Retinal Clinical Assessment With AI-derived Quantitative Information (NCT07291960) | Clinical Trial Compass
Not Yet RecruitingNot Applicable
Retinal Clinical Assessment With AI-derived Quantitative Information
29 participantsStarted 2026-04-15
Plain-language summary
This randomized controlled trial evaluates whether providing clinicians with AI-derived quantitative retinal information improves the quality and efficiency of retinal clinical assessment. Participating ophthalmologists and ophthalmology trainees will be randomly assigned to one of two groups. The intervention group will write clinical reports with access to automated quantitative measurements generated from fundus image analysis, including multiple retinal structural and vascular biomarkers. The control group will complete the same reporting tasks using only the original fundus images without AI-generated quantitative information.
All reports produced by both groups will be de-identified and independently evaluated by a separate panel of senior ophthalmologists who are blinded to group allocation. The expert evaluators will assess report accuracy, completeness, clarity, and overall clinical quality using predefined scoring criteria. The study aims to determine whether access to quantitative retinal biomarkers enhances clinicians' reporting performance and reduces reporting time during retinal assessment tasks.
Who can participate
SexALL
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Inclusion criteria
✓. Board-certified ophthalmologists or ophthalmology trainees (registrars or fellows) with clinical experience in interpreting fundus images.
✓. Capable of independently completing retinal clinical reports based on fundus photography.
✓. Willing and able to participate in the study tasks (report writing) under assigned study conditions.
✓. Able to provide informed consent.
✓. Senior ophthalmologists with at least 5 years of post-certification clinical experience.
✓. Not involved in the report-writing stage of the study.
✓. Willing to evaluate de-identified reports across predefined quality dimensions.
✓. Able to provide informed consent.
Exclusion criteria
✕. Lack of experience in interpreting fundus images (e.g., interns, medical students).
✕. Prior involvement in the development, training, or validation of the AI system being tested.
✕
What they're measuring
1
Expert-rated clinical report quality
Timeframe: Assessed after completion of all reporting tasks (approximately 1-2 weeks per participant)