Diabetic RetinopathyARTDRNCT06879834
Assessing of Artificial Intelligence-based Software Platform for Diabetic Retinopathy Screening
An observational study of Diabetic Retinopathy, run by The Filatov Institute of Eye Diseases and Tissue Therapy at 1 site in Ukraine.
Trial summary
To examine the potential for the detection of diabetic retinopathy (DR) using the artificial intelligence (AI)-based software platform Retina-AI. Read more about this study
- Who is it for?
- Ages 18 to 90 yearsHealthy volunteers can take part
- Conditions the study is for
- Diabetic Retinopathy
- What is being tested?
- taking fundus photos using non-mydriatic fundus camera
- Type of treatment
- Medical device
- How many people
- 200 participants
- Where
- 1 siteUkraine
- Study dates
- 2 Nov 2024to Dec 2025
- Phase
- Observational
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 90 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: 200 participants were planed to include in study, 100 of them had diabetes mellitus and 100 participants were as a control group have risk factors for diabetes mellitus. All participants were selected for the study based on the following inclusion and exclusion criteria
Who may be able to join
- Documented diagnosis of diabetes mellitus by definition.
- 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
Who cannot join
- -1. Patients under 18 years of age; 2. Failure to give informed consent; 3. 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.
- 4. 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Ukraine1 site, 1 recruiting
- Recruiting
The Filatov Institute of Eye Diseases and Tissue Therapy
Odesa, 65061
About this study
To examine the potential for the detection of diabetic retinopathy (DR) using the artificial intelligence (AI)-based software platform Retina-AI.
Read the detailed description
Operator took fundus images with a non-mydriatic fundus camera as per the Retina-AI CheckEye imaging protocol (an optic disc centered image and a fovea centered image for each eye).Thereafter, operator uploaded fundus images in the AI system for processing by the neural network.
- Conditions
- Diabetic Retinopathy
- Being tested
- taking fundus photos using non-mydriatic fundus camera
- Keywords
- Diabetic Retinopathy, Fundus photo, nonmydriatic camera, Artificail Intelligence, CheckEye, Fundus image, fundus photography
- Medical subject headings
- Diabetic Retinopathy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
taking fundus photos using non-mydriatic fundus cameraDevice
using artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography.
| Study group | Role | What they receive |
|---|---|---|
| main group | have diabetes mellitus Receives: Device: taking fundus photos using non-mydriatic fundus camera | |
| control group | have risk factors for developing diabetes mellitus Receives: Device: taking fundus photos using non-mydriatic fundus camera |
What is being measured
The primary outcome is the main question the study is designed to answer.
The accuracy
The accuracy of detecting of DR
Measured: Baseline
Secondary outcomes (2)
The percent of invalid images
The percent of invalid images for analysing by neural network
Measured: Baseline
The percent of false positive detection of DR
The percent of false positive detection of DR in individuals without DR
Measured: Baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Mar 2025
- Study start2 Nov 2024
- Primary completionAug 2025 (estimated)
- Study completionDec 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabetic RetinopathyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- The Filatov Institute of Eye Diseases and Tissue Therapy
- Sponsor type
- University, hospital or other
- Collaborators
- CheckEye LLC, Oftacentro SA
- Responsible party
- Principal investigator, Andrii Korol, MD, PhD, The Filatov Institute of Eye Diseases and Tissue Therapy
- Investigators
- Andrii MD Korol, PhD, Principal investigator, The Filatov Institute of Eye Diseases and Tissue Therapy
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06879834
- Sponsor's protocol ID
- 02.10.2024
- Acronym
- ARTDR
- Status last verified
- Mar 2025
- First submitted
- 11 Mar 2025
- Last updated
- 17 Mar 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No