Impact of Cerebral Microbleeds in Stroke Patients with Atrial Fibrillation.

OBJECTIVES: Cerebral microbleeds are associated with the risks of ischemic stroke and intracranial hemorrhage, causing clinical dilemmas for antithrombotic treatment decisions. We aimed to evaluate the risks of intracranial hemorrhage and ischemic stroke associated with microbleeds in patients with atrial fibrillation treated with vitamin K antagonists, direct oral anticoagulants, antiplatelets, and combination therapy (i.e. concurrent oral anticoagulant and antiplatelet). METHODS: We included patients with documented atrial fibrillation from the pooled individual patient data analysis by the Microbleeds International Collaborative Network. Risks of subsequent intracranial hemorrhage and ischemic stroke were compared between patients with and without microbleeds, stratified by antithrombotic use. RESULTS: A total of 7,839 patients were included. The presence of microbleeds was associated with an increased relative risk of intracranial hemorrhage (adjusted hazard ratio [aHR] = 2.74, 95% confidence interval = 1.76-4.26) and ischemic stroke (aHR = 1.29, 95% confidence interval = 1.04-1.59). For the entire cohort, the absolute incidence of ischemic stroke was higher than intracranial hemorrhage regardless of microbleed burden. However, for the subgroup of patients taking combination of anticoagulant and antiplatelet therapy, the absolute risk of intracranial hemorrhage exceeded that of ischemic stroke in those with 2 to 4 microbleeds (25 vs 12 per 1,000 patient-years) and ≥ 11 microbleeds (94 vs 48 per 1,000 patient-years). INTERPRETATION: Patients with atrial fibrillation and high burden of microbleeds receiving combination therapy have a tendency of higher rate of intracranial hemorrhage than ischemic stroke, with potential for net harm. Further studies are needed to help optimize stroke preventive strategies in this high-risk group. ANN NEUROL 2023;94:61-74.

Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD.

INTRODUCTION: We compared the machine learning-derived, MRI-based Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) with plasma neurofilament light chain (NfL) level in predicting conversion of early AD among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects. METHODS: We recruited participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had the following data: clinical features (age, gender, education, Montreal Cognitive Assessment [MoCA]), structural MRI, plasma biomarkers (p-tau181 , NfL), cerebrospinal fluid biomarkers (CSF) (Aß42, p-tau181 ), and apolipoprotein E (APOE) ε4 genotype. We defined AD using CSF Aß42 (A+) and p-tau181 (T+). We defined conversion (C+) if a subject progressed to the next syndromal stage within 4 years. RESULTS: Of 589 participants, 96 (16.3%) were A+T+C+. AD-RAI performed better than plasma NfL when added on top of clinical features, plasma p-tau181 , and APOE ε4 genotype (area under the curve [AUC] = 0.832 vs. AUC = 0.650 among CU, AUC = 0.853 vs. AUC = 0.805 among MCI) in predicting A+T+C+. DISCUSSION: AD-RAI outperformed plasma NfL in predicting syndromal conversion of early AD. HIGHLIGHTS: AD-RAI outperformed plasma NfL in predicting syndromal conversion among early AD. AD-RAI showed better metrics than volumetric hippocampal measures in predicting syndromal conversion. Combining clinical features, plasma p-tau181 and apolipoprotein E (APOE) with AD-RAI is the best model for predicting syndromal conversion.

Risk of intracerebral haemorrhage in Chinese patients with atrial fibrillation on warfarin with cerebral microbleeds: the IPAAC-Warfarin study.

