Cerebral Vascular Dysfunctions Detected in Human Small Vessel Disease and Implications for Preclinical Studies.

Cerebral small vessel disease (SVD) is highly prevalent and a common cause of ischemic and hemorrhagic stroke and dementia, yet the pathophysiology is poorly understood. Its clinical expression is highly varied, and prognostic implications are frequently overlooked in clinics; thus, treatment is currently confined to vascular risk factor management. Traditionally, SVD is considered the small vessel equivalent of large artery stroke (occlusion, rupture), but data emerging from human neuroimaging and genetic studies refute this, instead showing microvessel endothelial dysfunction impacting on cell-cell interactions and leading to brain damage. These dysfunctions reflect defects that appear to be inherited and secondary to environmental exposures, including vascular risk factors. Interrogation in preclinical models shows consistent and converging molecular and cellular interactions across the endothelial-glial-neural unit that increasingly explain the human macroscopic observations and identify common patterns of pathology despite different triggers. Importantly, these insights may offer new targets for therapeutic intervention focused on restoring endothelial-glial physiology.

Imaging Biomarkers of VCI: A Focused Update.

Vascular cognitive impairment is common after stroke, in memory clinics, medicine for the elderly services, and undiagnosed in the community. Vascular disease is said to be the second most common cause of dementia after Alzheimer disease, yet vascular dysfunction is now known to predate cognitive decline in Alzheimer disease, and most dementias at older ages are mixed. Neuroimaging has a major role in identifying the proportion of vascular versus other likely pathologies in patients with cognitive impairment. Here, we aim to provide a pragmatic but evidence-based summary of the current state of potential imaging biomarkers, focusing on magnetic resonance imaging and computed tomography, which are relevant to diagnosing, estimating prognosis, monitoring vascular cognitive impairment, and incorporating our own experiences. We focus on markers that are well-established, with a known profile of association with cognitive measures, but also consider more recently described, including quantitative tissue markers of vascular injury. We highlight the gaps in accessibility and translation to more routine clinical practice.

Systematic review and meta-analysis of automated methods for quantifying enlarged perivascular spaces in the brain.

Research into magnetic resonance imaging (MRI)-visible perivascular spaces (PVS) has recently increased, as results from studies in different diseases and populations are cementing their association with sleep, disease phenotypes, and overall health indicators. With the establishment of worldwide consortia and the availability of large databases, computational methods that allow to automatically process all this wealth of information are becoming increasingly relevant. Several computational approaches have been proposed to assess PVS from MRI, and efforts have been made to summarise and appraise the most widely applied ones. We systematically reviewed and meta-analysed all publications available up to September 2023 describing the development, improvement, or application of computational PVS quantification methods from MRI. We analysed 67 approaches and 60 applications of their implementation, from 112 publications. The two most widely applied were the use of a morphological filter to enhance PVS-like structures, with Frangi being the choice preferred by most, and the use of a U-Net configuration with or without residual connections. Older adults or population studies comprising adults from 18 years old onwards were, overall, more frequent than studies using clinical samples. PVS were mainly assessed from T2-weighted MRI acquired in 1.5T and/or 3T scanners, although combinations using it with T1-weighted and FLAIR images were also abundant. Common associations researched included age, sex, hypertension, diabetes, white matter hyperintensities, sleep and cognition, with occupation-related, ethnicity, and genetic/hereditable traits being also explored. Despite promising improvements to overcome barriers such as noise and differentiation from other confounds, a need for joined efforts for a wider testing and increasing availability of the most promising methods is now paramount.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning.

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|ß| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

Paranasal sinus occupancy assessed from magnetic resonance images-associations with clinical indicators in patients with systemic lupus erythematosus.

