Development and Validation of a Deep Learning-based Myopia and Myopic Maculopathy Detection and Prediction System

Myopia Clinical Trial

Official title:

Development and Validation of a Deep Learning-based Myopia and Myopic Maculopathy Detection and Prediction System

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT05835115
• Other study ID #: 2022SQ023
• Status: Completed
• Start date: April 1, 2022
• Est. completion date: April 1, 2023

Study information

• Verified date: April 2023
• Source: Shanghai Eye Disease Prevention and Treatment Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Myopia has become a global public health issue. Myopia affects the psychological health of children and adolescents and poses a financial burden. Therefore, early detection and prediction of children at a high risk of myopia development and progression are critical for precise and effective interventions. In this study, we developed a deep learning system DeepMyopia, based on fundus images with the following objectives: 1) to predict myopia onset and progression; 2) To detect myopic macular degeneration for AI-assisted diagnosis; 3) To predict the development of myopic macular degeneration; 4) evaluate its cost-effectiveness.

Description:

Myopia has become a global public health issue. Myopia affects the psychological health of children and adolescents and poses a financial burden. Furthermore, as myopia progresses it increases the risk of ocular complications such as myopic macular degeneration, leading to irreversible visual impairment or even blindness. According to the World Health Organization , more than 1 billion people worldwide are living with vision impairment caused by myopia, hyperopia, and other problems due to late detection. Therefore, early detection and prediction of children at a high risk of myopia development and progression are critical for precise and effective interventions.

In this study, we developed a deep learning system DeepMyopia, based on fundus images with the following objectives: 1) to predict myopia onset and progression; 2) To detect myopic macular degeneration for AI-assisted diagnosis; 3) To predict the development of myopic macular degeneration; 4) evaluate its cost-effectiveness.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 30526
• Est. completion date: April 1, 2023
• Est. primary completion date: April 1, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 4 Years to 18 Years

Eligibility

Inclusion Criteria:

1. Subjects with fundus images in the Shanghai Child and Adolescent Large-scale Eye Study (SCALE) ;

2. Subjects with fundus images in the Shanghai Time Outside to Reduce Myopia [STORM] trial;

3. Subjects with fundus images in the High Myopia Registration Study [SCALE-HM]

4. Subjects with fundus images in the Shanghai Myopia Screening (SMS) Study;

5. Subjects with fundus images in the Beijing Children Eye Study

6. Subjects with fundus images in the First Affiliated Hospital of Kunming Medical University;

7. Subjects with fundus images at the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University;

8. Subjects with fundus images at the Ophthalmology Department of the Affiliated Hospital of Inner Mongolia Medical University;

9. Subjects with fundus images at Zhongshan Eye Centre, Sun Yat-sen University;

10. Subjects with fundus images in the Hong Kong Children Eye Study;

Exclusion Criteria:

• Participants with poor-quality fundus images

Related Conditions & MeSH terms

• Macular Degeneration
• Myopia
• Myopic Macular Degeneration

Intervention

Diagnostic Test:
• A deep learning-based myopia and myopic maculopathy detection and prediction system
This deep learning system is capable of analyzing fundus images for myopia staging, myopic maculopathy detection, cycloplegic refraction estimation and prediction, and risk stratification of myopia and myopic maculopathy onset.

Locations

Country	Name	City	State
China	Shanghai Eye Disease Prevention and Treatment Center	Shanghai	Shanghai

Sponsors (9)

Lead Sponsor	Collaborator
Shanghai Eye Disease Prevention and Treatment Center	Beijing Friendship Hospital, Chinese University of Hong Kong, First Affiliated Hospital of Kunming Medical University, First Affiliated Hospital of Xinjiang Medical University, Peking Union Medical College Hospital, Shanghai Jiao Tong University School of Medicine, The Affiliated Hospital of Inner Mongolia Medical University, Zhongshan Ophthalmic Center, Sun Yat-sen University

Country where clinical trial is conducted

China, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	myopia staging detection possibility score	output of myopia staging task	immediately after inputting the data
Primary	myopic maculopathy detection possibility score	output of myopic maculopathy detection task	immediately after inputting the data
Primary	predicted spherical equivalent	output of assessing spherical equivalent task	immediately after inputting the data
Primary	predicted future annual spherical equivalent	output of predicting future spherical equivalent task	immediately after inputting the data
Primary	risk score of myopia and myopic maculopathy progression	output of the progression of myopia and myopic maculopathy predicion task	immediately after inputting the data