Retinal Vascular Signs and Cerebrovascular Diseases

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.

Disease of the Year: Cerebrovascular Disorders Section Editors: Valerie Biousse, MD Koto Ishida, MD Retinal Vascular Signs and Cerebrovascular Diseases Tyler Hyungtaek Rim, MD, MBA, Alvin Wei Jun Teo, MBBS, Henrik Hee Seung Yang, MSc, Carol Y. Cheung, PhD, Tien Yin Wong, MD, PhD 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 subclinical 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 Singapore 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. T. H. Rim was a scientific advisor to a start-up company, Medi-whale, Inc. He received stock as a part of the standard compensation package. T. Y. Wong is co-inventors of a patent on the various deep learning system in ophthalmology. Potential conflicts of interests are managed according to institutional policies of the Singapore Health System (SingHealth) and the National University of Singapore. The remaining authors declare no competing interests. T. H. Rim and A. W. J. Teo contributed equally as a first author. Address correspondence to Tien Yin Wong, MD, PhD, Singapore National Eye Center, 11 Third Hospital Avenue, Singapore 168751; E-mail: [e-mail] 44 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. Journal of Neuro-Ophthalmology 2020;40:44–59 doi: 10.1097/WNO.0000000000000888 © 2020 by North American Neuro-Ophthalmology Society C erebrovascular disease (CeVD), comprising stroke and vascular diseases of the brain, is one of the leading causes of death and severe disability globally (1). Screening of modifiable major risk factors for CeVD, such as hypertension, diabetes, and dyslipidemia, may prevent CeVD (1). However, identifying high-risk patients with CeVD remains challenging. The retina has been suggested as a surrogate marker for subclinical CeVD and may be useful to predict patients at risk of progression to clinical CeVD. Developmentally, the retina is part of the brain anatomy, a derivation of the embryological neural tube and extension of the subsequent diencephalon (2–4). Furthermore, the internal carotid artery supplies both the anterior brain and the retina. Specifically, the retinal vessels (100–300 mm in size) may reflect changes in cerebral vasculature and allow for a noninvasive visualization of the cerebral microcirculation in vivo (5). In this regard, blood–retina and blood–brain barrier dysfunction have been strongly implicated in the development of both retinal and cerebral microangiopathy (6). Previous studies over a century ago have shown that retinal diseases including hypertensive retinopathy and diabetic retinopathy (DR), and other retinal vessel changes have been Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders associated with the risk of CeVD (7–16). New studies show that more subtle retinal vessel changes are associated with subclinical CeVD, such as MRI-defined stroke (17), and symptomatic and asymptomatic lacunar infarcts (LI) in healthy populations (18,19). Finally, in high-risk patients with an acute stroke, retinal vessel changes may predict recurrent stroke, subsequent vascular events, and CeVD (20,21). Along with retinal vessel changes, many other common clinical retinal diseases, such as retinal vein occlusions (RVO) (22–24) and agerelated macular degeneration (AMD) have also been linked to CeVD. However, associations have been less consistently documented (25–28). Finally, there has been development of digital photography and semi-automated quantitative measurement of the retinal vessels (29,30). Studies using these methods have also shown that variations in retinal vessel diameter (e.g., narrowed retinal arteriolar diameter and widened venular diameter) are associated with risk of stroke and other CeVD (12,31) More recently, artificial intelligence (AI)-based technology such as deep learning (DL) have been used to perform automated analysis and diagnosis from medical images to predict CeVD risk factors such as hypertension directly, hence allowing for a complete “end-to-end” pointof-care screening for risk factors related to CeVD (32). In this review, we summarize the results from recent studies that examine the associations of retinal vascular signs with CeVD. We specifically focused on 2 major outcomes: clinical CeVD (including cerebral infarction, cerebral hemorrhage and stroke mortality) and sub-clinical CeVD (including MRI-defined lacunar infarct, and white matter lesions [WML]). We reviewed their associations with 3 major groups of retinal signs: traditional hypertensive retinopathy signs, clinical retinal diseases (including DR, AMD, RVO, 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 AI-DL techniques. Finally, we explore clinical implications of our review and suggest subsequent directions in research. RETINAL DISEASES Hypertensive Retinopathy In 1898, Dr. Robert Marcus Gunn described the abnormalities in retinal vessels in patients with hypertension. Keith et al refined and established the hypertensive retinopathy classification based on Dr. Gunn’s work (33). Since then, a simplified Mitchell–Wong grading system has been proposed as an alternative method for qualitative grading (34). Retinal microvascular abnormalities are well associated with hypertension (35,36). Classical retinopathy signs including microaneurysms, cotton wool spots, hard exudates, and hemorrhages are common findings in patients with diabetes mellitus or hypertension. To further differentiate, hypertension is more often accompanied by generalized and focal arteriolar narrowing, arteriolar wall opacification, and arteriovenous nicking (Fig. 1) (37). FIG. 1. Representative digital retinal fundus photographs of hypertensive retinopathy. Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 45 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders Retinopathy is also fairly common in asymptomatic older adults with no history of co-existing hypertension or diabetes (19,38). Results from the Atherosclerosis Risk in Communities Study demonstrated a correlation between retinopathy and future development of stroke (10). In addition, patients with retinopathy signs accompanied by WML of the cerebrum had an increased risk of incident stroke compared with patients without cerebral or retinal abnormalities (11). Numerous large population-based studies have also shown that retinal microvascular damage is independently associated with a spectrum of cerebrovascular ischemic diseases ranging from subclinical infarction, stroke, LI, WML, and death (Table 1 and Table 2). A meta-analysis (51) of 24 studies including 39,376 participants showed that the relative risk (RR) for stroke incidence and prevalence in the presence vs absence of retinopathy was 2.1 (95% confidence interval [CI], 1.7–2.6) and 2.5 (95% CI, 1.4–4.3), respectively. Arteriolar narrowing and decreased arteriovenous ratio (AVR) were not associated with incident stroke, but decreased AVR was associated with stroke prevalence (RR = 2.5; 95% CI, 1.4–4.3) (51). A recent meta-analysis of 28 prospective studies including 56,379 participants further revealed the association between CeVD subcategories (e.g., LI, WML) and various retinal microvascular abnormality signs (52). Any retinopathy was associated with increased risk of TABLE 1. Hypertensive retinopathy, clinical stroke, and stroke mortality (selected studies) Authors (Year) Aoki (39) (1975) Study Type Retrospective Population Classification Retinal photography 115 stroke Stroke derived from cases and 250 controls medical records 4,186 patients Retinal photography Stroke derived from medical records 855 patients Ophthalmoscope grading Stroke derived from medical records 2,859 patients Ophthalmoscope Schouten et al Retrospective grading (42) (1986) (15 and 25 All-cause mortality years followderived from up) medical records Nakayama et al Prospective 2,303 patients Retinal photography (43) (1997) (15.5 years Definite stroke vs follow-up) none (derived from medical records and CT imaging) Retinal photography Wong et al (10) Prospective (3.5 10,358 patients Stroke derived from (2001) years followmedical records up) Mitchell et al Prospective (7 3,654 patients Retinal photography Stroke diagnosed (8) (2005) years followwith neuroimaging up) Okada et al (40) (1976) Prospective (6 years followup) Svardsudd et al Prospective (4 (41) (1978) years followup) Kwon et al (44) Retrospective (2007) 550 patients Cheung et al (12) (2013) 3,189 patients Retinal photography Stroke derived from medical records Prospective (4.41 years follow-up) Retinal photography Stroke diagnosed with neuroimaging Associations Generalized arteriolar narrowing, focal narrowing, and retinopathy related to hemorrhagic stroke. Altered arteriolar reflex, focal narrowing, and AVN related to thrombotic stroke. Related to 6-year incident of thrombotic stroke. Not related to hemorrhagic stroke. Focal narrowing and AVN related to 12-year incident stroke. not related to myocardial infarct. Related to 15-year all-cause mortality in men (OR = 1.7), and 25-year all-cause mortality in women (OR = 1.3), after controlling for BP and other risk factors. Related to 15-year incident stroke in men (OR = 4.5) after controlling for BP and other risk factors. Any retinopathy is associated with increased risk of stroke (RR = 2.58; 1.59–4.20). Retinopathy in persons without diabetes, (RR = 1.7; 1.0–2.8), without severe hypertension (RR = 2.7; 1.2–6.2) or in persons with 2 or more retinal microvascular signs (RR = 2.7; 1.5–5.2) was significantly associated with combined stroke events. HTR were independent indicators for the presence of silent brain infarctions (OR = 2.01 for Grade 1; OR = 3.03 for Grade 2). The higher the grade of HTR, the more prevalent the silent brain infarctions. Retinopathy (HR = 1.94; 1.01–3.72) and larger retinal venular caliber (HR = 3.28; 1.30–8.26), were associated with risk of stroke. Selected studies are the most recent and relevant. AVN, arteriovenous nicking; BP, blood pressure; CT, Computed Tomography; HR, hazard ratio; HTR, Hypertensive Retinopathy; OR, Odds Ratio; RR, Relative Risk. 46 Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Authors (Year) Study Type Population Classification Associations Persons with retinopathy were more likely to have WMLs than those without retinopathy (22.9% vs 9.9%; RR, 2.5; 1.5–4.0). 