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AI-Empowered Fundus Platform

AI-Empowered Fundus Imaging: Building an Intelligent Platform for Diagnosis, Treatment, and Early Warning of Fundus Diseases

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT07424755
Enrollment
1000
Registered
2026-02-20
Start date
2024-10-01
Completion date
2026-12-01
Last updated
2026-02-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

High Myopia

Brief summary

According to estimates by the World Health Organization, approximately half of the global adult population currently suffers from varying degrees of myopia. In urban areas of China, the myopia rate among primary school students has reached about 40%, and can exceed 80% in high school students. The proportion of patients with high myopia (refractive error greater than 600 degrees) is also increasing year by year. This group is more prone to severe visual problems, including an increased risk of complications such as cataracts, glaucoma, and macular degeneration. Pathological myopia is the main risk factor for vision loss caused by high myopia. In such patients, the elongation of the ocular axis leads to local thinning and protrusion of the posterior pole of the eyeball, forming a posterior scleral staphyloma. Posterior scleral staphyloma is the most representative pathological feature of pathological myopia. Local dilation of the choroid leads to thinning and stretching of the retina, which may ultimately cause problems such as macular retinal schisis, seriously affecting vision and even leading to blindness. This project aims to develop a multimodal intelligent screening system by combining the excellent imaging technology and advanced artificial intelligence (AI) of the Optos non-mydriatic ultra-wide-angle laser scanning ophthalmoscope, B-scan ultrasonography ophthalmic diagnostic instrument, and optical coherence tomography (OCT). The system is designed to achieve precise identification and assessment of ocular fundus diseases, especially pathological myopia, and particularly the core condition of posterior scleral staphyloma (PSS). Simultaneously, a vision prediction model will be constructed to assist doctors in formulating personalized diagnosis and treatment strategies, predicting the trend of vision deterioration, and enhancing the effectiveness of early intervention. This system is expected to significantly improve the prevention and control of pathological myopia, reduce the risk of blindness, and play a pivotal role in telemedicine services, benefiting people in remote areas and promoting public health equity and service quality.

Interventions

DIAGNOSTIC_TESTMultimodal Ocular Imaging and Biometry with Aritifical Intelligence Analysis

The patient underwent a complete set of fundus color photography, B-scan ultrasonography, and OCT imaging during the consultation, and preoperative baseline data, including demographic information, health status, ophthalmic history, and ocular biometric parameters, were collected and recorded in detail

Sponsors

Shanghai 10th People's Hospital
Lead SponsorOTHER

Study design

Observational model
CASE_ONLY
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

Patients with a diagnosis of cataract and high myopia and posterior staphyloma, who underwent comprehensive ophthalmic examinations including ultra-widefield fundus photography (Optos), B-scan ultrasonography, and optical coherence tomography (OCT). Baseline data, including demographics, health status, ophthalmic history, and ocular biometric parameters, were completely documented.

Exclusion criteria

Patients with poor-quality images affecting PSS identification, severe coexisting ocular diseases including glaucoma, diabetic retinopathy that cause media opacities, or severe systemic diseases that could interfere with the study outcomes.

Design outcomes

Primary

MeasureTime frameDescription
Data collection outcomeFrom October 2024 to April 2026 (Data collection from patients who visited the hospital before October 2024)Demographic data clasification of posterior scleral staphyloma visual acuity and imaging data

Secondary

MeasureTime frameDescription
AI modeling AnalysisFrom April 2026 to October 2026Diagnostic performance of the AI model for posterior scleral staphyloma. Area under the receiver operating characteristic curve (AUC-ROC) of the AI model. Accuracy, sensitivity, and specificity of the model in detecting posterior scleral staphyloma. Comparison of AI performance and doctors' performance

Countries

China

Contacts

CONTACTyiwen Hu
1006108590@qq.com+86 18019320181

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 21, 2026