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AbstractPurpose: There is evidence that blood pressure variability (BPV) is associated with cerebral small vessel disease (SVD) and may therefore increase the risk of stroke and dementia. It remains unclear if BPV is associated with SVD progression over years. We examined whether visit-to-visit BPV is associated with white matter hyperintensity (WMH) progression over 14 years and MRI markers after 14 years.Materials and methods: We included participants with SVD from the Radboud University Nijmegen Diffusion tensor Magnetic resonance-imaging Cohort (RUNDMC) who underwent baseline assessment in 2006 and follow-up in 2011, 2015 and 2020. BPV was calculated as coefficient of variation (CV) of BP at all visits. Association between WMH progression rates over 14 years and BPV was examined using linear-mixed effects (LME) model. Regression models were used to examine association between BPV and MRI markers at final visit in participants.Results: A total of 199 participants (60.5 SD 6.6 years) who underwent four MRI scans and BP measurements were included, with mean follow-up of 13.7 (SD 0.5) years. Systolic BPV was associated with higher progression of WMH (β = 0.013, 95% CI 0.005 − 0.022) and higher risk of incident lacunes (OR: 1.10, 95% CI 1.01–1.21). There was no association between systolic BPV and grey and white matter volumes, Peak Skeleton of Mean Diffusivity (PSMD) or microbleed count after 13.7 years.Conclusions: Visit-to-visit systolic BPV is associated with increased progression of WMH volumes and higher risk of incident lacunes over 14 years in participants with SVD. Future studies are needed to examine causality of this association.

ObjectivesSARS-CoV-2 infection is associated with a decline in functional outcomes; many patients experience persistent symptoms, while the underlying pathophysiology remains unclear. This study investigated white matter (WM) integrity on brain MRI in hospitalized COVID-19 patients and its associations with clinical outcomes, including long COVID.Materials and methodsWe included hospitalized COVID-19 patients and controls from CORONavirus and Ischemic Stroke (CORONIS), an observational cohort study, who underwent MRI-DWI imaging at baseline shortly after discharge (

Abstract White matter hyperintensities (WMH) are the most prevalent markers of cerebral small vessel disease (SVD), which is the major vascular risk factor for dementia. Microvascular pathology and neuroinflammation are suggested to drive the transition from normal-appearing white matter (NAWM) to WMH, particularly in individuals with hypertension. However, current imaging techniques cannot capture ongoing NAWM changes. The transition from NAWM into WMH is a continuous process, yet white matter lesions are often examined dichotomously, which may explain their underlying heterogeneity. Therefore, we examined microvascular and neurovascular inflammation pathology in NAWM and severe WMH three-dimensionally, along with gradual magnetic resonance imaging (MRI) fluid-attenuated inversion recovery (FLAIR) signal (sub-)segmentation. In WMH, the vascular network exhibited reduced length and complexity compared to NAWM. Neuroinflammation was more severe in WMH. Vascular inflammation was more pronounced in NAWM, suggesting its potential significance in converting NAWM into WMH. Moreover, the (sub-)segmentation of FLAIR signal displayed varying degrees of vascular pathology, particularly within WMH regions. These findings highlight the intricate interplay between microvascular pathology and neuroinflammation in the transition from NAWM to WMH. Further examination of neurovascular inflammation across MRI-visible alterations could aid deepening our understanding on WMH conversion, and therewith how to improve the prognosis of SVD.

Introduction The INflammation and Small Vessel Disease (INSVD) study aims to investigate whether peripheral inflammation, immune (dys)regulation and blood–brain barrier (BBB) permeability relate to disease progression in cerebral small vessel disease (SVD). This research aims to pinpoint specific components of the immune response in SVD relating to disease progression. This could identify biomarkers of SVD progression, as well as potential therapeutic targets to inform the development and repurposing of drugs to reduce or prevent SVD, cognitive decline and vascular dementia.Methods and analysis INSVD is a prospective observational multicentre cohort study in individuals with symptomatic SVD. This longitudinal study combines comprehensive immunophenotyping of the peripheral blood immune compartment with advanced neuroimaging markers of SVD and BBB permeability. The main SVD marker of interest is white matter microstructure as determined by diffusion tensor imaging, a valuable marker of disease progression owing to its sensitivity to early alterations to white matter integrity. The research is being conducted in two sites—in the UK (Cambridge) and the Netherlands (Nijmegen)—with each site recruiting 100 participants (total n=200). Participants undergo clinical and cognitive assessments, blood draws, and brain MRI at baseline and 2-year follow-up.Ethics and dissemination This study received ethical approval from the local ethics boards (UK: East of England—Cambridge Central Research Ethics Committee (REC) ref: 22/EE/00141, Integrated Research Application System (IRAS) ID: 312 747. Netherlands: Medical Research Ethics Committee (MREC) Oost-Nederland, ref: 2022-13623, NL-number: NL80258.091.22). Written informed consent was obtained from all subjects before the study. Any participant-derived benefits resulting from this research, such as new insights into disease mechanisms or possible novel therapies, will be disseminated to study participants, patient groups and members of the public.Trial registration number NCT05746221.

Background: Previous research revealed differences in cerebellar white matter integrity by disease stages, indicating a compensatory role in Parkinson’s disease (PD). However, the temporal evolution of cerebellar white matter microstructure in patients with PD (PwPD) remains unclear. Objective: To unravel temporal evolution of cerebellar white matter and its dopaminergic correlates in PD. Methods: We recruited 124 PwPD from the PPMI study. The participants were divided into two subsets: Subset 1 (n = 41) had three MRI scans (baseline, 2 years, and 4 years), and Subset 2 (n = 106) had at least two MRI scans at baseline, 1 year, and/or 2 years. Free water-corrected diffusion metrics were used to measure the microstructural integrity in cerebellar peduncles (CP), the main white matter tracts connecting to and from the cerebellum. The ACAPULCO processing pipeline was used to assess cerebellar lobules volumes. Linear mixed-effect models were used to study longitudinal changes. We also examined the relationships between microstructural integrity in CP, striatal dopamine transporter specific binding ratio (SBR), and clinical symptoms. Results: Microstructural changes in CP showed a non-linear pattern in PwPD. Free water-corrected fractional anisotropy (FAt) increased in the first two years but declined from 2 to 4 years, while free water-corrected mean diffusivity exhibited the opposite trend. The initial increased FAt in CP correlated with cerebellar regional volume atrophy, striatal dopaminergic SBR decline, and worsening clinical symptoms, but this correlation varied across disease stages. Conclusions: Our findings suggest a non-linear evolution of microstructural integrity in CP throughout the course of PD, indicating the adaptive structural reorganization of the cerebellum simultaneously with progressive striatal dopaminergic degeneration in PD.

