Vision-Threatening Retinal LesionsALERT-UWFNCT07643129
Artificial Intelligence-Assisted Lesion-Based Urgent Referral Triage of Ultra-Widefield Retinal Images
A study testing AI-Assisted UWF Lesion-Based Triage System and Unassisted Interpretation in people with Vision-Threatening Retinal Lesions and Urgent Referral Retinal Findings, run by Xiamen Ophthalmology Center Affiliated to Xiamen University at 1 site in China.
Trial summary
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… Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Vision-Threatening Retinal Lesions, Urgent Referral Retinal Findings, Retinal Detachment
- What is being tested?
- AI-Assisted UWF Lesion-Based Triage System and Unassisted Interpretation
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 11 participants
- Where
- 1 siteChina
- Study dates
- 1 Jul 2026to 10 Aug 2026
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Licensed ophthalmologists
- Willing to participate as readers
- Completion of study training
Who cannot join
- Retinal specialists involved in establishing gold-standard labels
- Prior access to gold-standard labels
- Incomplete study participation
Trial locations and contacts
1 site in 1 country.
About this study
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
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.
Read the 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.
- Conditions
- Vision-Threatening Retinal Lesions, Urgent Referral Retinal Findings, Retinal Detachment, Pre-retinal Hemorrhage, Subretinal Hemorrhage, Retinal Neovascularization
- Being tested
- AI-Assisted UWF Lesion-Based Triage System, Unassisted Interpretation
- Keywords
- Artificial Intelligence, Urgent Referral, Lesion-Based Triage, Ultra-Widefield Imaging, Clinical Decision Support, Multi-Reader Multi-Case Study
- Medical subject headings
- Retinal Detachment, Retinal Neovascularization
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Assisted UWF Lesion-Based Triage SystemDiagnostic test
Readers interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations.
Unassisted InterpretationDiagnostic test
Readers interpret UWF retinal images without AI assistance.
| Study group | Role | What they receive |
|---|---|---|
| AI-Assisted Interpretation | Experimental | Readers interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations. Receives: Diagnostic Test: AI-Assisted UWF Lesion-Based Triage System |
| Unassisted Interpretation | Active comparator | Readers interpret UWF retinal images without AI assistance. Receives: Diagnostic Test: Unassisted Interpretation |
What is being measured
The primary outcome is the main question the study is designed to answer.
Correct Lesion-Based Urgent Referral Triage Rate
Proportion of reader referral decisions consistent with expert-adjudicated lesion-based urgent referral classifications.
Measured: Through study completion, up to 2 months
Secondary outcomes (6)
Sensitivity for Urgent Referral Findings
Sensitivity for correctly classifying non-urgent referral images according to expert-adjudicated lesion-based triage labels.
Measured: Through study completion, up to 2 months
Specificity for Urgent Referral Findings
Specificity for correctly classifying non-urgent referral images according to expert-adjudicated lesion-based triage labels.
Measured: Through study completion, up to 2 months
False-Negative Rate for Urgent Referral Findings
Proportion of urgent referral images incorrectly classified as non-urgent referral by readers.
Measured: Through study completion, up to 2 months
False-Positive Rate for Urgent Referral Findings
Proportion of non-urgent referral images incorrectly classified as urgent referral by readers.
Measured: Through study completion, up to 2 months
Reader Confidence Score
Reader-reported confidence level for referral decisions measured using a 5-point Likert scale, ranging from 1 (very uncertain) to 5 (very confident).
Measured: Immediately after image interpretation.
Change in Correct Urgent Referral Decisions After AI Assistance
Number and proportion of cases in which AI assistance changed an incorrect referral decision to a correct referral decision.
Measured: Through study completion, up to 2 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted11 Jun 2026
- Study start1 Jul 2026
- Primary completion10 Aug 2026
- Study completion10 Aug 2026
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Vision-Threatening Retinal LesionsStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Factorial
- Model description
- Each participating ophthalmologist will independently review a library of 600 UWF retinal images. For each reader, cases will be randomly assigned to either: * AI-assisted interpretation * Unassisted interpretation Readers will initially provide an interpretation without AI support. For AI-assigned cases, lesion-level AI findings and urgent referral recommendations will subsequently be displayed before final decision making.
- Masking
- None (open label)
- Enrolment
- 11 participants (actual)
Sponsor and investigators
- Lead sponsor
- Xiamen Ophthalmology Center Affiliated to Xiamen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, XiujuChen, Xiamen Ophthalmology Center Affiliated to Xiamen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07643129
- Sponsor's protocol ID
- XMYKZX-KY-2026-011
- Acronym
- ALERT-UWF
- Status last verified
- Sep 2026
- First submitted
- 7 Jun 2026
- Last updated
- 22 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 22 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- 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
- ClinicalTrials.gov ID
- NCT07643129
- Acronym / sponsor ID
- ALERT-UWF / XMYKZX-KY-2026-011
- Conditions
- Vision-Threatening Retinal Lesions, Urgent Referral Retinal Findings, Retinal Detachment, Pre-retinal Hemorrhage, Subretinal Hemorrhage, Retinal Neovascularization
- Keywords
- Artificial Intelligence, Urgent Referral, Lesion-Based Triage, Ultra-Widefield Imaging, Clinical Decision Support, Multi-Reader Multi-Case Study
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 11 participants (actual)
- Lead sponsor
- Xiamen Ophthalmology Center Affiliated to Xiamen UniversityUniversity, hospital or other
- Study start
- 1 Jul 2026 (actual)
- Primary completion
- 10 Aug 2026 (actual)
- Study completion
- 10 Aug 2026 (actual)
- First posted
- 11 Jun 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Primary purpose
- Diagnosis
- Allocation
- Randomised
- Intervention model
- Factorial
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Each participating ophthalmologist will independently review a library of 600 UWF retinal images. For each reader, cases will be randomly assigned to either: * AI-assisted interpretation * Unassisted interpretation Readers will initially provide an interpretation without AI support. For AI-assigned cases, lesion-level AI findings and urgent referral recommendations will subsequently be displayed before final decision making.
| Arm | Type | Receives |
|---|---|---|
| AI-Assisted Interpretation | Experimental | Diagnostic Test: AI-Assisted UWF Lesion-Based Triage SystemReaders interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations. |
| Unassisted Interpretation | Active comparator | Diagnostic Test: Unassisted InterpretationReaders interpret UWF retinal images without AI assistance. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (3 listed)
- Licensed ophthalmologists
- Willing to participate as readers
- Completion of study training
Key exclusion criteria (3 listed)
- Retinal specialists involved in establishing gold-standard labels
- Prior access to gold-standard labels
- Incomplete study participation
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Assisted UWF Lesion-Based Triage SystemReaders interpret UWF retinal images with lesion-level AI findings and urgent referral recommendations. | Diagnostic test | AI-Assisted Interpretation |
| Unassisted InterpretationReaders interpret UWF retinal images without AI assistance. | Diagnostic test | Unassisted Interpretation |
Primary outcome
Correct Lesion-Based Urgent Referral Triage Rate
Time frame: Through study completion, up to 2 months
Proportion of reader referral decisions consistent with expert-adjudicated lesion-based urgent referral classifications.
6 secondary outcomes
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
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Sep 2026.
- Individual participant dataSharing planned: Undecided
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Assisted UWF Lesion-Based Triage System and Unassisted Interpretation in people with Vision-Threatening Retinal Lesions and Urgent Referral Retinal Findings, run by Xiamen Ophthalmology Center Affiliated to Xiamen University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 22 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Correct Lesion-Based Urgent Referral Triage Rate (time frame: Through study completion, up to 2 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 22 Sep 2026.