BACKGROUND AND PURPOSE: Cerebral microbleeds (CMBs), which predict future intracerebral haemorrhage (ICH), may guide anticoagulant decisions for atrial fibrillation (AF). We aimed to evaluate the risk of warfarin-associated ICH in Chinese patients with AF with CMBs. METHODS: In this prospective, observational, multicentre study, we recruited Chinese patients with AF who were on or intended to start anticoagulation with warfarin from six hospitals in Hong Kong. CMBs were evaluated with 3T MRI brain at baseline. Primary outcome was clinical ICH at 2-year follow-up. Secondary outcomes were ischaemic stroke, systemic embolism, mortality of all causes and modified Rankin Scale ≥3. Outcome events were compared between patients with and without CMBs. RESULTS: A total of 290 patients were recruited; 53 patients were excluded by predefined criteria. Among the 237 patients included in the final analysis, CMBs were observed in 84 (35.4%) patients, and 11 had ≥5 CMBs. The mean follow-up period was 22.4±10.3 months. Compared with patients without CMBs, patients with CMBs had numerically higher rate of ICH (3.6% vs 0.7%, p=0.129). The rate of ICH was lower than ischaemic stroke for patients with 0 to 4 CMBs, but higher for those with ≥5 CMBs. CMB count (C-index 0.82) was more sensitive than HAS-BLED (C-index 0.55) and CHA2DS2-VASc (C-index 0.63) scores in predicting ICH. CONCLUSIONS: In Chinese patients with AF on warfarin, presence of multiple CMBs may be associated with higher rate of ICH than ischaemic stroke. Larger studies through international collaboration are needed to determine the risk:benefit ratio of oral anticoagulants in patients with AF of different ethnic origins.

Mapping the contribution and strategic distribution patterns of neuroimaging features of small vessel disease in poststroke cognitive impairment.

OBJECTIVES: Individual neuroimaging features of small vessel disease (SVD) have been reported to influence poststroke cognition. This study aimed to investigate the joint contribution and strategic distribution patterns of multiple types of SVD imaging features in poststroke cognitive impairment. METHODS: We studied 145 first-ever ischaemic stroke patients with MRI and Montreal Cognitive Assessment (MoCA) examined at baseline. The local burdens of acute ischaemic lesion (AIL), white matter hyperintensity, lacune, enlarged perivascular space and cross-sectional atrophy were quantified and entered into support vector regression (SVR) models to associate with the global and domain scores of MoCA. The SVR models were optimised with feature selection through 10-fold cross-validations. The contribution of SVD features to MoCA scores was measured by the prediction accuracy in the corresponding SVR model after optimisation. RESULTS: The combination of the neuroimaging features of SVD contributed much more to the MoCA deficits on top of AILs compared with individual SVD features, and the cognitive impact of different individual SVD features was generally similar. As identified by the optimal SVR models, the important SVD-affected regions were mainly located in the basal ganglia and white matter around it, although the specific regions varied for MoCA and its domains. CONCLUSIONS: Multiple types of SVD neuroimaging features jointly had a significant impact on global and domain cognitive functionings after stroke on top of AILs. The map of strategic cognitive-relevant regions of SVD features may help clinicians to understand their complementary impact on poststroke cognition.

Converting MMSE to MoCA and MoCA 5-minute protocol in an educationally heterogeneous sample with stroke or transient ischemic attack.

BACKGROUND: The Montreal Cognitive Assessment (MoCA) is psychometrically superior over the Mini-mental State Examination (MMSE) for cognitive screening in stroke or transient ischemic attack (TIA). It is free for clinical and research use. The objective of this study is to convert scores from the MMSE to MoCA and MoCA-5-minute protocol (MoCA-5 min) and to examine the ability of the converted scores in detecting cognitive impairment after stroke or TIA. METHODS: A total of 904 patients were randomly divided into training (n = 623) and validation (n = 281) samples matched for demography and cognition. MMSE scores were converted to MoCA and MoCA-5 min using (1) equipercentile method with log-linear smoothing and (2) Poisson regression adjusting for age and education. Receiver operating characteristics curve analysis was used to examine the ability of the converted scores in differentiating patients with cognitive impairment. RESULTS: The mean education was 5.8 (SD = 4.6; ranged 0-20) years. The entire spectrum of MMSE scores was converted to MoCA and MoCA-5 min using equipercentile method. Relationship between MMSE and MoCA scores was confounded by age and education, and a conversion equation with adjustment for age and education was derived. In the validation sample, the converted scores differentiated cognitively impaired patients with area under receiver operating characteristics curve 0.826 to 0.859. CONCLUSION: We provided 2 methods to convert scores from the MMSE to MoCA and MoCA-5 min based on a large sample of patients with stroke or TIA having a wide range of education and cognitive levels. The converted scores differentiated patients with cognitive impairment after stroke or TIA with high accuracy.

Delayed-onset dementia after stroke or transient ischemic attack.

