AI-Assisted Interpretation of Ultra-Widefield Retinal Images

NCT07651943 | Completed

• 1 other identifier: XMYKZX-KY-2026-008
• Study Type: observational
• Target: 462
• Locations: 1 country
• Sites: 5

Brief Summary

The goal of this prospective observational study is to evaluate the impact of artificial intelligence (AI) assistance on clinician interpretation of ultra-widefield (UWF) retinal images. The main questions it aims to answer are: whether AI assistance improves the diagnostic performance of ophthalmologists in detecting retinal findings on UWF retinal images; whether AI assistance improves sensitivity, specificity, and inter-reader agreement across clinicians with different levels of experience. Approximately 600 UWF retinal images prospectively collected from multiple ophthalmic centers in China will be included. Images will be independently annotated by expert retinal specialists to establish reference labels for retinal finding categories. Four ophthalmologists with different levels of clinical experience, including one senior retinal specialist and three junior ophthalmologists, will participate in a crossover multi-reader study. For each clinician, the dataset will be randomly divided into two equal subsets. During the first reading session, clinicians will evaluate one subset without AI assistance and the other subset with AI assistance. After a washout interval of at least two weeks, the reading conditions will be reversed in a second reading session with independently randomized image order. Under the AI-assisted condition, clinicians will be provided with category-level AI prediction probabilities for retinal findings. No localization maps, heatmaps, segmentation overlays, or automated diagnostic recommendations will be displayed. Clinicians will retain full autonomy over final decisions. Reader performance under AI-assisted and unaided conditions will be compared using expert reference annotations as the ground truth.

Conditions

Retinal Disease

Keywords

Artificial Intelligence; Ultra-Widefield Imaging; Retinal Imaging; Reader Study; Diagnostic Performance; AI-Assisted Diagnosis

Outcome Measures

Primary Outcomes (2)

• Sensitivity for retinal finding detection

  Sensitivity of clinicians in detecting retinal finding categories under AI-assisted and unaided conditions using expert annotations as the reference standard.

  through study completion, an average of 2 months

• Specificity for retinal finding detection

  Specificity of clinicians in detecting retinal finding categories under AI-assisted and unaided conditions.

  through study completion, an average of 2 months

Secondary Outcomes (3)

• Area under the receiver operating characteristic curve (AUC)

  through study completion, an average of 2 months

• Inter-reader agreement

  At study completion (up to 3 months)

• Diagnostic performance improvement among junior ophthalmologists

  At study completion (up to 3 months)

Study Arms (2)

AI-Assisted Interpretation

Clinicians interpret ultra-widefield retinal images with access to AI-generated category-level prediction probabilities for retinal findings.

Device: AI-Assisted Interpretation

Unaided Interpretation

Clinicians interpret ultra-widefield retinal images without AI assistance using routine retinal image interpretation alone.

Device: Unaided Interpretation

Interventions

AI-Assisted Interpretation DEVICE

Clinicians interpret ultra-widefield retinal images with access to AI-generated category-level prediction probabilities for retinal findings.

AI-Assisted Interpretation

Unaided Interpretation DEVICE

Clinicians interpret ultra-widefield retinal images without AI assistance using routine retinal image interpretation alone.

Unaided Interpretation

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Participants undergoing clinically indicated ultra-widefield retinal imaging at participating ophthalmic centers in China, including individuals with diverse retinal diseases and retinal findings encountered in real-world clinical practice.

You may qualify if:

• Participants undergoing ultra-widefield retinal imaging at participating ophthalmic centers;

You may not qualify if:

• Poor-quality or ungradable retinal images;

Sponsors & Collaborators

• Xiamen Ophthalmology Center Affiliated to Xiamen University: lead

Study Sites (5)

Chongqing Huaxia Eye Hospital

Chongqing, Chongqing Municipality, China

Location

Fuzhou Eye Hospital

Fuzhou, Fujian, 361000, China

Location

Xiamen Eye Center of Xiamen University

Xiamen, Fujian, 361000, China

Location

Hengshui Tongrui Eye Hospital

Hengshui, Hebei, China

Location

Heze Huaxia Eye Hospital

Heze, Shandong, China

Location

MeSH Terms

Conditions

Retinal Diseases

Condition Hierarchy (Ancestors)

Eye Diseases

Study Officials

• Xiuju Chen

  Xiamen Eye Center of Xiamen University

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Investigator

Study Record Dates

• First Submitted: June 5, 2026
• First Posted: June 16, 2026
• Study Start: January 1, 2026
• Primary Completion: February 1, 2026
• Study Completion: February 10, 2026
• Last Updated: June 16, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will not share

Locations

CN (5)