The Additional Contribution of White Matter Hyperintensity Location to Post-stroke Cognitive Impairment: Insights From a Multiple-Lesion Symptom Mapping Study

Long-Term Post-Stroke Cognition in Patients With Minor Ischemic Stroke is Related to Tract-Based Disconnection Induced by White Matter Hyperintensities

Over a third of minor stroke patients experience post-stroke cognitive impairment (PSCI), but no validated tools exist to identify at-risk patients early. This study investigated whether disconnection features derived from infarcts and white matter hyperintensities (WMH) could serve as markers for short- and long-term cognitive decline in first-ever minor ischemic stroke patients. First-ever minor ischemic stroke patients (NIHSS ≤ 7) were prospectively followed at 72-h, 6 months, and 36 months post-stroke with cognitive tests and brain MRI. Infarct and WMH volumes were semi-automatically assessed on DWI and FLAIR sequences. Bayesian tract-based disconnection models estimated remote pathological effects of infarcts and WMH. Associations between disconnection features and cognitive outcomes were analyzed using canonical correlation analyses, adjusted for age, education, and multiple comparisons. Among 105 patients (31% female, mean age 63 ± 12 years), infarct volume averaged 10.28 ± 17.10 cm3 and predominantly involved the middle cerebral artery territory (83%). WMH burden was higher in frontal periventricular white matter. Infarct-based features did not significantly relate to PCSI. However, a WMH-derived disconnection factor, involving commissural and frontal tracts, and the right superior longitudinal fasciculus, was significantly associated with PSCI at 6 months (OR = 9.96, p value = 0.02) and 36 months (OR = 12.27, p value = 0.006), particularly in executive/attention, language, and visuospatial domains. This factor, unrelated to WMH volume, outperformed demographic and clinical predictors of PSCI. WMH-induced disconnection may be associated with short- and long-term PSCI in minor stroke. Routine MR-derived features could identify at-risk patients for rehabilitation trials.

Prediction Models for Post-Stroke Cognitive Impairment: A Systematic Review and Meta-Analysis

BACKGROUND

Stroke is one of the most serious illnesses worldwide and is the primary cause of acquired disability among adults. Post-stroke cognitive impairment (PSCI) is a complication of stroke that significantly impacts patients' daily activities and social functions. Therefore, developing a risk prediction model for PSCI is essential for identifying and preventing disease progression.

OBJECTIVES

This study systematically reviewed and analyzed PSCI prediction models, identifying the associated risk factors.

METHODS

We systematically retrieved literature from PubMed, Cochrane Library, Embase, and other sources. Two researchers independently extracted the literature and assessed the risk of bias using the Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) checklist and The Prediction Model Risk of Bias Assessment Tool (PROBAST).

RESULTS

A total of 20 articles describe the PSCI prediction model, with an incidence rate ranging from 8% to 75%. The area under the receiver operating characteristic curve (AUC) value for the development models ranged from 0.66 to 0.969, while the validation models ranged from 0.763 to 0.893. Age, diabetes, hypersensitive C-reactive protein (hs-CRP), hypertension, and homocysteine (hcy) were identified as the strongest predictors.

CONCLUSION

In this systematic review, several PSCI prediction models demonstrate promising prediction performance, although they often lack external validation and exhibit high heterogeneity in some predictive factors. Therefore, we recommend that medical practitioners utilize a comprehensive set of predictive factors to screen for high-risk PSCI patients. Furthermore, future research should prioritize refining and validating existing models by incorporating novel variables and methodologies.

Quantitative Analysis of White Matter Hyperintensities as a Predictor of 1-Year Risk for Ischemic Stroke Recurrence

INTRODUCTION

This study evaluates the role of quantitative characteristics of white matter hyperintensities (WMHs) in predicting the 1-year recurrence risk of ischemic stroke.

