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Related Concept Videos

Diabetic Retinopathy01:27

Diabetic Retinopathy

DefinitionDiabetic retinopathy is a microvascular complication of diabetes affecting the retinal blood vessels.Risk FactorsDiabetic retinopathy is present in almost all individuals with type 1 diabetes and more than 60% of those with type 2 diabetes after two decades of disease.The risk increases with poor glycemic control, hypertension, dyslipidemia, smoking, pregnancy, and puberty.Although cataracts and glaucoma are also more frequent in people with diabetes, retinopathy remains the leading...

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Related Experiment Video

Updated: Jun 19, 2026

Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies
10:11

Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies

Published on: October 22, 2014

RetiMap: Automated Retinal Vascular Measures Link Microvascular Structure to Metabolic Health and Predict

Yeela Talmor-Barkan1, Michal Shapira2, Smadar Shilo3

  • 1Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel; Gray Faculty of Medical and Health Science, Tel Aviv University, Tel-Aviv, Israel; Department of Cardiology, Rabin Medical Center, Petah-Tikva, Israel; Pheno.AI, Tel-Aviv, Israel.

JACC. Basic to Translational Science
|June 17, 2026
PubMed
Summary
This summary is machine-generated.

Retinal vascular analysis using AI reveals strong links between eye blood vessel features and cardiometabolic health. These findings support using eye imaging for predicting cardiovascular events and monitoring systemic conditions.

Keywords:
average widthretinavessel density

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Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
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Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

Published on: March 26, 2020

Related Experiment Videos

Last Updated: Jun 19, 2026

Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies
10:11

Fundus Photography as a Convenient Tool to Study Microvascular Responses to Cardiovascular Disease Risk Factors in Epidemiological Studies

Published on: October 22, 2014

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
07:23

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography

Published on: March 26, 2020

Area of Science:

  • Ophthalmology
  • Cardiology
  • Artificial Intelligence

Background:

  • Fundus imaging offers noninvasive visualization of retinal microvasculature.
  • Artificial intelligence (AI) can extract quantitative vascular metrics from retinal images for biomarker discovery.

Purpose of the Study:

  • Characterize retinal microvascular features in a large healthy population.
  • Assess associations between these features and clinical phenotypes.
  • Evaluate their predictive ability for incident cardiovascular events.

Main Methods:

  • Analyzed fundus photographs from 8,467 healthy individuals (Human Phenotype Project) and 16,249 from UK Biobank.
  • Utilized an AI tool (AutoMorph) to extract 12 quantitative vascular metrics (e.g., density, tortuosity, curvature) for arteries and veins.
  • Derived age- and sex-stratified reference values and assessed associations with cardiometabolic, respiratory, and behavioral parameters.

Main Results:

  • Retinal vascular features showed significant age- and sex-related patterns.
  • Multiple associations were found between microvascular metrics and systemic traits, particularly arterial features with cardiometabolic factors (blood pressure, lipids, BMI) and sleep apnea.
  • Findings were replicated in UK Biobank and showed prognostic value for cardiovascular events.

Conclusions:

  • This AI-driven study provides normative data for retinal vascular traits.
  • Supports the use of fundus imaging for systemic risk stratification and cardiovascular event prediction.
  • Highlights the potential of retinal biomarkers for early detection of cardiometabolic and sleep disorders, advancing oculomics in preventive healthcare.