INTRODUCTION: Patients surviving stroke without immediate dementia are at high risk of delayed-onset dementia. Mechanisms underlying delayed-onset dementia are complex and may involve vascular and/or neurodegenerative diseases. METHODS: Dementia-free patients with stroke and/or transient ischemic attack (TIA; n = 919) were studied for 3 years prospectively, excluding those who developed dementia 3 to 6 months after stroke and/or TIA. RESULTS: Forty subjects (4.4%) developed dementia during the study period. Imaging markers of severe small vessel disease (SVD), namely presence of ≥3 lacunes and confluent white matter changes; history of hypertension and diabetes mellitus independently predicted delayed-onset dementia after adjustment for age, gender, and education. Only 6 of 31 (19.4%) subjects with delayed cognitive decline harbored Alzheimer's disease-like Pittsburg compound B (PiB) retention. Most PiB cases (16/25, 64%) had evidence of severe SVD. DISCUSSION: Severe SVD contributes importantly to delayed-onset dementia after stroke and/or TIA. Future clinical trials aiming to prevent delayed-onset dementia after stroke and/or TIA should target this high-risk group.

Longitudinal white matter changes in frontotemporal dementia subtypes.

Frontotemporal dementia is a degenerative brain condition characterized by focal atrophy affecting the frontal and temporal lobes predominantly. Changes in white matter with disease progression and their relationship to grey matter atrophy remain unknown in FTD. This study aimed to establish longitudinal white matter changes and compare these changes to regional grey matter atrophy in the main FTD subtypes. Diffusion and T1-weighted images were collected from behavioral-variant FTD (bvFTD: 12), progressive non-fluent aphasia (PNFA: 10), semantic dementia (SD: 11), and 15 controls at baseline and 12 months apart. Changes in white matter integrity were established by fractional anisotropy, mean, axial and radial diffusivity measurements using tract-based spatial statistics. Patterns of cortical grey matter atrophy were measured using voxel-based morphometry. At baseline, bvFTD showed severe cross-sectional changes in orbitofrontal and anterior temporal tracts, which progressed to involve posterior temporal and occipital white matter over the 12-month. In PNFA, cross-sectional changes occurred bilaterally in frontotemporal white matter (left > right), with longitudinal changes more prominent on the right. Initial white matter changes in SD were circumscribed to the left temporal lobe, with longitudinal changes extending to bilateral frontotemporal tracts. In contrast, progression of grey matter change over time was less pronounced in all FTD subtypes. Mean diffusivity was most sensitive in detecting baseline changes while fractional anisotropy and radial diffusivity revealed greatest changes over time, possibly reflecting different underlying pathological processes with disease progression. Our results indicate that investigations of white matter changes reveal important differences across FTD syndromes with disease progression.

Neuroimaging standards for research into small vessel disease-advances since 2013.

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

Efficacy and safety of cilostazol in decreasing progression of cerebral white matter hyperintensities-A randomized controlled trial.

Introduction: Cerebral small vessel disease (SVD) is an important cause of dementia that lacks effective treatment. We evaluated the efficacy and safety of cilostazol, an antiplatelet agent with potential neurovascular protective effects, in slowing the progression of white matter hyperintensities (WMHs) in stroke- and dementia-free subjects harboring confluent WMH on magnetic resonance imaging (MRI). Methods: In this single-center, randomized, double-blind, placebo-controlled study, we randomized stroke- and dementia-free subjects with confluent WMHs to receive cilostazol or placebo for 2 years in a 1:1 ratio. The primary outcome was change in WMH volume over 2 years. Secondary outcomes were changes in brain volumes, lacunes, cerebral microbleeds, perivascular space, and alterations in white matter microstructural integrity, cognition, motor function, and mood. Results: We recruited 120 subjects from October 27, 2014, to January 21, 2019. A total of 55 subjects in the cilostazol group and 54 subjects in the control group were included for intention-to-treat analysis. At 2-year follow-up, the changes in WMH volume were not statistically different between cilostazol treatment and placebo (0.3±1.0 mL vs -0.1±0.8 mL, p = 0.167). Secondary outcomes, bleeding and vascular events, were also not statistically different between the two groups. Discussion: In this trial with stroke- and dementia-free subjects with confluent WMHs, cilostazol did not impact WMH progression but demonstrated an acceptable safety profile. Future studies should address the treatment effects of cilostazol on subjects at different clinical stages of SVD.

Network impact score is an independent predictor of post-stroke cognitive impairment: A multicenter cohort study in 2341 patients with acute ischemic stroke.