METHODS

We conducted a retrospective analysis of 1061 patients with ischemic stroke from January 2018 to April 2021. WMHs were automatically segmented using a cluster-based method to quantify their volume and number of clusters (NoC). Additionally, two radiologists independently rated periventricular and deep WMHs using the Fazekas scale. The cohort was divided into a training set (70%) and a testing set (30%). We employed Cox proportional hazards models to develop predictors based on quantitative WMH characteristics, Fazekas scores, and clinical factors, and compared their performance using the concordance index (C-index).

RESULTS

A total of 180 quantitative variables related to WMHs were extracted. A higher NoC in deep white matter and brainstem, advanced age (> 90 years old), specific stroke subtypes, and absence of discharge antiplatelets showed stronger associations with the risk of ischemic stroke recurrence within 1 year. The nomogram incorporating quantitative WMHs data showed superior discrimination compared to those based on the Fazekas scale or clinical factors alone, with C-index values of 0.709 versus 0.647 and 0.648, respectively, in the testing set. Notably, a combined model including both WMHs and clinical factors achieved the highest predictive accuracy, with a C-index of 0.735 in the testing set.

CONCLUSION

Quantitative assessment of WMHs provides a valuable neuro-imaging tool for enhancing the prediction of ischemic stroke recurrence risk.

Strategic white matter hyperintensity locations associated with post-stroke cognitive impairment: A multicenter study in 1568 stroke patients

BACKGROUND

Post-stroke cognitive impairment (PSCI) occurs in up to 50% of stroke survivors. Presence of pre-existing vascular brain injury, in particular the extent of white matter hyperintensities (WMH), is associated with worse cognitive outcome after stroke, but the role of WMH location in this association is unclear.

AIMS

We determined if WMH in strategic white matter tracts explain cognitive performance after stroke.

METHODS

Individual patient data from nine ischemic stroke cohorts with magnetic resonance imaging (MRI) were harmonized through the Meta VCI Map consortium. The association between WMH volumes in strategic tracts and domain-specific cognitive functioning (attention and executive functioning, information processing speed, language and verbal memory) was assessed using linear mixed models and lasso regression. We used a hypothesis-driven design, primarily addressing four white matter tracts known to be strategic in memory clinic patients: the left and right anterior thalamic radiation, forceps major, and left inferior fronto-occipital fasciculus.

RESULTS

The total study sample consisted of 1568 patients (39.9% female, mean age = 67.3 years). Total WMH volume was strongly related to cognitive performance on all four cognitive domains. WMH volume in the left anterior thalamic radiation was significantly associated with cognitive performance on attention and executive functioning and information processing speed and WMH volume in the forceps major with information processing speed. The multivariable lasso regression showed that these associations were independent of age, sex, education, and total infarct volume and had larger coefficients than total WMH volume.

CONCLUSION

These results show tract-specific relations between WMH volume and cognitive performance after ischemic stroke, independent of total WMH volume. This implies that the concept of strategic lesions in PSCI extends beyond acute infarcts and also involves pre-existing WMH.

DATA ACCESS STATEMENT

The Meta VCI Map consortium is dedicated to data sharing, following our guidelines.

The volume and the distribution of premorbid white matter hyperintensities: Impact on post-stroke aphasia

White matter hyperintensities (WMH) are a radiological manifestation of progressive white matter integrity loss. The total volume and distribution of WMH within the corpus callosum have been associated with pathological cognitive ageing processes but have not been considered in relation to post-stroke aphasia outcomes. We investigated the contribution of both the total volume of WMH, and the extent of WMH lesion load in the corpus callosum to the recovery of language after first-ever stroke. Behavioural and neuroimaging data from individuals (N = 37) with a left-hemisphere stroke were included at the early subacute stage of recovery. Spoken language comprehension and production abilities were assessed using word and sentence-level tasks. Neuroimaging data was used to derive stroke lesion variables (volume and lesion load to language critical regions) and WMH variables (WMH volume and lesion load to three callosal segments). WMH volume did not predict variance in language measures, when considered together with stroke lesion and demographic variables. However, WMH lesion load in the forceps minor segment of the corpus callosum explained variance in early subacute comprehension abilities (t = -2.59, p = .01) together with corrected stroke lesion volume and socio-demographic variables. Premorbid WMH lesions in the forceps minor were negatively associated with early subacute language comprehension after aphasic stroke. This negative impact of callosal WMH on language is consistent with converging evidence from pathological ageing suggesting that callosal WMH disrupt the neural networks supporting a range of cognitive functions.

