High-throughput Large-model-based AI-assisted Diagnosis Using OCT

NCT07249307 | Not Yet Recruiting

• 1 other identifier: K9164
• Study Type: observational
• Target: 2,000
• Locations: 0 countries
• Sites: N/A

Brief Summary

This observational study aims to establish key technologies for high-throughput, large-model-based AI-assisted diagnosis using optical coherence tomography (OCT) and OCT angiography (OCTA). The study will collect real-world OCT/OCTA images and corresponding clinical information from patients with common blinding retinal and optic nerve diseases at Peking Union Medical College Hospital. A high-throughput diagnostic framework based on large-scale artificial intelligence models will be developed and evaluated. The primary objective is to determine the diagnostic performance of the AI system, including its ability to identify diabetic retinopathy, branch retinal vein occlusion, central retinal vein occlusion, age-related macular degeneration, pathologic myopic choroidal neovascularization, and glaucoma-related optic nerve damage. The results of this study are expected to support the development of standardized, efficient, and scalable AI-assisted diagnostic pathways for OCT imaging in clinical practice.

Conditions

Diabetic Retinopathy (DR); Retinal Vein Occlusion (RVO); Age-Related Macular Degeneration (AMD); Pathologic Myopia; Glaucoma

Outcome Measures

Primary Outcomes (1)

• Diagnostic performance of the AI-assisted OCT/OCTA model (AUC for multi-disease classification)

  Area under the receiver operating characteristic curve (AUC) of the high-throughput large-model-based OCT/OCTA diagnostic system for identifying major retinal and optic nerve diseases, including diabetic retinopathy, branch retinal vein occlusion, central retinal vein occlusion, age-related macular degeneration, pathologic myopic choroidal neovascularization, and glaucoma.

  Baseline imaging visit (time of image acquisition and model inference).

Secondary Outcomes (2)

• Sensitivity and specificity of the AI-assisted OCT/OCTA model

  At the time of image acquisition and model inference (baseline imaging visit).

• Agreement between AI-assisted diagnosis and clinician diagnosis

  At the time of image acquisition and model inference (baseline imaging visit).

Study Arms (6)

Diabetic Retinopathy Cohort

Patients undergoing routine OCT/OCTA examinations with clinically diagnosed diabetic retinopathy.

Other: No intervention

Branch Retinal Vein Occlusion Cohort

Patients with BRVO receiving standard clinical imaging evaluation.

Other: No intervention

Central Retinal Vein Occlusion Cohort

Patients with CRVO undergoing OCT/OCTA imaging as part of routine care.

Other: No intervention

Age-related Macular Degeneration Cohort

Patients diagnosed with AMD and evaluated using OCT/OCTA.

Other: No intervention

Pathologic Myopia with Choroidal Neovascularization Cohort

Patients with pathologic myopia and CNV who undergo OCT/OCTA imaging.

Other: No intervention

Glaucoma Cohort

Patients with glaucoma-related optic nerve damage undergoing OCT/OCTA imaging.

Other: No intervention

Interventions

No intervention OTHER

This observational study involves no experimental intervention. All OCT and OCTA examinations are performed as part of routine clinical care, and the study only analyzes retrospectively and prospectively collected imaging and clinical data to evaluate a large-model-based AI diagnostic system.

Age-related Macular Degeneration Cohort; Branch Retinal Vein Occlusion Cohort; Central Retinal Vein Occlusion Cohort; Diabetic Retinopathy Cohort; Glaucoma Cohort; Pathologic Myopia with Choroidal Neovascularization Cohort

Eligibility Criteria

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

Study Population

This study population consists of patients who undergo OCT and/or OCT angiography (OCTA) examinations as part of routine clinical care at Peking Union Medical College Hospital. Eligible participants are clinically diagnosed with one or more of the following conditions: diabetic retinopathy, branch retinal vein occlusion, central retinal vein occlusion, age-related macular degeneration, pathologic myopia with choroidal neovascularization, or glaucoma with optic nerve damage. Both retrospectively collected and prospectively enrolled patients are included. No healthy volunteers or experimental interventions are involved.

You may qualify if:

• \. Patients of any age or sex who undergo OCT and/or OCT angiography (OCTA) examinations as part of routine clinical care at Peking Union Medical College Hospital.
• \. Clinical diagnosis of at least one of the following conditions: Diabetic retinopathy, Branch retinal vein occlusion, Central retinal vein occlusion, Age-related macular degeneration, Pathologic myopia with choroidal neovascularization and Glaucoma with optic nerve damage.
• \. Imaging quality sufficient for analysis based on predefined OCT/OCTA quality control criteria.
• \. Ability to provide informed consent (for prospective participants), or availability of medical records that meet institutional ethical requirements (for retrospective data).

You may not qualify if:

• \- 1. Poor-quality OCT/OCTA images that do not meet analysis standards (e.g., severe motion artifacts, media opacity, incomplete scans).
• \. Patients unable to cooperate with standard ophthalmic imaging procedures. 3. Any condition judged by investigators to preclude accurate imaging evaluation or reliable diagnostic interpretation.

Sponsors & Collaborators

• Peking Union Medical College Hospital: lead

MeSH Terms

Conditions

Diabetic Retinopathy; Retinal Vein Occlusion; Macular Degeneration; Glaucoma

Condition Hierarchy (Ancestors)

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

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 18, 2025
• First Posted: November 25, 2025
• Study Start: November 30, 2025
• Primary Completion (Estimated): June 15, 2028
• Study Completion (Estimated): December 31, 2028
• Last Updated: November 25, 2025

Record last verified: 2025-11