Tlaiss Y, Akiki S, Moussawi N, Zeidan R, Zghaib A, Fassih I. Retina as a window to systemic hypertension: From hypertensive retinopathy to artificial intelligence-driven microvascular biomarkers. World J Hypertens 2026; 12(1): 124669 [DOI: 10.5494/wjh.124669]
Corresponding Author of This Article
Yehya Tlaiss, MD, Department of Ophthalmology, University of Balamand, Hazmieh, Beirut 1100, Beyrouth, Lebanon. yehyatlaiss@gmail.com
Research Domain of This Article
Cardiac & Cardiovascular Systems
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review-article
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Tlaiss Y, Akiki S, Moussawi N, Zeidan R, Zghaib A, Fassih I. Retina as a window to systemic hypertension: From hypertensive retinopathy to artificial intelligence-driven microvascular biomarkers. World J Hypertens 2026; 12(1): 124669 [DOI: 10.5494/wjh.124669]
Yehya Tlaiss, Serena Akiki, Naynawa Moussawi, Reine Zeidan, Abbas Zghaib, Issam Fassih, Department of Ophthalmology, University of Balamand, Beirut 1100, Beyrouth, Lebanon
Author contributions: Tlaiss Y conceived and designed the review, developed and executed the literature search strategy, performed evidence synthesis and wrote the manuscript; Akiki S and Moussawi N performed title, abstract and full-text screening and data extraction, and constructed the evidence tables; Zeidan R and Zghaib A performed the supplementary hand-search of reference lists, verified all extracted quantitative data against the primary sources and prepared the figures; Fassih I supervised the project, arbitrated screening disagreements and critically revised the manuscript for important intellectual content; and all authors have read and approved the final version of the manuscript.
AI contribution statement: The authors take full responsibility and accountability for all content of this manuscript, including any portions for which AI tools were used as assistive technologies. All AI-assisted outputs were carefully reviewed, validated, and approved by the authors. AI tools were not used to generate original scientific data, perform independent scientific analyses, or draw scientific conclusions.
Conflict-of-interest statement: All authors declare that they have no conflicts of interest relevant to this manuscript.
Corresponding author: Yehya Tlaiss, MD, Department of Ophthalmology, University of Balamand, Hazmieh, Beirut 1100, Beyrouth, Lebanon. yehyatlaiss@gmail.com
Received: June 23, 2026 Revised: July 25, 2026 Accepted: September 18, 2026 Published online: September 26, 2026 Processing time: 93 Days and 9.2 Hours
Abstract
The retinal microvasculature is the only vascular bed in the human body that can be visualised directly, non-invasively and repeatedly in vivo. Because retinal arterioles share embryological origin, calibre and autoregulatory physiology with the cerebral and coronary microcirculation, hypertension-induced retinal changes offer a unique window onto systemic small-vessel disease. For this narrative minireview, PubMed/MEDLINE, EMBASE, Scopus, Web of Science and IEEE Xplore were searched from database inception to April 30, 2026 for peer-reviewed English-language human studies of hypertensive retinopathy, quantitative retinal vascular biomarkers, multimodal retinal imaging and artificial intelligence (AI) applied to fundus images; population-based cohorts, individual-participant meta-analyses and AI studies reporting external validation were prioritised, and evidence was synthesised thematically and tabulated for cross-study comparison. Classical hypertensive retinopathy, graded for over eight decades by the Keith-Wagener-Barker and Scheie systems, has been supplemented by quantitative measurement of retinal vessel calibre and by geometric parameters such as fractal dimension and tortuosity. Large population cohorts have established that these parameters predict incident hypertension, stroke, coronary heart disease and mortality independently of conventional risk factors. Optical coherence tomography (OCT), OCT angiography and adaptive optics have extended assessment to the capillary and cellular level, while deep learning has enabled automated retinopathy grading and direct inference of blood pressure and cardiovascular risk from fundus photographs. Critically, the high accuracies reported on small private datasets are not reproduced on the first public benchmark, where the best algorithms achieved only fair agreement, and no randomised evidence yet shows that acting on a retina-derived biomarker improves outcomes. Clinical translation therefore depends on measurement standardisation, prospective multicentre and multi-ethnic external validation, explainable models, defined referral pathways from an abnormal retinal screen to blood pressure confirmation and cardiovascular risk management, and clarity on the regulatory status of software that infers systemic disease from ocular images.
Core Tip: The retina offers a directly visualisable model of the systemic microcirculation, and the integration of quantitative vascular metrics with deep-learning analysis of fundus images now allows blood pressure and cardiovascular risk to be inferred non-invasively at population scale. Realising this potential requires standardisation of measurement, validation across ethnicities and prospective demonstration that retina-derived biomarkers improve clinical decisions beyond established risk scores.
