Retinal imaging and AI in predictive vascular medicine: Early diagnosis, risk assessment, and cross-disciplinary insights

The field of retinal imaging has long provided a unique, non-invasive window to systemic vascular health, with microvascular changes observable in the retina serving as early harbingers of conditions such as hypertension, diabetes, and age-related vascular dysfunction. Recent years have witnessed remarkable advancements in retinal imaging modalities, including optical coherence tomography (OCT) and high-resolution fundus photography, coupled with transformative developments in artificial intelligence (AI) and machine learning. These innovations have significantly improved the detection and analysis of subtle retinal changes, empowering clinicians to predict cardiovascular and cerebrovascular risk even before the appearance of overt clinical symptoms. Despite this rapid progress, there remain important challenges—including standardization, clinical integration, and interdisciplinary implementation—that need to be addressed to fully harness the predictive potential of retinal imaging in vascular medicine.This Research Topic aims to advance the integration of retinal imaging and AI-driven analysis for the detection, risk stratification, and management of systemic vascular diseases. Our goal is to highlight innovative technologies and cross-disciplinary strategies that enable early diagnosis, inform timely interventions, and promote continuous patient monitoring. Emphasis will be placed on translating retinal biomarkers and AI-derived risk assessments into practical clinical tools, as well as fostering collaboration across ophthalmology, cardiology, endocrinology, neurology, geriatrics, and allied specialties. By doing so, we hope to bridge gaps between fundamental research, technical innovation, and real-world application to realize the vision of truly predictive and preventive vascular medicine.To gather further insights into the integration of retinal imaging and AI in vascular disease management, we welcome articles addressing, but not limited to, the following themes:o Retinal biomarkers and systemic vascular disease: Associations between retinal microvascular changes and risks or progression of hypertension, diabetes, cardiovascular disease, and aging-related vascular dysfunctiono Advanced retinal imaging technologies: Innovations in OCT, fundus photography, and other modalities for comprehensive vascular evaluationo AI and machine learning applications: Development and clinical deployment of automated algorithms for detecting retinal changes and estimating systemic vascular risko Translational and clinical relevance: Incorporation of retinal findings and AI-derived risk scores into cardiovascular, metabolic, and geriatric assessments for enhanced patient careo Interdisciplinary approaches: Collaborative models for utilizing retinal imaging as a predictive biomarker across diverse clinical populations and specialtiesThe Research Topic welcomes all article types that collectively underscore the transformative value of retinal imaging and AI in predictive vascular medicine, from early diagnosis to risk stratification and improved patient outcomes. Topic editors: Jae-Ho Han, Raffaele Landolfi, Joanne Matsubara Source: https://www.frontiersin.org/research-topics/76485/retinal-imaging-and-ai-in-predictive-vascular-medicine-early-diagnosis-risk-assessment-and-cross-disciplinary-insights