DOI 10.1080/02713683.2025.2504569
Objective Quality Assessment of the Capsulorhexis - A Novel Augmented Reality Tool for Trainees and Experts.
Аннотация
PURPOSE: To assess the usability of a smartphone-based augmented reality tool for capsulorhexis training.
METHODS
This is a single-center, prospective, clinical study conducted at the Department of Ophthalmology, University Hospital, LMU Munich, Munich, Germany. Surgery-naïve residents were included and divided into three subgroups: (1) augmented reality supported by the Custom Surgical MicroREC system during their capsulorhexis procedures; (2) Expert support supported by an experienced cataract surgeon; (3) No support without support. Capsulorhexis quality was graded by circularity, centration, and radius.
RESULTS
Twenty-one (ntotal = 21) participants were enrolled. The augmented reality group was statistically significantly better in terms of circularity than the Expert support (Mann-Whitney's U-test: p = .00175) and the No support group (Mann-Whitney's U-test: p = .00268). The procedure duration decreased statistically significantly for all three groups when try 1 and 10 were compared (augmented reality: p < .0001; Expert support: p = .0099; No support: p < .0001). The other parameters did not differ statistically significantly. The questionnaires handed to the augmented reality and No support group before and after the wet lab revealed a high importance of wet lab trainings to all polled participants. The provided wet lab setup was considered adequate by both groups.
CONCLUSION
Augmented reality can assist in cataract training. The Custom Surgical MicroREC system can have a positive influence on capsulorhexis quality in a training environment. Automated quality metrics measured by the augmented reality software provide an objective quality score of the performed surgical procedure. As the tested augmented reality system can be used in training as well as in a real-world setting, this will be a useful tool for trainees and expert surgeons alike.
Предметные рубрики MeSH
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