Background The study focuses on developing a cataract capsulorhexis training system incorporating 3D printing and machine vision technologies. This system aims to improve surgical skills and proficiency in cataract surgery among medical students and interns. The initiative utilizes an eye model that closely simulates the capsulorhexis phase of real cataract surgeries, thereby providing a realistic training environment. Method A comparative study was conducted involving two cohorts of junior ophthalmologists, each comprising 18 participants. Group A, serving as the control group, did not receive any specific training. In contrast, Group B underwent a structured training regimen over a period of 2 months, with a total training duration of 21 days. Participants in Group B performed 20 capsulorhexis procedures daily, adhering to a prescribed training schedule to ensure the cumulative training time reached 21 days. Subsequently, both groups’ capsulorhexis performance was assessed and scored using a virtual reality training system and an animal eye practice system. This dual-assessment approach provided a quantitative measure of the training model’s efficacy. Results Training with 3D-printed models significantly improves cataract surgery accuracy and consistency. In evaluations using Eyesi and animal eyes, the group B (trained with 3D-printed models) showed lower IOL decentration (0.140 ± 0.020 mm vs 0.198 ± 0.032 mm; P < 0.001) and higher capsulorhexis circularity (0.974 ± 0.022 vs 0.937 ± 0.041; P = 0.001) compared to the group A. Similar trends were observed in animal eye evaluations. However, no significant differences were found in capsulorhexis diameter control between groups. Thus, 3D-printed models enhance surgical precision but have limited impact on capsulorhexis diameter. Conclusions Group B, trained with 3D-printed models, demonstrated superior surgical precision and capsulorhexis regularity compared to Group A. Specifically, Group B showed significantly lower IOL decentration and a higher circularity index, indicating improved IOL positioning accuracy and capsulorhexis consistency. There was no significant difference in capsulorhexis diameter between the groups in the Eyesi evaluation, but in the animal eye assessment, Group B had a significantly smaller diameter (p = 0.007). Overall, training with 3D-printed models effectively enhances surgical precision and consistency, though its impact on capsulorhexis diameter control is minimal.

Exploring a 3D printed cataract capsulorhexis training system using machine vision and virtual reality technologies

期刊论文
发表日期：

2025年4月2日

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Qi Huang,
Lanhui Yu,
XueJun Gu

摘要

Background

The study focuses on developing a cataract capsulorhexis training system incorporating 3D printing and machine vision technologies. This system aims to improve surgical skills and proficiency in cataract surgery among medical students and interns. The initiative utilizes an eye model that closely simulates the capsulorhexis phase of real cataract surgeries, thereby providing a realistic training environment.

Method

A comparative study was conducted involving two cohorts of junior ophthalmologists, each comprising 18 participants. Group A, serving as the control group, did not receive any specific training. In contrast, Group B underwent a structured training regimen over a period of 2 months, with a total training duration of 21 days. Participants in Group B performed 20 capsulorhexis procedures daily, adhering to a prescribed training schedule to ensure the cumulative training time reached 21 days. Subsequently, both groups’ capsulorhexis performance was assessed and scored using a virtual reality training system and an animal eye practice system. This dual-assessment approach provided a quantitative measure of the training model’s efficacy.

Results

Training with 3D-printed models significantly improves cataract surgery accuracy and consistency. In evaluations using Eyesi and animal eyes, the group B (trained with 3D-printed models) showed lower IOL decentration (0.140 ± 0.020 mm vs 0.198 ± 0.032 mm; P < 0.001) and higher capsulorhexis circularity (0.974 ± 0.022 vs 0.937 ± 0.041; P = 0.001) compared to the group A. Similar trends were observed in animal eye evaluations. However, no significant differences were found in capsulorhexis diameter control between groups. Thus, 3D-printed models enhance surgical precision but have limited impact on capsulorhexis diameter.

Conclusions

Group B, trained with 3D-printed models, demonstrated superior surgical precision and capsulorhexis regularity compared to Group A. Specifically, Group B showed significantly lower IOL decentration and a higher circularity index, indicating improved IOL positioning accuracy and capsulorhexis consistency. There was no significant difference in capsulorhexis diameter between the groups in the Eyesi evaluation, but in the animal eye assessment, Group B had a significantly smaller diameter (p = 0.007). Overall, training with 3D-printed models effectively enhances surgical precision and consistency, though its impact on capsulorhexis diameter control is minimal.