BACKGROUND: Post-stroke cognitive impairment (PSCI) is a common consequence of stroke. Accurate prediction of PSCI risk is challenging. The recently developed network impact score, which integrates information on infarct location and size with brain network topology, may improve PSCI risk prediction. AIMS: To determine if the network impact score is an independent predictor of PSCI, and of cognitive recovery or decline. METHODS: We pooled data from patients with acute ischemic stroke from 12 cohorts through the Meta VCI Map consortium. PSCI was defined as impairment in ≥ 1 cognitive domain on neuropsychological examination, or abnormal Montreal Cognitive Assessment. Cognitive recovery was defined as conversion from PSCI < 3 months post-stroke to no PSCI at follow-up, and cognitive decline as conversion from no PSCI to PSCI. The network impact score was related to serial measures of PSCI using Generalized Estimating Equations (GEE) models, and to PSCI stratified according to post-stroke interval (<3, 3-12, 12-24, >24 months) and cognitive recovery or decline using logistic regression. Models were adjusted for age, sex, education, prior stroke, infarct volume, and study site. RESULTS: We included 2341 patients with 4657 cognitive assessments. PSCI was present in 398/844 patients (47%) <3 months, 709/1640 (43%) at 3-12 months, 243/853 (28%) at 12-24 months, and 208/522 (40%) >24 months. Cognitive recovery occurred in 64/181 (35%) patients and cognitive decline in 26/287 (9%). The network impact score predicted PSCI in the univariable (OR 1.50, 95%CI 1.34-1.68) and multivariable (OR 1.27, 95%CI 1.10-1.46) GEE model, with similar ORs in the logistic regression models for specified post-stroke intervals. The network impact score was not associated with cognitive recovery or decline. CONCLUSIONS: The network impact score is an independent predictor of PSCI. As such, the network impact score may contribute to a more precise and individualized cognitive prognostication in patients with ischemic stroke. Future studies should address if multimodal prediction models, combining the network impact score with demographics, clinical characteristics and other advanced brain imaging biomarkers, will provide accurate individualized prediction of PSCI. A tool for calculating the network impact score is freely available at https://metavcimap.org/features/software-tools/lsm-viewer/.

Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts.

BACKGROUND: Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in the first year after stroke. Infarct location is a potential determinant of PSCI, but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable. We aimed to identify infarct locations most strongly predictive of PSCI after acute ischaemic stroke and use this information to develop a prediction model. METHODS: In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was defined as performance lower than the fifth percentile of local normative data, on at least one cognitive domain on a multidomain neuropsychological assessment or on the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional brain template to visualise PSCI risk per location. For the prediction model of PSCI risk, a location impact score on a 5-point scale was derived from the VLSM results on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct. We did combined internal-external validation by leave-one-cohort-out cross-validation for all 12 cohorts using logistic regression. Predictive performance of a univariable model with only the location impact score was compared with a multivariable model with addition of other clinical PSCI predictors (age, sex, education, time interval between stroke onset and cognitive assessment, history of stroke, and total infarct volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater reliability, and intra-rater reliability were assessed with Cohen's weighted kappa. FINDINGS: In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women), 1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses (86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01; voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence, based on visual assessment of goodness of fit, between predicted and observed risk of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations showed that the location impact score by itself had similar performance to the combined model with other PSCI predictors, while allowing for easy visual assessment. Therefore the univariable model with only the location impact score was selected as the final model. Correspondence between visual ratings and actual location impact score (Cohen's weighted kappa: range 0·88-0·92), inter-rater agreement (0·85-0·87), and intra-rater agreement (for a single rater, 0·95) were all high. INTERPRETATION: To the best of our knowledge, this study provides the first comprehensive map of strategic infarct locations associated with risk of PSCI. A location impact score was derived from this map that robustly predicted PSCI across cohorts. Furthermore, we developed a quick and reliable visual rating scale that might in the future be applied by clinicians to identify individual patients at risk of PSCI. FUNDING: The Netherlands Organisation for Health Research and Development.

High white matter hyperintensity burden in strategic white matter tracts relates to worse global cognitive performance in community-dwelling individuals.

