Retinal parameters, cortical cerebral microinfarcts, and their interaction with cognitive impairment

Association of Retinal Biomarkers With the Subtypes of Ischemic Stroke and an Automated Classification Model

Purpose

Retinal microvascular changes are associated with ischemic stroke, and optical coherence tomography angiography (OCTA) is a potential tool to reveal the retinal microvasculature. We investigated the feasibility of using the OCTA image to automatically identify ischemic stroke and its subtypes (i.e. lacunar and non-lacunar stroke), and exploited the association of retinal biomarkers with the subtypes of ischemic stroke.

Methods

Two cohorts were included in this study and a total of 1730 eyes from 865 participants were studied. A deep learning model was developed to discriminate the subjects with ischemic stroke from healthy controls and to distinguish the subtypes of ischemic stroke. We also extracted geometric parameters of the retinal microvasculature at different retinal layers to investigate the correlations.

Results

Superficial vascular plexus (SVP) yielded the highest areas under the receiver operating characteristic curve (AUCs) of 0.922 and 0.871 for the ischemic stroke detection and stroke subtypes classification, respectively. For external data validation, our model achieved an AUC of 0.822 and 0.766 for the ischemic stroke detection and stroke subtypes classification, respectively. When parameterizing the OCTA images, we showed individuals with ischemic strokes had increased SVP tortuosity (B = 0.085, 95% confidence interval [CI] = 0.005-0.166, P = 0.038) and reduced FAZ circularity (B = -0.212, 95% CI = -0.42 to -0.005, P = 0.045); non-lacunar stroke had reduced SVP FAZ circularity (P = 0.027) compared to lacunar stroke.

Conclusions

Our study demonstrates the applicability of artificial intelligence (AI)-enhanced OCTA image analysis for ischemic stroke detection and its subtypes classification. Biomarkers from retinal OCTA images can provide useful information for clinical decision-making and diagnosis of ischemic stroke and its subtypes.

Atherosclerotic burden and cerebral small vessel disease: exploring the link through microvascular aging and cerebral microhemorrhages

Cerebral microhemorrhages (CMHs, also known as cerebral microbleeds) are a critical but frequently underestimated aspect of cerebral small vessel disease (CSVD), bearing substantial clinical consequences. Detectable through sensitive neuroimaging techniques, CMHs reveal an extensive pathological landscape. They are prevalent in the aging population, with multiple CMHs often being observed in a given individual. CMHs are closely associated with accelerated cognitive decline and are increasingly recognized as key contributors to the pathogenesis of vascular cognitive impairment and dementia (VCID) and Alzheimer's disease (AD). This review paper delves into the hypothesis that atherosclerosis, a prevalent age-related large vessel disease, extends its pathological influence into the cerebral microcirculation, thereby contributing to the development and progression of CSVD, with a specific focus on CMHs. We explore the concept of vascular aging as a continuum, bridging macrovascular pathologies like atherosclerosis with microvascular abnormalities characteristic of CSVD. We posit that the same risk factors precipitating accelerated aging in large vessels (i.e., atherogenesis), primarily through oxidative stress and inflammatory pathways, similarly instigate accelerated microvascular aging. Accelerated microvascular aging leads to increased microvascular fragility, which in turn predisposes to the formation of CMHs. The presence of hypertension and amyloid pathology further intensifies this process. We comprehensively overview the current body of evidence supporting this interconnected vascular hypothesis. Our review includes an examination of epidemiological data, which provides insights into the prevalence and impact of CMHs in the context of atherosclerosis and CSVD. Furthermore, we explore the shared mechanisms between large vessel aging, atherogenesis, microvascular aging, and CSVD, particularly focusing on how these intertwined processes contribute to the genesis of CMHs. By highlighting the role of vascular aging in the pathophysiology of CMHs, this review seeks to enhance the understanding of CSVD and its links to systemic vascular disorders. Our aim is to provide insights that could inform future therapeutic approaches and research directions in the realm of neurovascular health.

Ocular biomarkers of cognitive decline based on deep-learning retinal vessel segmentation

BACKGROUND

The current literature shows a strong relationship between retinal neuronal and vascular alterations in dementia. The purpose of the study was to use NFN+ deep learning models to analyze retinal vessel characteristics for cognitive impairment (CI) recognition.