Introduction: Cerebral small vessel disease (SVD) contributes to 45% of dementia cases worldwide. Only a minority of SVD patients develop dementia, yet we lack a reliable model for predicting incident dementia in SVD. Most attempts to date have relied on traditional statistical approaches, whereas machine learning (ML) methods are increasingly used for clinical prediction in other settings. Methods: We investigated whether ML methods improved prediction of incident dementia in SVD over traditional statistical. We included three cohorts with varying SVD severity (RUN DMC, n=503; SCANS, n=121; HARMONISATION, n=265). Baseline demographics, vascular risk factors, cognitive scores, and MRI features of SVD were used for prediction. We conducted both survival analysis and classification analysis predicting 3-year dementia risk. For each analysis, several ML methods were evaluated against standard Cox or logistic regression. Finally, we compared the feature importance ranking by different models. Results: We included 789 participants without missing data in the survival analysis, among whom 108 (13.7%) developed dementia during a median (IQR) follow-up period of 5.4 (4.1, 8.7) years. After excluding those censored before three years, we included 750 participants in the classification analysis, among whom 48 (6.4%) developed dementia by year 3. Comparing statistical and ML models, only the regularised Cox/logistic regression models outperformed their statistical counterparts overall, but not significantly so in survival analysis. Baseline cognitive scores were highly predictive, and all methods ranked global cognition as the most important feature. Discussion: ML survival or classification models brought little improvement over traditional statistical approaches in predicting incident dementia in SVD. ML approaches may be better suited to prediction problems using a larger number of input variables.

Introduction: The major vascular cause of dementia is cerebral small vessel disease (SVD). The diagnosis of SVD relies on MRI findings, including white matter hyperintensities (WMH) amongst others. Chronic hypertension and neuroinflammation are recognized as important risk factors for SVD and for the conversion of normal-appearing white matter (NAWM) into WMH. Unfortunately, most studies investigating the role of neuroinflammation in WMH relied on peripheral blood markers as a proxy for inflammation in the brain itself. Whether such markers accurately capture inflammatory changes within the cerebral white matter remains unknown. Therefore, we aimed to comprehensively investigate the impact of hypertension on perivascular- and neuroinflammation in both WMH and NAWM. Methods: We conducted high-field (7 Tesla) MRI on human post-mortem brains (n=22) of elderly people with chronic hypertension (n = 17) and age-matched controls (n=5) to assess SVD burden, focusing on the analysis of WMH by Fazekas score severity and volumetry. After careful evaluation, brain axial biopsies were taken, from which paraffin sections were cut and (immuno-histochemistry (IHC)) performed to examine neuroinflammation mediated by both microglia and astroglia, and perivascular inflammation. To accurately co-register our MRI findings to IHC data, we developed a custom written MATLAB script to compare changes in WMH on MRI to microscopical changes in IHC. Results: WMH were characterized by more activated microglia and astrogliosis compared to surrounding NAWM. Notably, hypertension was associated with a larger (perivascular) inflammatory response in both WMH and NAWM, suggesting that neuroinflammation plays a crucial role in the pathogenesis of WMH in individuals with hypertension. Discussion: Our results indicate that neuro(vascular)inflammation at the level of the brain itself is involved in the etiology of WMH. Future therapeutic strategies focusing on multitarget interventions including antihypertensive treatment as well as treatment against neuroinflammation may ameliorate WMH progression.

Background: High blood pressure variability (BPV) may be a risk factor for stroke and dementia in patients with ischemic stroke, but the underlying mechanism is unknown. We aimed to investigate whether high BPV is associated with presence and progression of white matter hyperintensities (WMH). Methods: We performed a post-hoc analysis on the MRI substudy of the PRoFESS trial, including 771 patients with ischemic stroke who underwent MRI at baseline and after a median of 2.1 years. WMH were rated with a semi-quantitative scale. Visit-to-visit BPV was expressed as the coefficient of variation (interval 3–6 months, median number of visits 7). The association of BPV with WMH burden and progression was assessed with linear and logistic regression analyses adjusted for confounders. Results: BPV was associated with burden of periventricular WMH (β 0.36 95%CI 0.19–0.53, per one SD increase in BPV) and subcortical (log-transformed) WMH (β 0.25, 95%CI 0.08–0.42). BPV was not associated with periventricular (OR 1.09, 95%CI 0.94–1.27) and subcortical WMH progression (OR 1.15, 95%CI 0.99–1.35). Associations were independent of mean BP. Conclusion: High visit-to-visit BPV was associated with both subcortical and periventricular WMH burden in patients with ischemic stroke, but not with WMH progression in this study.

Abstract The major vascular cause of dementia is cerebral small vessel disease (SVD), including white matter hyperintensities (WMH) amongst others. While the underlying pathology of SVD remains unclear, chronic hypertension and neuroinflammation are recognized as important risk factors for SVD and for the conversion of normal-appearing white matter (NAWM) to WMH. Unfortunately, most studies investigating the role of neuroinflammation in WMH relied on peripheral blood markers, e.g., markers for systemic or vascular inflammation, as a proxy for inflammation in the brain itself. However, it is unknown whether such markers accurately capture inflammatory changes within the cerebral white matter. Therefore, we aimed to comprehensively investigate the impact of hypertension on perivascular- and neuroinflammation in both WMH and NAWM. We conducted high field brain magnetic resonance imaging (MRI), followed by (immuno-)histopathological staining of neuroinflammatory markers on human post-mortem brains of elderly people with a history of hypertension (n = 17) and age-matched normotensive individuals (n = 5). MRI images were co-registered to (immuno-)histopathological data including stainings for microglia and astroglia to assess changes in MRI-based WMH at microscopic resolution. Perivascular inflammation was carefully assessed based on the severity of perivascular astrogliosis of the smallest vessels throughout white matter regions. Hypertension was associated with a larger inflammatory response in both WMH and NAWM. Notably, the presence of close-range perivascular inflammation was twice as common among those with hypertension than in controls both in WMH and NAWM, suggesting that neurovascular inflammation is critical in the etiology of WMH. Moreover, a higher degree of microglial activation was related to a higher burden of WMH. Our results indicate that neuro(vascular)inflammation at the level of the brain itself is involved in the etiology of WMH. Future therapeutic strategies focusing on multitarget interventions including antihypertensive treatment as well as neuroinflammation may ameliorate WMH progression.

