Non-Invasive Retinal Vessel Analysis as a Predictor for Cardiovascular Disease

被引:4
作者
Iorga, Raluca Eugenia [1 ]
Costin, Damiana [2 ]
Munteanu-Danulescu, Razvana Sorina [3 ]
Rezus, Elena [4 ]
Moraru, Andreea Dana [1 ]
机构
[1] Grigore T Popa Univ Med & Pharm, Dept Surg 2, Discipline Ophthalmol, Str Univ 16, Iasi 700115, Romania
[2] Grigore T Popa Univ Med & Pharm, Doctoral Sch, Iasi 700115, Romania
[3] L Pasteur Clin Hosp, Dept Gastroenterol, F-28630 Le Coudray, France
[4] Grigore T Popa Univ Med & Pharm, Dept Internal Med 2, Discipline Reumathol, Iasi 700115, Romania
来源
JOURNAL OF PERSONALIZED MEDICINE | 2024年 / 14卷 / 05期
关键词
retinal vessel analysis; cardiovascular disease; retinal microvascular biomarkers; artificial intelligence; COHERENCE TOMOGRAPHY ANGIOGRAPHY; DIABETIC-RETINOPATHY; BLOOD-PRESSURE; ARTIFICIAL-INTELLIGENCE; ATHEROSCLEROSIS RISK; HYPERTENSION; ARTERIOLAR; DIAMETERS; MORTALITY; HEALTHY;
D O I
10.3390/jpm14050501
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
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页数:18
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