METHODS

We included 908 participants from a community-based cohort followed for over 15 years (the prospective KaiLuan Study) who underwent brain magnetic resonance imaging (MRI) and fundus photography between 2021 and 2022. The cohort consisted of both cognitively healthy individuals (N = 417) and those with cognitive impairment (N = 491). We employed the NFN+ deep learning framework for retinal vessel segmentation and measurement. Associations between Retinal microvascular parameters (RMPs: central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension) and CI were assessed by Pearson correlation. P < 0.05 was considered statistically significant. The correlation between the CI and RMPs were explored, then the correlation coefficients between CI and RMPs were analyzed. Random Forest nonlinear classification model was used to predict whether one having cognitive decline or not. The assessment criterion was the AUC value derived from the working characteristic curve.

RESULTS

The fractal dimension (FD) and global vein width were significantly correlated with the CI (P < 0.05). Age (0.193), BMI (0.154), global vein width (0.106), retinal vessel FD (0.099), and CRAE (0.098) were the variables in this model that were ranked in order of feature importance. The AUC values of the model were 0.799.

CONCLUSIONS

Establishment of a predictive model based on the extraction of vascular features from fundus images has a high recognizability and predictive power for cognitive function and can be used as a screening method for CI.

Cerebral microinfarcts revisited: Detection, causes, and clinical relevance

Cerebral microinfarcts (CMIs) are small ischemic lesions invisible to the naked eye at brain autopsy, while the larger ones (0.5-4 mm in diameter) have been visualized in-vivo on magnetic resonance imaging (MRI). CMIs can be detected on diffusion-weighted imaging (DWI) as incidental small DWI-positive lesions (ISDPLs) and on structural MRI for those confined to the cortex and in the chronic phase. ISDPLs may evolve into old cortical-CMIs, white matter hyperintensities or disappear depending on their location and size. Novel techniques in neuropathology and neuroimaging facilitate the detection of CMIs, which promotes understanding of these lesions. CMIs have heterogeneous causes, involving both cerebral small- and large-vessel disease as well as heart diseases such as atrial fibrillation and congestive heart failure. The underlying mechanisms incorporate vascular remodeling, inflammation, blood-brain barrier leakage, penetrating venule congestion, cerebral hypoperfusion, and microembolism. CMIs lead to clinical outcomes, including cognitive decline, a higher risk of stroke and mortality, and accelerated neurobehavioral disturbances. It has been suggested that CMIs can impair brain function and connectivity beyond the microinfarct core and are also associated with perilesional and global cortical atrophy. This review aims to summarize recent progress in studies involving both cortical-CMIs and ISDPLs since 2017, including their detection, etiology, risk factors, MRI correlates, and clinical consequences.

Retinal microvasculature and incident dementia over 10 years: The Three-City-Alienor cohort

Introduction

We explored the longitudinal relationship between retinal vascular features and dementia incidence over 10 years.

Methods

Among 584 participants from the Three-City-Alienor (3C-Alienor) population-based cohort, quantitative retinal vascular features (caliber, tortuosity, fractal dimension) were measured using semi-automated software. Dementia was actively diagnosed over the follow-up period.

Results

One hundred twenty-eight participants (21.9%) developed dementia over a median of 7.1 years. In Cox proportional hazards models adjusted for sociodemographic characteristics, apolipoprotein E (APOE) ε4, and vascular factors, increased retinal arteriolar tortuosity was associated with all-cause dementia (hazard ratio per standard deviation increase, 1.21; 95% confidence interval: 1.02-1.44). Wider retinal calibers and a higher venular tortuosity were associated with mixed/vascular dementia, but not Alzheimer's disease. Fractal dimensions were not associated with dementia.

Discussion

Changes in the retinal microvasculature were associated with dementia risk. More studies are needed to replicate these findings and determine which features might help identify persons at risk at an early stage.

HIGHLIGHTS

The retinal microvasculature might reflect the brain microvasculatureWe explored the association between retinal vascular features and incident dementia584 participants from the Three-City-Alienor cohort were followed-up over 10 yearsIncreased arteriolar tortuosity and venular calibers were associated with dementia riskRetinal imaging might help identify persons at risk of future dementia.

