Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage of Ultra-Widefield Retinal Images
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: AI-Assisted UWF Lesion-Based Triage System, Unassisted Interpretation.
- Who it may be relevant to
- Registry conditions: Vision-Threatening Retinal Lesions, Urgent Referral Retinal Findings, Retinal Detachment, Pre-retinal Hemorrhage. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
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
Overview
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.
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.
Interventions
- Diagnostic test AI-Assisted UWF Lesion-Based Triage System
Readers interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations. - Diagnostic test Unassisted Interpretation
Readers interpret UWF retinal images without AI assistance.
Primary outcome measures
- Correct Lesion-Based Urgent Referral Triage Rate [Time frame: Through study completion, up to 2 months]
Secondary outcome measures (6)
- Sensitivity for Urgent Referral Findings [Time frame: Through study completion, up to 2 months]
- Specificity for Urgent Referral Findings [Time frame: Through study completion, up to 2 months]
- False-Negative Rate for Urgent Referral Findings [Time frame: Through study completion, up to 2 months]
- False-Positive Rate for Urgent Referral Findings [Time frame: Through study completion, up to 2 months]
- Reader Confidence Score [Time frame: Immediately after image interpretation.]
- Change in Correct Urgent Referral Decisions After AI Assistance [Time frame: Through study completion, up to 2 months]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- Randomized
- Model
- Factorial
- Masking
- Open label
- Primary purpose
- Diagnostic
Study locations
Center list to be confirmed — check the primary protocol.
Identifiers
NCT: NCT07643129 · XMYKZX-KY-2026-011