A Blinded, Self-control Trial to Evaluate an Artificial Intelligence Based CAD System for Diabetic Retinography

Chinese Academy of Medical Sciences & Peking Union Medical College

Status: Completed

Conditions: Diabetic Retinopathy

Treatments: Device: DR Grading with CAD; Other: DR Grading by expert panel

Study type: Interventional

Funder types: Other

Identifiers

NCT03973762

GTR201-Clinical

Details and patient eligibility

About

To evaluate the safety and performance of an innovative artificial intelligence based Computer-Aided Diagnosis(CAD) system for diabetic retinography, Retinal images of patients with diabetes mellitus or diabetic retinopathy(DR) were collected retrospectively. All images were graded by a retinal specialists expert panel and the CAD device using the International Clinical Diabetic Retinopathy severity scale criteria. Investigator responsible for DR grading by CAD system is blinded to the DR grading results from the expert panel. Finally, DR grading results of the CAD system and experts were compared using sensitivity and specificity.

Full description

1. Retinal images were collected retrospectively according to the following inclusion/exclusion criterion:

   Inclusion Criterion:

   Clinical history of diabetes mellitus or diabetic retinopathy; Fully Gradable Images; around 45° field which covers optic disc and macula; complete patient identification information;

   Exclusion Criterion:

   incomplete patient identification information;

2. DR grading by expert panel At first, retinal images are graded by three experts independently, then they met for a consensus meeting to discuss cases without initial agreement. If they can't achieve consensus, a final decision is made by the principal investigator. Experts give a grading of both DR and Diabetic Macular Edema (DME) for each image according to the International Clinical Diabetic Retinopathy severity scale criteria and hard exudates around optic disc.

3. Blinding and DR grading by CAD system Before DR grading by CAD system, a randomized identification(ID) is assigned to each retinal image, which ensures that investigator responsible for CAD system operation is masked to the expert panel grading result. Both DR and DME grading is generated by the CAD system and the results are exported.

4. Unblinding Finally, all data are unblinded and results of the CAD system are compared to the results of human grading, which is considered the gold standard, using measures as sensitivity and specificity;

Enrollment: 1,081 patients

Sex: All

Volunteers: No Healthy Volunteers

Inclusion criteria

• Clinical history of diabetes mellitus or diabetic retinopathy;
• Fully Gradable Images;
• around 45° field which covers optic disc and macula;
• complete patient identification information;

Exclusion criteria

• incomplete patient identification information

Trial design

Primary purpose: Diagnostic

Allocation: Non-Randomized

Interventional model: Parallel Assignment

Masking: Single Blind

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1,081 participants in 2 patient groups

DR Grading with CAD

Experimental group

Description:

DR Grading with CAD

Treatment:

Device: DR Grading with CAD

DR Grading by expert panel

Other group

Description:

DR Grading by expert panel

Treatment:

Other: DR Grading by expert panel