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Retinal Vascular Signs and Cerebrovascular Diseases
Tyler Hyungtaek Rim1, Alvin Wei Jun Teo, Henrik Hee Seung Yang
1Singapore Eye Research Institute (THR, AWJT, HHSY, TYW), Singapore National Eye Centre, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program (Eye ACP) (THR, TYW), Duke-NUS Medical School, Singapore; and Department of Ophthalmology and Visual Sciences (CYC), The Chinese University of Hong Kong, Hong Kong.
Insights
Retinal signs, including hypertensive retinopathy and diabetic retinopathy, are strongly linked to cerebrovascular disease (CeVD), such as stroke. Advanced imaging and AI can help detect CeVD early.
Area of Science:
- Ophthalmology and Neurology
- Vascular Medicine
- Medical Imaging
Background:
- Cerebrovascular disease (CeVD), including stroke, is a major global health concern.
- The retina serves as a window to the brain, sharing vascular and embryological origins with the cerebrum.
- Numerous studies explore the connection between retinal indicators and CeVD.
Purpose of the Study:
- To review and synthesize recent research on the association between retinal vascular signs and cerebrovascular disease.
- To categorize and evaluate various retinal indicators and their correlation with different types of CeVD.
- To examine the role of emerging technologies like AI in assessing this link.
Main Methods:
- Systematic search of 6 databases up to July 2019 for relevant studies.
- Classification of CeVD into clinical (stroke, infarction, hemorrhage, mortality) and sub-clinical (MRI-defined infarcts, white matter lesions).
- Categorization of retinal signs into hypertensive retinopathy, clinical retinal diseases, and vascular imaging measures.
Main Results:
- Hypertensive retinopathy consistently correlates with both clinical and sub-clinical CeVD.
- Diabetic retinopathy, retinal artery/vein occlusions show consistent links to clinical CeVD.
- Retinal vascular imaging and AI-deep learning show promise in detecting CeVD indicators.
Conclusions:
- Strong and growing evidence supports a close relationship between retinal vascular conditions and CeVD.
- New technologies, particularly AI and deep learning, offer potential for clinical application in CeVD detection.
- Retinal examination is a valuable tool for assessing risk and presence of cerebrovascular disease.
Background:
Cerebrovascular disease (CeVD), including stroke, is a leading cause of death globally. The retina is an extension of the cerebrum, sharing embryological and vascular pathways. The association between different retinal signs and CeVD has been extensively evaluated. In this review, we summarize recent studies which have examined this association.
Evidence Acquisition:
We searched 6 databases through July 2019 for studies evaluating the link between retinal vascular signs and diseases with CeVD. CeVD was classified into 2 groups: clinical CeVD (including clinical stroke, silent cerebral infarction, cerebral hemorrhage, and stroke mortality), and sub-clinical CeVD (including MRI-defined lacunar infarct and white matter lesions [WMLs]). Retinal vascular signs were classified into 3 groups: classic hypertensive retinopathy (including retinal microaneurysms, retinal microhemorrhage, focal/generalized arteriolar narrowing, cotton-wool spots, and arteriovenous nicking), clinical retinal diseases (including diabetic retinopathy [DR], age-related macular degeneration [AMD], retinal vein occlusion, retinal artery occlusion [RAO], and retinal emboli), and retinal vascular imaging measures (including retinal vessel diameter and geometry). We also examined emerging retinal vascular imaging measures and the use of artificial intelligence (AI) deep learning (DL) techniques.
Results:
Hypertensive retinopathy signs were consistently associated with clinical CeVD and subclinical CeVD subtypes including subclinical cerebral large artery infarction, lacunar infarction, and WMLs. Some clinical retinal diseases such as DR, retinal arterial and venous occlusion, and transient monocular vision loss are consistently associated with clinical CeVD. There is an increased risk of recurrent stroke immediately after RAO. Less consistent associations are seen with AMD. Retinal vascular imaging using computer assisted, semi-automated software to measure retinal vascular caliber and other parameters (tortuosity, fractal dimension, and branching angle) has shown strong associations to clinical and subclinical CeVD. Other new retinal vascular imaging techniques (dynamic retinal vessel analysis, adaptive optics, and optical coherence tomography angiography) are emerging technologies in this field. Application of AI-DL is expected to detect subclinical retinal changes and discrete retinal features in predicting systemic conditions including CeVD.
Conclusions:
There is extensive and increasing evidence that a range of retinal vascular signs and disease are closely linked to CeVD, including subclinical and clinical CeVD. New technology including AI-DL will allow further translation to clinical utilization.
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