Abstract Introduction We investigated the impact of the Corona Virus Disease 2019 (COVID-19) pandemic and the resulting lockdown on reperfusion treatments and door-to-treatment times during the first surge in Dutch comprehensive stroke centers. Furthermore, we studied the association between COVID-19-status and treatment times. Methods We included all patients receiving reperfusion treatment in 17 Dutch stroke centers from May 11th, 2017, until May 11th, 2020. We collected baseline characteristics, National Institutes of Health Stroke Scale (NIHSS) at admission, onset-to-door time (ODT), door-to-needle time (DNT), door-to-groin time (DGT) and COVID-19-status at admission. Parameters during the lockdown (March 15th, 2020 until May 11th, 2020) were compared with those in the same period in 2019, and between groups stratified by COVID-19-status. We used nationwide data and extrapolated our findings to the increasing trend of EVT numbers since May 2017. Results A decline of 14% was seen in reperfusion treatments during lockdown, with a decline in both IVT and EVT delivery. DGT increased by 12 min (50 to 62 min, p-value of

Background: Cerebral small vessel disease (SVD) contributes to 45% of dementia cases worldwide, yet we lack a reliable model for predicting dementia in SVD. Past attempts largely relied on traditional statistical approaches. Here, we investigated whether machine learning (ML) methods improved prediction of incident dementia in SVD from baseline SVD-related features over traditional statistical methods. Methods: We included three cohorts with varying SVD severity (RUN DMC, n = 503; SCANS, n = 121; HARMONISATION, n = 265). Baseline demographics, vascular risk factors, cognitive scores, and magnetic resonance imaging (MRI) features of SVD were used for prediction. We conducted both survival analysis and classification analysis predicting 3-year dementia risk. For each analysis, several ML methods were evaluated against standard Cox or logistic regression. Finally, we compared the feature importance ranked by different models. Results: We included 789 participants without missing data in the survival analysis, amongst whom 108 (13.7%) developed dementia during a median follow-up of 5.4 years. Excluding those censored before three years, we included 750 participants in the classification analysis, amongst whom 48 (6.4%) developed dementia by year 3. Comparing statistical and ML models, only regularised Cox/logistic regression outperformed their statistical counterparts overall, but not significantly so in survival analysis. Baseline cognition was highly predictive, and global cognition was the most important feature. Conclusions: When using baseline SVD-related features to predict dementia in SVD, the ML survival or classification models we evaluated brought little improvement over traditional statistical approaches. The benefits of ML should be evaluated with caution, especially given limited sample size and features.

Background: Cerebral small vessel disease is a leading cause of cognitive decline and vascular dementia. Small vessel disease pathology changes structural brain networks, but its impact on functional networks remains poorly understood. Structural and functional networks are closely coupled in healthy individuals, and decoupling is associated with clinical symptoms in other neurological conditions. We tested the hypothesis that structural–functional network coupling is related to neurocognitive outcomes in 262 small vessel disease patients. Methods: Participants underwent multimodal magnetic resonance imaging and cognitive assessment in 2011 and 2015. Structural connectivity networks were reconstructed using probabilistic diffusion tractography, while functional connectivity networks were estimated from resting-state functional magnetic resonance imaging. Structural and functional networks were then correlated to calculate a measure of structural–functional network coupling for each participant. Results: Lower whole-brain coupling was associated with reduced processing speed and greater apathy both cross-sectionally and longitudinally. In addition, coupling within the cognitive control network was associated with all cognitive outcomes, suggesting that neurocognitive outcomes in small vessel disease may be related to the functioning of this intrinsic connectivity network. Conclusions: Our work demonstrates the influence of structural–functional connectivity network decoupling in small vessel disease symptomatology. Cognitive control network function may be investigated in future studies.

Background: Similar to remote ischemic preconditioning bouts of exercise may possess immediate protective effects against ischemia-reperfusion injury. However, underlying mechanisms are largely unknown. This study compared the impact of single and repeated handgrip exercise versus remote ischemic preconditioning on inflammatory biomarkers in patients with cerebral small vessel disease (cSVD).Methods: In this crossover study, 14 patients with cSVD were included. All participants performed 4-day of handgrip exercise (4x5-minutes at 30% of maximal handgrip strength) and remote ischemic preconditioning (rIPC; 4x5-minutes cuff occlusion around the upper arm) twice daily. Patients were randomized to start with either handgrip exercise or rIPC and the two interventions were separated by > 9 days. Venous blood was drawn before and after one intervention, and after 4-day of repeated exposure. We performed a targeted proteomics on inflammation markers in all blood samples.Results: Targeted proteomics revealed significant changes in 9 out of 92 inflammatory proteins, with four proteins demonstrating comparable time-dependent effects between handgrip and rIPC. After adjustment for multiple testing we found significant decreases in FMS-related tyrosine kinase-3 ligand (Flt3L; 16.2% reduction; adjusted p-value: 0.029) and fibroblast growth factor-21 (FGF-21; 32.8% reduction adjusted p-value: 0.029) after single exposure. This effect did not differ between handgrip and rIPC. The decline in Flt3L after repeated handgrip and rIPC remained significant (adjusted p-value = 0.029), with no difference between rIPC and handgrip (adjusted p-value = 0.98).Conclusion: Single handgrip exercise and rIPC immediately attenuated plasma Flt3L and FGF-21, with the reduction of Flt3L remaining present after 4-day of repeated intervention, in people with cSVD. This suggests that single and repeated handgrip exercise and rIPC decrease comparable inflammatory biomarkers, which suggests activation of shared (anti-)inflammatory pathways following both stimuli. Additional studies will be needed to exclude the possibility that this activation is merely a time effect.

