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A quarter of ischaemic strokes are lacunar subtype, typically neurologically mild, usually resulting from intrinsic cerebral small vessel pathology, with risk factor profiles and outcome rates differing from other stroke subtypes. This European Stroke Organisation (ESO) guideline provides evidence-based recommendations to assist with clinical decisions about management of lacunar ischaemic stroke to prevent adverse clinical outcomes. The guideline was developed according to ESO standard operating procedures and Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology. We addressed acute treatment (including progressive lacunar stroke) and secondary prevention in lacunar ischaemic stroke, and prioritised the interventions of thrombolysis, antiplatelet drugs, blood pressure lowering, lipid lowering, lifestyle, and other interventions and their potential effects on the clinical outcomes recurrent stroke, dependency, major adverse cardiovascular events, death, cognitive decline, mobility, gait, or mood disorders. We systematically reviewed the literature, assessed the evidence and where feasible formulated evidence-based recommendations, and expert concensus statements. We found little direct evidence, mostly of low quality. We recommend that patients with suspected acute lacunar ischaemic stroke receive intravenous alteplase, antiplatelet drugs and avoid blood pressure lowering according to current acute ischaemic stroke guidelines. For secondary prevention, we recommend single antiplatelet treatment long-term, blood pressure control, and lipid lowering according to current guidelines. We recommend smoking cessation, regular exercise, other healthy lifestyle modifications, and avoid obesity for general health benefits. We cannot make any recommendation concerning progressive stroke or other drugs. Large randomised controlled trials with clinically important endpoints, including cognitive endpoints, are a priority for lacunar ischaemic stroke., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. For details, please see Supplemental Table 1.

Background and Objectives: While chronological age is one of the most influential determinants of poststroke outcomes, little is known of the impact of neuroimaging-derived biological "brain age." We hypothesized that radiomics analyses of T2-FLAIR images texture would provide brain age estimates and that advanced brain age of patients with stroke will be associated with cardiovascular risk factors and worse functional outcomes., Methods: We extracted radiomics from T2-FLAIR images acquired during acute stroke clinical evaluation. Brain age was determined from brain parenchyma radiomics using an ElasticNet linear regression model. Subsequently, relative brain age (RBA), which expresses brain age in comparison with chronological age-matched peers, was estimated. Finally, we built a linear regression model of RBA using clinical cardiovascular characteristics as inputs and a logistic regression model of favorable functional outcomes taking RBA as input., Results: We reviewed 4,163 patients from a large multisite ischemic stroke cohort (mean age = 62.8 years, 42.0% female patients). T2-FLAIR radiomics predicted chronological ages (mean absolute error = 6.9 years, r = 0.81). After adjustment for covariates, RBA was higher and therefore described older-appearing brains in patients with hypertension, diabetes mellitus, a history of smoking, and a history of a prior stroke. In multivariate analyses, age, RBA, NIHSS, and a history of prior stroke were all significantly associated with functional outcome (respective adjusted odds ratios: 0.58, 0.76, 0.48, 0.55; all p -values < 0.001). Moreover, the negative effect of RBA on outcome was especially pronounced in minor strokes., Discussion: T2-FLAIR radiomics can be used to predict brain age and derive RBA. Older-appearing brains, characterized by a higher RBA, reflect cardiovascular risk factor accumulation and are linked to worse outcomes after stroke., (© 2022 American Academy of Neurology.)