5-year cumulative incidence of clinical stroke was higher in persons with WMLs (RR = 3.4; 1.5–7.7) and in persons with vs without retinopathy (RR = 4.9; 2.0–11.9). Persons with both WMLs and retinopathy had a significantly higher 5-year cumulative incidence of stroke than those without (RR = 18.1; 5.9–55.4). Cerebral infarcts were associated with retinal microvascular abnormalities: Arteriovenous nicking (OR = 1.90; 1.25–2.88), focal arteriolar narrowing (OR = 1.89; 1.22–2.92), blot hemorrhages (OR = 2.95; 1.30–6.71), soft exudates (OR = 2.08; 0.69–6.31), microaneurysms, (OR = 3.17; 1.05–9.64), and smallest AVR compared with largest AVR (OR = 1.74; 0.95–3.21). Larger venular diameters were associated with risk of stroke (HR = 1.12; 1.02–1.24) and cerebral infarction (HR = 1.15; 1.02–1.29). Smaller arteriolar diameters were neither related to the risk of stroke (HR = 1.02; 0.93–1.13) nor to the risk of cerebral infarction (HR = 1.02; 0.90–1.15). Prospective (4.7 years follow-up) 1,684 patients Retinal photography Cooper et al (17) (2006) Ikram et al (45) (2006) Qiu et al (46) (2009) Yatsuya et al (18) (2010) Prospective (6 years follow-up) 1,684 patients Retinal photography Prospective (8.5 years follow-up) 5,540 patients Retinal photography Prospective (4yrfollow-up) Prospective (11.2 years follow-up) 4,176 patients Retinal photography Focal arteriolar narrowing and arteriovenous nicking were significantly associated with an increasing load of subcortical and periventricular WMHs 10,496 patients Retinal photography Prospective (10.5 years follow-up) Prospective (10 years follow-up) Crosssectional study 810 patients Retinal photography Central retinal arteriole equivalent was inversely associated with lacunar stroke (HR = 1.67; 1.23–2.26). Central retinal vein equivalent was positively associated also only with lacunar stroke incidence (HR = 1.44; 1.09–1.91). Retinal microvascular abnormalities were positively associated with lacunar stroke incidence: focal arteriolar narrowing (HR = 2.22; 1.11–4.48); arteriovenous nicking (HR = 2.38; 1.20–4.71), whereas retinopathy signs were positively associated with nonlacunar thrombotic (HR = 2.41; 1.47–3.95) and cardioembolic (HR = 2.25; 1.09–4.65) stroke incidence. Any retinopathy and retinal arteriovenous nicking were associated with increased odds of incident cerebral infarct (OR = 2.82) and lacunar infarct for retinopathy (OR = 3.19) and for arteriovenous nicking (OR = 2.48). 830 patients Retinal photography 241 patients Retinal photography Crosssectional study 1,185 patients Retinal photography Retinopathy (OR = 3.18; 1.71–5.89) and AV nicking (OR = 1.93; 1.24–3.02) and focal arteriolar narrowing (OR = 1.76; 1.19–2.59) were associated with a higher quartile of a novel brain microvascular disease score combining leukoaraiosis progression with incident subclinical lacunes. Grades 2–3 hypertensive retinopathy significantly associated with moderate-to-severe WMH (OR = 3.87; 1.64–9.13), but not with lacunar infarcts (OR = 2.22, 0.83–5.92). Higher retinopathy grade (OR = 1.40; 1.16–1.70), narrower arteriolar diameter (OR = 0.98; 0.97–0.99), fewer symmetrical arteriolar bifurcations (OR = 0.84; 0.75–0.95), higher arteriolar optimality deviation (OR = 1.16; 1.00–1.34), and more tortuous venules (OR = 1.20; 1.09–1.32) were associated with strokes/infarcts and WMH. Selected studies are the most recent and relevant. AVR, Arteriole-to-venule ratio; OR, Odds Ratio; RR, Relative Risk; WMH, white matter hyperintensities; WML, White matter lesions. Disease of the Year: Cerebrovascular Disorders Wong et al (11) (2002) Cheung et al (47) (2010) Hanff et al (48) (2014) Del Brutto et al (49) (2016) Hughes et al (50) (2016) 47 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. TABLE 2. Hypertensive retinopathy and MRI-defined subclinical stroke (selected studies) Disease of the Year: Cerebrovascular Disorders cerebral infarction (Odd Ratios [OR] = 1.96, 95% CI, 1.65–2.50). After systemic risk factor adjustment, focal arteriolar narrowing and retinopathy highly correlated with WMLs (OR = 1.24, 95% CI, 1.01–1.790), LIs (OR = 1.77, 95% CI, 1.14–2.74), and nonlacunar cerebral infarction (OR = 1.75, 1.14–2.69). Arteriovenous nicking was significantly associated with WMLs (OR = 1.51, 95% CI, 1.22–1.88) and LIs (OR = 1.70, 95% CI, 1.05–2.76). In addition, when the blood pressure exceeds autoregulation’s upper limit, focal arteriolar narrowing occurs (53). In contrast, arteriovenous nicking and generalized arteriolar narrowing are associated with chronic hypertension, which in turn leads to arteriolar wall sclerosis (36). Collectively, these results illustrate that changes in retinal vasculature are indicative of distinct cerebro-microvasculopathy. Therefore, they can be used to further stratify stroke patients for better care and management (16). Diabetic Retinopathy DR is the most common complication of diabetes (54). An early case–control study identified DR as a risk factor for non-embolic ischemic stroke in individuals with diabetes mellitus, independent of smoking, hypertension, and other complications of diabetes (55). The findings were later supported by a population-based, prospective study of patients with diabetes that found DR to be significantly correlated with incident stroke (56). In a systematic review including 9 studies (57), the presence of DR from type 1 or type 2 diabetes mellitus has been associated with development of CeVD (Table 3) (47,54–56,58–62). Atrial fibrillation confers a higher risk of ischemic stroke, and this risk substantially increases with the concomitant presence of 1 or more risk factors (63). Diabetes mellitus was also an important risk factor for ischemic stroke in atrial fibrillation patients, and has been included as a risk component of common scoring schemes (e.g., CHADS2: congestive heart failure, hypertension, age $75, diabetes mellitus, stroke/transient ischemic attack) for stroke risk stratification in atrial fibrillation. The development of DR reflects more advanced disease and may incrementally predict those with increased diabetes mellitus severity and a higher risk of stroke in atrial fibrillation. However, no studies have specifically implicated DR in stroke risk of patients with both DR and atrial fibrillation (Table 3) (64,65). Retinal Vein Occlusion and Retinal Artery Occlusion RVO and RAO are common causes of severe visual impairment (66). Although thrombus formation is mainly associated with RVO, RAO is mainly caused by embolism. The partial to complete occlusion of the central retinal artery or its branches most commonly occurs secondary to an embolic event sourced from the heart, aortic arch, or the ipsilateral carotid artery, and manifests as acute retinal arte48 rial ischemia and transient monocular vison loss (TMVL). Because RAO causes severe visual problems, its clinical progress and management are quite different from those of RVO. The mechanisms of RAO formation are similar to those of cerebral infarctions, and both may be associated with pathology of the internal carotid artery (67). A comprehensive review (68) recently highlighted brain MRI findings in patients with acute retinal arterial ischemia including RAO and TMVL (Table 4). It was found that 31% of these patients with either RAO or TMVL had concomitant, often asymptomatic, acute cerebral infarctions seen on diffusion weighted images (DWI) (21,69–74). Emboli of various origins can lead to RAO and vascular TMVL. Moreover, it is accompanied by an increased risk of acute cerebral infarctions, which were present in 27%– 76.4% of patients with central RAO and in 11.8%–30.8% of those with TMVL. In addition, 6 recent large population-based studies (75–79) emphasized that RAO patients have an increased risk of subsequent stroke. Therefore, these studies suggest the need for urgent and detailed stroke characterization in acute RAO patients to accurately identify and treat underlying disorders that may predispose these patients to develop CeVD. Among the middle-aged to elderly population, RVO is a frequent cause of painless visual loss (80). A recent metaanalysis (81) of 6 cohort studies (22–24,82,83) that involved 37,471 participants revealed that after adjusting for other systemic risk factors, patients with RVO were more likely to suffer from stroke (combined RR of 1.50, 95% CI, 1.19–1.90), compared