AI-assisted detection of glaucoma-related lesions in retinal photos
Official title: Validation of the Artificial Intelligence Subsystem of the DDART Medical Device for the Automated Detection of Lesions Compatible With Glaucoma in a Random Sample of Retinal Fundus Photograph
Run by Democritus University of Thrace · NCT07758569 · Data updated 2026-11-12
A device-powered AI system is being tested to see if it can automatically identify glaucoma-related lesions in retinal photos from adults.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 2000 (estimated) |
| Sponsor | Democritus University of Thrace Academic / other |
| Locations | 1 site (Alexandroupoli) |
| Status | Recruiting |
| Started | April 21, 2026 |
| Main results expected | April 19, 2027 |
| Study ends | April 19, 2027 |
| Registry record updated | August 11, 2026 |
| Trial ID | NCT07758569 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Adults 18 years and older with a high-resolution color fundus photograph and a specialist-confirmed diagnosis of glaucoma risk or presence.
✕Probably not a fit
Patients with low-quality images or eye conditions that obscure retinal features may not benefit from this AI tool.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to validate the AI subsystem of the DDART medical device for detecting glaucoma-compatible lesions in a random sample of color fundus photographs. Participants are adults with high-quality fundus images, and images with poor quality or comorbid eye diseases are excluded. The study analyzes the AI’s performance on existing images without assigning a treatment. No interventions beyond image capture are involved, and the setting is the University Hospital of Alexandroupolis under Democritus University of Thrace.
Why it matters
Potential benefit: If successful, the AI subsystem could help clinicians quickly flag glaucoma-related findings in retinal images.
How similar studies have gone: Previous studies have shown mixed but promising results for AI-assisted image analysis in ophthalmology.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Age ≥18 years. Availability of a high-resolution color fundus photograph. Confirmed diagnosis established by a specialist. Exclusion Criteria: * Poor-quality images. Coexisting ocular diseases that interfere with image interpretation.
Where it's running
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University Hospital of Alexandroupolis
Alexandroupoli, Greece Recruiting
Study contacts
- Study coordinator: Georgios Labiris
- Email: glampiri@med.duth.gr
- Phone: +302551030990
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.