BACKGROUND: White matter hyperintensities (WMH) are associated with cognitive impairment. The impact of WMH on cognitive domains (e.g. processing speed, executive functioning) depends on location. We determined whether the relevance of WMH location also applies to global cognitive functioning by testing if WMH in strategic white matter tracts are associated with global cognitive functioning independent of total WMH burden. METHODS: We included 830 community-dwelling individuals. WMH volume within two a priori specified strategic white matter tracts (forceps minor and anterior thalamic radiation) were entered in a linear regression model with the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) as outcome variables and corrected for total WMH volume and other MRI markers for vascular injury and neurodegenerations (i.e. brain parenchymal fraction, and the presence of lacunes and microbleeds). RESULTS: WMH in the forceps minor and left anterior thalamic radiation inversely correlated with MoCA, and WMH in the forceps minor inversely correlated with MMSE, independent of total WMH volume and other MRI markers. CONCLUSION: The impact of WMH on global cognitive functioning depends on location. Whether this reflects accumulated impairment in isolated cognitive domains or disruption of a network that is crucially involved in global cognitive performance remains to be determined.

Can transcranial Doppler ultrasound be used for screening cerebral small vessel diseases in the community?

OBJECTIVES: Elderly persons harbouring severe white matter hyperintensity (WMH), a radiological manifestation of cerebral small vessel disease (SVD), have an increased risk of dementia, stroke and poor functional outcomes. A simple screening tool will enhance their recruitment into preventive trials for SVD. We explored the clinical utility of the pulsatility index (PI) of the middle cerebral artery (MCA), obtained from transcranial Doppler ultrasound (TCD), in identifying severe WMH among community elderly persons with vascular risk factors. METHODS: Three hundred and thirty-one dementia- and stroke-free community elderly subjects with hypertension and/or diabetes mellitus underwent TCD to obtain the MCA PI. The WMH volume on 3.0 Tesla MRI was quantified and normalized to each subject's brain volume. The normalized WMH volumes were classified as low (<14.5 ml, 1 standard deviation [SD] above the mean, 84th percentile) or high (≥14.5 ml). The severity of WMH was also rated visually with the Fazekas score. Logistic regression and receiver-operator characteristics (ROC) analysis were performed to evaluate the association between the MCA PI and the severity of WMH. RESULTS: The MCA PI was not an independent predictor of severe WMH. An MCA PI ≥1.095 detected high normalized WMH volumes with an area under the curve (AUC) of 0.553 (95% CI 0.473-0.633), sensitivity of 0.556, and specificity of 0.523. ROC analysis of the MCA PI in predicting high Fazekas scores yielded similar findings. CONCLUSION: In stroke- and dementia-free elderly persons with vascular risk factors, the MCA PI was unable to identify severe WMH. (Word count: 260).

The Meta VCI Map consortium for meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping: Design and multicenter pilot study.

INTRODUCTION: The Meta VCI Map consortium performs meta-analyses on strategic lesion locations for vascular cognitive impairment using lesion-symptom mapping. Integration of data from different cohorts will increase sample sizes, to improve brain lesion coverage and support comprehensive lesion-symptom mapping studies. METHODS: Cohorts with available imaging on white matter hyperintensities or infarcts and cognitive testing were invited. We performed a pilot study to test the feasibility of multicenter data processing and analysis and determine the benefits to lesion coverage. RESULTS: Forty-seven groups have joined Meta VCI Map (stroke n = 7800 patients; memory clinic n = 4900; population-based n = 14,400). The pilot study (six ischemic stroke cohorts, n = 878) demonstrated feasibility of multicenter data integration (computed tomography/magnetic resonance imaging) and achieved marked improvement of lesion coverage. DISCUSSION: Meta VCI Map will provide new insights into the relevance of vascular lesion location for cognitive dysfunction. After the successful pilot study, further projects are being prepared. Other investigators are welcome to join.

Harmonizing brain magnetic resonance imaging methods for vascular contributions to neurodegeneration.

INTRODUCTION: Many consequences of cerebrovascular disease are identifiable by magnetic resonance imaging (MRI), but variation in methods limits multicenter studies and pooling of data. The European Union Joint Program on Neurodegenerative Diseases (EU JPND) funded the HARmoNizing Brain Imaging MEthodS for VaScular Contributions to Neurodegeneration (HARNESS) initiative, with a focus on cerebral small vessel disease. METHODS: Surveys, teleconferences, and an in-person workshop were used to identify gaps in knowledge and to develop tools for harmonizing imaging and analysis. RESULTS: A framework for neuroimaging biomarker development was developed based on validating repeatability and reproducibility, biological principles, and feasibility of implementation. The status of current MRI biomarkers was reviewed. A website was created at www.harness-neuroimaging.org with acquisition protocols, a software database, rating scales and case report forms, and a deidentified MRI repository. CONCLUSIONS: The HARNESS initiative provides resources to reduce variability in measurement in MRI studies of cerebral small vessel disease.