with those without RVO at baseline (Table 5). However, although RAO has an elevated risk of immediate subsequent stroke, there are no supporting data that RVO patients are in immediate danger (79,82). This indicates that disparate temporal sequences of stroke exist in RVO vs RAO and should be considered for patient stratification and treatment management. We conducted an explorative analysis by integrating our previous RAO (79) and RVO (82) studies. We extracted data from the Korean national health insurance database containing 4,277 retinal vascular occlusion patients (3,962 RVO and 313 RAO) and 21,268 sociodemographicmatched controls from 2004 to 2013. Kaplan–Meier analysis (Fig. 2) showed that the stroke-free rate decreased more abruptly in RAO patients when compared with those with RVO at the beginning of the study. At 60 days, ischemic stroke occurred in 87 (0.4%), 30 (0.8%), and 11 (3.5%) of sociodemographic-matched controls, RVO, and RAO patients, respectively. At 60 days, the hazard ratio for stroke increased by approximately 9- and 2-fold for RAO and RVO patients respectively, when compared with controls. In 2011, the American Heart Association and American Stroke Association recommended urgent etiological work up and imaging in patients suspected of brain or retinal ischemia (87). However, a recent survey on RAO treatment showed that only 35% of ophthalmologists refer central Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders TABLE 3. Diabetic retinopathy and relation to stroke Authors (Year) Study Type Petitti et al (55) (1995) Case control Klein et al (58) (2004) Prospective (4, 10, 14, 20 years followup) Prospective (7.8 years followup) Cheung et al (56) (2007) Population Classification Associations 2,124 patients (T1DM & T2DM) 996 patients (T1DM) Medical records to diagnose stroke and DR Presence of DR is associated with ischemic stroke (RR = 4.0; 1.0– 14.5). DR associated with stroke (OR = 1.6; 1.1–2.3). 1,617 patients (T1DM & T2DM) Cheung et al (47) (2010) Prospective (10.5 years follow-up) 810 patients (T1DM & T2DM) Kawasaki et al (61) (2013) Prospective (8 years followup) Prospective (12 years followup) 2,033 patients (T2DM) Hägg et al (60) (2014) Prospective (9.0 ± 2.7 years follow-up) 4,083 patients Lip et al (65) (2015) Registry 8,962 patients (T1DM & T2DM) Chou et al (64) (2016) Registry Hankey et al (62) (2016) Prospective (5 years followup) 50,180 patients (T1DM & T2DM) 9,795 patients (T2DM) Hägg et al (59) (2013) 4,083 patients (T1DM) Retinal photographs Stroke derived from patient contact and death records Retinal photographs Stroke diagnosed from hospital records, death records and patient survey Stroke diagnosed on neuroimaging. Retinal photographs were used. Retina photographs. Stroke diagnosed via medical records. Postlaser treatment of retina was considered DR. Stroke derived from medical records, CT/MRI imaging/autopsy Post laser treatment of retina were considered DR. Type of stroke identified with MRI/CT DR and stroke derived from medical records. Stroke diagnosed with neuroimaging, DR and AF diagnosed from medical records. DR diagnosis undefined. Stroke diagnosed on neuroimaging DR is associated with ischemic stroke (HR = 2.34; 1.13–4.86). DR associated with incident cerebral infarct (OR = 7.35; 1.72–31.34) and incident lacunar infarct (OR = 5.32; 1.23–23.03). Mild-to-moderate DR is associated with stroke (HR = 1.69; 1.03– 2.80). Severe DR associated with stroke (HR = 3.0; 1.9–4.5), cerebral infarction (HR = 2.7; 1.6–4.4), and cerebral hemorrhage (HR = 3.9; 1.7–8.9). DR associated with hemorrhagic stroke (HR = 2.99; 1.18–7.55). In patients with AF, there was no significant difference in risk of stroke between patients with DR and no DR (RR = 1.21; 0.80–1.84, P = 0.37) In patients with AF, risk of ischemic stroke was similar between patients with and without diabetic microvascular complications. DR associated with small-artery ischemic stroke (HR = 1.82; 1.08– 3.07). AF, atrial fibrillation; CT, computed tomography; DR, diabetic retinopathy; HR, hazard ratio; OR, odds ratio; RR, relative risk; T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus. RAO patients to the emergency department (88). Our explorative analysis confirms that because of higher risk for early stroke, a systemic evaluation should be performed as soon as possible to prevent stroke from occurring in patients with RAO. Age-Related Macular Degeneration AMD is the leading cause of blindness worldwide (89). It is an acquired disease of the macula due to late-onset neurodegeneration of the photoreceptor-retinal pigment epithelium Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 complex. Drusen are composed of focal yellow extracellular polymorphous material that are found in the macula. AMD is generally classified into early, intermediate, and late AMD. The pathophysiology of AMD is not fully understood, but thought to be vascular in nature, sharing similar risk factors to cardiovascular events such as age, cholesterol, hypertension, and smoking (90,91). There is evidence that AMD is independently associated with increased risk of cardiovascular events and mortality, with early AMD predicting a doubling of cardiovascular mortality (RR, 2.32; 95% CI, 1.03–5.19) 49 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders TABLE 4. Retinal artery occlusion and stroke Authors (Year) Study Type Helenius et al Retrospective (69) (2012) Chang et al Registry (76) (2012) Lee et al (70) Retrospective (2014) Tanaka et al Retrospective (71) (2014) Lauda et al Retrospective (72) (2015) Park et al (78) Self-controlled (2015) case series Cho et al (73) Retrospective (2016) Rim et al (79) Retrospective (2016) Golsari et al Prospective (74) (2017) (follow-up undefined) Tanaka et al Prospective (3 (21) (2018) mth and 1 years followup) Zhang et al Retrospective (84) (2018) Lavin et al (85) Retrospective (2018) Chodnicki et al Retrospective (86) (2019) Population Classification Associations Abnormal DWI in 24% of patients (33% CRAO/BRAO vs 18% TMVL). Same vascular territory as VL in 90% of patients with DWI-MRI changes. CRAO = 464 Stroke and RAO derived from 91 RAO patients (19.61%) and 280 Controls = medical records controls (10.05%) had a stroke (P , 2,748 0.0001). 33 patients Retinal photography 24.2% of patients with CRAO had acute Stroke diagnosed with DWI-MRI ischemic stroke. Same vascular territory as VL in all patients. No difference was observed between the 13 patients Isolated TMVL derived from TMVL and non-TMVL groups in the medical records frequency of hyperintense DWI lesions Stroke diagnosed with DWI-MRI (30.8% vs 21.0%, respectively; P = 0.488) TMVL group was more likely to have stenotic lesions in the extracranial ICA than non-TMB (P = 0.022). 213 patients TMVL/BRAO/CRAO derived from CRAO (OR = 1.10; P = 0.71) and BRAO (OR = 1.91; P = 0.02) are clinical exam independently associated with DWIStroke diagnosed with DWI-MRI positive acute brain ischemia. 10% of CRAO patients associated with 1,655 patients CRAO from claims records stroke. Stroke derived from medical records 46 patients BRAO from retinal photographs Embolic group had a higher frequency of Stroke diagnosed with DWI-MRI acute cerebral infarctions and stenotic carotid arteries. (P = 0.017 and P = 0.028, respectively) RAO and stroke derived from Stroke more likely to occur in RAO group RAO = 401 medical records than comparison group (P , 0.001). Controls = RAO associated with an increased risk 2,003 of stroke occurrence (HR = 1.78; 1.32–2.41). 112 patients TMVL/BRAO/CRAO from medical 15% of patients had abnormal DWI-MRI. records (CRAO: 76.4%, BRAO: 11.8% vs TMVL: Stroke diagnosed with DWI-MRI 11.8%). 40 patients TIA from medical records 18% of patients with TMVL had abnormal DWI-MRI. 129 patients Isolated TMVL/BRAO/CRAO from medical records Stroke diagnosed with DWI-MRI 41 patients TMVL/BRAO/CRAO from medical 19.5% had abnormal DWI-MRI. Lesion records positive MRI is 4.3% in TMVL, 33.3% Stroke diagnosed with DWI-MRI in CRAO, and 40% in BRAO. CRAO from medical records 37% of patients had abnormal DWI-MRI. Stroke diagnosed with DWI-MRI CRAO 5.3% had symptomatic ischemic stroke Stroke diagnosed with DWI-MRI around time of CRAO, 2.3% occurring 15 days before CRAO, (1.3%) occurring simultaneously with CRAO, and 1.7% occurring after CRAO. TIA and TMVL were seen in 1.7% and 8.7% of patients respectively. 