Automated AI-based System for Early Diagnosis of Diabetic Retinopathy

NCT05324189 | Unknown FDA Device

• 1 other identifier: 21-00371
• Study Type: observational
• Target: 1,000
• Locations: 1 country
• Sites: 1

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.

Conditions

Diabetic Retinopathy

Outcome Measures

Primary Outcomes (2)

• Sensitivity of identification of referable and non-referable Diabetic Retinopathy (DR) for early diagnosis of DR

  iPredict DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. The output of AI model and ophthalmologists' grading will be compared for image level and subject level accuracy measurement. Using the gold standard (i.e., the ophthalmologist's grading following ETDRS protocol), the sensitivity, specificity, precision, recall, accuracy, F-measure, positive predictive value and negative predictive value are calculated as: Sens=TP/(TP+FN) Spec=TN/(TN+FP) where TP is the number of true positives (referable DR subjects correctly classified), FN is the number of false negatives (referable DR subjects incorrectly classified as non-referable), TN is the number of true negatives (non-referable subjects correctly classified), and FP is the number of false positives (non-referable DR subjects incorrectly classified as referable DR).

  2 years

• Specificity of identification of referable and non-referable Diabetic

  iPredict DR can detect non-referable DR (normal retina or mild DR) and referable DR (moderate or severe DR including non-proliferative, proliferative DR and diabetic macular edema) at a similar level of expert ophthalmologists. The output of AI model and ophthalmologists' grading will be compared for image level and subject level accuracy measurement.

  2 years

Secondary Outcomes (1)

• The accuracy of identification of referable and non-referable DR for early diagnosis of DR

  2 years

Study Arms (2)

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.

Diagnostic Test: Referable versus Non Referable Diabetic Retinopathy diagnostic test

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.

Diagnostic Test: Referable versus Non Referable Diabetic Retinopathy diagnostic test

Interventions

Referable versus Non Referable Diabetic Retinopathy diagnostic test 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 (mtm) Diabetic Retinopathy (DR) Not Detected or Non referable DR

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

Participants who fit the eligibility inclusion criteria and not the exclusion criteria.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• The New York Eye & Ear Infirmary: lead
• iHealthScreen Inc: collaborator

Study Sites (1)

New York Eye and Ear Infirmary of Mount Sinai

New York, New York, 10003, United States

Location

MeSH Terms

Conditions

Diabetic Retinopathy

Condition Hierarchy (Ancestors)

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

Central Study Contacts

R. Theodore Smith, MD, PHD

CONTACT

646-943-7925; rolandtheodore.smith@mssm.edu

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: November 8, 2021
• First Posted: April 12, 2022
• Study Start: April 18, 2022
• Primary Completion: December 1, 2023
• Study Completion: December 1, 2024
• Last Updated: April 12, 2022

Record last verified: 2021-11

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)