NCT07291960Not yet recruiting
Retinal Clinical Assessment With AI-derived Quantitative Information
AI-derived Retinal Quantification Versus Routine Clinical Interpretation in Ophthalmic Assessment: a Randomized Controlled Trial
Source: ClinicalTrials.gov · Last updated 29 Apr 2026
Brief summary (registry, in English)
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.
- Status (registry)
- Not yet recruiting
- Study type
- Observational
- Enrollment
- 29 (estimated)
- First submitted
- 5 Dec 2025
- Start date
- 15 Apr 2026
- Primary completion date
- 15 May 2026
- Lead sponsor
- Beijing Tongren Hospital
- Diseases
- Diabetic eye disease
- NCT number
- NCT07291960
What you commit to
- Study type: Observational
- Planned participants: 29
- From 15 Apr 2026 to the primary completion date, 15 May 2026
- No sites listed in no country
- Visits and tests: ask the trial team, the registry does not list them
Built from the registry fields of ClinicalTrials.gov. It describes the study, not your situation.
Who cannot take part
Copied verbatim from ClinicalTrials.gov and grouped by topic. Only the trial team decides who can take part.
Prior treatment
- Prior involvement in the development, training, or validation of the AI system being tested.
- Prior exposure to or involvement in development of the AI system.
Other illness
- Any condition that may interfere with ability to perform study tasks (e.g., prolonged absence).
- Expert Evaluators
Other
- Clinician Participants
- Lack of experience in interpreting fundus images (e.g., interns, medical students).
- Inability to complete reporting tasks due to time constraints or technical limitations.
- Participation in the intervention or control reporting arms.
- Any conflict of interest affecting impartiality of report quality evaluation.
- Fundus Images
- Poor-quality images with insufficient clarity for interpretation.
- Images containing artifacts or cropping that prevent accurate segmentation or assessment.
- Images with any remaining patient identifiers (excluded to maintain confidentiality).
Who the study is looking for
- 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.
- Fundus Images (Data Inputs)
- Retinal fundus photographs of sufficient quality for clinical interpretation.
- Images representing a range of common retinal findings (normal or abnormal).
- Previously collected, de-identified images with no patient-identifiable information.
Sex: All · Accepts healthy volunteers
This page is information, not medical advice. Discuss any trial with your doctor.