103 patients 300 patients Selected studies are the most recent and relevant. BRAO, branch retinal artery occlusion; CRAO, central retinal artery occlusion; DWI-MRI, diffuse weighted imaging MRI; ICA, internal carotid artery; OR, odd ratio; RAO, retinal artery occlusion; TIA, transient ischemic attack; TMVL, vascular transient monocular visual loss. 50 Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders TABLE 5. Retinal vein occlusion and stroke (selected studies) Authors (Year) Study Type Cugati et al (22) (2007) Prospective (12 years follow-up) Ho et al (23) (2009) Retrospective Werther et al (24) (2011) Retrospective Bertelsen et al (83) (2014) Registry Rim et al (82) (2015) Prospective (9 years follow-up) Population Classification Associations 8,282 patients Retinal photographs. RVO not associated with Vascular deaths were cerebrovascular-related determined using either death mortality (HR = 0.9; 0.4–2.1) certificates or the Australian National Death Index. RVO not associated with an RVO = 350 control RVO (ICD-9). increased risk of stroke. (HR = 2,100 Stroke based on medical = 1.01; 0.65–1.57) records RVO patients age 60–69 years had a 2.34-fold (1.05– 5.24) higher risk of suffering a stroke RVO = 4,500 RVO (ICD-9). Risk of developing stroke is Control = Stroke derived from medical higher for RVO vs controls 13,500 records (RR = 1.72; 1.27–2.34; P = 0.001) Risk of developing stroke is CRVO = 439 Retinal photographs. higher with CRVO (RR = Control = 2,195 Death records were obtained 2.09; 1.51–2.89). from Danish registry. RVO = 1,031 RVO and ischemic or RVO was associated with an Control = 5,074 hemorrhagic stroke (ICD-9). increased risk of stroke development (HR = 1.48; 1.24–1.76) Selected studies are the most recent and relevant. CRVO, central retinal vein occlusion; HR, hazard ratio; ICD-9, International Classification of Diseases, Ninth Revision; RR, relative risk; RVO, retinal vein occlusion. and late AMD, a 5-fold higher cardiovascular mortality (RR, 5.57; 95% CI, 1.35–22.99). A 10-fold higher stroke mortality (RR, 10.21; 95% CI, 2.39–43.60) was also found in the same study (92). However, the association of AMD with stroke in other studies is mixed (Table 6). Some studies found that early AMD was associated with stroke (RR = 1.87; 95% CI, 1.21–2.88) (25). Another study found that early or late AMD was not associated with stroke (93). It was also found that late AMD was more strongly associated with hemorrhagic stroke than with cerebral infarction (94,95). However, a metaanalysis involving 9 studies with 1,420,978 patients found no FIG. 2. Stroke-free rate in retinal artery and vein occlusion. In this explorative pooled analysis, the stroke-free rate decreased more abruptly in retinal artery occlusion group. Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 51 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders significant relationship between AMD and stroke (OR, 1.12; CI, 0.86–1.47; I2 = 96%) (96). Another meta-analysis included associations of stroke and AMD while investigating AMD as a risk factor for cardiovascular events and mortality (97). In this study, 8 studies involving 1,424,573 participants were included. It showed that there was high heterogeneity in the 8 studies comparing AMD with the risk of stroke (I2 = 92%; P , 0.00001), and the RR (95% CI) from the randomeffects model was 1.13 (0.93–1.36) (97). There is therefore no conclusive evidence that AMD is associated with an increased risk of stroke. More research is needed to prove the association between these 2 conditions. RETINAL VASCULAR IMAGING MEASURES Compared with qualitative assessments, with the advances in image processing technology, quantitative objective measurements of the retinal vessel offer early detection of subtle early microvascular abnormalities of the retina with higher accuracy. This quantitative measurement provides new insights into the pathogenic mechanisms underlying CeVDs. The retinal vessel can be captured as 3 different retinal vascular signs: classic retinopathy, retinal vascular caliber change, and global geometric pattern changes (100). Retinal Vascular Caliber The standard retinal vascular caliber parameters are central retinal artery equivalent (CRAE), central retinal vein equivalent (CRVE), and AVR. CRAE and CRVE indicate the average width or retinal arterioles, and average width of retinal venules, respectively. Recent epidemiologic studies have illustrated that changes in these parameters are connected to diabetes mellitus, cardiovascular disease, hypertension, and other systemic conditions (10,29– 31,101–109). In particular, retinal venular widening is associated with increased risk of stroke and stroke mortality (10,12,13). This was further confirmed in a meta-analysis of 20,798 participants (110). TABLE 6. AMD and stroke Authors (Year) Study Type Wong et al (25) Prospective (10 (2006) years followup) Alexander et al Retrospective (2 (26) (2007) years followup) Liao et al (27) Retrospective (2 (2008) years followup) Retrospective (3 Nguyen-Koa years followet al (28) up) (2008) Sun et al (93) Prospective (6 (2009) years followup) Population 10,405 patients 62,179 patients 1,303,186 patients 27,411 patients Classification Associations Early and late AMD based on fundus photography Stroke (ICD-9, ICD-10) Neovascular AMD only Stroke (ICD-9) Neovascular AMD and nonneovascular AMD (ICD-9) Stroke (ICD-9) Neovascular AMD only (ICD-9) Stroke (ICD-9) 2,228 patients Early and late AMD based on fundus photography Stroke via review of medical records Retrospective (5 1,254 patients Neovascular AMD only Hu et al (98) (2010) years followup) Prospective (13 6,207 patients Early and late AMD based on Wieberdink fundus photography years followet al (94) Self-reported verified stroke up) (2011) with medical records by neurologists Ikram et al (95) Prospective (13 12,216 Early and late AMD based on (2012) years followpatients fundus photography up) Self-reported stoke verified against discharge list Fernandez et al Prospective (5 6,233 Early and late AMD based on (99) (2012) years followfundus photography up) Stroke via review of medical records (neurologist) Early AMD was associated with stroke (RR = 1.85; 1.19–2.88) Neovascular AMD was not associated with stroke (RR = 0.94; 0.85–1.03) AMD was associated with stroke (RR = 1.21; 1.18–1.24) Neovascular AMD showed protective effect for stroke (RR = 0.56; 0.45– 0.70) AMD was not associated with stroke (RR = 1.08; 0.73–1.60) Neovascular AMD was associated with stroke (RR = 2.01; 1.34–3.02) AMD was not associated with stroke (RR = 1.02; 0.88–1.18) AMD was associated with stroke (RR = 1.51; 1.11–2.05) No significant association was found between subgroups of early AMD or late AMD and incident CVD events (6.6% vs 5.5%, P = 0.19 for CVD). AMD, aged related macular degeneration; CVD, cerebrovascular disease; ICD-9, International Classification of Diseases, Ninth Revision; MESA, Multi-ethnic Study of Atherosclerosis; RR, relative risk. 52 Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders Computer-aided quantitative, objective measurements of retinal vessel narrowing and widening secondary to subtle microvascular dysfunction is possible (111). The Atherosclerosis Risk in Communities (ARIC) Study-based computer analysis program is most frequently used (10). In the ARIC study, the zone of retinal vascular caliber measurement was defined as the radial area of 0.5–1.0 disc diameters from the optic disc margin (112,113). This particular method of fundoscopy image analysis has been further augmented and semi-automated through software development (Singapore I Vessel Assessment [SIVA], National University of Singapore, Singapore, (114); and Vessel assessment and measurement platform for images of the retina [VAMPIRE] (115)). Furthermore, new software can further quantify the retinal vasculature more comprehensively by factoring in fractal dimension, junction exponent deviation, tortuosity, and branching angle in addition to retinal vascular caliber change. Global Geometrical Patterns in Retinal Vasculature Retinal vascular branching pattern can be quantified using several global geometrical parameters including fractal dimension, tortuosity, and branching angle (Fig. 3). In accordance to Murray’s principle of minimum work, the branching of the human circulatory system follows the optimum design principle (116). This can be further extrapolated to show that although theoretical peak blood flow efficiency is achieved by optimal branching of the retinal vasculature, any deviations to the suboptimal or less will lead to microcirculatory impairment, shear stress, and pathogenesis. Collectively, these abnormalities represent vascular damages (117). Fractal dimension is an aggregated global measure of retinal vascular branching. A reduction in vascular fractal dimension can be attributed to retinal vessel narrowing and collapse. This phenotype is typically associated with hypoxia. In contrast, elevated vessel tortuosity is a mark of vessel wall dysfunction and blood–retinal barrier damage (118). These dysfunctional changes inversely affect the cerebral arteriole’s blood flow control, and result in increased risk of local ischemia (119–121). Altogether, these studies suggest that novel structural parameters can potentially generate further insight beyond those obtained from qualitative indicators (Fig. 3). EMERGING RETINAL VASCULAR IMAGING TECHNIQUES Quantitative examination of the retinal vasculature can be applied to additional imaging modalities including optical coherence tomography (OCT) angiography, and ultra-wide field retinal imaging. En face images can further analyze vessel tortuosity (122), fractal dimension, and branching angles (12). However, access to such methods in the clinical setting is limited by the specialized analysis and high-quality image requirements. Further evaluation is necessary to confirm the benefits of these new imaging modalities before applying clinical practice (summarized in Table 7). Dynamic Retinal Vessel Analysis One early marker of stroke and other small vessel diseases of the brain is endothelial dysfunction (123,124). When the retina is stimulated, that is, flickering lights, the increased neural activity sends feedback to the retinal vessel endothelium to secrete nitric oxide