NCT07318428

AI-Assisted Detection of Posterior Segment Diseases: DR, AMD, RVO, and Glaucoma

A Multicenter Clinical Study to Validate the Performance Improvement of Fundus Photography Reading Software

• Status: Enrolling By Invitation
• Phase: N/A
• Study type: Interventional
• Enrollment: 10 (estimated)
• Sponsor: Inje University · Academic / Other
• Sex: All
• Age: —
• Healthy volunteers: Not accepted

Summary

The purpose of this multi-center study is to evaluate the extent to which AI-assisted fundus image interpretation improves the diagnostic performance of ophthalmologists. Rather than assessing the standalone algorithm performance, this study aims to determine the clinical value of using AI as a decision-support tool within actual clinical workflows. At each participating institution, five ophthalmologists within three years of board certification and five ophthalmology residents will participate as readers. All readers will interpret fundus images both with and without the AI-based assistance software. The study will quantitatively compare diagnostic accuracy and reading time across the two conditions for four posterior segment diseases: diabetic retinopathy, age-related macular degeneration, retinal vein occlusion, and glaucoma.

Conditions

• Diabetic Retinopathy
• Age Related Macular Degeneration
• Retinal Vein Occlusion
• Glaucoma
• Glaucoma Suspect

Interventions

Type	Name	Description
DEVICE	VUNO Med-Fundus AI	The intervention consists of an AI-based fundus image interpretation software that provides automated outputs for 12 retinal and optic nerve findings (e.g., hemorrhage, exudates, drusen, optic disc change). The system does not generate a direct disease diagnosis. Instead, the AI displays the presence or absence of 12 predefined findings along with their lesion locations. Readers may use this finding-level information as decision-support when determining the presence of the four target diseases (diabetic retinopathy, age-related macular degeneration, retinal vein occlusion, and glaucoma).

Timeline

• Start date: 2026-02-20
• Primary completion: 2026-04-30
• Completion: 2026-05-30
• First posted: 2026-01-06
• Last updated: 2026-03-11

Locations

5 sites across 1 country: South Korea