The current study aimed to investigate whether diffusion-weighted imaging-positive (DWI+) lesions after acute intracerebral hemorrhage (ICH) are associated with underlying small vessel disease (SVD) or linked to the acute ICH. We included patients ≥18 years with spontaneous ICH confirmed on neuroimaging and performed 3T MRIs after a median of 11 days (interquartile range [IQR] 6–43). DWI+ lesions were assessed in relation to the hematoma (perihematomal vs. distant and ipsilateral vs. contralateral). Differences in clinical characteristics, ICH characteristics, and MRI markers of SVD between participants with or without DWI+ lesions were investigated using non-parametric tests. We observed 54 DWI+ lesions in 30 (22%) of the 138 patients (median age [IQR] 65 [55–73] years; 71% men, 59 lobar ICH) with available DWI images. We found DWI+ lesions ipsilateral (54%) and contralateral (46%) to the ICH, and 5 (9%) DWI+ lesions were located in the immediate perihematomal region. DWI+ lesion presence was associated with probable CAA diagnosis (38 vs. 15%, p = 0.01) and larger ICH volumes (37 [8–47] vs. 12 [6–24] ml, p = 0.01), but not with imaging features of SVD. Our findings suggest that DWI+ lesions after ICH are a feature of both the underlying SVD and ICH-related mechanisms.

IntroductionPost-stroke fatigue is frequently present in young adults, but its underlying mechanism is still unclear. The aim of the study was to investigate the association between lesion location, network efficiency and chronic post-stroke fatigue based on voxel-based lesion-symptom mapping and structural network connectivity analysis.Patients and MethodsOne hundred and thirty five young patients, aged 18–50 years, with a first-ever transient ischemic attack or cerebral infarction from the Follow-Up of Transient ischemic attack and stroke patients and Unelucidated Risk factor Evaluation (FUTURE) study, underwent 1.5T MRI and were assessed for fatigue using the self-report Checklist Individual Strength. Stroke lesions were manually segmented, and structural network efficiency was calculated using the diffusion MRI-based brain networks and graph theory for each patient. Univariate and multivariate analyses was performed to study the associations between MRI parameters and chronic post-stroke fatigue. In addition, we used voxel-based lesion-symptom mapping to analyze the relationship between the lesion location and chronic post-stroke fatigue.ResultsMean age at index event was 39.0 years (SD ± 8.2), and mean follow-up duration was 11.0 years (SD ± 8.0). 50 patients (37%) had post-stroke fatigue. Voxel-based lesion-symptom mapping showed no significant relation between stroke lesions and the presence of chronic post-stroke fatigue. Furthermore, there were no significant associations between the lesion size or network efficiency, and the presence of chronic post-stroke fatigue.DiscussionWe did not find any association between stroke characteristics (lesion location and size) and chronic post-stroke fatigue (CIS20-R), nor associations between structural brain network connectivity and post-stroke fatigue on the long term in young stroke patients.

Background and Purpose Serum neurofilament light (NfL)-chain is a circulating marker for neuroaxonal injury and is also associated with severity of cerebral small vessel disease (SVD) cross-sectionally. Here we explored the association of serum-NfL with imaging and cognitive measures in SVD longitudinally. Methods From 503 subjects with SVD, baseline and follow-up magnetic resonance imaging (MRI) was available for 264 participants (follow-up 8.7±0.2 years). Baseline serum-NfL was measured by an ultrasensitive single-molecule-assay. SVD-MRI-markers including white matter hyperintensity (WMH)-volume, mean diffusivity (MD), lacunes, and microbleeds were assessed at both timepoints. Cognitive testing was performed in 336 participants, including SVD-related domains as well as global cognition and memory. Associations with NfL were assessed using linear regression analyses and analysis of covariance (ANCOVA). Results Serum-NfL was associated with baseline WMH-volume, MD-values and presence of lacunes and microbleeds. SVD-related MRI- and cognitive measures showed progression during follow-up. NfL-levels were associated with future MRI-markers of SVD, including WMH, MD and lacunes. For the latter, this association was independent of baseline lacunes. Furthermore, NfL was associated with incident lacunes during follow-up (P=0.040). NfL-levels were associated with future SVD-related cognitive impairment (processing speed: β=–0.159; 95% confidence interval [CI], –0.242 to –0.068; P=0.001; executive function β=–0.095; 95% CI, –0.170 to –0.007; P=0.033), adjusted for age, sex, education, and depression. Dementia-risk increased with higher NfL-levels (hazard ratio, 5.0; 95% CI, 2.6 to 9.4; P

Background: DTI is sensitive to white matter (WM) microstructural damage and has been suggested as a surrogate marker for phase 2 clinical trials in cerebral small vessel disease (SVD). The study’s objective is to establish the best way to analyse the diffusion-weighted imaging data in SVD for this purpose. The ideal method would be sensitive to change and predict dementia conversion, but also straightforward to implement and ideally automated. As part of the OPTIMAL collaboration, we evaluated five different DTI analysis strategies across six different cohorts with differing SVD severity. Methods: Those 5 strategies were: (1) conventional mean diffusivity WM histogram measure (MD median), (2) a principal component-derived measure based on conventional WM histogram measures (PC1), (3) peak width skeletonized mean diffusivity (PSMD), (4) diffusion tensor image segmentation θ (DSEG θ) and (5) a WM measure of global network efficiency (Geff). The association between each measure and cognitive function was tested using a linear regression model adjusted by clinical markers. Changes in the imaging measures over time were determined. In three cohort studies, repeated imaging data together with data on incident dementia were available. The association between the baseline measure, change measure and incident dementia conversion was examined using Cox proportional-hazard regression or logistic regression models. Sample size estimates for a hypothetical clinical trial were furthermore computed for each DTI analysis strategy. Results: There was a consistent cross-sectional association between the imaging measures and impaired cognitive function across all cohorts. All baseline measures predicted dementia conversion in severe SVD. In mild SVD, PC1, PSMD and Geff predicted dementia conversion. In MCI, all markers except Geff predicted dementia conversion. Baseline DTI was significantly different in patients converting to vascular dementia than to Alzheimer’ s disease. Significant change in all measures was associated with dementia conversion in severe but not in mild SVD. The automatic and semi-automatic measures PSMD and DSEG θ required the lowest minimum sample sizes for a hypothetical clinical trial in single-centre sporadic SVD cohorts. Conclusion: DTI parameters obtained from all analysis methods predicted dementia, and there was no clear winner amongst the different analysis strategies. The fully automated analysis provided by PSMD offers advantages particularly for large datasets.

