Automated AI-based System for Early Diagnosis of Diabetic Retinopathy

NCT ID: NCT05324189

Last Updated: 2022-04-12

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 1000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-04-18
• Study Completion Date: 2024-12-01

Brief Summary

In this pivotal trial, we aim to perform a prospective study to find the efficacy of iPredict, an artificial intelligence (AI) based software tool on early diagnosis of Diabetic Retinopathy (DR)in the primary care, optometrist and other diabetes-screening clinics. DR is one of the leading causes of blindness in the United States and other developed countries. Every individual with diabetes is at risk of DR. It does not show any symptom until the disease is progressed to advanced stages. If the disease is caught at an early stage, it can be prevented, managed or treated effectively. Currently, screening for DR is done by the Ophthalmologists, which is limited to areas with limited availability. This is also time-consuming and expensive. All of these can be complemented by automated screening and set up the screening in the primary care clinics.

Detailed Description

In this pivotal trial, we aim to invite diabetic patients to participate in the trial by having non-dilated photos of their eyes taken by an FDA-approved DRS plus camera at their own doctor's office which will test the feasibility of our proposed automated AI based DR diagnosis software solution,. The color fundus photos will be captured and then be transmitted securely and analyzed by iHealthScreen's HIPAA compliant server at Amazon cloud. The deep learning module will analyze the image for finding the disease severity. The automated report will be generated which will report as referable DR or more than mild (mtm) DR detected i.e., moderate DR, severe DR - proliferative or non-proliferative DR or Non-referable DR or mtm DR not detected, i.e., mild DR or no DR.

The same images will be evaluated by 3 ophthalmologists and will be adjudicated if any disagreement between the gradings. The automatic and expert evaluation will be compared to compute the sensitivity, specificity and AUC.

Conditions

Diabetic Retinopathy

Study Design

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

Study Groups

More than mild (mtm) Diabetic Retinopathy (DR) Not Detected or Non referable DR

More than mild Diabetic Retinopathy (mtm DR) not detected or non referable DR using the iPredict's AI-based DR screening software utilizing color fundus imaging.

Referable versus Non Referable Diabetic Retinopathy diagnostic test

Intervention Type: DIAGNOSTIC_TEST

Artificial intelligence read reports Referable versus Non Referable Diabetic Retinopathy

More than mild (mtm) Diabetic Retinopathy (DR) Detected or Referable DR

More than mild Diabetic Retinopathy (mtm DR), moderate to severe DR detected, non proliferative DR detected, proliferative DR detected or referable DR using the iPredict's AI-based DR screening software utilizing color fundus imaging.

Referable versus Non Referable Diabetic Retinopathy diagnostic test

Intervention Type: DIAGNOSTIC_TEST

Artificial intelligence read reports Referable versus Non Referable Diabetic Retinopathy

Interventions

Referable versus Non Referable Diabetic Retinopathy diagnostic test

Artificial intelligence read reports Referable versus Non Referable Diabetic Retinopathy

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Age of Subjects: Patients ≥ 18 years of age.
• Gender of Subjects: Both males and females will be invited to participate.
• Subjects with diabetes (A1C level 6.5 or higher) or Fasting Plasma Glucose (blood sugar level) 126 mg/dL (≥7.0 mmol/L)
• Subjects must be willing and are able to comply with clinic visit, understand the study-related procedures/provisions, and provide signed informed consent.
• asymptomatic patients with DR.

Exclusion Criteria

• Subject has retinal degenerations and retinal vascular diseases such as age-related macular degeneration or having undergone prior retinal surgery.
• History of ocular injections,
• Subject has persistent visual impairment in any eye;
• History of macular edema or retinal vascular (vein or artery) occlusion;
• laser treatment of the retina, or intraocular surgery other than cataract surgery without complications;
• Subject is currently enrolled in an interventional study of an investigational device or drug;
• Subject has ungradable clinical reference standard photographs (i.e., not gradable quality image). If the patient image is not gradable automatically, we will suggest the patient to refer the ophthalmologist.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

iHealthScreen Inc

INDUSTRY

Sponsor Role: collaborator

The New York Eye & Ear Infirmary

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

New York Eye and Ear Infirmary of Mount Sinai

New York, New York, United States

Countries

United States

Central Contacts

R. Theodore Smith, MD, PHD

Role: CONTACT

rolandtheodore.smith@mssm.edu

646-943-7925

Other Identifiers

21-00371

Identifier Type: -

Identifier Source: org_study_id