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OBJECTIVE: The impact of white matter hyperintensities (WMH) on language possibly depends on lesion location through disturbance of strategic white matter tracts. We examined the impact of WMH location on language in elderly Asians. DESIGN: Cross-sectional. SETTING: Population-based. PARTICIPANTS: Eight-hundred nineteen residents of Singapore, ages (≥65 years). MEASUREMENTS: Clinical, cognitive and 3T magnetic resonance imaging assessments were performed on all participants. Language was assessed using the Modified Boston Naming Test (MBNT) and Verbal Fluency (VF). Hypothesis-free region-of-interest-based (ROI) analyses based on major white matter tracts were used to determine the association between WMH location and language. Conditional dependencies between the regional WMH volumes and language were examined using Bayesian-network analysis. RESULTS: ROI-based analyses showed that WMH located within the anterior thalamic radiation (mean difference: -0.12, 95% confidence interval [CI]: -0.22; -0.02, p = 0.019) and uncinate fasciculus (mean difference: -0.09, 95% CI: -0.18; -0.01, p = 0.022) in the left hemisphere were significantly associated with worse VF but did not survive multiple testing. Conversely, WMH volume in the left cingulum of cingulate gyrus was significantly associated with MBNT performance (mean difference: -0.09, 95% CI: -0.17; -0.02, p = 0.016). Bayesian-network analyses confirmed the left cingulum of cingulate gyrus as a direct determinant of MBNT performance. CONCLUSION: Our findings identify the left cingulum of cingulate gyrus as a strategic white matter tract for MBNT, suggesting that language - is sensitive to subcortical ischemic damage. Future studies on the role of sporadic ischemic lesions and vascular cognitive impairment should not only focus on total WMH volume but should also take WMH lesion location into account when addressing language.

We have provided an overview on the profound impact of COVID-19 upon older people with Alzheimer's disease and other dementias and the challenges encountered in our management of dementia in different health-care settings, including hospital, out-patient, care homes, and the community during the COVID-19 pandemic. We have also proposed a conceptual framework and practical suggestions for health-care providers in tackling these challenges, which can also apply to the care of older people in general, with or without other neurological diseases, such as stroke or parkinsonism. We believe this review will provide strategic directions and set standards for health-care leaders in dementia, including governmental bodies around the world in coordinating emergency response plans for protecting and caring for older people with dementia amid the COIVD-19 outbreak, which is likely to continue at varying severity in different regions around the world in the medium term.

Cerebral cortical microinfarcts (CMIs) are small ischemic lesions associated with cognitive impairment and dementia. CMIs are frequently observed in cortical watershed areas suggesting that hypoperfusion contributes to their development. We investigated if presence of CMIs was related to a decrease in cerebral perfusion, globally or specifically in cortex surrounding CMIs. In 181 memory clinic patients (mean age 72 9 years, 51% male), CMI presence was rated on 3-T magnetic resonance imaging (MRI). Cerebral perfusion was assessed from cortical gray matter of the anterior circulation using pseudo-continuous arterial spin labeling parameters cerebral blood flow (CBF) (perfusion in mL blood/ 100 g tissue/min) and spatial coefficient of variation (CoV) (reflecting arterial transit time (ATT)). Patients with CMIs had a 12% lower CBF (beta ¼ .20) and 22% higher spatial CoV (beta ¼ .20) (both p <.05) without a specific regional pattern on voxel-based CBF analysis. CBF in a 2 cm region-of-interest around the CMIs did not differ from CBF in a reference zone in the contralateral hemisphere. These findings show that CMIs in memory clinic patients are primarily related to global reductions in cerebral perfusion, thus shed

Introduction Nonfocal transient neurological attacks (TNAs) are associated with an increased risk of future dementia, but it is unclear whether TNAs are also associated with concurrent cognitive impairment. We hypothesized that recent TNAs are related to worse cognitive functioning. We tested our hypothesis in patients with heart failure, as these patients are at risk of cerebral hypoperfusion, which might play a role in the etiology of TNAs. Methods We performed neuropsychological testing in all patients with heart failure enrolled in the Heart Brain Connection study. We assessed global cognition, attention-psychomotor speed, executive functioning, memory and language. All patients were interviewed with a standardized questionnaire on the occurrence of TNAs in the preceding 6 months. We studied associations between TNAs and cognitive functioning with linear and logistic regression analyses, adjusted for age, sex and education. We performed additional analyses in patients without previous stroke or TIA and in patients without brain infarction on MRI. Results Thirty-seven (23%) of 158 patients (mean age 70 years, 67% men) experienced one or more TNAs. Patients with a recent TNA were more likely to be impaired on≥1 cognitive domains than patients without TNAs [41% vs. 18%, adjusted odds ratio 4.6, 95% confdence interval (CI) 1.8–11.8]. Patients with TNAs performed worse than patients without TNAs on global cognition (mean diference in z scores −0.36, 95% CI −0.54 to −0.18), and on the cognitive domains attentionpsychomotor speed (mean diference −0.40, 95% CI −0.66 to −0.14), memory (mean diference −0.57, 95% CI −0.98 to −0.15) and language (mean diference −0.47, 95% CI −0.79 to −0.16). These associations were independent of cardiac output and volume of white matter hyperintensities. Subgroup analyses in patients without previous stroke or TIA or brain infarction on MRI (n=78) yielded comparable results, with the exception of the cognitive domain language, which was no

