The Use of Artificial Intelligence in the Early Detection and the Follow-Up of Diabetic Retinopathy of Diabetic Patients Followed at the CHUM: Evaluation of NeoRetina Automated Algorithm (DIAGNOS Inc.)
试验速览
- 阶段
- 不适用
- 状态
- 终止
- 发起方
- 入组人数
- 24
- 试验地点
- 1
- 主要终点
- Manual Analysis of Retinal Images - Absence or Presence of Diabetic Retinopathy (DR)
研究概览
简要总结
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.
详细描述
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).
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Patients of 18 years old and older;
- •Ability to provide informed consent;
- •Diagnostic for diabetes : 3a) Type 1 diabetes of a lest 5 years of evolution; or 3b) Type 2 diabetes;
- •Diabetic patient followed and refered by a physician of the Centre hospitalier de l'Université de Montréal (CHUM) : 4a) followed by an endocrinologist of the CHUM; or 4b) hospitalized at the CHUM; or 4c) on the waiting list of the Ophthalmology Clinic of the CHUM for the evaluation of DR.
排除标准
- •Patients less than 18 years old;
- •Inability to provide informed consent;
- •Patient who already had a treatment (surgery, laser, injection, etc.) for any retinal condition : Age-related macular degeneration (AMD), retinal vascular occlusion (RVO); etc.
研究组 & 干预措施
Diabetic Retinopathy (DR)
Screening of DR with artificial intelligence (NeoRetina algorithm) and diagnostic evaluation with a standard of care ophthalmological examination.
干预措施: Screening of DR and DME with artificial intelligence using NeoRetina (Diagnostic Test)
Diabetic Retinopathy (DR)
Screening of DR with artificial intelligence (NeoRetina algorithm) and diagnostic evaluation with a standard of care ophthalmological examination.
干预措施: Routine ophthalmological evaluation of DR and DME (Diagnostic Test)
Diabetic Retinopathy (DR)
Screening of DR with artificial intelligence (NeoRetina algorithm) and diagnostic evaluation with a standard of care ophthalmological examination.
干预措施: Manual grading of DR and DME by CHUM ophthalmologists based on retinal photographies acquired by Diagnos (Diagnostic Test)
结局指标
主要结局
Manual Analysis of Retinal Images - Absence or Presence of Diabetic Retinopathy (DR)
时间窗: Baseline
Manual analysis of retinal images acquired by Diagnos by an ophthalmologist of the CHUM to determine the absence or the presence of diabetic retinopathy (DR) (blind assessment) * R0 : No DR * R+ : Presence of DR
Artificial Intelligence - Absence or Presence of Diabetic Macular Edema (DME)
时间窗: Baseline
Analysis of retinal images by artificial intelligence (NeoRetina) to determine the absence or the presence of diabetic macular edema (DME) * M0 : No DME * M+ : Presence of DME
Eye Examination - Absence or Presence of Diabetic Macular Edema (DME)
时间窗: Baseline
Eye examination done by an ophthalmologist to determine the absence or the presence of diabetic macular edema (DME) (blind assessment) * M0 : No DME * M+ : Presence of DME
Manual Analysis of Retinal Images - Absence or Presence of Diabetic Macular Edema (DME)
时间窗: Baseline
Manual analysis of retinal images acquired by Diagnos by an ophthalmologist of the CHUM to determine the absence or the presence of diabetic macular edema (DME) (blind assessment) * M0 : No DME * M+ : Presence of DME
Artificial Intelligence - Severity of Diabetic Macular Edema (DME)
时间窗: Baseline
Analysis of retinal images by artificial intelligence (NeoRetina) to grade the severity of diabetic macular edema (DME) * M1 : Non Central DME * M2 : Central DME
Manual Analysis of Retinal Images - Severity of Diabetic Macular Edema (DME)
时间窗: Baseline
Manual analysis of retinal images acquired by Diagnos by an ophthalmologist of the CHUM to grade the severity of diabetic macular edema (DME) (blind assessment) * M1 : Non Central DME * M2 : Central DME
Artificial Intelligence - Absence or Presence of Diabetic Retinopathy (DR)
时间窗: Baseline
Analysis of retinal images by artificial intelligence (NeoRetina) to determine the absence or the presence of diabetic retinopathy (DR) * R0 : No DR * R+ : Presence of DR
Eye Examination - Absence or Presence of Diabetic Retinopathy (DR)
时间窗: Baseline
Eye examination done by an ophthalmologist to determine the absence or the presence of diabetic retinopathy (DR) (blind assessment) * R0 : No DR * R+ : Presence of DR
Manual Analysis of Retinal Images - Severity of Diabetic Retinopathy (DR)
时间窗: Baseline
Manual revision of retinal images acquired by Diagnos by an ophthalmologist of the CHUM to grade the severity of diabetic retinopathy (DR) (blind assessment) * R1 - Mild NPDR: Mild Nonproliferative Diabetic Retinopathy * R2 - Moderate NPDR: Moderate Nonproliferative Diabetic Retinopathy * R3 - Severe NPDR : Severe Nonproliferative Diabetic Retinopathy * R4 - PDR : Proliferative Diabetic Retinopathy
Artificial Intelligence - Severity of Diabetic Retinopathy (DR)
时间窗: Baseline
Analysis of retinal images by artificial intelligence (NeoRetina) to grade the severity of diabetic retinopathy (DR) * R1 - Mild NPDR: Mild Nonproliferative Diabetic Retinopathy * R2 - Moderate NPDR: Moderate Nonproliferative Diabetic Retinopathy * R3 - Severe NPDR : Severe Nonproliferative Diabetic Retinopathy * R4 - PDR : Proliferative Diabetic Retinopathy
Eye Examination - Severity of Diabetic Retinopathy (DR)
时间窗: Baseline
Eye examination done by an ophthalmologist to grade the severity of diabetic retinopathy (DR) (blind assessment) * R1 - Mild NPDR: Mild Nonproliferative Diabetic Retinopathy * R2 - Moderate NPDR: Moderate Nonproliferative Diabetic Retinopathy * R3 - Severe NPDR : Severe Nonproliferative Diabetic Retinopathy * R4 - PDR : Proliferative Diabetic Retinopathy
Eye Examination - Severity of Diabetic Macular Edema (DME)
时间窗: Baseline
Eye examination done by an ophthalmologist to grade the severity of diabetic macular edema (DME) (blind assessment) * M1 : Non Central DME * M2 : Central DME
次要结局
- Performance of NeoRetina Algorithm - Diabetic Macular Edema (DME)(3 years)
- Performance of NeoRetina Algorithm - Diabetic Retinopathy (DR)(3 years)