A narrative review of retinal vascular parameters and the applications (Part I): Measuring methods

The retina is often used to evaluate the vascular health status of eyes and the whole body directly and noninvasively in vivo. Retinal vascular parameters included caliber, tortuosity and fractal dimension. These variables represent the density or geometric characteristics of the vascular network apart from reflecting structural changes in the retinal vessel system. Currently, these parameters are often used as indicators of retinal disease, cardiovascular and cerebrovascular disease. Advanced digital fundus photography apparatus and computer-assisted analysis techniques combined with artificial intelligence, make the quantitative calculation of these parameters easier, objective, and labor-saving.

Effects of Carotid Artery Stiffness on Cerebral Small-Vessel Disease and Cognition

Background Carotid artery stiffness is associated with cognitive impairment and dementia, but the underlying mechanisms remain unknown. We examined the associations of carotid artery stiffness with cerebral small-vessel disease markers, cognition, and dementia subtypes in a memory clinic cohort. Methods and Results A total of 272 participants underwent carotid ultrasonography, 3 Tesla brain magnetic resonance imaging, and neuropsychological assessment. Carotid ultrasonography was used to assess β-index, pressure-strain elastic modulus, and pulse-wave velocity-β. Brain magnetic resonance images were graded for cerebral small-vessel disease markers, including white matter hyperintensities, lacunes, and cerebral microbleeds. Participants were classified as having no cognitive impairment, cognitive impairment and no dementia, or dementia subtyped as Alzheimer disease and vascular dementia. Cognition was assessed using National Institute of Neurological Disorders and Stroke-Canadian Stroke Network harmonization battery. After adjusting for age, sex, cardiovascular risk factors, and diseases, multivariable models showed that β-index (β=0.69; P=0.002), elastic modulus (β=0.78; P<0.001), and pulse-wave velocity-β (β=0.80; P<0.001) were associated with white matter hyperintensities, and elastic modulus (odds ratio [OR], 1.39 [95% CI, 1.04-1.85]) and pulse-wave velocity-β (OR, 1.47 [95% CI, 1.10-1.98]) were independently associated with lacunes. Similarly, β-index (OR, 2.04 [95% CI, 1.14-4.13]), elastic modulus (OR, 2.22 [95% CI, 1.25-4.42]), and pulse-wave velocity-β (OR, 2.50 [95% CI, 1.36-5.18]) were independently associated with vascular dementia. Carotid stiffness measures were independently associated with worse performance in global cognition, visuomotor speed, visuospatial function, and executive function. These associations became largely nonsignificant after further adjusting for cerebral small-vessel disease markers. Conclusions In memory clinic patients, carotid artery stiffness was associated with white matter hyperintensities and lacunes, impairment in global and domain-specific cognition, and causative subtypes of dementia, particularly vascular. The effects of carotid stiffness on cognition were not independent of, and were partially mediated by, cerebral small-vessel disease.

Retinal Thickness Associates with Cognition Dysfunction in Young Adult with Type 1 Diabetes in Taiwan

BACKGROUND

Several factors could affect the cognitive dysfunction in patients with type 1 diabetes (T1D).

OBJECTIVES

To report the characteristic of cognitive dysfunction in T1D and find its association with the retinal thickness.

SUBJECTS

We recruited one hundred and seven patients with T1D in our study.

METHODS

Detailed clinical and demographic factors and Cambridge Automated Neuropsychological Test Battery (CANTAB) were performed in all participants. The age at onset>5 years old and ≤5 years old groups was defined as old- and young-onset groups. The levels of the average values of 5-year glycated hemoglobin (HbA1c_5) before study were collected. Ophthalmic study and central retinal thickness (CRT) were performed.

RESULTS

The median age of T1D was 24.9 years old and 57 participants were women. The median age at onset was 7.4 years old, and mean disease duration was 17.2 years. After adjusting off multiple covariates by the regression analyses, the young-onset group had significantly a longer latency in sustained attention than old-onset group (P = 0.02). The HbA1c_5 showed a significantly negative association with the sustained attention (P = 0.03). The average values of CRT showed significantly negative correlations with the reaction time in sustained attention and visual searching (P = 0.04 and P < 0.01, respectively).

CONCLUSIONS

Our results suggest that age at onset and glycemic control had significant impacts on different cognitive domains in T1D. The CRT had a significant correlation with sustained attention, which could be a surrogate markers of brain structural changes in T1D.