Clinical Trials Logo

Clinical Trial Summary

This prospective study aims to validate if NeoRetina, an artificial intelligence algorithm developped by DIAGNOS Inc. and trained to automatically detect the presence of diabetic retinopathy (DR) by the analysis of macula centered eye fundus photographies, can detect this disease and grade its severity.


Clinical Trial Description

More than 880 000 Quebecers (more than 10% of the population) suffer from diabetes, which is the main cause of blindness in diabetic adults under 65 years of age, and around 40% of people with diabetes suffer from diabetic retinopathy (DR). The early detection of DR and a regular follow-up is thus crucial to prevent the progression of this disease. However, the public health care system in Quebec does not actually have the capacity to allow all people with diabetes to see an ophthalmologist within a short delay. Artificial intelligence might help in screening DR and in refering to eye doctors only patients who suffer from this eye disease. The investigators of this study hypothesize that artificial intelligence (AI) is a useful technology for the screening of diabetic retinopathy (DR) that can detect the absence or the presence of DR with an efficiency and an accuracy similar to that of an ophthalmological evaluation. The goal of this study is to compare the screening results of DR obtained with NeoRetina pure artificial intelligence algorithm (automated analysis of color photos of the retina) with the results of a routine ophthalmological evaluation done in a clinical context at the Centre hospitalier de l'Université de Montréal (CHUM). The main objective of this study is to determine if artificial intelligence (AI) could be a useful technology for the early detection and the follow-up of diabetic retinopathy (DR). The first specific objective is to determine the efficiency and the accuracy of NeoRetina (DIAGNOS Inc.) automated algorithm for the screening and the grading of the severity of diabetic retinopathy (DR) by the analysis of eye fundus images from diabetic patients compared to that of an eye examination done by an ophthalmologist in a clinical context. The second specific objective is to evaluate if NeoRetina can determine, with efficiency and accuracy, the absence of diabetic retinopathy (DR), the presence of diabetic retinopathy (DR) and the severity of the disease. Recruited diabetic participants will be screened for DR by AI with NeoRetina. Participants will also have a full eye examination (blind assessment) with an ophthalmologist of the CHUM in order to determine if they suffer from this eye complication of diabetes. The results of the screening done by AI with NeoRetina will be compared to those of the ocular evaluation done by an ophthalmologist. Ophthalmologists from the CHUM will also revise the retinal images acquired by DIAGNOS (blind assessment) in order to determine if DR is present and will manually grade the severity of the disease. ;


Study Design


Related Conditions & MeSH terms


NCT number NCT04699864
Study type Interventional
Source Centre hospitalier de l'Université de Montréal (CHUM)
Contact Marie-Catherine Tessier, MSc
Phone 514-890-8000
Email marie-catherine.tessier.chum@ssss.gouv.qc.ca
Status Not yet recruiting
Phase N/A
Start date April 2024
Completion date December 2026

See also
  Status Clinical Trial Phase
Completed NCT03660384 - Silicone Oil Versus Gas in PDR Patients Undergoing Vitrectomy N/A
Completed NCT03660345 - PPV With Internal Limiting Membrane Peeling for Treatment-Naïve DME Phase 3
Completed NCT03660371 - ILM Peeling in PDR Patients Undergoing PPV for VH N/A
Completed NCT04905459 - ARDA Software for the Detection of mtmDR
Active, not recruiting NCT04271709 - Manhattan Vision Screening and Follow-Up Study (NYC-SIGHT) N/A
Recruiting NCT03713268 - Intraoperative OCT Guidance of Intraocular Surgery II
Completed NCT05022615 - Comparing 3 Imaging Systems
Completed NCT00385333 - Metabolic Mapping to Measure Retinal Metabolism Phase 2
Recruiting NCT04101604 - Biomarkers of Common Eye Diseases
Completed NCT03702374 - Combined Antioxidant Therapy on Oxidative Stress, Mitochondrial Dysfunction Markers in Diabetic Retinopathy Phase 3
Completed NCT01908816 - An Open-label Extended Clinical Protocol of Ranibizumab to Evaluate Safety and Efficacy in Rare VEGF Driven Ocular Diseases. Phase 3
Completed NCT04009980 - Long-term Retinal Changes After Topical Citicoline Administration in Patients With Mild Signs of Diabetic Retinopathy in Type 1 Diabetes Mellitus. N/A
Completed NCT02924311 - Routine Clinical Practice for Use of Intravitreal Aflibercept Treatment in Patients With Diabetic Macular Edema
Not yet recruiting NCT06257082 - Video-based Patient Education Intervention for Diabetic Eye Screening in Latinx Communities N/A
Not yet recruiting NCT05452993 - Screening for Diabetic Retinopathy in Pharmacies With Artificial Intelligence Enhanced Retinophotography N/A
Withdrawn NCT02812030 - Aflibercept for Retinopathy in the Real World N/A
Completed NCT02391558 - Clinical Evaluation of Noninvasive OCT Angiography Using a Zeiss OCT Prototype to Compare to Fluorescein Angiography N/A
Active, not recruiting NCT02330042 - OCT Biomarkers for Diabetic Retinopathy
Active, not recruiting NCT02353923 - OcuStem Nutritional Supplement in Diabetic Patients With Mild to Moderate Non-proliferative Retinopathy N/A
Completed NCT02390245 - Philadelphia Telemedicine Glaucoma Detection and Follow-Up Study N/A