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
- Are there results?
- Not yet: the study is under way
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
Study at a glance
From the registry record, last updated by the sponsor on 17 Mar 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Assessing of Artificial Intelligence-based Software Platform for Diabetic Retinopathy Screening
- ClinicalTrials.gov ID
- NCT06879834
- Acronym / sponsor ID
- ARTDR / 02.10.2024
- Conditions
- Diabetic Retinopathy
- Keywords
- Diabetic Retinopathy, Fundus photo, nonmydriatic camera, Artificail Intelligence, CheckEye, Fundus image, fundus photography
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- The Filatov Institute of Eye Diseases and Tissue TherapyUniversity, hospital or other
- Collaborators
- CheckEye LLC, Oftacentro SA
- Study start
- 2 Nov 2024 (actual)
- Primary completion
- Aug 2025 (estimated)
- Study completion
- Dec 2025 (estimated)
- First posted
- 17 Mar 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
To examine the potential for the detection of diabetic retinopathy (DR) using the artificial intelligence (AI)-based software platform Retina-AI.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| main group | – | Device: taking fundus photos using non-mydriatic fundus camerahave diabetes mellitus |
| control group | – | Device: taking fundus photos using non-mydriatic fundus camerahave risk factors for developing diabetes mellitus |
Who may qualify
- Ages
- 18 to 90 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- 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
Key inclusion criteria (4 listed)
- 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
Key exclusion criteria (2 listed)
- -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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| taking fundus photos using non-mydriatic fundus camerausing artificial intelligence to identify diabetic retinopathy in the early stages using fundus photography. | Device | control group, main group |
Primary outcome
The accuracy
Time frame: Baseline
The accuracy of detecting of DR
2 secondary outcomes
The percent of invalid images
Time frame: Baseline
The percent of false positive detection of DR
Time frame: Baseline
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Mar 2025.
- Detecting diabetic retinopathy using an artificial intelligence-based software platform: a pilot studyLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Andrii MD Korol, PhD principal investigator
The Filatov Institute of Eye Diseases and Tissue Therapy
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabetic Retinopathy, run by The Filatov Institute of Eye Diseases and Tissue Therapy at 1 site in Ukraine.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 17 Mar 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Ukraine. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Andrii MD Korol, PhD (380936327266, andrii.r.korol@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The accuracy (time frame: Baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Mar 2025.