AI-derived Retinal Quantification Versus Routine Clinical Interpretation in Ophthalmic Assessment: a Randomized Controlled Trial
Overview
- Phase
- Not Applicable
- Status
- Not yet recruiting
- Sponsor
- Beijing Tongren Hospital
- Enrollment
- 21
- Primary Endpoint
- Expert-rated clinical report quality
Overview
Brief 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.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Sex
- All
- Accepts Healthy Volunteers
- Yes
Inclusion Criteria
- •Clinician Participants (Report Writers)
- •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.
- •Expert Evaluators (Outcome Assessors)
- •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
- •Clinician Participants
- •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.
- •Inability to complete reporting tasks due to time constraints or technical limitations.
- •Any condition that may interfere with ability to perform study tasks (e.g., prolonged absence).
- •Expert Evaluators
- •Participation in the intervention or control reporting arms.
- •Prior exposure to or involvement in development of the AI system.
- •Any conflict of interest affecting impartiality of report quality evaluation.
- •Fundus Images
Outcomes
Primary Outcomes
Expert-rated clinical report quality
Time Frame: Assessed after completion of all reporting tasks (approximately 1-2 weeks per participant)
All clinical reports generated by clinicians in both the AI-assisted and control groups will be anonymized and independently evaluated by a separate panel of senior ophthalmologists who are blinded to group allocation. The expert evaluators will score each report using predefined criteria assessing accuracy, completeness, clarity, consistency with the fundus image, and overall clinical quality. Scores will be recorded using a standardized multi-dimensional rating scale. The primary outcome is the mean overall quality score per report.
Secondary Outcomes
No secondary outcomes reported