Background and Objectives: To examine whether high white matter hyperintensity (WMH) burden is associated with greater stroke severity and worse functional outcomes in lesion pattern-specific ways., Methods: MR neuroimaging and NIH Stroke Scale data at index stroke and the modified Rankin Scale (mRS) score at 3-6 months after stroke were obtained from the MRI-Genetics Interface Exploration study of patients with acute ischemic stroke (AIS). Individual WMH volume was automatically derived from fluid-attenuated inversion recovery images. Stroke lesions were automatically segmented from diffusion-weighted imaging (DWI) images, parcellated into atlas-defined brain regions and further condensed to 10 lesion patterns via machine learning-based dimensionality reduction. Stroke lesion effects on AIS severity and unfavorable outcomes (mRS score >2) were modeled within purpose-built Bayesian linear and logistic regression frameworks. Interaction effects between stroke lesions and a high vs low WMH burden were integrated via hierarchical model structures. Models were adjusted for age, age 2 , sex, total DWI lesion and WMH volumes, and comorbidities. Data were split into derivation and validation cohorts., Results: A total of 928 patients with AIS contributed to acute stroke severity analyses (age: 64.8 [14.5] years, 40% women) and 698 patients to long-term functional outcome analyses (age: 65.9 [14.7] years, 41% women). Stroke severity was mainly explained by lesions focused on bilateral subcortical and left hemispherically pronounced cortical regions across patients with both a high and low WMH burden. Lesions centered on left-hemispheric insular, opercular, and inferior frontal regions and lesions affecting right-hemispheric temporoparietal regions had more pronounced effects on stroke severity in case of high compared with low WMH burden. Unfavorable outcomes were predominantly explained by lesions in bilateral subcortical regions. In difference to the lesion location-specific WMH effects on stroke severity, higher WMH burden increased the odds of unfavorable outcomes independent of lesion location., Discussion: Higher WMH burden may be associated with an increased stroke severity in case of stroke lesions involving left-hemispheric insular, opercular, and inferior frontal regions (potentially linked to language functions) and right-hemispheric temporoparietal regions (potentially linked to attention). Our findings suggest that patients with specific constellations of WMH burden and lesion locations may have greater benefits from acute recanalization treatments. Future clinical studies are warranted to systematically assess this assumption and guide more tailored treatment decisions., (© 2022 American Academy of Neurology.)

Background: Asundexian (Bayer AG, Leverkusen, Germany), an oral small molecule factor XIa (FXIa) inhibitor, might prevent thrombosis without increasing bleeding. Asundexian's effect for secondary prevention of recurrent stroke is unknown., Methods: In this randomised, double-blind, placebo-controlled, phase 2b dose-finding trial (PACIFIC-Stroke), patients with acute (within 48 h) non-cardioembolic ischaemic stroke were recruited from 196 hospitals in 23 countries. Patients were eligible if they were aged 45 years or older, to be treated with antiplatelet therapy, and able to have a baseline MRI (either before or within 72 h of randomisation). Eligible participants were randomly assigned (1:1:1:1), using an interactive web-based response system and stratified according to anticipated antiplatelet therapy (single vs dual), to once daily oral asundexian (BAY 2433334) 10 mg, 20 mg, or 50 mg, or placebo in addition to usual antiplatelet therapy, and were followed up during treatment for 26-52 weeks. Brain MRIs were obtained at study entry and at 26 weeks or as soon as possible after treatment discontinuation. The primary efficacy outcome was the dose-response effect on the composite of incident MRI-detected covert brain infarcts and recurrent symptomatic ischaemic stroke at or before 26 weeks after randomisation. The primary safety outcome was major or clinically relevant non-major bleeding as defined by International Society on Thrombosis and Haemostasis criteria. The efficacy outcome was assessed in all participants assigned to treatment, and the safety outcome was assessed in all participants who received at least one dose of study treatment. This study is registered with ClinicalTrials.gov, NCT04304508, and is now complete., Findings: Between June 15, 2020, and July 22, 2021, 1880 patients were screened and 1808 participants were randomly assigned to asundexian 10 mg (n=455), 20 mg (n=450), or 50 mg (n=447), or placebo (n=456). Mean age was 67 years (SD 10) and 615 (34%) participants were women, 1193 (66%) were men, 1505 (83%) were White, and 268 (15%) were Asian. The mean time from index stroke to randomisation was 36 h (SD 10) and median baseline National Institutes of Health Stroke Scale score was 2·0 (IQR 1·0-4·0). 783 (43%) participants received dual antiplatelet treatment for a mean duration of 70·1 days (SD 113·4) after randomisation. At 26 weeks, the primary efficacy outcome was observed in 87 (19%) of 456 participants in the placebo group versus 86 (19%) of 455 in the asundexian 10 mg group (crude incidence ratio 0·99 [90% CI 0·79-1·24]), 99 (22%) of 450 in the asundexian 20 mg group (1·15 [0·93-1·43]), and 90 (20%) of 447 in the asundexian 50 mg group (1·06 [0·85-1·32]; t statistic -0·68; p=0·80). The primary safety outcome was observed in 11 (2%) of 452 participants in the placebo group versus 19 (4%) of 445 in the asundexian 10 mg group, 14 (3%) of 446 in the asundexian 20 mg group, and 19 (4%) of 443 in the asundexian 50 mg group (all asundexian doses pooled vs placebo hazard ratio 1·57 [90% CI 0·91-2·71])., Interpretation: In this phase 2b trial, FXIa inhibition with asundexian did not reduce the composite of covert brain infarction or ischaemic stroke and did not increase the composite of major or clinically relevant non-major bleeding compared with placebo in patients with acute, non-cardioembolic ischaemic stroke., Funding: Bayer AG., Competing Interests: Declaration of interests All coauthors or their institutions received financial support from Bayer for participation in the PACIFIC-Stroke trial except HM, PC, BK, and CN who are employees of Bayer. HM, PC, BK, and CN do not hold any stock or stock options with Bayer., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background and Purpose: Up-to-date population-based information about long-term survival, causes of death and recurrence after stroke is needed., Methods: Four hundred consecutive individuals in a population-based cohort of first-ever stroke between 2015 and 2016 in Lund, Sweden, were followed up to 3 years regarding (i) survival (Swedish Population Register); (ii) causes of death (Swedish Causes of Death Register); and (iii) stroke recurrence (interview and medical chart review). Index and recurrent ischaemic stroke cases were classified using the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) and Oxfordshire Community Stroke Project; and comorbidities were classified using the Charlson Comorbidity Index. Cox regression was used to determine predictors for 3-year mortality. Survival rates were compared with three local studies over a 30-year timespan., Results: Amongst 400 first-ever stroke patients, 265 (66%) survived 3 years post-stroke. Age (hazard ratio [HR] 1.09; 95% confidence interval [CI] 1.06-1.11), stroke severity (HR 1.11; 95% CI 1.08-1.13) and comorbidities (HR 1.36; 95% CI 1.22-1.53) were independently related to 3-year mortality. Amongst index ischaemic stroke patients, survival was lowest amongst those with cardio-aortic embolism (51/91; 56%). Cerebrovascular disease (54/135; 40%) and ischaemic heart disease (25/135; 19%) were the most common causes of death. Within 3 years, 30 (8%) had recurrent stroke. Amongst patients with index ischaemic stroke, 16/29 (55%) had a different TOAST pathogenetic mechanism or hemorrhagic stroke upon recurrence. Stroke survival improved between 1983-1985 and 2015-2016 (p = 0.002), but no significant change was observed between 2001-2002 and 2015-2016 (p = 0.48)., Conclusions: Stroke survival rates are relatively high, but their improvement over recent decades may be slowing down, possibly due to the composition of the first-ever stroke population. The common occurrence of changed pathogenetic mechanisms between first-ever and recurrent stroke highlights the value of reassessment in recurrent stroke., (© 2021 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

There is a critical need to elucidate molecular mechanisms underlying brain injury, repair, and recovery following ischemic stroke-a global health problem with major social and economic impact. Despite 5 decades of intensive research, there are no widely accepted neuroprotective drugs that mitigate ischemic brain injury, or neuroreparative drugs, or personalized approaches that guide therapies to enhance recovery. We here explore novel reverse translational approaches that will complement traditional forward translational methods in identifying mechanisms relevant to human stroke outcome. Although genome-wide association studies have yielded over 30 genetic loci that influence ischemic stroke risk, only a few genome-wide association studies have been performed for stroke outcome. We discuss important considerations for genetic studies of ischemic stroke outcome-including carefully designed phenotypes that capture injury/recovery mechanisms, anchored in time to stroke onset. We also address recent genome-wide association studies that provide insight into mechanisms underlying brain injury and repair. There are several ongoing initiatives exploring genomic associations with novel phenotypes related to stroke outcome. To improve the understanding of the genetic architecture of ischemic stroke outcome, larger studies using standardized phenotypes, preferably embedded in standard-of-care measures, are needed. Novel techniques beyond genome-wide association studies-including exploiting informatics, multi-omics, and novel analytics-promise to uncover genetic and molecular pathways from which drug targets and other new interventions may be identified.

Background and Purpose- We evaluated deep learning algorithms' segmentation of acute ischemic lesions on heterogeneous multi-center clinical diffusion-weighted magnetic resonance imaging (MRI) data sets and explored the potential role of this tool for phenotyping acute ischemic stroke. Methods- Ischemic stroke data sets from the MRI-GENIE (MRI-Genetics Interface Exploration) repository consisting of 12 international genetic research centers were retrospectively analyzed using an automated deep learning segmentation algorithm consisting of an ensemble of 3-dimensional convolutional neural networks. Three ensembles were trained using data from the following: (1) 267 patients from an independent single-center cohort, (2) 267 patients from MRI-GENIE, and (3) mixture of (1) and (2). The algorithms' performances were compared against manual outlines from a separate 383 patient subset from MRI-GENIE. Univariable and multivariable logistic regression with respect to demographics, stroke subtypes, and vascular risk factors were performed to identify phenotypes associated with large acute diffusion-weighted MRI volumes and greater stroke severity in 2770 MRI-GENIE patients. Stroke topography was investigated. Results- The ensemble consisting of a mixture of MRI-GENIE and single-center convolutional neural networks performed best. Subset analysis comparing automated and manual lesion volumes in 383 patients found excellent correlation (ρ=0.92; P<0.0001). Median (interquartile range) diffusion-weighted MRI lesion volumes from 2770 patients were 3.7 cm 3 (0.9-16.6 cm 3 ). Patients with small artery occlusion stroke subtype had smaller lesion volumes ( P<0.0001) and different topography compared with other stroke subtypes. Conclusions- Automated accurate clinical diffusion-weighted MRI lesion segmentation using deep learning algorithms trained with multi-center and diverse data is feasible. Both lesion volume and topography can provide insight into stroke subtypes with sufficient sample size from big heterogeneous multi-center clinical imaging phenotype data sets.

White matter hyperintensity (WMH) burden is a critically important cerebrovascular phenotype linked to prediction of diagnosis and prognosis of diseases, such as acute ischemic stroke (AIS). However, current approaches to its quantification on clinical MRI often rely on time intensive manual delineation of the disease on T2 fluid attenuated inverse recovery (FLAIR), which hinders high-throughput analyses such as genetic discovery. In this work, we present a fully automated pipeline for quantification of WMH in clinical large-scale studies of AIS. The pipeline incorporates automated brain extraction, intensity normalization and WMH segmentation using spatial priors. We first propose a brain extraction algorithm based on a fully convolutional deep learning architecture, specifically designed for clinical FLAIR images. We demonstrate that our method for brain extraction outperforms two commonly used and publicly available methods on clinical quality images in a set of 144 subject scans across 12 acquisition centers, based on dice coefficient (median 0.95; inter-quartile range 0.94-0.95; p < 0.01) and Pearson correlation of total brain volume (r = 0.90). Subsequently, we apply it to the large-scale clinical multi-site MRI-GENIE study (N = 2783) and identify a decrease in total brain volume of -2.4 cc/year. Additionally, we show that the resulting total brain volumes can successfully be used for quality control of image preprocessing. Finally, we obtain WMH volumes by building on an existing automatic WMH segmentation algorithm that delineates and distinguishes between different cerebrovascular pathologies. The learning method mimics expert knowledge of the spatial distribution of the WMH burden using a convolutional auto-encoder. This enables successful computation of WMH volumes of 2533 clinical AIS patients. We utilize these results to demonstrate the increase of WMH burden with age (0.950 cc/year) and show that single site estimates can be biased by the number of subjects recruited., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Background and Purpose: Whereas traditional views of language processing in the brain have assumed that the language function is concentrated to a limited number of cortical areas (Broca's and Wernicke's areas), current knowledge points at a much more complex system of language and speech processing involving many brain areas, both cortical and subcortical. The purpose of the