Early-onset and delayed-onset poststroke dementia - revisiting the mechanisms.

Incident stroke has long been recognized to cause dementia shortly after the event. Patients who survive stroke without early-onset poststroke dementia (PSD) are at a high risk of developing dementia months to years after the initial stroke incident, which has generated enthusiasm for exploring treatments to prevent delayed-onset PSD in survivors of stroke. However, results from clinical trials completed in the past 10-15 years have been disappointing. In light of these results, the present Review revisits the mechanisms of both early-onset and delayed-onset PSD and proposes preventive strategies and directions for future clinical trials. Early-onset PSD results from a complex interplay between stroke lesion features and brain resilience, whereas delayed-onset PSD is associated mainly with the presence of severe sporadic small vessel disease (SVD), and to a lesser extent with Alzheimer disease pathology or recurrent stroke. As well as preventing stroke and delivering acute stroke treatments to reduce initial brain damage, measures to increase brain resilience could also reduce the risk of developing dementia if an incident stroke occurs. Future efforts to prevent delayed-onset PSD should focus on the study of sporadic SVD and on evaluating whether other strategies, in addition to conventional secondary stroke prevention, are effective in dementia prevention in this high-risk group.

Development and validation of a risk score (CHANGE) for cognitive impairment after ischemic stroke.

Post-stroke cognitive impairment (PSCI) warrants early detection and management. We sought to develop a risk score for screening patients at bedside for risk of delayed PSCI. Ischemic stroke survivors with PSCI and no cognitive impairments (NCI) 3-6 months post-stroke were studied to identify candidate variables predictive of PSCI. These variables were used to develop a risk score using regression models. The score, and the best identified clinical cutoff point, underwent development, stability testing, and internal and external validation in three independent cohorts from Singapore and Hong Kong. Across 1,088 subjects, the risk score, dubbed CHANGE, had areas under the receiver operating characteristics curve (AUROC) from 0.74 to 0.82 in detecting significant risk for PSCI, and had predicted values following actual prevalence. In validation data 3-6 and 12-18 months post-stroke, subjects with low, medium, and high scores had PSCI prevalence of 7-23%, 25-58%, and 67-82%. CHANGE was effective in screening ischemic stroke survivors for significant risk of developing PSCI up to 18 months post-stroke. CHANGE used readily available and reliable clinical data, and may be useful in identifying at-risk patients for PSCI.

Relations between Recent Past Leisure Activities with Risks of Dementia and Cognitive Functions after Stroke.

BACKGROUND: Leisure activity participation has been shown to lower risks of cognitive decline in non-stroke populations. However, effects of leisure activities participation upon cognitive functions and risk of dementia after stroke are unclear. The purpose of this study is to examine the effects of recent past leisure activities participation upon cognitive functions and risk of incident dementia after stroke. METHODS: Hospital-based, retrospective cohort study. 88 of 1,013 patients with stroke or TIA having no prestroke dementia were diagnosed to have incident poststroke dementia (PSD) 3-6 months after stroke. Regular participation (≥3 times per week) in intellectual, recreational, social and physical activities over the year before the index stroke was retrospectively recorded at 3-6 months after stroke. RESULTS: Logistic regression analyses showed that regular participation in intellectual (RR 0.36, 95%CI 0.20-0.63) and stretching & toning physical exercise (0.37, 0.21-0.64) was significantly associated with a reduced risk of PSD after controlling for age, education, prestroke cognitive decline, stroke subtype, prior strokes and chronic brain changes including white matter changes, old infarcts and global atrophy. Results were similar in patients with past strokes in unadjusted models. Participation in increased number of activities in general (r = 0.41, p<0.01) and in intellectual (r = 0.40, p<0.01), recreational (r = 0.24, p<0.01), strenuous aerobic (r = 0.23, p<0.01) and mind-body (r = 0.10, p<0.01) activities was associated with higher poststroke Mini-mental State Examination scores in models adjusted for prestroke cognitive decline. CONCLUSIONS: Regular participation in intellectual activities and stretching & toning exercise was associated with a significantly reduced short-term risk of PSD in patients with and without recurrent strokes. Participation in greater number of recent past leisure activities was associated with better poststroke cognitive performance. Findings of this retrospective cohort study call for studies of activity intervention for prevention of cognitive decline in individuals at elevated risk of stroke.

