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

NCT07318428 | Completed

• 1 other identifier: 2025-07-033
• Study Type: interventional
• Target: 10
• Locations: 1 country
• Sites: 5

Brief 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

Outcome Measures

Primary Outcomes (3)

• Performance of readers with and without AI assistance: Sensitivity

  Sensitivity of reader diagnoses for each of the four target diseases (DR, AMD, RVO, glaucoma) will be assessed with and without AI assistance, using the image-level reference standard as the comparator, through two reading sessions in which all 10 readers review all cases-randomised for each reader-with a washout period implemented to mitigate recall bias.

  Through study completion, approximately 2 months

• Performance of readers with and without AI assistance: Specificity

  Specificity of reader diagnoses for each of the four target diseases (DR, AMD, RVO, glaucoma) will be assessed with and without AI assistance, using the image-level reference standard as the comparator, through two reading sessions in which all 10 readers review all cases-randomised for each reader-with a washout period implemented to mitigate recall bias.

  Through study completion, approximately 2 months

• Reading time per image

  Reading time per image will be measured during both unassisted and AI-assisted interpretation sessions. For each case, the total time from the moment the image is displayed to the moment the reader submits the final disease classification will be recorded automatically by the reading platform. Mean reading time per image will be calculated for each reader and compared between the two conditions to evaluate whether AI assistance reduces interpretation time.

  Through study completion, approximately 2 months

Study Arms (2)

AI-Assisted Reading

EXPERIMENTAL

Readers interpret the fundus images with AI-generated outputs available.

Device: VUNO Med-Fundus AI

Unassisted Reading

NO INTERVENTION

Readers interpret fundus images without access to the AI system.

Interventions

VUNO Med-Fundus AI DEVICE

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).

AI-Assisted Reading

Eligibility Criteria

• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Licensed physicians qualified to interpret fundus images.
• Ophthalmologists within three years of board certification, or ophthalmology residents with no restriction on clinical experience.
• Able and willing to complete both the unassisted and AI-assisted reading sessions.
• Able to provide informed consent for participation in the reader study.
• Affiliated with one of the participating clinical sites.

Sponsors & Collaborators

• Inje University: lead
• Pusan National University Yangsan Hospital: collaborator
• Dong-A University Hospital: collaborator
• Kosin University Gospel Hospital: collaborator
• Pusan National University Hospital: collaborator

Study Sites (5)

Inje University Busan Paik Hospital

Busan, 47392, South Korea

Location

Dong-A University Hospital

Busan, 49201, South Korea

Location

Pusan National University Hospital

Busan, 49241, South Korea

Location

Kosin University Gospel Hospital

Busan, 49267, South Korea

Location

Pusan National University Yangsan Hospital

Yangsan, 50612, South Korea

Location

MeSH Terms

Conditions

Diabetic Retinopathy; Macular Degeneration; Retinal Vein Occlusion; Glaucoma; Ocular Hypertension

Condition Hierarchy (Ancestors)

Retinal Diseases; Eye Diseases; Diabetic Angiopathies; Vascular Diseases; Cardiovascular Diseases; Diabetes Complications; Diabetes Mellitus; Endocrine System Diseases; Retinal Degeneration; Venous Thrombosis; Thrombosis; Embolism and Thrombosis

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SEQUENTIAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Assistant Professor of Ophthalmology

Study Record Dates

• First Submitted: December 23, 2025
• First Posted: January 6, 2026
• Study Start: February 20, 2026
• Primary Completion: April 3, 2026
• Study Completion: May 22, 2026
• Last Updated: June 1, 2026

Record last verified: 2026-01

Data Sharing

• IPD Sharing: Will not share

Locations

KR (5)