Cerebrovascular 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 µm 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 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 age-related 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” point-of-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.
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). 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 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).
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 arterial 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 meta-analysis (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 sociodemographic-matched 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 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 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) 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 meta-analysis involving 9 studies with 1,420,978 patients found no 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 random-effects 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).
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-μm 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.
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).
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).
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, age-related degenerative conditions including Alzheimer's disease, and systemic ailments such as multiple sclerosis, from both fundus photographs and OCT images. At this time, to 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 time-consuming 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 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.
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