OBJECTIVES: Nasal, paranasal sinus and mucosal disorders are common symptoms in autoimmune rheumatic diseases. Soft tissue changes and fluid accumulation in the osteomeatal complexes and paranasal sinuses manifest as opaqueness on radiological images which can be assessed using visual scoring and computational methods on CT scans, but their results do not always correlate. Using MRI, we investigate the applicability of different image analysis methods in SLE. METHODS: We assessed paranasal sinus opaqueness on MRI from 51 SLE patients, using three visual scoring systems and expert-delineated computational volumes, and examined their association with markers of disease activity, inflammation, endothelial dysfunction and common small vessel disease (SVD) indicators, adjusting for age and sex-at-birth. RESULTS: The average paranasal sinus volume occupation was 4.55 (6.47%) [median (interquartile range) = 0.67 (0.25-2.65) ml], mainly in the maxillary and ethmoid sinuses. It was highly correlated with Lund-Mackay (LM) scores modified at 50% opaqueness cut-off (Spearman's ρ: 0.71 maxillary and 0.618 ethmoids, P < 0.001 in all), and with more granular variations of the LM system. The modified LM scores were associated with SVD scores (0: B = 5.078, s.e. = 1.69, P = 0.0026; 2: B = -0.066, s.e. = 0.023, P = 0.0045) and disease activity (anti-dsDNA: B = 4.59, s.e. = 2.22, P = 0.045; SLEDAI 3-7: 2.86 < B < 4.30; 1.38 < s.e. < 1.63; 0.0083 ≤ P ≤ 0.0375). Computationally derived percent opaqueness yielded similar results. CONCLUSION: In patients with SLE, MRI computational assessment of sinuses opaqueness and LM scores modified at a 50% cut-off may be useful tools in understanding the relationships among paranasal sinus occupancy, disease activity and SVD markers.

CADASIL Affects Multiple Aspects of Cerebral Small Vessel Function on 7T-MRI.

OBJECTIVE: Cerebral small vessel diseases (cSVDs) are a major cause of stroke and dementia. We used cutting-edge 7T-MRI techniques in patients with Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL), to establish which aspects of cerebral small vessel function are affected by this monogenic form of cSVD. METHODS: We recruited 23 CADASIL patients (age 51.1 ± 10.1 years, 52% women) and 13 age- and sex-matched controls (46.1 ± 12.6, 46% women). Small vessel function measures included: basal ganglia and centrum semiovale perforating artery blood flow velocity and pulsatility, vascular reactivity to a visual stimulus in the occipital cortex and reactivity to hypercapnia in the cortex, subcortical gray matter, white matter, and white matter hyperintensities. RESULTS: Compared with controls, CADASIL patients showed lower blood flow velocity and higher pulsatility index within perforating arteries of the centrum semiovale (mean difference - 0.09 cm/s, p = 0.03 and 0.20, p = 0.009) and basal ganglia (mean difference - 0.98 cm/s, p = 0.003 and 0.17, p = 0.06). Small vessel reactivity to a short visual stimulus was decreased (blood-oxygen-level dependent [BOLD] mean difference -0.21%, p = 0.04) in patients, while reactivity to hypercapnia was preserved in the cortex, subcortical gray matter, and normal appearing white matter. Among patients, reactivity to hypercapnia was decreased in white matter hyperintensities compared to normal appearing white matter (BOLD mean difference -0.29%, p = 0.02). INTERPRETATION: Multiple aspects of cerebral small vessel function on 7T-MRI were abnormal in CADASIL patients, indicative of increased arteriolar stiffness and regional abnormalities in reactivity, locally also in relation to white matter injury. These observations provide novel markers of cSVD for mechanistic and intervention studies. ANN NEUROL 2023;93:29-39.

Noninvasive In Vivo Thrombus Imaging in Patients With Ischemic Stroke or Transient Ischemic Attack-Brief Report.

