Detecting Eye Diseases Via Hybrid Deep Learning Algorithms From Fundus Images

NCT06213896 | Completed

• 1 other identifier: EC-2023-TR
• Study Type: observational
• Target: 1,528
• Locations: 1 country
• Sites: 1

Brief Summary

Eye health is of great importance for quality of life. Some eye diseases can progress and cause permanent damage up to vision loss if they are not treated early. Therefore, it is of great importance to have regular eye examinations and to detect possible eye diseases before they progress. Healthy people should also undergo eye screening once a year, and those with any complaints regarding eye health should be examined. With the advancing technology, Artificial Intelligence (AI) has begun to play a significant role in the healthcare sector. Retinal diseases, serious health problems resulting from damage to the back part of the eye's retina, include conditions such as retinopathy, macular degeneration, and glaucoma. Artificial intelligence, with its visual recognition and analysis capabilities, holds great potential in the early diagnosis of retinal diseases. AI-based diagnosis of retinal diseases typically involves the use of specialized algorithms that analyze retinal images. These algorithms identify abnormal features in the eye, providing doctors with a quick and accurate diagnosis. EyeCheckup v2.0 will diagnose glaucoma suspicion, severe glaucoma suspicion, age-related macular degeneration diagnosis, RVO diagnosis, diabetic retinopathy diagnosis and stage, presence/absence of DME suspicion and other retinal diseases from fundus images. This study is designed to assess the safety and efficacy of EyeCheckup v2.0. The study is a single center study to determine the sensitivity and specificity of EyeCheckup to retinal and optic disc diseases. EyeCheckup v2.0 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.

Conditions

Glaucoma; Age-Related Macular Degeneration; Retinal Vein Occlusion; Diabetic Retinopathy; Diabetic Macular Edema; Eye Diseases

Keywords

Artificial Intelligence; Eye Diseases

Outcome Measures

Primary Outcomes (1)

• To determine the accuracy of diagnosis with artificial intelligence algorithm

  Comparison of the compatibility of the diagnosis of the artificial intelligence algorithm with the diagnoses of retina and glaucoma specialists

  through study completion, an average of 1 year

Secondary Outcomes (1)

• To determine the sensitivity and specificity of EyeCheckup v2.0 to detect retinal and optic disc diseases

  through study completion, an average of 1 year

Interventions

Mydriatic Agent DRUG

Subjects will be administered mydriatic medication to dilate their pupils.

Also known as: Tropicamide drops

Color Fundus Photography PROCEDURE

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

EyeCheckup v2.0 DEVICE

Screening for existence of eye diseases

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Primary care clinic invitation to volunteer, Eighteen years of age or older Have been referred to an ophthalmologist for eye examination to screen for eye disease

You may qualify if:

• Must understand the study and sign informed consent. No history of retinal vascular disease, cataracts or any other disease that may affect the appearance of the retina or optic disc (refractive error and ocular surface disease are allowed).
• No history of intraocular surgery or ocular laser treatment for any retinal disease, other than cataract surgery.
• years and over

You may not qualify if:

• Not understand the study or informed consent, Media opacity or other defect that would prevent taking a fundus photograph with the feature to be evaluated (which could not be taken with a non-mydriatic fundus camera in 6 attempts or was rejected 6 times by the EyeCheckup quality algorithm due to quality), Has intraocular surgery other than cataracts or has had laser treatment on the retina, Contraindicated for imaging with the fundus imaging systems used in the study, Under 18 years

Sponsors & Collaborators

• Ural Telekomunikasyon Sanayi Ticaret Anonim Sirketi: lead

Study Sites (1)

Akdeniz University Hospital

Antalya, 07070, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Glaucoma; Macular Degeneration; Retinal Vein Occlusion; Diabetic Retinopathy; Eye Diseases

Interventions

Mydriatics

Condition Hierarchy (Ancestors)

Ocular Hypertension; Retinal Degeneration; Retinal Diseases; Venous Thrombosis; Thrombosis; Embolism and Thrombosis; Vascular Diseases; Cardiovascular Diseases; Diabetic Angiopathies; 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

Study Design

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

Study Record Dates

• First Submitted: January 9, 2024
• First Posted: January 19, 2024
• Study Start: March 1, 2023
• Primary Completion: April 18, 2024
• Study Completion: April 18, 2024
• Last Updated: May 14, 2024

Record last verified: 2024-01

Locations

TU (1)