and other vasoactive factors that cause vasodilation. If endothelial function is impaired, this will be reflected in the degree of vasodilation, which can be used as a surrogate marker of endothelial dysfunction and microcirculation damage (125). Real-time evaluation of the flickering light-induced vasodilation is possible with the Dynamic Vessel Analyzer (IMEDOS, Jena, Germany). This novel method demonstrated that patients with diabetes and severe DR had decreased vasodilation response and endothelial dysfunction (117). Adaptive Optics Imaging of the Retina Wavefront distortions and optical aberrations, inherent factors of optical systems, can be compensated by adaptive optics, which is also used in astronomic telescopes and laser communication systems. Currently, adaptive optics systems for the human retina can achieve a 2-mm resolution, which is high enough to visualize nerve fiber bundles and capillaries (126). This application can potentially detect cellular degeneration processes of the vasculature in vivo. Furthermore, the system’s high resolution advantage is the retinal microvessel wall-to-lumen ratio measurability (127), a feature of small vessel disease and predictor of end-organ damage (128,129). Besides ocular diseases, these adaptive optics can also be applied to study cerebral diseases. FIG. 3. Measurement of global geometrical patterns from ocular fundus photography fractal dimension (A), tortuosity (B and C), and bifurcation (D). Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 53 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders TABLE 7. Emerging Retinal Vascular Imaging (selected studies) Authors (Year) Population Method Meixner et al (127) (2015) 47 patients Adaptive optics Spaide et al (130) (2015) 12 eyes OCT angiography vs fluorescein angiography Arnould et al (131) (2018) 237 patients OCT angiography Associations WLR depended significantly on the wall thickness (r = 0.715; P , 0.01) of retinal arterioles, but was independent of the total vessel diameter (r = 0.052; P = 0.728). WLR correlated significantly with age (r = 0.769; P , 0.01). Arterial hypertension and a higher BMI were significantly associated with an increased age-adjusted WLR. Radial peripapillary capillary network was visualized completely by SSADA vs fluorescein angiography. Mean proportion of the inner vascular plexus being 95.3% (92.2%–97.8%) vs 4.7% (2.6%– 5.7%) for the outer capillary plexus from the SSADA scans. The AHA risk score (OR = 1.06; 1.04–1.09) and LVEF (OR = 0.95; 0.93–0.98) were significantly associated with the lowest tertile of retinal vascular density. Selected studies were most relevant. AHA, American Heart Association; BMI, body mass index; LVEF, left ventricular ejection fraction; OR, odd ratio; SD-OCT, spectral domain optical coherence tomography; SSADA, split-spectrum amplitude-decorrelation angiograph; WLR, wall-lumen ratio. OCT Angiography Recently, several forms of OCT with angiography have been reported to improve vessel contrast with micron-level axial resolution and precise retinal vessel segmentation (130). Recent advancements in OCT angiography have permitted noninvasive evaluation of retinal vascular abnormalities such as ischemia. Superficial retinal capillary plexus vascular density was associated with American Heart Association (AHA) risk and Global Registry of Acute Coronary Events (GRACE) scores and was suggested as a good surrogate marker (131). However, the association between CeVD and abnormal finding in OCT angiography has yet to be examined in humans (Table 7). We have repeated additional experiments because Google’s research has not yet been reproduced. This explorative analysis included 172,170 colour fundus photographs from 9,956 adults 40 years and older in the Singapore Epidemiology of Eye Diseases Study. Age prediction via DL using retinal imaging (Fig. 4) showed mean absolute error of 3.90 and goodness-of-fit of 0.75 (R2). DL algorithms have higher precision and accuracy in the detection of subclinical changes compared with professional human operators. In the future, DL algorithms may be used to identify vascular pathologies including CeVD, agerelated degenerative conditions including Alzheimer’s disease, and systemic ailments such as multiple sclerosis, from both fundus photographs and OCT images. At this time, to DEEP LEARNING FOR MEDICAL IMAGE ANALYSIS The strength of DL is in its ability to transform digital images to morphological datasets that hold quantitative information about, but not limited to, macular and retinal pathologies (132). Ophthalmology is particularly well positioned to benefit from advances in DL techniques. In the ophthalmology field, AI using DL has been broadly studied (133,134). Notably, Google-backed researchers applied their DL algorithm to retinal fundus images from a 284,335 participant dataset and were able to predict cardiovascular risk factors including old age and male gender (32). Cardiovascular risks were identified with high accuracy: age (mean absolute error, 3.26 years), sex (area under the curve (65), 0.97), systolic blood pressure (mean absolute error, 11 mm Hg), and major cardiac adverse events (area under the curve, 0.70). The study results demonstrate that DL-assisted retinal image grading may have future value in screening and early diagnostic evaluation of systemic diseases (135). 54 FIG. 4. Prediction of age via deep learning from retinal image. The deep learning algorithm predicts the age from a retinal image. Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders FIG. 5. Clinical translational pathway. develop DL algorithms with higher accuracy in the prediction of cardiovascular risk and mortality, training and verification via larger datasets with higher numbers of cardiovascular events are required (136). Once “exploited” extensively by machine learning methodologies, the retina can serve as a window to identify other vascular-related pathological disorders (137). CLINICAL TRANSLATIONAL PATHWAY Current advances and clinical application of retinal fundoscopy image-based CeVD risk stratification methods are constrained by our lack of knowledge to map microvessel changes of the retina to cerebrovascular accidents and diseases. Retinopathy can be evaluated from retinal photographs by ophthalmologists, opticians, trained readers, and computer-aided retinal analytic programs (138,139). Currently, the evaluation of such features is quite long and detailed and requires expert evaluators. For instance, manual identification of retinopathy signs and measurement of vessel diameters using semi-automated tools are fairly timeconsuming processes. Simultaneous use of fully automated detection of retinopathy signs and a fully automated measurement tool, SIVA, will facilitate efficient assessment of changes in the retina and retinal vasculature (140). One proposed method is to individualize risk assessment for each patient. This can be done by taking into account known vascular risk factors in the evaluation of hypertensive retinopathy signs (Fig. 5). For this, we need to develop and validate a risk stratification model using prospective data. In previous studies of patients with hypertension (141,142), retinal vessel sign degeneration, an indicator of blood pressure drop, has been used as a marker in monitoring antihypertensive medication response. Potentially, this can serve as a biomarker to administer, monitor, and assess CeVD treatments. CONCLUSION AND FUTURE DIRECTIONS Most studies suggest that retinal vascular signs and diseases are connected to cerebrovascular abnormalities. For patients with RAO, existing guidelines recommend appropriate follow-up to evaluate for risk of stroke. For other associations, no clear guidelines are available. With advances in technology, it is also possible to quantify more subtle retinal Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 vessel abnormalities. AI-based DL technology has shown excellent performance in image analysis beyond human cognition. Retinal examination and retinal vessel analysis, along with the discovery of novel risk factors, and improved risk stratification of patients at intermediate to high risk of CeVD will improve diagnosis, early intervention, and prognosis of cerebrovascular accidents and diseases. These studies are necessary to validate the efficacy of retinal imaging before it is fully translated to clinical practice. REFERENCES 1. Menken M, Munsat TL, Toole JF. The global burden of disease study: implications for neurology. Arch Neurol. 2000;57:418– 420. 2. Pei YF, Rhodin JA. The prenatal development of the mouse eye. Anat Rec. 1970;168:105–125. 3. Patton N, Aslam T, MacGillivray T, Pattie A, Deary IJ, Dhillon B. Retinal vascular image analysis as a potential screening tool for cerebrovascular disease: a rationale based on homology between cerebral and retinal microvasculatures. J Anat. 2005;206:319–348. 4. Patton N, Aslam TM, MacGillivray T, Deary IJ, Dhillon B, Eikelboom RH, Yogesan K, Constable IJ. Retinal image analysis: concepts, applications and potential. Prog Retin Eye Res. 2006;25:99–127. 5. Levy BI, Ambrosio G, Pries AR, Struijker-Boudier HA. Microcirculation in hypertension: a new target for treatment? Circulation. 2001;104:735–740. 6. London A, Benhar I, Schwartz M. The retina as a window to the brain—from eye research to CNS disorders. Nat Rev Neurol. 