Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage of Ultra-Widefield Retinal Images: A Multi-Reader Multi-Case Randomized Reader Study (ALERT-UWF)

June 7, 2026 updated by: XiujuChen, Xiamen Ophthalmology Center Affiliated to Xiamen University

Clinical Utility of an Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage System for Ultra-Widefield Retinal Images: A Prospective Multi-Reader Multi-Case Randomized Reader Study

his study evaluates the clinical utility of an artificial intelligence (AI)-assisted lesion-based urgent referral triage system for ultra-widefield (UWF) retinal images.

Unlike disease-classification systems, the AI system identifies predefined vision-threatening retinal findings and generates lesion-level urgent referral recommendations. Participating ophthalmologists will evaluate UWF retinal images under randomized AI-assisted and unassisted conditions.

The primary objective is to determine whether lesion-based AI assistance improves urgent referral triage performance compared with unaided image interpretation.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Detailed Description

Ultra-widefield retinal imaging is increasingly used for retinal disease screening and referral triage. Many vision-threatening retinal abnormalities require timely identification and referral to retinal specialists.

The AI system evaluated in this study is designed as a lesion-based triage tool rather than a disease-diagnosis system. The model identifies predefined urgent referral retinal findings and generates referral recommendations based on lesion-level evidence.

Urgent referral findings include:

  • Retinal detachment
  • Untreated retinal tear or retinal hole
  • Vitreous hemorrhage
  • Pre-retinal hemorrhage
  • Subretinal hemorrhage
  • Retinal neovascularization
  • Optic disc neovascularization
  • Tractional fibrovascular membrane Treated retinal tears associated with laser barricade scars are classified as non-urgent referral findings.

A total of 600 UWF retinal images acquired using Zeiss and Optos imaging systems will be included.

Participating ophthalmologists will independently evaluate images in randomized AI-assisted and unassisted settings.

The primary objective is to determine whether AI assistance improves lesion-based urgent referral triage accuracy.

Study Type

Interventional

Enrollment (Estimated)

8

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Description

Inclusion Criteria:

  • Licensed ophthalmologists
  • Willing to participate as readers
  • Completion of study training

Exclusion Criteria:

  • Retinal specialists involved in establishing gold-standard labels
  • Prior access to gold-standard labels
  • Incomplete study participation

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Randomized
  • Interventional Model: Factorial Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: AI-Assisted Interpretation
Readers interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations.
Diagnostic test: AI-Assisted UWF Lesion-Based Triage System
Readers interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations.
Active Comparator: Unassisted Interpretation
Readers interpret UWF retinal images without AI assistance.
Diagnostic test: Unassisted Interpretation
Readers interpret UWF retinal images without AI assistance.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Correct Lesion-Based Urgent Referral Triage Rate
Time Frame: Immediately after image interpretation.
Proportion of reader referral decisions consistent with expert-adjudicated lesion-based urgent referral classifications.
Immediately after image interpretation.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Sensitivity for Urgent Referral Findings
Time Frame: Immediately after image interpretation.
Sensitivity for Urgent Referral Findings
Immediately after image interpretation.
Specificity for Urgent Referral Findings
Time Frame: Immediately after image interpretation.
Specificity for correctly classifying non-urgent referral images according to expert-adjudicated lesion-based triage labels.
Immediately after image interpretation.
False-Negative Rate for Urgent Referral Findings
Time Frame: Immediately after image interpretation.
Proportion of urgent referral images incorrectly classified as non-urgent referral by readers.
Immediately after image interpretation.
False-Positive Rate for Urgent Referral Findings
Time Frame: Immediately after image interpretation.
Proportion of non-urgent referral images incorrectly classified as urgent referral by readers.
Immediately after image interpretation.
Reader Confidence Score
Time Frame: Immediately after image interpretation.
Reader-reported confidence level for referral decisions measured using a 5-point Likert scale, ranging from 1 (very uncertain) to 5 (very confident).
Immediately after image interpretation.
Change in Correct Urgent Referral Decisions After AI Assistance
Time Frame: Immediately after image interpretation.
Number and proportion of cases in which AI assistance changed an incorrect referral decision to a correct referral decision.
Immediately after image interpretation.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Xiamen Ophthalmology Center Affiliated to Xiamen University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

June 15, 2026

Primary Completion (Estimated)

June 25, 2026

Study Completion (Estimated)

June 30, 2026

Study Registration Dates

First Submitted

June 7, 2026

First Submitted That Met QC Criteria

June 7, 2026

First Posted (Actual)

June 11, 2026

Study Record Updates

Last Update Posted (Actual)

June 11, 2026

Last Update Submitted That Met QC Criteria

June 7, 2026

Last Verified

June 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • XMYKZX-KY-2026-011

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Retinal Detachment

Clinical Trials on AI-Assisted UWF Lesion-Based Triage System

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Japan

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

Subscribe