current study was to make an unbiased assessment of which cerebral areas are affected in first-ever acute ischaemic stroke patients identified as having language and speech impairments according to the National Institutes of Health Stroke Scale (NIHSS)., Methods: Data from 34 patients with language and speech impairment, with a score of 1-3 on item 9 of the NIHSS, following ischaemic stroke were collected from the Lund Stroke Register. Magnetic resonance images acquired up to 20 days after stroke onset were used to create an overlap lesion image using MRIcron software., Results: The classical language areas, Wernicke's and Broca's areas, were affected in less than one-fourth of the patients. The most frequently affected region was a subcortical region--the left caudate nucleus and the adjacent corona radiata., Conclusions: These findings contribute to the growing body of evidence that the basal ganglia have a crucial role in the control over language and speech processing., (© 2015 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Background: The aim was to investigate whether the effects of major risk factors for ischemic stroke were modified by long-term exposure to air pollution in Scania, southern Sweden., Methods: Cases were defined as first-ever ischemic strokes in patients born between 1923 and 1965 during 2001-2006 (n = 7,244). Data were collected from The Swedish National Stroke Register (Riks-stroke) and the Malmö and Lund Stroke Registers. Population controls were matched on age and sex. Modeled outdoor annual mean NO(x) concentrations were used as proxy for long-term exposure to air pollution. Heterogeneity across NO(x) categories was tested for smoking, hypertension, diabetes mellitus, atrial fibrillation and physical inactivity. Data were analyzed as case-control data and to some extent as case-only data, with logistic regression analysis., Results: The case-control odds ratios for ischemic stroke in association with diabetes were 1.3 [95% confidence interval (CI): 1.1-1.6] and 2.0 (95% CI: 1.2-3.4) in the lowest and highest NO(x) category, respectively (p value for testing heterogeneity across the categories = 0.056). The case-only approach gave further support for the risk associated with diabetes to increase with NO(x) (p for trend = 0.033). We observed no main effect of mean NO(x) or any conclusive effect modifications between NO(x) and smoking, hypertension, atrial fibrillation or physical inactivity., Conclusions: In a low-level air pollution area, the risk for ischemic stroke associated with diabetes seemed to increase with long-term exposure to air pollution., (Copyright © 2010 S. Karger AG, Basel.)

Previous Icelandic studies reported that single nucleotide polymorphisms (SNPs) in the phosphodiesterase 4D (PDE4D) region and the 5-lipoxygenase activating protein ALOX5AP were associated with ischaemic stroke, whereas other studies reported ambiguous findings. We examined 932 ischaemic stroke patients from a Swedish population-based stroke register, and 396 control subjects. We assessed possible associations between ischaemic stroke and nine preselected SNPs in the chromosome regions of the PDE4D gene, including rs12188950 (SNP45) and rs3887175 (SNP39); the ALOX5AP gene, including rs17222814 (SG13S25) and the promoter region of the MHC class II transactivator, MHC2TA. The T allele of SNP45 showed negative association with ischaemic stroke (odds ratio, OR=0.72; 95% confidence interval (CI): 0.58-0.91; P=0.0055). Among hypertensive subjects, this influence of the T allele of SNP45, and the T allele of SNP39, were more pronounced (with OR=0.52; 95% CI: 0.37-0.73; P=0.0001 and OR=0.57; 95% CI: 0.41-0.79; P=0.0007, respectively). These SNPs also interacted with hypertension with a relative excess risk due to interaction of -1.66 (P=0.0002) for SNP45 and -1.65 (P=0.0005) for SNP39. The P-values remained significant after correction for multiple testing. Among nonhypertensives, the A allele of SG13S25 indicated increased stroke risk (OR=1.82; 95% CI: 1.21-2.74; P=0.0039; not significant after Bonferroni correction). SNP45 was associated with ischaemic stroke even when controlling for hypertension, diabetes, heart disease and smoking. Our meta-analysis of 13 studies (including ours) showed no overall influence of SNP45 on ischaemic stroke. However, the 13 studies may differ because of nonrandom causes, as suggested by the heterogeneity test (P=0.042). This might support previously undetected mechanisms causing fluctuating ischaemic stroke risk.