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

NCT ID: NCT04805541

Last Updated: 2024-07-15

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 900 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-02-01
• Study Completion Date: 2022-07-04

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).

Detailed Description

This is a prospective study to assess the safety and efficacy of EyeCheckup in screening for DR.

This study was carried out in a single center at Akdeniz University Faculty of Medicine with primary endpoints to determine the sensitivity and specificity of EyeCheckup to diabetic retinopathy in the primary care setting.

Methods and tools to be used in the study:

• Fundus photography with non-mydriatic camera and classification of diabetic retinopathy with artificial intelligence algorithm,
• Evaluation of seven field dilated fundus images by retina specialists and comparison of results for clinical validation of the system.

Clinical and laboratory tests to be performed:

• Fundus photography with a non-mydriatic camera. In this study, no invasive procedure is applied to the patient, the retinal photograph will be taken with a special digital camera called a fundus camera. In patients whose non-mydriatic image cannot be obtained, tropicamide drops will be instilled to dilate the pupil, and then photographs will be taken.
• Pupil dilation will be achieved by instilling Tropicamide drops in both eyes of the patient, and then 4 quadrant photographs of both eyes will be taken with a mydriatic fundus camera.

After exclusions, this study will enroll up to 900 subjects who are diagnosed with diabetes by the endocrinology polyclinic and meet the eligibility criteria. Participants who meet the eligibility criteria will be recruited after obtaining written informed consent from primary health care providers. Subjects will undergo fundus photography per, Food and Drug Administration (FDA) cleared, ophthalmic cameras (product code: HKI). Images will be taken according to a specific EyeCheckup imaging protocol provided to the ophthalmic camera operator and then analyzed by the EyeCheckup device.

The photography protocol consists of two images of the ocular fundus (one optic disc nerve centered, one macula centered), obtained from both eyes of enrolled participants.

After the retinal images taken from ophthalmic cameras (product code: HKI), images are analyzed with EyeCheckup and a scan report is prepared. If it is necessary to enlarge the pupils, eye enlarging eye drops are applied and wait 15-30 minutes. This information is noted. DR is diagnosed by examination by a retina specialist with the captured images. EyeCheckup success rate is calculated by comparing both reports.

Conditions

Diabetic Retinopathy; Diabetic Eye Problems; Diabetic Macular Edema

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: PROSPECTIVE

Interventions

Color Fundus Photography

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

Intervention Type: PROCEDURE

Mydriatic Agent

Subjects will be administered mydriatic medication to dilate their pupils.

Intervention Type: DRUG

EyeCheckup - AI Based DR Screening

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

Intervention Type: DEVICE

Other Intervention Names

Tropicamide drops

Eligibility Criteria

Inclusion Criteria

• A diagnosis of diabetes mellitus
• Understanding of study and provision of written informed consent
• 18 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

Exclusion Criteria

• 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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Akdeniz University

OTHER

Sponsor Role: collaborator

Ural Telekomunikasyon Sanayi Ticaret Anonim Sirketi

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

A Burak Bilgin, Assoc. Prof.

Role: PRINCIPAL_INVESTIGATOR

Instructor, Retinal Surgeon, Academic Advisor

Locations

Akdeniz University Hospital

Antalya, , Turkey (Türkiye)

Countries

Turkey (Türkiye)

References

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.

Reference Type: DERIVED

PMID: 38467864 (View on PubMed)

Provided Documents

Document Type: Study Protocol and Statistical Analysis Plan

View Document

Other Identifiers

EC-2021DR-TR

Identifier Type: -

Identifier Source: org_study_id