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Updated: Jun 25, 2025
Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
Published on: March 26, 2020
Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease
Raluca Eugenia Iorga1, Damiana Costin2, Răzvana Sorina Munteanu-Dănulescu3
1Department of Surgery II, Discipline of Ophthalmology, "Grigore T. Popa" University of Medicine and Pharmacy, Strada Universitatii No. 16, 700115 Iași, Romania.
Insights
Retinal microvascular imaging, using biomarkers like CRAE and AVR, can non-invasively predict cardiovascular disease risk. AI enhances this process, aiding in early detection and prevention.
Area of Science:
- Ophthalmology
- Cardiology
- Medical Imaging
Background:
- Cardiovascular disease (CVD) is a leading global cause of mortality.
- Microcirculatory alterations, particularly in the retinal vasculature, can serve as indicators of cardiovascular risk.
- Non-invasive analysis of retinal vessels offers a promising avenue for assessing systemic vascular health.
Purpose of the Study:
- To review current literature on retinal microvascular biomarkers for cardiovascular disease (CVD) prediction.
- To discuss the methodological advantages of dynamic retinal vessel analysis (DRVA).
- To identify research gaps and highlight the potential of AI in retinal vascular imaging for CVD screening and monitoring.
Main Methods:
- Analysis of fundus images to quantify microvascular changes.
- Measurement of central retinal arteriolar (CRAE) and venular (CRVE) equivalents, and the arteriolar-to-venular diameter ratio (AVR).
- Utilizing dynamic retinal vessel analysis (DRVA) with flicker light stimulation.
- Application of Artificial Intelligence (AI) tools like QUARTZ and SIVA-DLS for image analysis.
Main Results:
- Narrower CRAE, wider CRVE, and lower AVR are associated with increased cardiovascular events.
- DRVA enables quantification of retinal vascular changes in response to stimuli.
- AI-driven systems demonstrate efficiency in extracting information from fundus photographs, improving diagnostic accuracy.
Conclusions:
- Retinal microvascular biomarkers (CRAE, CRVE, AVR) show potential for predicting cardiovascular mortality.
- AI-powered retinal vascular imaging can aid in cardiovascular risk identification and primary prevention.
- Further research is needed to explore the clinical application of these biomarkers for systemic vascular health assessment and event prediction.
Abstract:
Cardiovascular disease (CVD) is the most frequent cause of death worldwide. The alterations in the microcirculation may predict the cardiovascular mortality. The retinal vasculature can be used as a model to study vascular alterations associated with cardiovascular disease. In order to quantify microvascular changes in a non-invasive way, fundus images can be taken and analysed. The central retinal arteriolar (CRAE), the venular (CRVE) diameter and the arteriolar-to-venular diameter ratio (AVR) can be used as biomarkers to predict the cardiovascular mortality. A narrower CRAE, wider CRVE and a lower AVR have been associated with increased cardiovascular events. Dynamic retinal vessel analysis (DRVA) allows the quantification of retinal changes using digital image sequences in response to visual stimulation with flicker light. This article is not just a review of the current literature, it also aims to discuss the methodological benefits and to identify research gaps. It highlights the potential use of microvascular biomarkers for screening and treatment monitoring of cardiovascular disease. Artificial intelligence (AI), such as Quantitative Analysis of Retinal vessel Topology and size (QUARTZ), and SIVA-deep learning system (SIVA-DLS), seems efficient in extracting information from fundus photographs and has the advantage of increasing diagnosis accuracy and improving patient care by complementing the role of physicians. Retinal vascular imaging using AI may help identify the cardiovascular risk, and is an important tool in primary cardiovascular disease prevention. Further research should explore the potential clinical application of retinal microvascular biomarkers, in order to assess systemic vascular health status, and to predict cardiovascular events.