BACKGROUND: 18F-GP1 is a novel positron-emitting radiotracer that is highly specific for activated platelets and thrombus. In a proof-of-concept study, we aimed to determine its potential clinical application in establishing the role and origin of thrombus in ischemic stroke. METHODS: Eleven patients with recent ischemic stroke (n=9) or transient ischemic attack (n=2) underwent 18F-GP1 positron emission tomography and computed tomography angiography at a median of 11 (range, 2-21) days from symptom onset. 18F-GP1 uptake (maximum target-to-background ratio) was assessed in the carotid arteries and brain. RESULTS: 18F-GP1 uptake was identified in 10 of 11 patients: 4 in the carotid arteries only, 3 in the brain only, and 3 in both the brain and carotid arteries. In those with carotid uptake, 4 participants had >50% stenosis and 3 had nonstenotic disease. One case had bilateral stenotic disease (>70%), but only the culprit carotid artery demonstrated 18F-GP1 uptake. The average uptake was higher in the culprit (median maximum target-to-background ratio, 1.55 [interquartile range, 1.26-1.82]) compared with the contralateral nonculprit carotid artery (maximum target-to-background ratio, 1.22 [1.19-1.6]). In those with brain 18F-GP1 uptake (maximum target-to-background ratio, 6.45 [4.89-7.65]), areas of acute infarction on computed tomography correlated with brain 18F-GP1 uptake in 6 cases. Ex vivo autoradiography of postmortem infarcted brain tissue showed focal uptake corresponding to intraluminal thrombus within the culprit vessel and downstream microvasculature. There was also evidence of diffuse uptake within some of the infarcted brain tissue reflecting parenchymal petechial hemorrhage. CONCLUSIONS: 18F-GP1 positron emission tomography and computed tomography angiography is a novel noninvasive method of identifying in vivo cerebrovascular thrombosis, which holds major promise in understanding the role and origin of thrombosis in stroke. REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT03943966.

Occupational and domestic exposure associations with cerebral small vessel disease and vascular dementia: A systematic review and meta-analysis.

INTRODUCTION: The prevalence of cerebral smallvessel disease (SVD) and vascular dementia according to workplace or domestic exposure to hazardous substances is unclear. METHODS: We included studies assessing occupational and domestic hazards/at-risk occupations and SVD features. We pooled prevalence estimates using random-effects models where possible, or presented a narrative synthesis. RESULTS: We included 85 studies (n = 47,743, mean age = 44·5 years). 52/85 reported poolable estimates. SVD prevalence in populations exposed to carbon monoxide was 81%(95% CI = 60-93%; n = 1373; results unchanged in meta-regression), carbon disulfide73% (95% CI = 54-87%; n = 131), 1,2-dichloroethane 88% (95% CI = 4-100%, n = 40), toluene 82% (95% CI = 3-100%, n = 64), high altitude 49% (95% CI = 38-60%; n = 164),and diving 24% (95% CI = 5-67%, n = 172). We narratively reviewed vascular dementia studies and contact sport, lead, military, pesticide, and solvent exposures as estimates were too few/varied to pool. DISCUSSION: SVD and vascular dementia may be associated with occupational/domestic exposure to hazardous substances. CRD42021297800.

Linking white matter hyperintensities to regional cortical thinning, amyloid deposition, and synaptic density loss in Alzheimer's disease.

INTRODUCTION: We investigated the association between white matter hyperintensities (WMH) and regional cortical thickness, amyloid and tau deposition, and synaptic density in the WMH-connected cortex using multimodal images. METHODS: We included 107 participants (59 with Alzheimer's disease [AD]; 27 with mild cognitive impairment; 21 cognitively normal controls) with amyloid beta (Aß) positivity on amyloid positron emission tomography (PET). The cortex connected to WMH was identified using probabilistic tractography. RESULTS: We found that WMH connected to the cortex with more severe regional degeneration as measured by cortical thickness, Aß and tau deposition, and synaptic vesicle glycoprotein 2 A (SV2A) density using 18F-SynVesT-1 PET. In addition, higher ratios of Aß in the deep WMH-connected versus WMH-unconnected cortex were significantly related to lower cognitive scores. Last, the cortical thickness of WMH-connected cortex reduced more than WMH-unconnected cortex over 12 months. DISCUSSION: Our results suggest that WMH may be associated with AD-intrinsic processes of degeneration, in addition to vascular mechanisms. HIGHLIGHTS: We studied white matter hyperintensities (WMHs) and WMH-connected cortical changes. WMHs are associated with more severe regional cortical degeneration. Findings suggest WMHs may be associated with Alzheimer's disease-intrinsic processes of degeneration.