Abstract Background Patient-Reported Outcome Measures (PROMs) have been proposed for benchmarking health care quality across hospitals, which requires extensive case-mix adjustment. The current study’s aim was to develop and compare case-mix models for mortality, a functional outcome, and a patient-reported outcome measure (PROM) in ischemic stroke care. Methods Data from ischemic stroke patients, admitted to four stroke centers in the Netherlands between 2014 and 2016 with available outcome information (N = 1022), was analyzed. Case-mix adjustment models were developed for mortality, modified Rankin Scale (mRS) scores and EQ-5D index scores with respectively binary logistic, proportional odds and linear regression models with stepwise backward selection. Predictive ability of these models was determined with R-squared (R2) and area-under-the-receiver-operating-characteristic-curve (AUC) statistics. Results Age, NIHSS score on admission, and heart failure were the only common predictors across all three case-mix adjustment models. Specific predictors for the EQ-5D index score were sex (β = 0.041), socio-economic status (β = − 0.019) and nationality (β = − 0.074). R2-values for the regression models for mortality (5 predictors), mRS score (9 predictors) and EQ-5D utility score (12 predictors), were respectively R2 = 0.44, R2 = 0.42 and R2 = 0.37. Conclusions The set of case-mix adjustment variables for the EQ-5D at three months differed considerably from the set for clinical outcomes in stroke care. The case-mix adjustment variables that were specific to this PROM were sex, socio-economic status and nationality. These variables should be considered in future attempts to risk-adjust for PROMs during benchmarking of hospitals.

Abstract Background Intravenous thrombolysis (IVT) plays a prominent role in the treatment of acute ischemic stroke (AIS). The sooner IVT is administered, the higher the odds of a good outcome. Therefore, registering the in-hospital time to treatment with IVT, i.e. the door-to-needle time (DNT), is a powerful way to measure quality improvement. The aim of this study was to identify determinants that are associated with extended DNT. Methods Patients receiving IVT in 2015 and 2016 registered in the Dutch Acute Stroke Audit were included. DNT and onset-to-door time (ODT) were dichotomized using the median (i.e. extended DNT) and the 90th percentile (i.e. severely extended DNT). Logistic regression was performed to identify determinants associated with (severely) extended DNT/ODT and its effect on in-hospital mortality. A linear model with natural spline was used to investigate the association between ODT and DNT. Results Included were 9518 IVT treated patients from 75 hospitals. Median DNT was 26 min (IQR 20–37). Determinants associated with a higher likelihood of extended DNT were female sex (OR 1.17, 95% CI 1.05–1.31) and admission during off-hours (OR 1.12, 95% CI 1.01–1.25). Short ODT correlated with longer DNT, whereas longer ODT correlated with shorter DNT. Young age (OR 1.38, 95% CI 1.07–1.76) and admission to a comprehensive stroke center (OR 1.26, 1.10–1.45) were associated with severely extended DNT, which was associated with in-hospital mortality (OR 1.54, 95%CI 1.19–1.98). Conclusions Even though DNT in the Netherlands is short compared to other countries, lowering the DNT may be achievable by focusing on specific subgroups.

Abstract Background Some studies have suggested that transdermal administration of glyceryl trinitrate (GTN; nitroglycerin) in the first few hours after symptom onset increases the chance of a favourable outcome after ischaemic stroke or intracerebral haemorrhage, possibly through an increase in intracranial collateral blood flow and a reduction in blood pressure. The Multicentre Randomised trial of Acute Stroke treatment in the Ambulance with a nitroglycerin Patch (MR ASAP) aims to assess the effect of transdermal GTN, started within 3 h after stroke onset in the prehospital setting, on functional outcome at 90 days in patients with acute ischaemic stroke or intracerebral haemorrhage. Methods MR ASAP is a phase III, multicentre, randomised, open-label clinical trial with a blinded outcome assessment. A total of 1400 adult patients with suspected stroke and a systolic blood pressure ≥ 140 mmHg will be randomised to transdermal GTN (5 mg/day), administered as a transdermal patch by paramedics in the prehospital setting within 3 h of stroke onset and continued for 24 h or to standard care. The primary outcome is the score on the modified Rankin Scale (mRS) at 90 days, analysed with ordinal logistic regression. Secondary outcomes include blood pressure and collateral circulation at hospital admission, neurological deficit measured with the National Institutes of Health Stroke Scale at 24 h, and mortality and poor outcome (mRS score 3 to 6) at 90 days. This trial will be conducted in the Netherlands and will use a deferred consent procedure. The trial is part of the Collaboration for New Treatments of Acute Stroke (CONTRAST) programme. Discussion MR ASAP will assess whether very early administration of GTN improves outcome after stroke in a setting where rates of intravenous thrombolysis and endovascular treatment for acute ischaemic stroke are high. The deferred consent procedure facilitates prompt GTN treatment and will prevent delay to revascularisation therapies. If early transdermal GTN treatment proves to be effective, this low-cost treatment can be readily implemented into daily clinical practice. Trial registration ISRCTN Registry, ISRCTN99503308. Registered on 2 January 2018.

Abstract Background Remote ischemic postconditioning (rIPostC) refers to the observation that repeated, short periods of ischemia protect remote areas against tissue damage during and after prolonged ischemia. Based on previous observations of a potential neuroprotective effect of rIPostC, the aim of this study is to evaluate whether repeated rIPostC after an ischemic stroke can reduce infarct size, which could be translated to an improvement in clinical outcomes. Methods/design We will enroll 200 ischemic stroke patients to daily rIPostC or sham conditioning during hospitalization into a randomized single-blind placebo-controlled trial. The intervention consists of twice daily exposure to four cycles of 5-min cuff inflation around the upper arm to > 20 mmHg above systolic blood pressure (i.e., rIPostC) or 50 mmHg (i.e., control), followed by 5 minutes of deflation. The primary outcome is infarct size, measured using an MRI diffusion-weighted image at the end of hospitalization. Secondary outcomes include the Modified Rankin Scale, National Institutes of Health Stroke Scale, quality of life, and cardiovascular and cerebrovascular morbidity and mortality. To explore possible underlying mechanisms of rIPostC, venous blood will be sampled to assess biomarkers of inflammation and vascular health. Discussion Previous studies in animals and humans, using a single bout of remote ischemic conditioning, report a potential effect of rIPostC in attenuating neural damage. Although repeated rIPostC has been investigated for cardiovascular disease patients and preclinical stroke models, no previous study has explored the potential physiological and clinical effects of repeatedly applying rIPostC during the hospitalization phase after a stroke. Trial registration Netherlands Trial Register, NTR6880. Registered on 8 December 2017.

