NCT05324189

Automated AI-based System for Early Diagnosis of Diabetic Retinopathy

Pivotal Trial of Automated AI-based System for Early Diagnosis of Diabetic Retinopathy Using Retinal Color Imaging

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,000 (estimated)
• Sponsor: The New York Eye & Ear Infirmary · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

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

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	Referable versus Non Referable Diabetic Retinopathy diagnostic test	Artificial intelligence read reports Referable versus Non Referable Diabetic Retinopathy

Timeline

• Start date: 2022-04-18
• Primary completion: 2023-12-01
• Completion: 2024-12-01
• First posted: 2022-04-12
• Last updated: 2022-04-12

Locations

1 site across 1 country: United States

Regulatory

• FDA-regulated device study