Retinal Vessel Diameters and Physical Activity in Patients With Mild to Moderate Rheumatic Disease Without Cardiovascular Comorbidities

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

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.

Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases-Evolution and Perspectives

The study of retinal vessels in relation to cardiovascular risk has a long history. The advent of a dedicated tool based on digital imaging, i.e., the retinal vessel analyzer, and also other software such as Integrative Vessel Analysis (IVAN), Singapore I Vessel Assessment (SIVA), and Vascular Assessment and Measurement Platform for Images of the Retina (VAMPIRE), has led to the accumulation of a formidable body of evidence regarding the prognostic value of retinal vessel analysis (RVA) for cardiovascular and cerebrovascular disease (including arterial hypertension in children). There is also the potential to monitor the response of retinal vessels to therapies such as physical activity or bariatric surgery. The dynamic vessel analyzer (DVA) remains a unique way of studying neurovascular coupling, helping to understand the pathogenesis of cerebrovascular and neurodegenerative conditions and also being complementary to techniques that measure macrovascular dysfunction. Beyond cardiovascular disease, retinal vessel analysis has shown associations with and prognostic value for neurological conditions, inflammation, kidney function, and respiratory disease. Artificial intelligence (AI) (represented by algorithms such as QUantitative Analysis of Retinal vessel Topology and siZe (QUARTZ), SIVA-DLS (SIVA-deep learning system), and many others) seems efficient in extracting information from fundus photographs, providing prognoses of various general conditions with unprecedented predictive value. The future challenges will be integrating RVA and other qualitative and quantitative risk factors in a unique, comprehensive prediction tool, certainly powered by AI, while building the much-needed acceptance for such an approach inside the medical community and reducing the "black box" effect, possibly by means of saliency maps.

Retinal vessel diameters and function in cardiovascular risk and disease

In the last two decades evidence has gradually accumulated suggesting that the eye may be a unique window for cardiovascular risk stratification based on the assessment of subclinical damage of retinal microvascular structure and function. This can be facilitated by non-invasive analysis of static retinal vessel diameters and dynamic recording of flicker light-induced and endothelial function-related dilation of both retinal arterioles and venules. Recent new findings have made retinal microvascular biomarkers strong candidates for clinical implementation as reliable risk predictors. Beyond a review of the current evidence and state of research, the article aims to discuss the methodological benefits and pitfalls and to identify research gaps and future directions. Above all, the potential use for screening and treatment monitoring of cardiovascular disease risk are highlighted. The article provides fundamental comprehension of retinal vessel imaging by explaining anatomical and physiological essentials of the retinal microcirculation leading to a detailed description of the methodological approach. This allows for better understanding of the underlying retinal microvascular pathology associated with the prevalence and development of cardiovascular disease. A body of new evidence is presented on the clinical validity and predictive value of retinal vessel diameters and function for incidence cardiovascular disease and outcome. Findings in children indicate the potential for utility in childhood cardiovascular disease prevention, and the efficacy of exercise interventions highlight the treatment sensitivity of retinal microvascular biomarkers. Finally, coming from the availability of normative data, solutions for diagnostic challenges are discussed and conceptual steps towards clinical implementation are put into perspective.