2013;9:44. 7. Wong TY, Klein R, Nieto FJ, Klein BE, Sharret AR, Meuer SM, Hubbard LD, Tielsch JM. Retinal microvascular abnormalities and 10-year cardiovascular mortality: a population-based case-control study. Ophthalmology. 2003;110:933–940. 8. Mitchell P, Wang JJ, Wong TY, Smith W, Klein R, Leeder SR. Retinal microvascular signs and risk of stroke and stroke mortality. Neurology. 2005;65:1005–1009. 9. Witt N, Wong TY, Hughes AD, Chaturvedi N, Klein BE, Evans R, McNamara M, Thom SAM, Klein R. Abnormalities of retinal microvascular structure and risk of mortality from ischemic heart disease and stroke. Hypertension. 2006;47:975–981. 10. Wong TY, Klein R, Couper DJ, Cooper LS, Shahar E, Hubbard LD, Wofford MR, Sharrett AR. Retinal microvascular abnormalities and incident stroke: the atherosclerosis risk in communities study. Lancet. 2001;358:1134–1140. 11. Wong TY, Klein R, Sharrett AR, Couper DJ, Klein BE, Liao DP, Hubbard LD, Mosley TH; ARIC. Cerebral white matter lesions, retinopathy, and incident clinical stroke. JAMA. 2002;288:67–74. 12. Cheung CY, Tay WT, Ikram MK, Ong YT, De Silva DA, Chow KY, Wong TY. Retinal microvascular changes and risk of stroke: the Singapore Malay Eye Study. Stroke. 2013;44:2402–2408. 55 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders 13. Kawasaki R, Xie J, Cheung N, Lamoureux E, Klein R, Klein BE, Cotch MF, Sharrett AR, Shea S, Wong TY; MESA. Retinal microvascular signs and risk of stroke: the Multi-Ethnic Study of Atherosclerosis (MESA). Stroke. 2012;43:3245–3251. 14. Wang JJ, Baker ML, Hand PJ, Hankey GJ, Lindley RI, Rochtchina E, Wong TY, Liew G, Mitchell P. Transient ischemic attack and acute ischemic stroke: associations with retinal microvascular signs. Stroke. 2011;42:404–408. 15. Goto I, Katsuki S, Ikui H, Kimoto K, Mimatsu T. Pathological studies on the intracerebral and retinal arteries in cerebrovascular and noncerebrovascular diseases. Stroke. 1975;6:263–269. 16. Ong YT, De Silva DA, Cheung CY, Chang HM, Chen CP, Wong MC, Wong TY, Lkram MK. Microvascular structure and network in the retina of patients with ischemic stroke. Stroke. 2013;44:2121–2127. 17. Cooper LS, Wong TY, Klein R, Sharrett AR, Bryan RN, Hubbard LD, Couper DJ, Heiss G, Sorlie PD. Retinal microvascular abnormalities and MRI-defined subclinical cerebral infarction: the atherosclerosis risk in communities study. Stroke. 2006;37:82–86. 18. Yatsuya H, Folsom AR, Wong TY, Klein R, Klein BE, Sharrett AR. Retinal microvascular abnormalities and risk of lacunar stroke: atherosclerosis risk in communities study. Stroke. 2010;41:1349–1355. 19. Wong TY, Mosley TH Jr, Klein R, Klein BE, Sharrett AR, Couper DJ, Hubbard LD. Retinal microvascular changes and MRI signs of cerebral atrophy in healthy, middle-aged people. Neurology. 2003;61:806–811. 20. De Silva DA, Manzano JJ, Liu EY, Woon FP, Wong WX, Chang HM, Chen C, Lindley RI, Wang JJ, Mitchell P, Wong TY. Retinal microvascular changes and subsequent vascular events after ischemic stroke. Neurology. 2011;77:896–903. 21. Tanaka K, Uehara T, Kimura K, Okada Y, Hasegawa Y, Tanahashi N, Suzuki A, Nakagawara J, Arii K, Nagahiro S, Ogasawara K. Comparison of clinical characteristics among subtypes of visual symptoms in patients with transient ischemic attack: analysis of the PROspective multicenter registry to identify subsequent cardiovascular events after TIA (PROMISE-TIA) Registry. J Stroke Cerebrovasc Dis. 2018;27:1711–1716. 22. Cugati S, Wang JJ, Knudtson MD, Rochtchina E, Klein R, Klein BE, Wong TY, Mitchell P. Retinal vein occlusion and vascular mortality: pooled data analysis of 2 population-based cohorts. Ophthalmology. 2007;114:520–524. 23. Ho JD, Liou SW, Lin HC. Retinal vein occlusion and the risk of stroke development: a five-year follow-up study. Am J Ophthalmol. 2009;147:283–290 e282. 24. Werther W, Chu L, Holekamp N, Do DV, Rubio RG. Myocardial infarction and cerebrovascular accident in patients with retinal vein occlusion. Arch Ophthalmol. 2011;129:326–331. 25. Wong TY, Klein R, Sun C, Mitchell P, Couper DJ, Lai H, Hubbard LD, Sharrett AR. Age-related macular degeneration and risk for stroke. Ann Intern Med. 2006;145:98–106. 26. Alexander SL, Linde-Zwirble WT, Werther W, Depperschmidt EE, Wilson LJ, Palanki R, Saroj N, Butterworth SL, Ianchulev T. Annual rates of arterial thromboembolic events in medicare neovascular age-related macular degeneration patients. Ophthalmology. 2007;114:2174–2178. 27. Liao D, Mo J, Duan Y, Klein R, Scott IU, Huang KA, Zhou H. Is age-related macular degeneration associated with stroke among elderly Americans? open Ophthalmol J. 2008;2:37. 28. Nguyen-Khoa BA, Goehring EL Jr, Werther W, Gower EW, Do DV, Jones JK. Hospitalized cardiovascular diseases in neovascular age-related macular degeneration. Arch Ophthalmol. 2008;126:1280–1286. 29. Cheung CY, Tay WT, Mitchell P, Wang JJ, Hsu W, Lee ML, Lau QP, Zhu AL, Klein R, Saw SM, Wong TY. Quantitative and qualitative retinal microvascular characteristics and blood pressure. J Hypertens. 2011;29:1380–1391. 30. Cheung N, Donaghue KC, Liew G, Rogers SL, Wang JJ, Lim SW, Jenkins AJ, Hsu W, Lee ML, Wong TY. Quantitative 56 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. assessment of early diabetic retinopathy using fractal analysis. Diabetes Care. 2009;32:106–110. Cheung CY, Zheng Y, Hsu W, Lee ML, Lau QP, Mitchell P, Wang JJ, Klein R, Wong T. Retinal vascular tortuosity, blood pressure, and cardiovascular risk factors. Ophthalmology. 2011;118:812–818. Poplin R, Varadarajan AV, Blumer K, Liu Y, McConnell MV, Corrado GS, Peng L, Webster DR. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning. Nat Biomed Eng. 2018;2:158. Keith NM. Some different types of essential hypertension: their course and prognosis. Am J Med Sci. 1939;197:332– 343. Wong TY, McIntosh R. Hypertensive retinopathy signs as risk indicators of cardiovascular morbidity and mortality. Br Med Bull. 2005;73-74:57–70. Tso MO, Jampol LM. Pathophysiology of hypertensive retinopathy. Ophthalmology. 1982;89:1132–1145. Wong TY, Mitchell P. Hypertensive retinopathy. N Engl J Med. 2004;351:2310–2317. Wong TY, Klein R, Klein BE, Tielsch JM, Hubbard L, Nieto FJ. Retinal microvascular abnormalities and their relationship with hypertension, cardiovascular disease, and mortality. Surv Ophthalmol. 2001;46:59–80. Wong TY, Klein R, Sharrett AR, Manolio TA, Hubbard LD, Marino EK, Kuller L, Burke G, Tracy RP, Polak JF, Gottdiener JS. The prevalence and risk factors of retinal microvascular abnormalities in older persons: the cardiovascular health study. Ophthalmology. 2003;110:658–666. Aoki N. Epidemiological evaluation of funduscopic findings in cerebrovascular diseases. I. Fundoscopic findings as risk factors for cerebrovascular diseases. Jpn Circ J. 1975;39:257–269. Okada H, Horibe H, Yoshiyuki O, Hayakawa N, Aoki N. A prospective study of cerebrovascular disease in Japanese rural communities, Akabane and Asahi. Part 1: evaluation of risk factors in the occurrence of cerebral hemorrhage and thrombosis. Stroke. 1976;7:599–607. Svardsudd K, Wedel H, Aurell E, Tibblin G. Hypertensive eye ground changes. Prevalence, relation to blood pressure and prognostic importance. The study of men born in 1913. Acta Med Scand. 1978;204:159–167. Schouten EG, Vandenbroucke JP, van der Heide-Wessel C, van der Heide RM. Retinopathy as an independent indicator of all-causes mortality. Int J Epidemiol. 1986;15:234–236. Nakayama T, Date C, Yokoyama T, Yoshiike N, Yamaguchi M, Tanaka H. A 15.5-year follow-up study of stroke in a Japanese provincial city. The Shibata Study. Stroke. 1997;28:45–52. Kwon HM, Kim BJ, Oh JY, Kim SJ, Lee SH, Oh BH, Yoon BW. Retinopathy as an indicator of silent brain infarction in asymptomatic hypertensive subjects. J Neurol Sci. 2007;252:159–162. Ikram MK, de Jong FJ, Bos MJ, Vingerling JR, Hofman A, Koudstaal PJ, De Jong PT, Breteler MM. Retinal vessel diameters and risk of stroke: the Rotterdam Study. Neurology. 2006;66:1339–1343. Qiu C, Cotch MF, Sigurdsson S, Klein R, Jonasson F, Klein BE, Garcia M, Jonsson PV, Harris TB, Eiriksdottir G, Kjartansson O. Microvascular lesions in the brain and retina: the age, gene/environment susceptibility-Reykjavik study. Ann Neurol. 2009;65:569–576. Cheung N, Mosley T, Islam A, Kawasaki R, Sharrett AR, Klein R, Coker LH, Knopman DS, Shibata DK, Catellier D, Wong TY. Retinal microvascular abnormalities and subclinical magnetic resonance imaging brain infarct: a prospective study. Brain. 2010;133:1987–1993. Hanff TC, Sharrett AR, Mosley TH, Shibata D, Knopman DS, Klein R, Klein BE, Gottesman RF. Retinal microvascular abnormalities predict progression of brain microvascular disease: an atherosclerosis risk in communities magnetic resonance imaging study. Stroke. 2014;45:1012–1017. Del Brutto OH, Mera RM, Viteri EM, Pólit J, Ledesma EA, Cano JA, Plaza KJ, Zambrano M, Costa AF. Hypertensive retinopathy Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders 50. 51. 52. 53. 54. 55. 56. 57. 58. 59. 60. 61. 62. 63. 64. 65. and cerebral small vessel disease in Amerindians living in rural Ecuador: the Atahualpa Project. Int J Cardiol. 2016;218:65–68. Hughes AD, Falaschetti E, Witt N, Wijetunge S, Thom SA, Tillin T, Aldington SJ, Chaturvedi N. Association of retinopathy and retinal microvascular abnormalities with stroke and cerebrovascular disease. Stroke. 