Detection and Classification of Diabetic Retinopathy From Posterior Pole Images With A Deep Learning Model

NCT04805541 | Completed Results FDA Device

• 1 other identifier: EC-2021DR-TR
• Study Type: observational
• Target: 900
• Locations: 1 country
• Sites: 1

Brief Summary

The duration of diabetes is directly related to eye complications. Diabetic retinopathy affects 80 percent of those who have had diabetes for 20 years or more. At least 90% of new cases can be reduced with proper treatment and monitoring of the eyes. The longer a person has diabetes, the more likely it is to develop diabetic retinopathy. Each year in the United States, diabetic retinopathy accounts for 12% of all new cases of blindness. It is also the leading cause of blindness in people between the ages of 20 and 64. The most important complication of diabetes leading to vision loss is diabetic retinopathy. Depending on this, macular edema, bleeding into the retina and vitreous,neovascular glaucoma can cause blindness. Diabetic retinopathy (DR) is a leading cause of vision-loss globally. Of an estimated 285 million people with diabetes mellitus worldwide, approximately one third have signs of DR and of these, a further one third of DR is vision-threatening DR, including diabetic macular edema (DME). Diabetic retinopathy is a retinal disease that can often be stopped with early diagnosis, but if neglected, it can lead to severe vision loss, including permanent blindness. Diabetes has high morbidity and there are millions of people who should be screened for diabetic retinopathy (DR). Annual eye screening is recommended for all diabetic patients since vision loss can be prevented if DR is diagnosed in its early stages. Currently, the number of clinical personnel trained for DR screening is less than that needed to screen a growing diabetic population. Therefore, the automatic DR screening system will be able to screen more diabetic patients and diagnose them early. EyeCheckup is an automated retinal screening device designed automatically analyze color fundus photographs of diabetic patients to identify patients with referable or vision threatening DR. This study is designed to assess the safety and efficacy of EyeCheckup. The study is a single center study to determine the sensitivity and specificity of EyeCheckup to diabetic retinopathy. EyeCheckup is an automated software device that is designed to analyze ocular fundus digital color photographs taken in frontline primary care settings in order to quickly screen for diabetic retinopathy (DR).

Conditions

Diabetic Retinopathy; Diabetic Eye Problems; Diabetic Macular Edema

Outcome Measures

Primary Outcomes (4)

• Sensitivity(mtmDR)

  Sensitivity for detecting more than mild diabetic retinopathy

  1 visit (1 day)

• Sensitivity(vtDR)

  Sensitivity for detecting vision threatening diabetic retinopathy

  1 visit (1 day)

• Specificity(mtmDR)

  Specificity for detecting more than mild diabetic retinopathy

  1 visit (1 day)

• Specificity(vtDR)

  Specificity for detecting vision threatening diabetic retinopathy

  1 visit (1 day)

Secondary Outcomes (2)

• Diagnosability

  1 Day

• Non-Dilated EyeCheckup Usage

  1 Day

Interventions

Color Fundus Photography PROCEDURE

Subjects will undergo fundus photography before and after administration of mydriatic agent.

Mydriatic Agent DRUG

Subjects will be administered mydriatic medication to dilate their pupils.

Also known as: Tropicamide drops

EyeCheckup - AI Based DR Screening DEVICE

Screening for existence of "More than mild" or "Vision-threatening" Diabetic Retinopathy, and/or Diabetic Macular Edema.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

* Primary care clinic - invitation to volunteer, * Diabetic Patients * Eighteen years of age or older * Have been referred to an ophthalmologist for eye examination to screen for diabetic retinopathy * Diseases Polyclinic with the diagnosis of diabetes and were able to view the posterior polar region of the eye with an ophthalmic camera. 900 volunteer patients who applied to the Akdeniz University Endocrinology and Metabolic

You may qualify if:

• A diagnosis of diabetes mellitus
• Understanding of study and provision of written informed consent
• years of age or older
• No history of any other retinal vascular disease, glaucoma, or other disease that may affect the appearance of the retina or optic disc (refractive error and ocular surface disease are allowed)
• Other than cataract surgery, no history of intraocular surgery, ocular laser treatments for any retinal disease, or ocular injections for diabetic macular edema or proliferative disease No media opacity precluding good retinal photography

You may not qualify if:

• No diagnosis of diabetes mellitus
• Potential subject cannot understand study or informed consent
• A history of retinal vascular disease other than diabetic retinopathy that may affect the appearance of the retina or optic disc
• Previous intraocular surgery including cataract; previous laser to the retina; or previous intraocular injections for the treatment of diabetic retinopathy
• Pregnant women or women with gestational diabetes mellitus
• A media opacity in either eye that is severe enough to preclude good retinal photography
• Permanent vision impairment in one or both eyes
• The participant is contraindicated for imaging with fundus imaging systems used in the study:
• Participant is hypersensitive to light
• Participant recently received photodynamic therapy (PDT)
• Participant uses drugs that cause photosensitivity

Sponsors & Collaborators

• Ural Telekomunikasyon Sanayi Ticaret Anonim Sirketi: lead
• Akdeniz University: collaborator

Study Sites (1)

Akdeniz University Hospital

Antalya, 07070, Turkey (Türkiye)

Location

Related Publications (2)

• Aydemir M, Bilgin AB, Sari R, Dogan ME, Bulut M, Akar Y. Assessment of Correlation Between Diabetic Retinopathy and Metabolic Biomarkers Using Artificial Intelligence. J Diabetes Res. 2026 Jan 14;2026:9085827. doi: 10.1155/jdr/9085827. eCollection 2026.

  PMID: 41541002 DERIVED

• Dogan ME, Bilgin AB, Sari R, Bulut M, Akar Y, Aydemir M. Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence. Eye (Lond). 2024 Jun;38(9):1694-1701. doi: 10.1038/s41433-024-03000-9. Epub 2024 Mar 11.

  PMID: 38467864 DERIVED

MeSH Terms

Conditions

Diabetic Retinopathy

Interventions

Mydriatics

Condition Hierarchy (Ancestors)

Retinal Diseases; Eye Diseases; Diabetic Angiopathies; Vascular Diseases; Cardiovascular Diseases; Diabetes Complications; Diabetes Mellitus; Endocrine System Diseases

Intervention Hierarchy (Ancestors)

Autonomic Agents; Peripheral Nervous System Agents; Physiological Effects of Drugs; Pharmacologic Actions; Chemical Actions and Uses

Results Point of Contact

• Title: Prof.Dr. Ahmet Burak Bilgin
• Organization: Akdeniz University

gozdrburakbilgin@gmail.com

5465473336

Study Officials

• A Burak Bilgin, Assoc. Prof.

  Instructor, Retinal Surgeon, Academic Advisor

  PRINCIPAL INVESTIGATOR

Publication Agreements

• PI is Sponsor Employee: No
• Restrictive Agreement: No

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: March 15, 2021
• First Posted: March 18, 2021
• Study Start: February 1, 2022
• Primary Completion: July 4, 2022
• Study Completion: July 4, 2022
• Last Updated: July 15, 2024
• Results First Posted: July 15, 2024

Record last verified: 2024-01

Data Sharing

• IPD Sharing: Will not share

Locations

TU (1)