Neuropsychiatric Symptom Clusters in Stroke and Transient Ischemic Attack by Cognitive Status and Stroke Subtype: Frequency and Relationships with Vascular Lesions, Brain Atrophy and Amyloid.

BACKGROUND: The objectives of this study are 1) to examine the frequencies of neuropsychiatric symptom clusters in patients with stroke or transient ischemic attack (TIA) by cognitive level and stroke subtype; and 2) to evaluate effect of demographic, clinical, and neuroimaging measures of chronic brain changes and amyloid upon neuropsychiatric symptom clusters. METHODS: Hospital-based, cross-sectional study. 518 patients were administered the Neuropsychiatric Inventory (NPI) 3-6 months post index admission. NPI symptoms were classified into four symptom clusters (Behavioral Problems, Psychosis, Mood Disturbance & Euphoria) derived from a confirmatory factor analysis of the 12 NPI items. Multivariable logistic regression was used to determine independent associations between demographic, clinical and neuroimaging measures of chronic brain changes (white matter changes, old infarcts, whole brain atrophy, medial temporal lobe atrophy [MTLA] and frontal lobe atrophy [FLA]) with the presence of NPI symptoms and all symptom clusters except euphoria. 11C-Pittsburg Compound B Positron Emission Tomography (11C-PiB PET) was performed in 24 patients to measure amyloid retention for Alzheimer's Disease (AD) pathology. RESULTS: 50.6% of the whole sample, including 28.7% cognitively normal and 66.7% of patients with mild cognitive symptoms, had ≥1 NPI symptoms. Frequencies of symptom clusters were largely similar between stroke subtypes. Compared to patients with cardioembolic stroke and intracranial haemorrhage, those with TIA had less frequent mood disturbance. Stroke severity at admission and MTLA were the most robust correlates of symptoms. FLA was associated with behavioral problems cluster only. Frequency of symptom clusters did not differ between patients with and without significant amyloid retention. CONCLUSION: Frequency of neuropsychiatric symptoms increased with level of cognitive impairment but was largely similar between stroke subtypes. Stroke severity and MTLA were associated with neuropsychiatric symptoms. AD pathology appeared to be unrelated to neuropsychiatric manifestations but further studies with larger sample size are required to substantiate this finding.

Grey and white matter correlates of recent and remote autobiographical memory retrieval--insights from the dementias.

The capacity to remember self-referential past events relies on the integrity of a distributed neural network. Controversy exists, however, regarding the involvement of specific brain structures for the retrieval of recently experienced versus more distant events. Here, we explored how characteristic patterns of atrophy in neurodegenerative disorders differentially disrupt remote versus recent autobiographical memory. Eleven behavioural-variant frontotemporal dementia, 10 semantic dementia, 15 Alzheimer's disease patients and 14 healthy older Controls completed the Autobiographical Interview. All patient groups displayed significant remote memory impairments relative to Controls. Similarly, recent period retrieval was significantly compromised in behavioural-variant frontotemporal dementia and Alzheimer's disease, yet semantic dementia patients scored in line with Controls. Voxel-based morphometry and diffusion tensor imaging analyses, for all participants combined, were conducted to investigate grey and white matter correlates of remote and recent autobiographical memory retrieval. Neural correlates common to both recent and remote time periods were identified, including the hippocampus, medial prefrontal, and frontopolar cortices, and the forceps minor and left hippocampal portion of the cingulum bundle. Regions exclusively implicated in each time period were also identified. The integrity of the anterior temporal cortices was related to the retrieval of remote memories, whereas the posterior cingulate cortex emerged as a structure significantly associated with recent autobiographical memory retrieval. This study represents the first investigation of the grey and white matter correlates of remote and recent autobiographical memory retrieval in neurodegenerative disorders. Our findings demonstrate the importance of core brain structures, including the medial prefrontal cortex and hippocampus, irrespective of time period, and point towards the contribution of discrete regions in mediating successful retrieval of distant versus recently experienced events.