2016;47:2862–2864. Doubal F, Hokke P, Wardlaw J. Retinal microvascular abnormalities and stroke: a systematic review. J Neurol Neurosurg Psychiatry. 2009;80:158–165. Dumitrascu OM, Demaerschalk BM, Valencia Sanchez C, Almader-Douglas D, O’Carroll CB, Aguilar MI, Lyden PD, Kumar G. Retinal microvascular abnormalities as surrogate markers of cerebrovascular ischemic disease: a meta-analysis. J Stroke Cerebrovasc Dis. 2018;27:1960–1968. Lassen NA, Agnoli A. The upper limit of autoregulation of cerebral blood flow—on the pathogenesis of hypertensive encepholopathy. Scand J Clin Lab Invest. 1972;30:113–116. Ting DS, Cheung GC, Wong TY. Diabetic retinopathy: global prevalence, major risk factors, screening practices and public health challenges: a review. Clin Exp Ophthalmol. 2016;44:260–277. Petitti DB, Bhatt H. Retinopathy as a risk factor for nonembolic stroke in diabetic subjects. Stroke. 1995;26:593–596. Cheung N, Rogers S, Couper DJ, Klein R, Sharrett AR, Wong TY. Is diabetic retinopathy an independent risk factor for ischemic stroke? Stroke. 2007;38:398–401. Pearce I, Simó R, Lövestam-Adrian M, Wong DT, Evans M. Association between diabetic eye disease and other complications of diabetes: implications for care. A systematic review. Diabetes Obes Metab. 2019;21:467–478. Klein BE, Klein R, McBride PE, Cruickshanks KJ, Palta M, Knudtson MD, Moss SE, Reinke JO. Cardiovascular disease, mortality, and retinal microvascular characteristics in type 1 diabetes: Wisconsin epidemiologic study of diabetic retinopathy. Arch Intern Med. 2004;164:1917–1924. Hagg S, Thorn LM, Putaala J, Liebkind R, Harjutsalo V, Forsblom CM, Gordin D, Tatlisumak T, Groop PH; FinnDiane Study Group. Incidence of stroke according to presence of diabetic nephropathy and severe diabetic retinopathy in patients with type 1 diabetes. Diabetes Care. 2013;36:4140–4146. Hagg S, Thorn LM, Forsblom CM, Gordin D, Saraheimo M, Tolonen N, Wadén J, Liebkind R, Putaala J, Tatlisumak T, Groop PH. Different risk factor profiles for ischemic and hemorrhagic stroke in type 1 diabetes mellitus. Stroke. 2014;45:2558–2562. Kawasaki R, Tanaka S, Tanaka S, Abe S, Sone H, Yokote K, Ishibashi S, Katayama S, Ohashi Y, Akanuma Y, Yamada N. Risk of cardiovascular diseases is increased even with mild diabetic retinopathy: the Japan Diabetes Complications Study. Ophthalmology. 2013;120:574–582. Hankey GJ, Anderson NE, Ting RD, Veillard AS, Romo M, Wosik M, Sullivan DR, O’Connell RL, Hunt D, Keech AC. Rates and predictors of risk of stroke and its subtypes in diabetes: a prospective observational study. J Neurol Neurosurg Psychiatry. 2013;84:281–287. Stroke Risk in Atrial Fibrillation Working G. Independent predictors of stroke in patients with atrial fibrillation: a systematic review. Neurology. 2007;69:546–554. Chou AY, Liu CJ, Chao TF, Wang KL, Tuan TC, Chen TJ, Chen SA. Presence of diabetic microvascular complications does not incrementally increase risk of ischemic stroke in diabetic patients with atrial fibrillation: a nationwide cohort study. Medicine. 2016;95:e3992. Lip GY, Clementy N, Pierre B, Boyer M, Fauchier L. The impact of associated diabetic retinopathy on stroke and severe bleeding risk in diabetic patients with atrial fibrillation: Th e Loire Valley Atrial Fibrillation Project. Chest. 2015;147:1103– 1110. Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 66. Hayreh SS, Podhajsky PA, Zimmerman MB. Retinal artery occlusion: associated systemic and ophthalmic abnormalities. Ophthalmology. 2009;116:1928–1936. 67. Biousse V, Newman N. Retinal and optic nerve ischemia. Continuum (Minneap Minn). 2014;20:838–856. 68. Biousse V, Nahab F, Newman NJ. Management of acute retinal ischemia: follow the guidelines! Ophthalmology. 2018;125:1597–1607. 69. Helenius J, Arsava EM, Goldstein JN, Cestari DM, Buonanno FS, Rosen BR, Ay H. Concurrent acute brain infarcts in patients with monocular visual loss. Ann Neurol. 2012;72:286–293. 70. Lee J, Kim SW, Lee SC, Kwon OW, Kim YD, Byeon SH. Cooccurrence of acute retinal artery occlusion and acute ischemic stroke: diffusion-weighted magnetic resonance imaging study. Am J Ophthalmol. 2014;157:1231–1238. 71. Tanaka K, Uehara T, Kimura K, Okada Y, Hasegawa Y, Tanahashi N, Suzuki A, Takagi S, Nakagawara J, Arii K, Nagahiro S. Features of patients with transient monocular blindness: a multicenter retrospective study in Japan. J Stroke Cerebrovasc Dis. 2014;23:e151–155. 72. Lauda F, Neugebauer H, Reiber L, Juttler E. Acute silent brain infarction in monocular visual loss of ischemic origin. Cerebrovasc Dis. 2015;40:151–156. 73. Cho KH, Kim CK, Woo SJ, Park KH, Park SJ. Cerebral small vessel disease in Branch retinal artery occlusion. Invest Ophthalmol Vis Sci. 2016;57:5818–5824. 74. Golsari A, Bittersohl D, Cheng B, Griem P, Beck C, Hassenstein A, Nedelmann M, Magnus T, Fiehler J, Gerloff C, Thomalla G. Silent brain infarctions and leukoaraiosis in patients with retinal ischemia: a prospective single-center observational study. Stroke. 2017;48:1392–1396. 75. Callizo J, Feltgen N, Ammermann A, Ganser J, Bemme S, Bertelmann T, Pfeiffer S, Duvinage A, Gröschel K, Hoerauf H, Wachter R. Atrial fibrillation in retinal vascular occlusion disease and non-arteritic anterior ischemic optic neuropathy. PLoS One. 2017;12:e0181766. 76. Chang YS, Jan RL, Weng SF, Wang JJ, Chio CC, Wei FT, Chu CC. Retinal artery occlusion and the 3-year risk of stroke in Taiwan: a nationwide population-based study. Am J Ophthalmol. 2012;154:645–652 e641. 77. Chang YS, Chu CC, Weng SF, Chang C, Wang JJ, Jan RL. The risk of acute coronary syndrome after retinal artery occlusion: a population-based cohort study. Br J Ophthalmol. 2015;99:227–231. 78. Park SJ, Choi NK, Yang BR, Park KH, Lee J, Jung SY, Woo SJ. Risk and risk periods for stroke and acute myocardial infarction in patients with central retinal artery occlusion. Ophthalmology. 2015;122:2336–2343.e2332. 79. Rim TH, Han J, Choi YS, Hwang SS, Lee CS, Lee SC, Kim SS. Retinal artery occlusion and the risk of stroke development: twelve-year nationwide cohort study. Stroke. 2016;47:376– 382. 80. McIntosh RL, Rogers SL, Lim L, Cheung N, Wang JJ, Mitchell P, Kowalski JW, Nguyen HP, Wong TY. Natural history of central retinal vein occlusion: an evidence-based systematic review. Ophthalmology. 2010;117:1113– 1123.e1115. 81. Li M, Hu X, Huang J, Tan Y, Yang B, Tang Z. Impact of retinal vein occlusion on stroke incidence: a meta-analysis. J Am Heart Assoc. 2016;5:e004703. 82. Rim TH, Kim DW, Han JS, Chung EJ. Retinal vein occlusion and the risk of stroke development: a 9-year nationwide population-based study. Ophthalmology. 2015;122:1187– 1194. 83. Bertelsen M, Linneberg A, Christoffersen N, Vorum H, Gade E, Larsen M. Mortality in patients with central retinal vein occlusion. Ophthalmology. 2014;121:637–642. 84. Zhang LY, Zhang J, Kim RK, Matthews JL, Rudich DS, Greer DM, Lesser RL, Amin H. Risk of acute ischemic stroke in patients with monocular vision loss of vascular etiology. J Neuroophthalmol. 2018;38:328–333. 57 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders 85. Lavin P, Patrylo M, Hollar M, Espaillat KB, Kirshner H, Schrag M. Stroke risk and risk factors in patients with central retinal artery occlusion. Am J Ophthalmol. 2018;196:96–100. 86. Chodnicki KD, Pulido JS, Hodge DO, Klaas JP, Chen JJ. Stroke risk before and after central retinal artery occlusion in a US cohort. Mayo Clin Proc. 2019;94:236–241. 87. Furie KL, Kasner SE, Adams RJ, Albers GW, Bush RL, Fagan SC, Halperin JL, Johnston SC, Katzan I, Kernan WN, Mitchell PH. Guidelines for the prevention of stroke in patients with stroke or transient ischemic attack: a guideline for healthcare professionals from the American Heart Association/American Stroke Association. Stroke. 2011;42:227–276. 88. Atkins EJ, Bruce BB, Newman NJ, Biousse V. Translation of clinical studies to clinical practice: survey on the treatment of central retinal artery occlusion. Am J Ophthalmol. 2009;148:172–173. 89. Wong WL, Su X, Li X, Li X, Cheung CM, Klein R, Cheng CY, Wong TY. Global prevalence of age-related macular degeneration and disease burden projection for 2020 and 2040: a systematic review and meta-analysis. Lancet Glob Health. 2014;2:e106–116. 90. Chakravarthy U, Wong TY, Fletcher A, Piault E, Evans C, Zlateva G, Buggage R, Pleil A, Mitchell P. Clinical risk factors for age-related macular degeneration: a systematic review and meta-analysis. BMC Ophthalmol. 2010;10:31. 91. Lim LS, Mitchell P, Seddon JM, Holz FG, Wong TY. Age-related macular degeneration. Lancet. 2012;379:1728–1738. 92. Tan JS, Wang JJ, Liew G, Rochtchina E, Mitchell P. Age-related macular degeneration and mortality from cardiovascular disease or stroke. Br J Ophthalmol. 2008;92:509–512. 93. Sun C, Klein R, Wong TY. Age-related macular degeneration and risk of coronary heart disease and stroke: the Cardiovascular Health Study. Ophthalmology. 2009;116:1913–1919. 94. Wieberdink RG, Ho L, Ikram MK, Koudstaal PJ, Hofman A, de Jong PT, Vingerling JR, Breteler MM. Age-related macular degeneration and the risk of stroke: the Rotterdam study. Stroke. 2011;42:2138–2142. 95. Ikram MK, Mitchell P, Klein R, Sharrett AR, Couper DJ, Wong TY. Age-related macular degeneration and long-term risk of stroke subtypes. Stroke. 2012;43:1681–1683. 