Evaluating artificial intelligence software for delineating hemorrhage extent on CT brain imaging in stroke: AI delineation of ICH on CT.

BACKGROUND: The extent and distribution of intracranial hemorrhage (ICH) directly affects clinical management. Artificial intelligence (AI) software can detect and may delineate ICH extent on brain CT. We evaluated e-ASPECTS software (Brainomix Ltd.) performance for ICH delineation. METHODS: We qualitatively assessed software delineation of ICH on CT using patients from six stroke trials. We assessed hemorrhage delineation in five compartments: lobar, deep, posterior fossa, intraventricular, extra-axial. We categorized delineation as excellent, good, moderate, or poor. We assessed quality of software delineation with number of affected compartments in univariate analysis (Kruskall-Wallis test) and ICH location using logistic regression (dependent variable: dichotomous delineation categories 'excellent-good' versus 'moderate-poor'), and report odds ratios (OR) and 95 % confidence intervals (95 %CI). RESULTS: From 651 patients with ICH (median age 75 years, 53 % male), we included 628 with assessable CTs. Software delineation of ICH extent was 'excellent' in 189/628 (30 %), 'good' in 255/628 (41 %), 'moderate' in 127/628 (20 %), and 'poor' in 57/628 cases (9 %). The quality of software delineation of ICH was better when fewer compartments were affected (Z = 3.61-6.27; p = 0.0063). Software delineation of ICH extent was more likely to be 'excellent-good' quality when lobar alone (OR = 1.56, 95 %CI = 0.97-2.53) but 'moderate-poor' with any intraventricular (OR = 0.56, 95 %CI = 0.39-0.81, p = 0.002) or any extra-axial (OR = 0.41, 95 %CI = 0.27-0.62, p<0.001) extension. CONCLUSIONS: Delineation of ICH extent on stroke CT scans by AI software was excellent or good in 71 % of cases but was more likely to over- or under-estimate extent when ICH was either more extensive, intraventricular, or extra-axial.

Circulating Metabolome and White Matter Hyperintensities in Women and Men.

BACKGROUND: White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. METHODS: We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)<0.05 were considered significant. RESULTS: In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (PFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (PFDR.full.adj=1.40×10-7) and in both the pooled sample (PFDR.full.adj=1.66×10-4) and statin-untreated (PFDR.full.adj=1.65×10-6) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (PFDR=0.047). CONCLUSIONS: Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.

Assessing Brain Tissue Viability on Nonenhanced Computed Tomography After Ischemic Stroke.

BACKGROUND: Treatment for ischemic stroke can be offered beyond conventional time limits for patients with favorable computed tomography perfusion (CTP), but this is not universally available. We sought a threshold for brain attenuation on nonenhanced computed tomography (NECT) to differentiate CTP-defined penumbra vs core, and correlated NECT features with CTP. METHODS: We retrospectively assessed consecutive patients presenting to King Abdulaziz University Hospital with ischemic stroke (2017-2020), baseline NECT, and a visible defect on concurrent CTP. Using CTP as the reference standard, we measured the attenuation of ischemic and healthy contralateral brain on NECT to produce attenuation ratios (ischemic/normal) for penumbra and core. We used area under the receiver operating characteristic curve to estimate the optimal computed tomography (CT) attenuation ratio for penumbra. Per patient, we qualitatively assessed 8 regions within the affected cerebral hemisphere: on NECT as normal, hypoattenuating (with/out swelling), or isolated swelling and on CTP as normal, penumbra, or core. We sought associations between isolated swelling and penumbra, and between hypoattenuation and core. RESULTS: We include 142 patients (86 male), mean age 61±14 years. Median 261 minutes (interquartile range, 173-382) to NECT. We measured 206 ischemic lesions (124 penumbra, 82 core). Optimal CT attenuation ratio for identifying penumbra was >0.87, with 86% sensitivity 91% specificity (area under the receiver operating characteristic curve, 0.95 [95% CI, 0.92-0.98]; P<0.0001). We qualitatively assessed 976 cerebral regions (72 isolated swelling, 254 hypoattenuation). On NECT, isolated swelling usually corresponded to CTP penumbra (70/72, 97%), whereas visible NECT hypoattenuation was found with core (141/254, 56%) and penumbra (109/254, 43%). CTP core lesions were rarely normal on NECT (13/155, 8%). CONCLUSIONS: After ischemic stroke, brain tissue viability can be assessed using NECT. Isolated swelling is highly specific to penumbra. Visible hypoattenuation does not always represent core, nearly half of such lesions were penumbral on concurrent CTP and can be differentiated by measuring lesion attenuation.