Methods of a Study to Assess the Contribution of Cerebral Small Vessel Disease and Dementia Risk Alleles to Racial Disparities in Vascular Cognitive Impairment and Dementia

Background Non-Hispanic Black adults have a higher proportion of vascular cognitive impairment and Alzheimer's disease and related dementias compared with non-Hispanic White adults that may be due to differences in the burden of cerebral small vessel disease and risk alleles for Alzheimer's disease and related dementias. We describe here the methods of an ancillary study to the REGARDS (Reason for Geographic and and Racial Difference in Stroke) study, which will examine the role of magnetic resonance imaging markers of cerebral small vessel disease and vascular as well as genetic risk factors for Alzheimer's disease and related dementias in racial disparity in the prevalence and trajectory of vascular cognitive impairment and dementia in non-Hispanic White and non-Hispanic Black participants. Methods In participants with no prior history of stroke who had an incident stroke or transient ischemic attack after enrollment in the study, magnetic resonance imaging scans will be evaluated using the Standards for Reporting Vascular Changes on Neuroimaging international consensus criteria and automated analysis pipelines for quantification of cerebral small vessel disease. Participants will be genotyped for APOE ε4 and TREM2 risk alleles for Alzheimer's disease and related dementias. The 6-item screener will define global cognitive function and be the primary cognitive outcome. Conclusions With at least 426 non-Hispanic Black and 463 non-Hispanic White participants who have at least 2 prior and 2 poststroke or transient ischemic attack cognitive assessments, we will have at least 80% power to detect a minimum effect size of 0.09 SD change in Z score, with correction for as many as 20 tests (ie, at P<0.0025, after adjusting for up to 20 covariates) for cognitive decline.

Analysis of Risk Factors for White Matter Hyperintensity in Older Adults without Stroke

BACKGROUND

White matter hyperintensity (WMH) is prevalent in older adults aged 60 and above. A large proportion of people with WMH have not experienced stroke and little has been reported in the literature.

METHODS

The case data of patients aged ≥60 years without stroke in Wuhan Tongji Hospital from January 2015 to December 2019 were retrospectively analyzed. It was a cross-sectional study. Univariate analysis and logistic regression were used to analyze independent risk factors for WMH. The severity of WMH was assessed using the Fazekas scores. The participants with WMH were divided into periventricular white matter hyperintensity (PWMH) group and deep white matter hyperintensity (DWMH) group, then the risk factors of WMH severity were explored separately.

RESULTS

Eventually, 655 patients were included; among the patients, 574 (87.6%) were diagnosed with WMH. Binary logistic regression showed that age and hypertension were associated with the prevalence of WMH. Ordinal logistic regression showed that age, homocysteine, and proteinuria were associated with the severity of WMH. Age and proteinuria were associated with the severity of PWMH. Age and proteinuria were associated with the severity of DWMH.

CONCLUSIONS

The present study showed that in patients aged ≥60 years without stroke, age and hypertension were independent risk factors for the prevalence of WMH; while the increasing of age, homocysteine, and proteinuria were associated with greater WMH burden.

White matter hyperintensities and longitudinal cognitive decline in cognitively normal populations and across diagnostic categories: A meta-analysis, systematic review, and recommendations for future study harmonization

INTRODUCTION

The primary aim of this paper is to improve the clinical interpretation of white matter hyperintensities (WMHs) and provide an overarching summary of methodological approaches, allowing researchers to design future studies targeting current knowledge gaps.

METHODS

A meta-analysis and systematic review was performed investigating associations between baseline WMHs and longitudinal cognitive outcomes in cognitively normal populations, and populations with mild cognitive impairment (MCI), Alzheimer's disease (AD), and stroke.

RESULTS

Baseline WMHs increase the risk of cognitive impairment and dementia across diagnostic categories and most consistently in MCI and post-stroke populations. Apolipoprotein E (APOE) genotype and domain-specific cognitive changes relating to strategic anatomical locations, such as frontal WMH and executive decline, represent important considerations. Meta-analysis reliability was assessed using multiple methods of estimation, and results suggest that heterogeneity in study design and reporting remains a significant barrier.

DISCUSSION

Recommendations and future directions for study of WMHs are provided to improve cross-study comparison and translation of research into consistent clinical interpretation.

Leukoaraiosis Mediates the Association of Total White Blood Cell Count With Post-Stroke Cognitive Impairment

Background and Purpose

The inflammatory response could play a key role in cognitive impairment. However, there has been limited research into the association between total white blood cell (WBC) count and post-stroke cognitive impairment (PSCI), and the significance of leukoaraiosis (LA) in this relationship is unknown. We aimed to examine the total WBC count in relation to PSCI and whether this association was mediated by LA.

Methods

Consecutive patients with first-ever ischemic stroke were prospectively enrolled from October 2020 to June 2021. The total WBC count was measured after admission. Cognitive function evaluations were performed at the 3-month follow-up using Mini-mental State Examination (MMSE). We defined the PSCI as an MMSE score <27.

Results

A total of 276 patients (mean age, 66.5 years; 54.7% male) were included in this analysis. Among them, 137 (49.6%) patients experienced PSCI. After adjustment for potential confounders, higher total WBC count was significantly correlated with an increased risk of LA [per 1-SD increase, odds ratio (OR), 1.39; 95% CI 1.06–1.82; p = 0.017] and PSCI (per 1-SD increase, OR, 1.51; 95% CI 1.12–2.04; p = 0.006). Furthermore, mediation analysis demonstrated that the association between total WBC count and PSCI was partly mediated by LA (the regression coefficient was changed by 9.7% for PSCI, and 12.4% for PSCI severity, respectively).

Conclusion

Increased total WBC count is a risk factor for PSCI. The presence of LA was partially responsible for the PSCI in patients who had a higher total WBC count.

Atrial Fibrillation and Dementia: A Report From the AF-SCREEN International Collaboration

Growing evidence suggests a consistent association between atrial fibrillation (AF) and cognitive impairment and dementia that is independent of clinical stroke. This report from the AF-SCREEN International Collaboration summarizes the evidence linking AF to cognitive impairment and dementia. It provides guidance on the investigation and management of dementia in patients with AF on the basis of best available evidence. The document also addresses suspected pathophysiologic mechanisms and identifies knowledge gaps for future research. Whereas AF and dementia share numerous risk factors, the association appears to be independent of these variables. Nevertheless, the evidence remains inconclusive regarding a direct causal effect. Several pathophysiologic mechanisms have been proposed, some of which are potentially amenable to early intervention, including cerebral microinfarction, AF-related cerebral hypoperfusion, inflammation, microhemorrhage, brain atrophy, and systemic atherosclerotic vascular disease. The mitigating role of oral anticoagulation in specific subgroups (eg, low stroke risk, short duration or silent AF, after successful AF ablation, or atrial cardiopathy) and the effect of rhythm versus rate control strategies remain unknown. Likewise, screening for AF (in cognitively normal or cognitively impaired patients) and screening for cognitive impairment in patients with AF are debated. The pathophysiology of dementia and therapeutic strategies to reduce cognitive impairment warrant further investigation in individuals with AF. Cognition should be evaluated in future AF studies and integrated with patient-specific outcome priorities and patient preferences. Further large-scale prospective studies and randomized trials are needed to establish whether AF is a risk factor for cognitive impairment, to investigate strategies to prevent dementia, and to determine whether screening for unknown AF followed by targeted therapy might prevent or reduce cognitive impairment and dementia.

Distinct roles of right temporoparietal cortex in pentagon copying test

Pentagon Copying Test (PCT) is commonly used to assess visuospatial deficits, but the neural substrates underlying pentagon copying are not well understood. The Qualitative Scoring Pentagon Test (QSPT), an optimized scoring system, classifies five categories of errors patients make in pentagons copying and grades them depending on the errors' severity. To determine the strategic brain regions involved in the PCT, we applied the QSPT system to evaluate the visuospatial impairment of 136 acute ischemic stroke patients on the PCT and used Support Vector Regression Lesion-Symptom Mapping to investigate relevant brain regions. The total QSPT score was correlated with the right supramarginal gyrus. The angle number errors and closure errors were principally associated with lesions of the posterior temporoparietal cortex, including the right middle occipital gyrus and middle temporal gyrus, while the intersection errors and rotation errors were related to the more anterior part of the right temporoparietal lobe with the additional frontal cortex. In conclusion, the right temporoparietal cortex is the strategic region for pentagon copying tasks. The angle number and closure represent the visuospatial processing of within-object features, while intersection and rotation require between-object manipulation. The posterior-anterior distinction in the right temporoparietal region underlies the differences of within-object and between-object processing.

Evaluation of White Matter Microstructural Alterations in Patients with Post-Stroke Cognitive Impairment at the Sub-Acute Stage

PURPOSE

To investigate white matter alterations in post-stroke cognitive impairment (PSCI) patients at the subacute stage employing diffusion kurtosis and tensor imaging.

METHODS

Thirty PSCI patients at the subacute phase and 30 healthy controls (HC) underwent diffusion kurtosis imaging (DKI) scans and neuropsychological assessments. Based on the tract-based spatial statistics and atlas-based ROI analysis, fractional anisotropy (FA), mean diffusivity (MD), mean kurtosis (MK), kurtosis fractional anisotropy (KFA), axial kurtosis (AK), and radial kurtosis (RK) were compared in specific white matter fiber bundles between the groups (with family-wise error correction). Adjusting for age and gender, a partial correlation was conducted between neurocognitive assessments and DKI metrics in the PSCI group.

RESULTS

In comparison with the HC, PSCI patients significantly showed decreased MK, RK, and FA and increased MD values in the genu of corpus callosum, anterior limb internal capsule, and left superior corona radiata. In addition, DKI detected more white matter region changes in MK (31/48), KFA (40/48), and RK (25/48) than DTI with FA (28/48) and MD (21/48), which primarily consisted of the right cingulum, right superior longitudinal fasciculus, and left posterior limb of internal capsule. In the left anterior limb of internal capsule, MK and RK values were significantly negatively correlated with TMT-B (r = -0.435 and -0.414, P < 0.05), and KFA values (r = -0.385, P < 0.05) of corpus callosum negatively associated with TMT-B.

CONCLUSION

Combing DTI, DKI, and neuropsychological tests, we found extensive damaged white matter microstructure and poor execution performance in subacute PSCI patients. DKI could detect more subtle white matter changes than DTI metrics. Our findings provide added information for exploring the mechanisms of PSCI and conducting cognitive rehabilitation in the subacute stage.

Cognitive Impairment and Dementia After Stroke: Design and Rationale for the DISCOVERY Study

Stroke is a leading cause of the adult disability epidemic in the United States, with a major contribution from poststroke cognitive impairment and dementia (PSCID), the rates of which are disproportionally high among the health disparity populations. Despite the PSCID's overwhelming impact on public health, a knowledge gap exists with regard to the complex interaction between the acute stroke event and highly prevalent preexisting brain pathology related to cerebrovascular and Alzheimer disease or related dementia. Understanding the factors that modulate PSCID risk in relation to index stroke event is critically important for developing personalized prognostication of PSCID, targeted interventions to prevent it, and for informing future clinical trial design. The DISCOVERY study (Determinants of Incident Stroke Cognitive Outcomes and Vascular Effects on Recovery), a collaborative network of thirty clinical performance clinical sites with access to acute stroke populations and the expertise and capacity for systematic assessment of PSCID will address this critical challenge. DISCOVERY is a prospective, multicenter, observational, nested-cohort study of 8000 nondemented ischemic and hemorrhagic stroke patients enrolled at the time of index stroke and followed for a minimum of 2 years, with serial cognitive evaluations and assessments of functional outcome, with subsets undergoing research magnetic resonance imaging and positron emission tomography and comprehensive genetic/genomic and fluid biomarker testing. The overall scientific objective of this study is to elucidate mechanisms of brain resilience and susceptibility to PSCID in diverse US populations based on complex interplay between life-course exposure to multiple vascular risk factors, preexisting burden of microvascular and neurodegenerative pathology, the effect of strategic acute stroke lesions, and the mediating effect of genomic and epigenomic variation.