96. Fernandez AB, Panza GA, Cramer B, Chatterjee S, Jayaraman R, Wu WC. Age-related macular degeneration and incident stroke: a systematic review and meta-analysis. PLoS One. 2015;10:e0142968. 97. Wang J, Xue Y, Thapa S, Wang L, Tang J, Ji K. Relation between age-related macular degeneration and cardiovascular events and mortality: a systematic review and meta-analysis. Biomed Res Int. 2016;2016:8212063. 98. Hu CC, Ho JD, Lin HC. Neovascular age-related macular degeneration and the risk of stroke: a 5-year populationbased follow-up study. Stroke. 2010;41:613–617. 99. Fernandez AB, Wong TY, Klein R, Collins D, Burke G, Cotch MF, Klein B, Sadeghi MM, Chen J. Age-related macular degeneration and incident cardiovascular disease: the MultiEthnic Study of Atherosclerosis. Ophthalmology. 2012;119:765–770. 100. Cheung CY, Ikram MK, Sabanayagam C, Wong TY. Retinal microvasculature as a model to study the manifestations of hypertension. Hypertension. 2012;60:1094–1103. 101. Sasongko MB, Wong TY, Nguyen TT, Cheung CY, Shaw JE, Kawasaki R, Lamoureux EL, Wang JJ. Retinal vessel tortuosity and its relation to traditional and novel vascular risk markers in persons with diabetes. Curr Eye Res. 2016;41:551–557. 102. Sasongko MB, Wong TY, Nguyen TT, Cheung CY, Shaw JE, Wang JJ. Retinal vascular tortuosity in persons with diabetes and diabetic retinopathy. Diabetologia. 2011;54:2409– 2416. 103. Liew G, Mitchell P, Rochtchina E, Wong TY, Hsu W, Lee ML, Wainwright A, Wang JJ. Fractal analysis of retinal microvasculature and coronary heart disease mortality. Eur Heart J. 2011;32:422–429. 58 104. Cheung N, Liew G, Lindley RI, Liu EY, Wang JJ, Hand P, Baker M, Mitchell P, Wong TY. Retinal fractals and acute lacunar stroke. Ann Neurol. 2010;68:107–111. 105. Liew G, Wang JJ, Cheung N, Zhang YP, Hsu W, Lee ML, Mitchell P, Tikellis G, Taylor B, Wong TY. The retinal vasculature as a fractal: methodology, reliability, and relationship to blood pressure. Ophthalmology. 2008;115:1951–1956. 106. Wong TY, Klein R, Sharrett AR, Duncan BB, Couper DJ, Klein BE, Hubbard LD, Nieto FJ. Retinal arteriolar diameter and risk for hypertension. Ann Intern Med. 2004;140:248–255. 107. Wong TY, Klein R, Sharrett AR, Duncan BB, Couper DJ, Tielsch JM, Klein BE, Hubbard LD. Retinal arteriolar narrowing and risk of coronary heart disease in men and women. The atherosclerosis risk in communities study. JAMA. 2002;287:1153–1159. 108. Wong TY, Shankar A, Klein R, Klein BE, Hubbard LD. Retinal arteriolar narrowing, hypertension, and subsequent risk of diabetes mellitus. Arch Intern Med. 2005;165:1060–1065. 109. Wong TY, Klein R, Sharrett AR, Schmidt MI, Pankow JS, Couper DJ, Klein BE, Hubbard LD, Duncan BB, ARIC Investigators. Retinal arteriolar narrowing and risk of diabetes mellitus in middle-aged persons. JAMA. 2002;287:2528– 2533. 110. McGeechan K, Liew G, Macaskill P, Irwig L, Klein R, Klein BE, Wang JJ, Mitchell P, Vingerling JR, De Jong PT, Witteman JC. Prediction of incident stroke events based on retinal vessel caliber: a systematic review and individual-participant metaanalysis. Am J Epidemiol. 2009;170:1323–1332. 111. Ikram MK, Ong YT, Cheung CY, Wong TY. Retinal vascular caliber measurements: clinical significance, current knowledge and future perspectives. Ophthalmologica. 2013;229:125–136. 112. Parr JC, Spears GF. General caliber of the retinal arteries expressed as the equivalent width of the central retinal artery. Am J Ophthalmol. 1974;77:472–477. 113. Hubbard LD, Brothers RJ, King WN, Clegg LX, Klein R, Cooper LS, Sharrett AR, Davis MD, Cai J. Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the atherosclerosis risk in communities study. Ophthalmology. 1999;106:2269–2280. 114. Cheung CY, Hsu W, Lee ML, Wang JJ, Mitchell P, Lau QP, Hamzah H, Ho M, Wong TY. A new method to measure peripheral retinal vascular caliber over an extended area. Microcirculation. 2010;17:495–503. 115. Perez-Rovira A, MacGillivray T, Trucco E, Chin KS, Zutis K, Lupascu C, Tegolo D, Giachetti A, Wilson PJ, Doney A, Dhillon B. VAMPIRE: vessel assessment and measurement platform for images of the REtina. Paper presented at: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2011. 116. Murray CD. The physiological principle of minimum work: I. The vascular system and the cost of blood volume. Proc Natl Acad Sci U S A. 1926;12:207–214. 117. Cheung CY, Ikram MK, Klein R, Wong TY. The clinical implications of recent studies on the structure and function of the retinal microvasculature in diabetes. Diabetologia. 2015;58:871–885. 118. Hammes HP, Feng Y, Pfister F, Brownlee M. Diabetic retinopathy: targeting vasoregression. Diabetes. 2011;60:9– 16. 119. Lammie GA. Hypertensive cerebral small vessel disease and stroke. Brain Pathol. 2002;12:358–370. 120. Benderro GF, Lamanna JC. Hypoxia-induced angiogenesis is delayed in aging mouse brain. Brain Res. 2011;1389:50–60. 121. Tomita Y, Kubis N, Calando Y, Dinh AT, Méric P, Seylaz J, Pinard E. Long-term in vivo investigation of mouse cerebral microcirculation by fluorescence confocal microscopy in the area of focal ischemia. J Cereb Blood Flow Metab. 2005;25:858–867. 122. Kalitzeos AA, Lip GY, Heitmar R. Retinal vessel tortuosity measures and their applications. Exp Eye Res. 2013;106:40–46. Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Disease of the Year: Cerebrovascular Disorders 123. Hassan A, Gormley K, O’Sullivan M, Knight J, Sham P, Vallance P, Bamford J, Markus H. Endothelial nitric oxide gene haplotypes and risk of cerebral small-vessel disease. Stroke. 2004;35:654–659. 124. Markus HS. Genes, endothelial function and cerebral small vessel disease in man. Exp Physiol. 2008;93:121–127. 125. Lim M, Sasongko MB, Ikram MK, Lamoureux E, Wang JJ, Wong TY, Cheung CY. Systemic associations of dynamic retinal vessel analysis: a review of current literature. Microcirculation. 2013;20:257–268. 126. Lombardo M, Serrao S, Devaney N, Parravano M, Lombardo G. Adaptive optics technology for high-resolution retinal imaging. Sensors (Basel). 2013;13:334–366. 127. Meixner E, Michelson G. Measurement of retinal wall-tolumen ratio by adaptive optics retinal camera: a clinical research. Graefes Arch Clin Exp Ophthalmol. 2015;253:1985–1995. 128. Koch E, Rosenbaum D, Brolly A, Sahel JA, Chaumet-Riffaud P, Girerd X, Rossant F, Paques M. Morphometric analysis of small arteries in the human retina using adaptive optics imaging: relationship with blood pressure and focal vascular changes. J Hypertens. 2014;32:890–898. 129. Rim TH, Choi YS, Kim SS, Kang MJ, Oh J, Park S, Byeon SH. Retinal vessel structure measurement using spectral-domain optical coherence tomography. Eye (Lond). 2016;30:111– 119. 130. Spaide RF, Klancnik JM Jr, Cooney MJ. Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography. JAMA Ophthalmol. 2015;133:45–50. 131. Arnould L, Guenancia C, Azemar A, Alan G, Pitois S, Bichat F, Zeller M, Gabrielle PH, Bron AM, Creuzot-Garcher C, Cottin Y. The EYE-MI pilot study: a prospective acute coronary syndrome cohort evaluated with retinal optical coherence tomography angiography. Invest Ophthalmol Vis Sci. 2018;59:4299–4306. 132. Ting DSW, Cheung CY, Lim G, Tan GS, Quang ND, Gan A, Hamzah H, Garcia-Franco R, San Yeo IY, Lee SY, Wong EY. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal Rim et al: J Neuro-Ophthalmol 2020; 40: 44-59 133. 134. 135. 136. 137. 138. 139. 140. 141. 142. images from multiethnic populations with diabetes. JAMA. 2017;318:2211–2223. Ting DSW, Pasquale LR, Peng L, Campbell JP, Lee AY, Raman R, Tan GS, Schmetterer L, Keane PA, Wong TY. Artificial intelligence and deep learning in ophthalmology. Br J Ophthalmol. 2019;103:167–175. Ting DSW, Wu WC, Toth C. Deep learning for retinopathy of prematurity screening. Br J Ophthalmol. 2019;103:577–579. Ting DSW, Wong TY. Eyeing cardiovascular risk factors. Nat Biomed Eng. 2018;2:140–141. Ting DSW, Peng L, Varadarajan AV, Keane PA, Burlina P, Chiang MF, Schmetterer L, Pasquale LR, Bressler NM, Webster DR, Abramoff M. Deep learning in ophthalmology: the technical and clinical considerations. Prog Retin Eye Res. 2019;72:100759. Schmidt-Erfurth U, Sadeghipour A, Gerendas BS, Waldstein SM, Bogunovic H. Artificial intelligence in retina. Prog Retin Eye Res. 2018;67:1–29. Wong TY, Duncan BB, Golden SH, Klein R, Couper DJ, Klein BE, Hubbard LD, Sharrett AR, Schmidt MI. Associations between the metabolic syndrome and retinal microvascular signs: the atherosclerosis risk in communities study. Invest Ophthalmol Vis Sci. 2004;45:2949–2954. Faust O, Acharya UR, Ng EY, Ng KH, Suri JS. Algorithms for the automated detection of diabetic retinopathy using digital fundus images: a review. J Med Syst. 2012;36:145–157. Abramoff MD, Folk JC, Han DP, Walker JD, Williams DF, Russell SR, Massin P, Cochener B, Gain P, Tang L, Lamard M. Automated analysis of retinal images for detection of referable diabetic retinopathy. JAMA Ophthalmol. 2013;131:351–357. Thom S, Stettler C, Stanton A, Witt N, Tapp R, Chaturvedi N, Allemann S, Mayet J, Sever P, Poulter N, O’Brien E. Differential effects of antihypertensive treatment on the retinal microcirculation: an anglo-scandinavian cardiac outcomes trial substudy. Hypertension. 2009;54:405–408. Hughes AD, Stanton AV, Jabbar AS, Chapman N, MartinezPerez ME, McG Thom SA. Effect of antihypertensive treatment on retinal microvascular changes in hypertension. J Hypertens. 2008;26:1703–1707. 59 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited.