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COMPLETED
NCT07651943

AI-Assisted Interpretation of Ultra-Widefield Retinal Images

Sponsor: Xiamen Ophthalmology Center Affiliated to Xiamen University

View on ClinicalTrials.gov

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.

Official title: Prospective Multi-Center Evaluation of AI-Assisted Interpretation of Ultra-Widefield Retinal Images in a Multi-Reader Crossover Study

Key Details

Gender

All

Age Range

18 Years - Any

Study Type

OBSERVATIONAL

Enrollment

462

Start Date

2026-01-01

Completion Date

2026-02-10

Last Updated

2026-06-16

Healthy Volunteers

Yes

Conditions

Interventions

DEVICE

AI-Assisted Interpretation

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

DEVICE

Unaided Interpretation

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

Locations (5)

Chongqing Huaxia Eye Hospital

Chongqing, Chongqing Municipality, China

Fuzhou Eye Hospital

Fuzhou, Fujian, China

Xiamen Eye Center of Xiamen University

Xiamen, Fujian, China

Hengshui Tongrui Eye Hospital

Hengshui, Hebei, China

Heze Huaxia Eye Hospital

Heze, Shandong, China