Machine-learning method for localization of cerebral white matter hyperintensities in healthy adults based on retinal images

Retinal vessels are known to be associated with various cardiovascular and cerebrovascular disease outcomes. Recent research has shown significant correlations between retinal characteristics and the presence of cerebral small vessel disease as measured by white matter hyperintensities from cerebral magnetic resonance imaging. Early detection of age-related white matter changes using retinal images is potentially helpful for population screening and allow early behavioural and lifestyle intervention. This study investigates the ability of the machine-learning method for the localization of brain white matter hyperintensities. All subjects were age 65 or above without any history of stroke and dementia and recruited from local community centres and community networks. Subjects with known retinal disease or disease influencing vessel structure in colour retina images were excluded. All subjects received MRI on the brain, and age-related white matter changes grading was determined from MRI as the primary endpoint. The presence of age-related white matter changes on each of the six brain regions was also studied. Retinal images were captured using a fundus camera, and the analysis was done based on a machine-learning approach. A total of 240 subjects are included in the study. The analysis of various brain regions included the left and right sides of frontal lobes, parietal–occipital lobes and basal ganglia. Our results suggested that data from both eyes are essential for detecting age-related white matter changes in the brain regions, but the retinal parameters useful for estimation of the probability of age-related white matter changes in each of the brain regions may differ for different locations. Using a classification and regression tree approach, we also found that at least three significant heterogeneous subgroups of subjects were identified to be essential for the localization of age-related white matter changes. Namely those with age-related white matter changes in the right frontal lobe, those without age-related white matter changes in the right frontal lobe but with age-related white matter changes in the left parietal–occipital lobe, and the rest of the subjects. Outcomes such as risks of severe grading of age-related white matter changes and the proportion of hypertension were significantly related to these subgroups. Our study showed that automatic retinal image analysis is a convenient and non-invasive screening tool for detecting age-related white matter changes and cerebral small vessel disease with good overall performance. The localization analysis for various brain regions shows that the classification models on each of the six brain regions can be done, and it opens up potential future clinical application.

Post-stroke Cognition at 1 and 3 Years Is Influenced by the Location of White Matter Hyperintensities in Patients With Lacunar Stroke

Lacunar strokes are a common type of ischemic stroke. They are known to have long-term cognitive deficits, but the influencing factors are still largely unknown. We investigated if the location of the index lacunar stroke or regional WMH and their change at 1 year could predict the cognitive performance at 1 and 3 years post-stroke in lacunar stroke patients. We used lacunar lesion location and WMH-segmented data from 118 patients, mean age 64.9 who had a brain MRI scan soon after presenting with symptoms, of which 88 had a repeated scan 12 months later. Premorbid intelligence (National Adult Reading Test) and current intelligence [Addenbrooke's Cognitive Exam-Revised (ACE-R)] were measured at 1, 12, and 36 months after the stroke. ANCOVA analyses adjusting for baseline cognition/premorbid intelligence, vascular risk factors, age, sex and total baseline WMH volume found that the recent small subcortical infarcts (RSSI) in the internal/external capsule/lentiform nucleus and centrum semiovale did not predict cognitive scores at 12 and 36 months. However, RSSI location moderated voxel-based associations of WMH change from baseline to 1 year with cognitive scores at 1 and 3 years. WMH increase in the external capsule, intersection between the anterior limb of the internal and external capsules, and optical radiation, was associated with worsening of ACE-R scores 1 and 3 years post-stroke after accounting for the location of the index infarct, age and baseline cognition.

Pandemic of the aging society - sporadic cerebral small vessel disease

Age-related sporadic cerebral small vessel disease (CSVD) has gained increasing attention over the past decades because of its increasing prevalence associated with an aging population. The widespread application of and advances in brain magnetic resonance imaging in recent decades have significantly increased researchers’ understanding in the in vivo evolution of CSVD, its impact upon the brain, its risk factors, and the mechanisms that explain the various clinical manifestation associated with sporadic CSVD. In this review, we aimed to provide an update on the pathophysiology, risk factors, biomarkers, and the determinants and spectrum of the clinical manifestation of sporadic CSVD.

Magnetic resonance imaging manifestations of cerebral small vessel disease: automated quantification and clinical application

The common cerebral small vessel disease (CSVD) neuroimaging features visible on conventional structural magnetic resonance imaging include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. The CSVD neuroimaging features have shared and distinct clinical consequences, and the automatic quantification methods for these features are increasingly used in research and clinical settings. This review article explores the recent progress in CSVD neuroimaging feature quantification and provides an overview of the clinical consequences of these CSVD features as well as the possibilities of using these features as endpoints in clinical trials. The added value of CSVD neuroimaging quantification is also discussed for researches focused on the mechanism of CSVD and the prognosis in subjects with CSVD.

White Matter Hyperintensity Burden Is Associated With Hippocampal Subfield Volume in Stroke

White matter hyperintensities of presumed vascular origin (WMH) are a prevalent form of cerebral small-vessel disease and an important risk factor for post-stroke cognitive dysfunction. Despite this prevalence, it is not well understood how WMH contributes to post-stroke cognitive dysfunction. Preliminary findings suggest that increasing WMH volume is associated with total hippocampal volume in chronic stroke patients. The hippocampus, however, is a complex structure with distinct subfields that have varying roles in the function of the hippocampal circuitry and unique anatomical projections to different brain regions. For these reasons, an investigation into the relationship between WMH and hippocampal subfield volume may further delineate how WMH predispose to post-stroke cognitive dysfunction. In a prospective study of acute ischemic stroke patients with moderate/severe WMH burden, we assessed the relationship between quantitative WMH burden and hippocampal subfield volumes. Patients underwent a 3T MRI brain within 2–5 days of stroke onset. Total WMH volume was calculated in a semi-automated manner. Mean cortical thickness and hippocampal volumes were measured in the contralesional hemisphere. Total and subfield hippocampal volumes were measured using an automated, high-resolution, ex vivo computational atlas. Linear regression analyses were performed for predictors of total and subfield hippocampal volumes. Forty patients with acute ischemic stroke and moderate/severe white matter hyperintensity burden were included in this analysis. Median WMH volume was 9.0 cm³. Adjusting for intracranial volume and stroke laterality, age (β = −3.7, P < 0.001), hypertension (β = −44.7, P = 0.04), WMH volume (β = −0.89, P = 0.049), and mean cortical thickness (β = 286.2, P = 0.006) were associated with total hippocampal volume. In multivariable analysis, age (β = −3.3, P < 0.001) and cortical thickness (β = 205.2, P = 0.028) remained independently associated with total hippocampal volume. In linear regression for predictors of hippocampal subfield volume, increasing WMH volume was associated with decreased hippocampal-amygdala transition area volume (β = −0.04, P = 0.001). These finding suggest that in ischemic stroke patients, increased WMH burden is associated with selective hippocampal subfield degeneration in the hippocampal-amygdala transition area.

Association between white matter hyperintensities and stroke in a West African patient population: Evidence from the Stroke Investigative Research and Educational Network study

BACKGROUND

This study is part of the Stroke Investigative Research and Educational Network (SIREN), the largest study of stroke patients in Africa to date, with computed tomography (CT) or magnetic resonance (MR) imaging data for each patient to confirm stroke. Prior imaging studies performed using high-field MR (≥1.5T) have shown that white matter hyperintensities (WMH), signs of microangiopathy in the subcortical brain, are correlated with many stroke risk factors as well as poor stroke outcomes. The aim of this study was the evaluation of MR images (0.3T-1.5T) from the SIREN study to determine associations between WMH volumes in West African patients and both stroke outcomes and stroke risk factors identified in the SIREN study.

MATERIALS AND METHODS

Brain MR images of 130 Western African stroke patients (age ​= ​57.87 ​± ​14.22) were processed through Lesion Segmentation Toolbox of the Statistical Parametric Mapping software to extract all areas of hyperintensity in the brain. WMH was separated from stroke lesion hyperintensity and WMH volume was computed and summed. A stepwise linear regression and multivariate analysis was performed between patients' WMH volume and sociodemographic and clinical indices.

RESULTS

Multivariate analysis showed that high WMH volume was statistically significantly positively correlated with age (β ​= ​0.44, p ​= ​0.001), waist/hip ratio (β ​= ​0.22, p ​= ​0.03), and platelet count (β ​= ​0.19, p ​= ​0.04) after controlling for head size in a Western African stroke population.

CONCLUSION

Associations between WMH and age and waist/hip ratio previously identified in Western countries were demonstrated for the first time in a resource-limited, homogeneous black African community using low-field MR scanners.

The new insights into human brain imaging after stroke

Over the last two decades, developments of human brain stroke imaging have raised several questions about the place of new MRI biomarkers in the acute management of stroke and the prediction of poststroke outcome. Recent studies have demonstrated the main role of perfusion-weighted imaging in the identification of the best cerebral perfusion profile for a better response after reperfusion therapies in acute ischemic stroke. A major issue remains the early prediction of stroke outcome. While voxel-based lesion-symptom mapping emphasized the influence of stroke location, the analysis of the brain parenchyma underpinning the stroke lesion showed the relevance of prestroke cerebral status, including cortical atrophy, white matter integrity, or presence of chronic cortical cerebral microinfarcts. Moreover, besides the evaluation of the visually abnormal brain tissue, the analysis of normal-appearing brain parenchyma using diffusion tensor imaging and magnetization transfer imaging or spectroscopy offered new biomarkers to improve the prediction of the prognosis and new targets to follow in therapeutic trials. The aim of this review was to depict the main new radiological biomarkers reported in the last two decades that will provide a more thorough prediction of functional, motor, and neuropsychological outcome following the stroke. These new developments in neuroimaging might be a cornerstone in the emerging personalized medicine for stroke patients.

Biological and imaging predictors of cognitive impairment after stroke: a systematic review

BACKGROUND

Cognitive impairment is frequent after stroke, and several studies have suggested that biological and imaging characteristics present before stroke are associated with the development of post-stroke cognitive impairment.

OBJECTIVE

The aim of our study was to systematically review biological and imaging predictors of cognitive impairment after stroke.

METHOD

Studies were identified from bibliographic databases and reference lists, and were included if conducted in patients with acute stroke, with at least 30 patients, and a follow-up of at least 3 months. We included articles on potential biomarkers of cognitive impairment that pre-existed to stroke.

RESULTS

We identified 22,169 articles, including 20,349 with abstract. After analysis, 66 studies conducted in 42 cohorts met selection criteria. They included 30-9522 patients [median 170; interquartile range (IQR) 104-251] with a median follow-up of 12 months (IQR 3-36). All studies met quality criteria for description of the study population and standardization of biomarkers. Twenty-nine studies met all quality criteria. There was no convincing evidence that any biological marker may predict cognitive impairment. The most consistent predictors of cognitive impairment after stroke were global atrophy and medial temporal lobe atrophy.

CONCLUSION

Pre-existing cerebral atrophy is the most consistent predictor of cognitive impairment that can be identified in patients with an acute stroke.