Background: The etiology of cerebral small vessel disease (SVD) remains elusive, though evidence is accumulating that inflammation contributes to its pathophysiology. We recently showed retrospectively that pro-inflammatory monocytes are associated with the long-term progression of white matter hyperintensities (WMHs). In this prospective high-frequency imaging study, we hypothesize that the incidence of SVD progression coincides with a pro-inflammatory monocyte phenotype.Methods: Individuals with SVD underwent monthly magnetic resonance imaging (MRI) for 10 consecutive months to detect SVD progression, defined as acute diffusion-weighted imaging-positive (DWI+) lesions, incident microbleeds, incident lacunes, and WMH progression. Circulating inflammatory markers were measured, cytokine production capacity of monocytes was assessed after ex vivo stimulation, and RNA sequencing was performed on isolated monocytes in a subset of participants.Results: 13 out of 35 individuals developed SVD progression (70 ± 6 years, 54% men) based on incident lesions (n = 7) and/or upper quartile WMH progression (n = 9). Circulating E-selectin concentration (p < 0.05) and the cytokine production capacity of interleukin (IL)-1β and IL-6 (p < 0.01) were higher in individuals with SVD progression. Moreover, RNA sequencing revealed a pro-inflammatory monocyte signature including genes involved in myelination, blood–brain barrier, and endothelial–leukocyte interaction.Conclusions: Circulating monocytes of individuals with progressive SVD have an inflammatory phenotype, characterized by an increased cytokine production capacity and a pro-inflammatory transcriptional signature.

Cerebral small vessel disease (SVD), including white matter hyperintensities (WMH), microbleeds, lacunes, was related to gait disturbances, while the underlying mechanism is unclear. Here, we investigated the relation between structural network efficiency, cognition and gait performance in 272 elderly subjects with SVD. All participants underwent 1.5 T MRI, gait and neuropsychological assessment. Conventional MRI markers for SVD, i.e. WMH volume, number of lacunes and microbleeds, were assessed. Diffusion tensor imaging-based tractography was used to reconstruct the brain network for each individual, followed by graph-theoretical analyses to compute the well-established network measure, global efficiency. We found that lower global efficiency was associated with worse gait performance, including slower gait speed and shorter stride length, independent of conventional MRI markers for SVD. This association was partly mediated via cognitive function. We identified subnetworks of white matter connections associated with gait and cognition, characterized by dominant involvement of frontal tracts. Our findings suggest that network disruption is associated with gait disturbances through cognitive dysfunction in elderly with SVD. Gait is a highly cognitive process and the crucial role of cognition should be considered when investigating gait disturbances in the elderly with SVD.

Introduction: Cerebral hypoperfusion is thought to play an important role in the etiology of cerebral small vessel disease (SVD). Orthostatic hypotension (OH) is assumed to be a cause of cerebral hypoperfusion by causing recurrent hypoperfusion episodes, and might thus be related to progression of SVD. Here, we investigated whether presence of OH is associated with the progression of SVD MRI-markers and cognitive decline over a time period of 9 years in a cohort of sporadic SVD patients. Methods: This study included SVD patients from the RUN DMC study, a prospective longitudinal single-center cohort study. In total, 503 patients were included at baseline (2006), from whom 351 participated at first follow-up (2011), and 293 at second follow-up (2015). During all visits, patients underwent MRI and cognitive testing. Association between presence of OH at baseline and progression of SVD-markers on MRI and cognitive decline over time was estimated using linear mixed-effects models. Results: Of the 503 patients who participated at baseline, 46 patients (9.1%) had OH. Cross-sectional analysis of the baseline data showed that OH was associated with higher white matter hyperintensity (WMH) volume (β = 0.18, p = 0.03), higher mean diffusivity (MD; β = 0.02, p = 0.002), and with presence of microbleeds (OR 2.37 95% CI 1.16–4.68). Longitudinally, OH was however not associated with a progression of total WMH volume (β = -0.17, p = 0.96) or with higher MD (β = -0.001, p = 0.49). There was no association between OH and cognitive performance, both at baseline and over time. Conclusion: In this longitudinal observational study, there was no evidence that presence of OH is associated with progression of SVD-markers or cognitive decline over time. Our findings indicate that OH may not be causally related to SVD progression over time

Cerebral small vessel disease (SVD) is a common disease in older adults and a major contributor to vascular cognitive impairment and dementia. White matter network damage is a potentially important mechanism by which SVD causes cognitive impairment. Earlier studies showed that a higher degree of white matter network damage, indicated by lower global efficiency (a graph-theory measure assessing efficiency of network information transfer), was associated with lower scores on cognitive performance independent of MRI markers for SVD. However, it is unknown whether this global efficiency index is the strongest predictor for cognitive impairment, as there is a wide range of network measures. Here, we investigate which network measure is the most informative in explaining baseline cognitive performance and decline over a period of 8.7 years in SVD. We used data from the Radboud University Nijmegen Diffusion tensor and MRI Cohort (RUN DMC), which included 436 participants without dementia (65.2 ± 8.8 years) but with evidence of SVD on neuroimaging. Binarized and weighted structural brain networks were reconstructed using diffusion tensor imaging and deterministic streamlining. Using graph-theory, we calculated 21 global network measures and performed linear regression analyses, elastic net analysis and linear mixed effect models to compare these measures. All analyses were adjusted for potential confounders (age, sex, educational level, depressive symptoms and conventional SVD MRI-markers (e.g. white matter hyperintensities (WMH), lacunes of presumed vascular origin and microbleeds). The elastic net analyses showed that, at baseline, global efficiency had the strongest association with cognitive index (CI), while characteristic path length showed the strongest association with psychomotor speed (PMS) and memory. Binary local efficiency showed the strongest association with attention & executive function (A&EF). In addition, linear mixed-effect models demonstrated that baseline global efficiency predicts decline in CI (χ2(1) = 8.18, p = 0.004),PMS (χ2(1) = 7.75, p = 0.005), memory (χ2(1) = 27.28, p = 0.000) over time and that binary local efficiency predicts decline in A&EF (χ2(1) = 8.66, p = 0.003) over time. Our results suggest that among all network measures, network efficiency measures, i.e. global efficiency and local efficiency, are the strongest predictors for cognitive functions at cross-sectional level and also predict faster cognitive decline in SVD, which is in line with earlier findings. These findings suggests that in our study sample network efficiency measures are the most suitable surrogate markers for cognitive performance in patients with cerebral SVD among all network measures and MRI markers, and play a key role in the genesis of cognitive decline in SVD.

