Assisted Surgery.
(pp. pp. 41-42).
CRAS: Conference on New Technologies for Computer and Robot Assisted Surgery: Napoi, Italy.
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Abstract
Suturing is a fundamental task in ophthalmic surgery. Focused training is necessary to master technical (tissue handling, knot tying) and cognitive (appropriate selection of instruments, forward planning) skills and develop a high level of hand-eye coordination required for ophthalmic microsurgical procedures. Formulating novel objective measures of operational performance will be beneficial for training in ophthalmic microsurgery. Capturing eye movements and points of focus while performing surgical tasks can provide meaningful information to assess the operator’s technical and cognitive skills and overall performance. The locations of gaze focus and spatial distribution of fixations embed valuable information for assessing the use of instruments, the sequence and quality in executing subtasks, and possibly the level of hand-eye coordination the operator demonstrates. This study explores eye-tracking for developing performance metrics for suturing tasks in ophthalmic surgery and preliminary analysis focuses on the total duration of executing a surgical suture and its subtasks. It also introduces the spatial distribution of fixations as a feature to characterize the level of surgical expertise. Eye-tracking has been used as a tool for skill analysis in a variety of different surgical applications. Copogna et al. [1], compared anesthesiologists of different expertise levels performing an epidural block. Attentional heat-maps and gaze plots showed different gaze dispersion between the groups. Causer et al., showed that quiet eye training significantly improved learning of surgical knot tying compared to a traditional technical approach [2]. In [3], expert and novice neurosurgeons performing under a surgical microscope were examined, concluding that experts spend more time fixating on the region of interest before performing an action. Lee et al., used eye-tracking data to identify gaze patterns and blind spots in a real-time EGD [4]. While efforts have been made to analyze gaze patterns [3],[4], it has yet to be developed a metric that can be used to statistically compare the spatial distributions of gaze focus points, a rather useful tool to evaluate the skill level of groups with different expertise.
| Type: | Proceedings paper |
|---|---|
| Title: | Surgical knot training in ophthalmic surgery: Skill assessment with eye-tracking |
| Event: | CRAS 2022: 11th Joint Workshop on New Technologies for Computer/Robot Assisted Surgery |
| Location: | Naples, Italy |
| Dates: | 25 Apr 2022 - 27 Apr 2022 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://cras-eu.org/cras-2022/ |
| Language: | English |
| Additional information: | This work is subjected to copyright. It is published as an open-access publication under the “Creative Commons Attribution 4.0 International” license. |
| Keywords: | Surgical data science, skill assessment, ophthalmic surgery |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10160573 |
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