AIMDR: ARTIFICIAL INTELLIGENCE FOR MASS SCREENING OF THE DIABETIC RETINOPATHY IN THE CHERNIVTSI REGION (Pilot Study)

Sponsor

The Filatov Institute of Eye Diseases and Tissue Therapy (Other)

Overall Status

Recruiting

CT.gov ID

NCT06112691

Collaborator

Komisarenko Institute of Endocrinology and Metobolism (Other), CheckEye LLC (Industry)

660

Enrollment

Location

Anticipated Duration (Months)

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

The purpose of this study is to create a patient-centric environment for early detection of DR with AI-driven solutions.

Condition or Disease	Intervention/Treatment	Phase
Diabetic Retinopathy	Device: taking fundus photos using non-mydriatic fundus camera - FundusScope Rodenstock

Detailed Description

The purpose of this study is to create a patient-centric environment for early detection of DR with AI-driven solutions.

This study is planned as a follow-up. Participants who meet the eligibility criteria will be recruited from sites staffed by the trained photographers. After assessing eligibility and securing written informed consent, fundus photographs will be captured using a nonmydriatic ocular fundus camera. Images will be taken according to a specific RAssbyAI Check Eye's imaging protocol provided to camera operator, and then analyzed by the RAssbyAI Check Eye's. The photography protocol consists of two images of the ocular fundus (one optic disc centered, one fovea centered).

Study Design

Study Type:

Observational

Anticipated Enrollment :

660 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

USING ARTIFICIAL INTELLIGENCE FOR MASS SCREENING OF THE DIABETIC RETINOPATHY

Actual Study Start Date :

Feb 1, 2022

Anticipated Primary Completion Date :

Oct 1, 2024

Anticipated Study Completion Date :

Nov 1, 2024

Arms and Interventions

Arm	Intervention/Treatment
main group diabetes mellitus	Device: taking fundus photos using non-mydriatic fundus camera - FundusScope Rodenstock using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.
control group without diagnosis of diabetes mellitus without retinal diseases	Device: taking fundus photos using non-mydriatic fundus camera - FundusScope Rodenstock using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.

Arm

Intervention/Treatment

main group

diabetes mellitus

Device: taking fundus photos using non-mydriatic fundus camera - FundusScope Rodenstock

using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.

control group

without diagnosis of diabetes mellitus without retinal diseases

Device: taking fundus photos using non-mydriatic fundus camera - FundusScope Rodenstock

using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.

Outcome Measures

Primary Outcome Measures

The accuracy [Baseline-Month 12]
The accuracy of detecting of DR

Secondary Outcome Measures

The percent of invalid images [Baseline-Month 12]
The percent of invalid images for analysing by neural network
The percent of false positive detection of DR [Baseline-Month 12]
The percent of false positive detection of DR in individuals without DR

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years to 90 Years

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Yes

Inclusion Criteria:

Documented diagnosis of Diabetes mellitus as defined by:

Having met the criteria established by either the World Health Organization (WHO) or the American Diabetes Association (ADA) B. Hemoglobin A1c (HbA1c)>= 6.5% based on repeated assessments C. Fasting Plasma Glucose (FPG) >= 126 mg/dL (7.0 mmol/L) based on repeated assessments D. Oral Glucose Tolerance test with 2 hr plasma glucose >= 200 mg/dL (11.1mmol/L) using equivalent of 75g anhydrous glucose dose in water.
Symptoms of hyperglycemia or hyperglycemic crisis with random plasma glucose

=200mg/dL (11.1 mmol/L).

Understanding of the Study and willingness and ability to sign informed consent
Patient age 18 or above
Diagnostic for diabetes: 4a) Type 1 diabetes of a lest 5 years of evolution; or 4b) Type 2 diabetes

Exclusion Criteria:

Patients under 18 years of age;
Failure to give informed consent;
Presence of retinal diseases - acquired disease: age-related macular degeneration (AMD), occlusion of retinal vessels (ORV), etc.; birth defects: coloboma of choroid or optic nerve disc, etc.; hereditary diseases: retinitis pigmentosa, angioid streaks of the retina, etc.
A patient who has already undergone treatment (surgery, laser, etc.) for any disease of the retina: age-related macular degeneration (AMD), retinal vascular occlusion (ARV), etc. These patients should be excluded or allocated to a separate group.