Background and Purpose Neurofilament light chain (NfL) is a blood marker for neuroaxonal damage. We assessed the association between serum NfL and cerebral small vessel disease (SVD), which is highly prevalent in elderly individuals and a major cause of stroke and vascular cognitive impairment. Methods Using a cross-sectional design, we studied 53 and 439 patients with genetically defined SVD (Cerebral Autosomal-Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy [CADASIL]) and sporadic SVD, respectively, as well as 93 healthy controls. Serum NfL was measured by an ultrasensitive single-molecule array assay. We quantified magnetic resonance imaging (MRI) markers of SVD, i.e., white matter hyperintensity volume, lacune volume, brain volume, microbleed count, and mean diffusivity obtained from diffusion tensor imaging. Clinical characterization included neuropsychological testing in both SVD samples. CADASIL patients were further characterized for focal neurological deficits (National Institutes of Health stroke scale [NIHSS]) and disability (modified Rankin scale [mRS]). Results Serum NfL levels were elevated in both SVD samples (P

Abstract The anatomical location of imaging features is of crucial importance for accurate diagnosis in many medical tasks. Convolutional neural networks (CNN) have had huge successes in computer vision, but they lack the natural ability to incorporate the anatomical location in their decision making process, hindering success in some medical image analysis tasks. In this paper, to integrate the anatomical location information into the network, we propose several deep CNN architectures that consider multi-scale patches or take explicit location features while training. We apply and compare the proposed architectures for segmentation of white matter hyperintensities in brain MR images on a large dataset. As a result, we observe that the CNNs that incorporate location information substantially outperform a conventional segmentation method with handcrafted features as well as CNNs that do not integrate location information. On a test set of 50 scans, the best configuration of our networks obtained a Dice score of 0.792, compared to 0.805 for an independent human observer. Performance levels of the machine and the independent human observer were not statistically significantly different (p-value = 0.06).

Lacunes of presumed vascular origin (lacunes) are associated with an increased risk of stroke, gait impairment, and dementia and are a primary imaging feature of the small vessel disease. Quantification of lacunes may be of great importance to elucidate the mechanisms behind neuro-degenerative disorders and is recommended as part of study standards for small vessel disease research. However, due to the different appearance of lacunes in various brain regions and the existence of other similar-looking structures, such as perivascular spaces, manual annotation is a difficult, elaborative and subjective task, which can potentially be greatly improved by reliable and consistent computer-aided detection (CAD) routines. In this paper, we propose an automated two-stage method using deep convolutional neural networks (CNN). We show that this method has good performance and can considerably benefit readers. We first use a fully convolutional neural network to detect initial candidates. In the second step, we employ a 3D CNN as a false positive reduction tool. As the location information is important to the analysis of candidate structures, we further equip the network with contextual information using multi-scale analysis and integration of explicit location features. We trained, validated and tested our networks on a large dataset of 1075 cases obtained from two different studies. Subsequently, we conducted an observer study with four trained observers and compared our method with them using a free-response operating characteristic analysis. Shown on a test set of 111 cases, the resulting CAD system exhibits performance similar to the trained human observers and achieves a sensitivity of 0.974 with 0.13 false positives per slice. A feasibility study also showed that a trained human observer would considerably benefit once aided by the CAD system.

Cerebral small vessel disease (SVD) is considered the most important vascular contributor to the development of cognitive impairment and dementia. There is increasing awareness that SVD exerts its clinical effects by disrupting white matter connections, predominantly disrupting connections between rich club nodes, a set of highly connected and interconnected regions. Here we examined the progression of disturbances in rich club organization in older adults with SVD and their associations with conventional SVD markers and cognitive decline. We additionally investigated associations of baseline network measures with dementia. In 270 participants of the RUN DMC study, we performed diffusion tensor imaging (DTI) and cognitive assessments longitudinally. Rich club organization was examined in structural networks derived from DTI followed by deterministic tractography. Global efficiency (p

Cerebral small vessel disease, including white matter hyperintensities (WMH) and lacunes of presumed vascular origin, is common in elderly people and is related to cognitive impairment and dementia. One possible mechanism could be the disruption of white matter tracts (both within WMH and normal-appearing white matter) that connect distributed brain regions involved in cognitive functions. Here, we investigated the relation between microstructural integrity of the white matter and cognitive functions in patients with small vessel disease. The Radboud University Nijmegen Diffusion tensor and Magnetic resonance Cohort study is a prospective cohort study among 444 independently living, non-demented elderly with cerebral small vessel disease, aged between 5500 and 85 years. All subjects underwent magnetic resonance imaging and diffusion tensor imaging scanning and an extensive neuropsychological assessment. We showed that loss of microstructural integrity of the white matter at specific locations was related to specific cognitive disturbances, which was mainly located in the normal-appearing white matter (p

Introduction. Subjective cognitive impairment (SCI), depressive symptoms, and fatigue are common after stroke and are associated with reduced quality of life. We prospectively investigated their prevalence and course after a transient ischemic attack (TIA) or nonfocal transient neurological attack (TNA) and the association with diffusion-weighted imaging (DWI) lesions. Methods. The Cognitive Failures Questionnaire, Hospital Anxiety and Depression Scale, and Subjective Fatigue subscale from the Checklist Individual Strength were used to assess subjective complaints shortly after TIA or TNA and six months later. With repeated measure analysis, the associations between DWI lesion presence or clinical diagnosis (TIA or TNA) and subjective complaints over time were determined. Results. We included 103 patients (28 DWI positive). At baseline, SCI and fatigue were less severe in DWI positive than in DWI negative patients, whereas at follow-up, there were no differences. SCI (p=0.02) and fatigue (p=0.01) increased in severity only in DWI positive patients. There were no differences between TIA and TNA. Conclusions. Subjective complaints are highly prevalent in TIA and TNA patients. The short-term prognosis is not different between DWI-positive and DWI negative patients, but SCI and fatigue increase in severity within six months after the event when an initial DWI lesion is present.