Cerebrovascular Reactivity in Patients With Small Vessel Disease: A Cross-Sectional Study.

BACKGROUND: Cerebrovascular reactivity (CVR) is inversely related to white matter hyperintensity severity, a marker of cerebral small vessel disease (SVD). Less is known about the relationship between CVR and other SVD imaging features or cognition. We aimed to investigate these cross-sectional relationships. METHODS: Between 2018 and 2021 in Edinburgh, we recruited patients presenting with lacunar or cortical ischemic stroke, whom we characterized for SVD features. We measured CVR in subcortical gray matter, normal-appearing white matter, and white matter hyperintensity using 3T magnetic resonance imaging. We assessed cognition using Montreal Cognitive Assessment. Statistical analyses included linear regression models with CVR as outcome, adjusted for age, sex, and vascular risk factors. We reported regression coefficients with 95% CIs. RESULTS: Of 208 patients, 182 had processable CVR data sets (median age, 68.2 years; 68% men). Although the strength of association depended on tissue type, lower CVR in normal-appearing tissues and white matter hyperintensity was associated with larger white matter hyperintensity volume (BNAWM=-0.0073 [95% CI, -0.0133 to -0.0014] %/mm Hg per 10-fold increase in percentage intracranial volume), more lacunes (BNAWM=-0.00129 [95% CI, -0.00215 to -0.00043] %/mm Hg per lacune), more microbleeds (BNAWM=-0.00083 [95% CI, -0.00130 to -0.00036] %/mm Hg per microbleed), higher deep atrophy score (BNAWM=-0.00218 [95% CI, -0.00417 to -0.00020] %/mm Hg per score point increase), higher perivascular space score (BNAWM=-0.0034 [95% CI, -0.0066 to -0.0002] %/mm Hg per score point increase in basal ganglia), and higher SVD score (BNAWM=-0.0048 [95% CI, -0.0075 to -0.0021] %/mm Hg per score point increase). Lower CVR in normal-appearing tissues was related to lower Montreal Cognitive Assessment without reaching convention statistical significance (BNAWM=0.00065 [95% CI, -0.00007 to 0.00137] %/mm Hg per score point increase). CONCLUSIONS: Lower CVR in patients with SVD was related to more severe SVD burden and worse cognition in this cross-sectional analysis. Longitudinal analysis will help determine whether lower CVR predicts worsening SVD severity or vice versa. REGISTRATION: URL: https://www.isrctn.com; Unique identifier: ISRCTN12113543.

Sex Differences in Poststroke Cognitive Impairment: A Multicenter Study in 2343 Patients With Acute Ischemic Stroke.

BACKGROUND: Poststroke cognitive impairment (PSCI) occurs in about half of stroke survivors. Cumulative evidence indicates that functional outcomes of stroke are worse in women than men. Yet it is unknown whether the occurrence and characteristics of PSCI differ between men and women. METHODS: Individual patient data from 9 cohorts of patients with ischemic stroke were harmonized and pooled through the Meta-VCI-Map consortium (n=2343, 38% women). We included patients with visible symptomatic infarcts on computed tomography/magnetic resonance imaging and cognitive assessment within 15 months after stroke. PSCI was defined as impairment in ≥1 cognitive domains on neuropsychological assessment. Logistic regression analyses were performed to compare men to women, adjusted for study cohort, to obtain odds ratios for PSCI and individual cognitive domains. We also explored sensitivity and specificity of cognitive screening tools for detecting PSCI, according to sex (Mini-Mental State Examination, 4 cohorts, n=1814; Montreal Cognitive Assessment, 3 cohorts, n=278). RESULTS: PSCI was found in 51% of both women and men. Men had a lower risk of impairment of attention and executive functioning (men: odds ratio, 0.76 [95% CI, 0.61-0.96]), and language (men: odds ratio, 0.67 [95% CI, 0.45-0.85]), but a higher risk of verbal memory impairment (men: odds ratio, 1.43 [95% CI, 1.17-1.75]). The sensitivity of Mini-Mental State Examination (<25) for PSCI was higher for women (0.53) than for men (0.27; P=0.02), with a lower specificity for women (0.80) than men (0.96; P=0.01). Sensitivity and specificity of Montreal Cognitive Assessment (<26.) for PSCI was comparable between women and men (0.91 versus 0.86; P=0.62 and 0.29 versus 0.28; P=0.86, respectively). CONCLUSIONS: Sex was not associated with PSCI occurrence but affected domains differed between men and women. The latter may explain why sensitivity of the Mini-Mental State Examination for detecting PSCI was higher in women with a lower specificity compared with men. These sex differences need to be considered when screening for and diagnosing PSCI in clinical practice.

White Matter Hyperintensity Volume and Poststroke Cognition: An Individual Patient Data Pooled Analysis of 9 Ischemic Stroke Cohort Studies.

BACKGROUND: White matter hyperintensities (WMH) are associated with cognitive dysfunction after ischemic stroke. Yet, uncertainty remains about affected domains, the role of other preexisting brain injury, and infarct types in the relation between WMH burden and poststroke cognition. We aimed to disentangle these factors in a large sample of patients with ischemic stroke from different cohorts. METHODS: We pooled and harmonized individual patient data (n=1568) from 9 cohorts, through the Meta VCI Map consortium (www.metavcimap.org). Included cohorts comprised patients with available magnetic resonance imaging and multidomain cognitive assessment <15 months poststroke. In this individual patient data meta-analysis, linear mixed models were used to determine the association between WMH volume and domain-specific cognitive functioning (Z scores; attention and executive functioning, processing speed, language and verbal memory) for the total sample and stratified by infarct type. Preexisting brain injury was accounted for in the multivariable models and all analyses were corrected for the study site as a random effect. RESULTS: In the total sample (67 years [SD, 11.5], 40% female), we found a dose-dependent inverse relationship between WMH volume and poststroke cognitive functioning across all 4 cognitive domains (coefficients ranging from -0.09 [SE, 0.04, P=0.01] for verbal memory to -0.19 [SE, 0.03, P<0.001] for attention and executive functioning). This relation was independent of acute infarct volume and the presence of lacunes and old infarcts. In stratified analyses, the relation between WMH volume and domain-specific functioning was also largely independent of infarct type. CONCLUSIONS: In patients with ischemic stroke, increasing WMH volume is independently associated with worse cognitive functioning across all major domains, regardless of old ischemic lesions and infarct type.

External Validation of e-ASPECTS Software for Interpreting Brain CT in Stroke.

OBJECTIVE: The purpose of this study was to test e-ASPECTS software in patients with stroke. Marketed as a decision-support tool, e-ASPECTS may detect features of ischemia or hemorrhage on computed tomography (CT) imaging and quantify ischemic extent using Alberta Stroke Program Early CT Score (ASPECTS). METHODS: Using CT from 9 stroke studies, we compared software with masked experts. As per indications for software use, we assessed e-ASPECTS results for patients with/without middle cerebral artery (MCA) ischemia but no other cause of stroke. In an analysis outside the intended use of the software, we enriched our dataset with non-MCA ischemia, hemorrhage, and mimics to simulate a representative "front door" hospital population. With final diagnosis as the reference standard, we tested the diagnostic accuracy of e-ASPECTS for identifying stroke features (ischemia, hyperattenuated arteries, and hemorrhage) in the representative population. RESULTS: We included 4,100 patients (51% women, median age = 78 years, National Institutes of Health Stroke Scale [NIHSS] = 10, onset to scan = 2.5 hours). Final diagnosis was ischemia (78%), hemorrhage (14%), or mimic (8%). From 3,035 CTs with expert-rated ASPECTS, most (2084/3035, 69%) e-ASPECTS results were within one point of experts. In the representative population, the diagnostic accuracy of e-ASPECTS was 71% (95% confidence interval [CI] = 70-72%) for detecting ischemic features, 85% (83-86%) for hemorrhage. Software identified more false positive ischemia (12% vs 2%) and hemorrhage (14% vs <1%) than experts. INTERPRETATION: On independent testing, e-ASPECTS provided moderate agreement with experts and overcalled stroke features. Therefore, future prospective trials testing impacts of artificial intelligence (AI) software on patient care and outcome are required before widespread implementation of stroke decision-support software. ANN NEUROL 2022;92:943-957.

Are neuropsychiatric symptoms a marker of small vessel disease progression in older adults? Evidence from the Lothian Birth Cohort 1936.

BACKGROUND: Neuropsychiatric symptoms could form part of an early cerebral small vessel disease prodrome that is detectable before stroke or dementia onset. We aimed to identify whether apathy, depression, anxiety, and subjective memory complaints associate with longitudinal white matter hyperintensity (WMH) progression. METHODS: Community-dwelling older adults from the observational Lothian Birth Cohort 1936 attended three visits at mean ages 73, 76, and 79 years, repeating MRI, Mini-Mental State Examination, neuropsychiatric (Dimensional Apathy Scale, Hospital Anxiety and Depression Scale), and subjective memory symptoms. We ran regression and mixed-effects models for symptoms and normalised WMH volumes (cube root of WMH:ICV × 10). RESULTS: At age 73, 76, and 79, m = 672, n = 476, and n = 382 participants attended MRI respectively. Worse apathy at age 79 was associated with WMH volume increase (ß = 0.27, p = 0.04) in the preceding 6 years. A 1SD increase in apathy score at age 79 associated with a 0.17 increase in WMH (ß = 0.17 normalised WMH percent ICV, p = 0.009). In apathy subscales, executive (ß = 0.13, p = 0.05) and emotional (ß = 0.13, p = 0.04) scores associated with increasing WMH more than initiation scores (ß = 0.11, p = 0.08). Increasing WMH also associated with age (ß = 0.40, p = 0.002) but not higher depression (ß = -0.01, p = 0.78), anxiety (ß = 0.05, p = 0.13) scores, or subjective memory complaints (ß = 1.12, p = 0.75). CONCLUSIONS: Apathy independently associates with preceding longitudinal WMH progression, while depression, anxiety, and subjective memory complaints do not. Patients with apathy should be considered for enrolment to small vessel disease trials.

A Scoping Review on Biomarkers of Endothelial Dysfunction in Small Vessel Disease: Molecular Insights from Human Studies.

Small vessel disease (SVD) is a highly prevalent disorder of the brain's microvessels and a common cause of dementia as well as ischaemic and haemorrhagic strokes. Though much about the underlying pathophysiology of SVD remains poorly understood, a wealth of recently published evidence strongly suggests a key role of microvessel endothelial dysfunction and a compromised blood-brain barrier (BBB) in the development and progression of the disease. Understanding the causes and downstream consequences associated with endothelial dysfunction in this pathological context could aid in the development of effective diagnostic and prognostic tools and provide promising avenues for potential therapeutic interventions. In this scoping review, we aim to summarise the findings from clinical studies examining the role of the molecular mechanisms underlying endothelial dysfunction in SVD, focussing on biochemical markers of endothelial dysfunction detectable in biofluids, including cell adhesion molecules, BBB transporters, cytokines/chemokines, inflammatory markers, coagulation factors, growth factors, and markers involved in the nitric oxide cascade.

Clinical Diagnosis and Magnetic Resonance Imaging in Patients With Transient and Minor Neurological Symptoms: A Prospective Cohort Study.

BACKGROUND: The utility of magnetic resonance imaging (MRI) brain in patients with transient or minor neurological symptoms is uncertain. We sought to determine the proportion of participants with transient or minor neurological symptoms who had MRI evidence of acute ischemia at different clinical probabilities of transient ischemic attack (TIA) or minor stroke. METHODS: Cohort of participants with transient or minor neurological symptoms from emergency and outpatient settings. Clinicians at different levels of training gave each participant a diagnostic probability (probable when TIA/stroke was the most likely differential diagnosis; possible when TIA/stroke was not the most likely differential diagnosis; or uncertain when diagnostic probability could not be given) before 1.5 or 3T brain MRI ≤5 days from onset. Post hoc, each clinical syndrome was defined blind to MRI findings as National Institute of Neurological Disorders and Stroke criteria TIA/stroke; International Headache Society criteria migraine aura; non-TIA focal symptoms; or nonfocal symptoms. MRI evidence of acute ischemia was defined by 2 reads of MRI. Stroke was ascertained for at least 90 days and up to 18 months after recruitment. RESULTS: Two hundred seventy-two participated (47% female, mean age 60, SD 14), 58% with MRI ≤2 days of onset. Most (92%) reported focal symptoms. MR evidence of acute ischemia was found, for stroke/TIA clinical probabilities of probable 23 out of 75 (31% [95% CI, 21%-42%]); possible 26 out of 151 (17% [12%-24%]); and uncertain 9 out of 43, (20% [10%-36%]). MRI evidence of acute ischemia was found in National Institute of Neurological Disorders and Stroke criteria TIA/stroke 40 out of 95 (42% [32%-53%]); migraine aura 4 out of 38 (11% [3%-25%]); non-TIA focal symptoms 16 out of 99 (16% [10%-25%]); and no focal features 1 out of 29 (3% [0%-18%]). After MRI, a further 14 (5% [95% CI, 3-8]) would be treated with an antiplatelet drug compared with treatment plan before MRI. By 18 months, a new ischemic stroke occurred in 9 out of 61 (18%) patients with MRI evidence of acute ischemia and 2 out of 211 (1%) without (age-adjusted hazard ratio, 13 [95% CI, 3-62]; P<0.0001). CONCLUSIONS: MRI evidence of acute brain ischemia was found in about 1 in 6 transient or minor neurological symptoms patients with a nonstroke/TIA initial diagnosis or uncertain diagnosis. Methods to determine the clinical and cost-effectiveness of MRI are needed in this population.

Accuracy of Automated Computer-Aided Diagnosis for Stroke Imaging: A Critical Evaluation of Current Evidence.

There is increasing interest in computer applications, using artificial intelligence methodologies, to perform health care tasks previously performed by humans, particularly in medical imaging for diagnosis. In stroke, there are now commercial artificial intelligence software for use with computed tomography or MR imaging to identify acute ischemic brain tissue pathology, arterial obstruction on computed tomography angiography or as hyperattenuated arteries on computed tomography, brain hemorrhage, or size of perfusion defects. A rapid, accurate diagnosis may aid treatment decisions for individual patients and could improve outcome if it leads to effective and safe treatment; or conversely, to disaster if a delayed or incorrect diagnosis results in inappropriate treatment. Despite this potential clinical impact, diagnostic tools including artificial intelligence methods are not subjected to the same clinical evaluation standards as are mandatory for drugs. Here, we provide an evidence-based review of the pros and cons of commercially available automated methods for medical imaging diagnosis, including those based on artificial intelligence, to diagnose acute brain pathology on computed tomography or magnetic resonance imaging in patients with stroke.