Generative Adversarial Networks Synthetic Optical Coherence Tomography Images as an Education Tool for Image Diagnosis of Macular Diseases: A Randomized Trial (Preprint)
Authors: Peng Jie , Xie Xiaoling , Xie Meng , Luo Li , Xiao Haodong , Lu Zupeng , Ye Hongfei , Chen Li , Yang Jianlong , Zhang Mingzhi , Zhao Peiquan , Zheng Ce 
Published: January 2024

BACKGROUND

Macular diseases are one of the leading causes of blindness. Diagnosis of macular diseases is an important part of ophthalmic education. Optical coherence tomography (OCT) is now a standard imaging modality for diagnosing and treating macular disease. Accurate interpretations of OCT with macular diseases are vital for ophthalmic resident training worldwide. Previously, we proposed generative adversarial networks (GANs) model for synthetic OCT images of macular disorders. Our result also showed its potential value for educational purposes. This study aimed to establish an educational tool based on GANs synthetic images for ophthalmic residents’ and medical students’ education and evaluate its validity.

OBJECTIVE

To evaluate the assessment of GANs synthetic OCT images as an education tool for image diagnosis of macular diseases in medical students and ophthalmic residents trainingIn Group GANs OCT, scores improved from 80.0(46.0, 85.5) to 92.0(81.0,95.5) five minutes after training (p<0.001) and 92.30± 5.36 one-week after training (p<0.001). Similarly, in Group real OCT, scores improved from 66.00±19.52 to 92.90± 5.71(p<0.001) and 93.20± 6.10 (p<0.001), respectively. No significantly difference were found for scores of tests, score improvements and time consumptions between Group GANs OCT and Group real OCT. Medical students had significantly higher score improvement after training than residents(p<0.001) did.

METHODS

In this randomized trial, twenty fifth-year medical students and 20 ophthalmic residents were enrolled and randomly assigned (1:1 allocation) into Group real OCT and Group GANs OCT. All participants had a pre-test to show their educational background, followed by a 30-minute-smartphone-based GANs/real OCT images-based education program for macular diseases recognition training. Another two tests were scheduled five minutes and one week after the training to test their short-term and long-term performances. Scores and time consumptions were recorded and compared. After all tests, an anonymous subjective questionnaire was acquired.

RESULTS

In Group GANs OCT, scores improved from 80.0(46.0, 85.5) to 92.0(81.0,95.5) five minutes after training (p<0.001) and 92.30± 5.36 one-week after training (p<0.001). Similarly, in Group real OCT, scores improved from 66.00±19.52 to 92.90± 5.71(p<0.001) and 93.20± 6.10 (p<0.001), respectively. No significantly difference were found for scores of tests, score improvements and time consumptions between Group GANs OCT and Group real OCT. Medical students had significantly higher score improvement after training than residents(p<0.001) did.

CONCLUSIONS

The education tool using synthetic OCT images had a similar educational ability compared to that using real OCT images, which improved the interpretation ability of ophthalmic residents and medical students in both short-term and long-term performances. The smartphone-based educational tool could be promoted more widely for educational applications.

CLINICALTRIAL

Chinses Clinical Trial Registry, No. ChiCTR 2100053195.