Memory impairment after stroke is poorly understood as stroke rarely occurs in the hippocampus. Previous studies have observed smaller ipsilateral hippocampal volumes after stroke compared with controls. Possibly, these findings on macroscopic level are not the first occurrence of structural damage and are preceded by microscopic changes that may already be associated with a worse memory function. We therefore examined the relationship between hippocampal integrity, volume, and memory performance long after first-ever ischemic stroke in young adults.We included all consecutive first-ever ischemic stroke patients, without hippocampal strokes or recurrent stroke/TIA, aged 18-50 years, admitted to our academic hospital between 1980 and 2010. One hundred and forty-six patients underwent T1 MPRAGE, DTI scanning and completed the Rey Auditory Verbal Learning Test and were compared with 84 stroke-free controls. After manual correction of hippocampal automatic segmentation, we calculated mean hippocampal fractional anisotropy (FA) and diffusivity (MD).On average 10 years after ischemic stroke, lesion volume was associated with lower ipsilateral hippocampal integrity (p0.05).Patients with average ipsilateral hippocampal volume could already have lower ipsilateral hippocampal integrity, although at present with no attendant worse memory performance compared with patients with high hippocampal integrity. Longitudinal studies are needed to investigate whether a low hippocampal integrity after stroke might lead to exacerbated memory decline with increasing age.

BACKGROUND: Diabetes diagnosed prior to stroke in young adults is strongly associated with recurrent vascular events. The relevance of impaired fasting glucose (IFG) and incidence of diabetes after young stroke is unknown. We investigated the long-term incidence of diabetes after young stroke and evaluated the association of diabetes and impaired fasting glucose with recurrent vascular events. METHODS: This study was part of the FUTURE study. All consecutive patients between January 1, 1980, and November 1, 2010 with TIA or ischemic stroke, aged 18-50, were recruited. A follow-up assessment was performed in survivors between November 1, 2009 and January 1, 2012 and included an evaluation for diabetes, fasting venous plasma glucose and recurrent vascular events. The association of diabetes and IFG with recurrent vascular events was assessed by logistic regression analysis, adjusted for age, sex and follow-up duration. RESULTS: 427 survivors without a medical history of diabetes were included in the present analysis (mean follow-up of 10.1 (SD 8.4) years; age 40.3 (SD 7.9) years). The incidence rate of diabetes was 7.9 per 1000 person-years and the prevalence of IFG was 21.1%. Patients with diabetes and IFG were more likely to have experienced any vascular event than those with normal fasting glucose values (OR 3.5 (95%CI 1.5-8.4) for diabetes and OR 2.5 (95%CI 1.3-4.8) for IFG). CONCLUSIONS: Diabetes or IFG in young stroke survivors is frequent and is associated with recurrent vascular events. Regular screening for IFG and diabetes in this population, yields potential for secondary prevention.

The pathophysiology of episodic memory dysfunction after infarction is not completely understood. It has been suggested that infarctions located anywhere in the brain can induce widespread effects causing disruption of functional networks of the cortical regions. The default mode network, which includes the medial temporal lobe, is a functional network that is associated with episodic memory processing. We investigated whether the default mode network activity is reduced in stroke patients compared to healthy control subjects in the resting state condition. We assessed the whole brain network properties during resting state functional MRI in 21 control subjects and 20 'first-ever' stroke patients. Patients were scanned 9-12 weeks after stroke onset. Stroke lesions were located in various parts of the brain. Independent component analyses were conducted to identify the default mode network and to compare the group differences of the default mode network. Furthermore, region-of-interest based analysis was performed to explore the functional connectivity between the regions of the default mode network. Stroke patients performed significantly worse than control subjects on the delayed recall score on California verbal learning test. We found decreased functional connectivity in the left medial temporal lobe, posterior cingulate and medial prefrontal cortical areas within the default mode network and reduced functional connectivity between these regions in stroke patients compared with controls. There were no significant volumetric differences between the groups. These results demonstrate that connectivity within the default mode network is reduced in 'first-ever' stroke patients compared to control subjects. This phenomenon might explain the occurrence of post-stroke cognitive dysfunction in stroke patients.

BACKGROUND: Little is known about the incidence and risk of seizures after stroke in young adults. Especially in the young seizures might dramatically influence prognosis and quality of life. We therefore investigated the long-term incidence and risk of post-stroke epilepsy in young adults with a transient ischemic attack (TIA), ischemic stroke (IS) or intracerebral hemorrhage (ICH). METHODS AND FINDINGS: We performed a prospective cohort study among 697 consecutive patients with a first-ever TIA, IS or ICH, aged 18-50 years, admitted to our hospital between 1-1-1980 till 1-11-2010. The occurrence of epilepsy was assessed by standardized questionnaires and verified by a neurologist. Cumulative risks were estimated with Kaplan-Meier analysis. Cox proportional hazard models were used to calculate relative risks. After mean follow-up of 9.1 years (SD 8.2), 79 (11.3%) patients developed post-stroke epilepsy and 39 patients (5.6%) developed epilepsy with recurrent seizures. Patients with an initial late seizure more often developed recurrent seizures than patients with an initial early seizure. Cumulative risk of epilepsy was 31%, 16% and 5% for patients with an ICH, IS and TIA respectively (Logrank test ICH and IS versus TIA p

Although the symptoms of a transient ischemic attack (TIA) by definition resolve completely, the subsequent risk of cardiovascular complications is substantial. Urgent diagnosis and start of secondary prevention can reduce these risks. In light of the potential unfavourable prognosis, especially the first days after a TIA, we have developed and implemented a 24/7 TIA-service. Patients can be referred at any time and timing of analysis is determined by means of short-term risk assessment with a validated tool. Within half a day all investigations necessary to diagnose TIA and identify risk factors take place and secondary prevention at all levels is started immediately. This service is realized through integration of workflow of different specialities at multiple levels of care. Although patient service improves, the beneficial effects of a 24/7 TIA-service need to be established before further implementation is started. A preliminary analysis on the effects of continuous TIA-care and suggestions for the development of the necessary process and outcome indicators are provided.

Population-based studies have investigated the relation between β-amyloid levels in cerebrospinal fluid or plasma and white matter lesions (WMLs). However, these circulating levels of β-amyloid in cerebrospinal fluid or plasma may not reliably reflect the actual degree of amyloid present in the brain. Therefore, we investigated the relation between WMLs and β-amyloid plaques and amyloid angiopathy in brain tissue. WML on MRI or CT were rated in 28 nondemented patients whose neuroimaging was available prior to death. β-amyloid in plaques and arterioles were immunohistochemically stained and quantified in postmortem brain necropsies. WMLs were present in 43% of the total population. Both cortex and periventricular region showed no differences for β-amyloid deposition in either plaques or blood vessel walls in patients with WMLs compared to those without WMLs. Thus, our results indicate that there is no relation between the degree of WMLs and β-amyloid deposition in the brain.