Background and Purpose— Predicting malignant middle cerebral artery (MCA) infarction can help to identify patients who may benefit from preventive decompressive surgery. We aimed to investigate the association between the ratio of intracranial cerebrospinal fluid (CSF) volume to intracranial volume (ICV) and malignant MCA infarction. Methods— Patients with an occlusion proximal to the M3 segment of the MCA were selected from the DUST (Dutch Acute Stroke Study). Admission imaging included noncontrast computed tomography (CT), CT perfusion, and CT angiography. Patient characteristics and CT findings were collected. The ratio of intracranial CSF volume to ICV (CSF/ICV) was quantified on admission thin-slice noncontrast CT. Malignant MCA infarction was defined as a midline shift of >5 mm on follow-up noncontrast CT, which was performed 3 days after the stroke or in case of clinical deterioration. To test the association between CSF/ICV and malignant MCA infarction, odds ratios and 95% CIs were calculated for 3 multivariable models by using binary logistic regression. Model performances were compared by using the likelihood ratio test. Results— Of the 286 included patients, 35 (12%) developed malignant MCA infarction. CSF/ICV was independently associated with malignant MCA infarction in 3 multivariable models: (1) with age and admission National Institutes of Health Stroke Scale (odds ratio, 3.3; 95% CI, 1.1–11.1), (2) with admission National Institutes of Health Stroke Scale and poor collateral score (odds ratio, 7.0; 95% CI, 2.6–21.3), and (3) with terminal internal carotid artery or proximal M1 occlusion and poor collateral score (odds ratio, 7.7; 95% CI, 2.8–23.9). The performance of model 1 (areas under the receiver operating characteristic curves, 0.795 versus 0.824; P=0.033), model 2 (areas under the receiver operating characteristic curves, 0.813 versus 0.850; P<0.001), and model 3 (areas under the receiver operating characteristic curves, 0.811 versus 0.856; P<0

Many methods have been proposed for tissue segmentation in brain MRI scans. The multitude of methods proposed complicates the choice of one method above others. We have therefore established the MRBrainS online evaluation framework for evaluating (semi)automatic algorithms that segment gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) on 3T brain MRI scans of elderly subjects (65–80 y). Participants apply their algorithms to the provided data, after which their results are evaluated and ranked. Full manual segmentations of GM, WM, and CSF are available for all scans and used as the reference standard. Five datasets are provided for training and fifteen for testing. The evaluated methods are ranked based on their overall performance to segment GM, WM, and CSF and evaluated using three evaluation metrics (Dice, H95, and AVD) and the results are published on the MRBrainS13 website. We present the results of eleven segmentation algorithms that participated in the MRBrainS13 challenge workshop at MICCAI, where the framework was launched, and three commonly used freeware packages: FreeSurfer, FSL, and SPM. The MRBrainS evaluation framework provides an objective and direct comparison of all evaluated algorithms and can aid in selecting the best performing method for the segmentation goal at hand., QC 20160112. QC 20160113

Background: The Parelsnoer Institute is a collaboration between 8 Dutch University Medical Centers in which clinical data and biomaterials from patients suffering from chronic diseases (so called "Pearls") are collected according to harmonized protocols. The Pearl Neurodegenerative Diseases focuses on the role of biomarkers in the early diagnosis, differential diagnosis and in monitoring the course of neurodegenerative diseases, in particular Alzheimer's disease. The objective of this paper is to describe the design and methods of the Pearl Neurodegenerative Diseases, as well as baseline descriptive variables, including their biomarker profile. Methods: The Pearl Neurodegenerative Diseases is a 3-year follow-up study of patients referred to a memory clinic with cognitive complaints. At baseline, all patients are subjected to a standardized examination, including clinical data and biobank materials, e.g. blood samples, MRI and cerebrospinal fluid. At present, in total more than 1000 patients have been included, of which cerebrospinal fluid and DNA samples are available of 211 and 661 patients, respectively. First descriptives of a subsample of the data (n = 665) shows that patients are diagnosed with dementia (45%), mild cognitive impairment (31%), and subjective memory complaints (24%). Discussion: The Pearl Neurodegenerative Diseases is an ongoing large network collecting clinical data and biomaterials of more than 1000 patients with cognitive impairments. The project has started with data analyses of the baseline characteristics and biomarkers, which will be the starting point of future specific research questions that can be answered by this unique dataset.

Background: Prediction of clinical outcome in the acute stage of ischaemic stroke can be difficult when based on patient characteristics, clinical findings and on non-contrast CT. CT perfusion and CT angiography may provide additional prognostic information and guide treatment in the early stage. We present the study protocol of the Dutch acute Stroke Trial (DUST). The DUST aims to assess the prognostic value of CT perfusion and CT angiography in predicting stroke outcome, in addition to patient characteristics and non-contrast CT. For this purpose, individualised prediction models for clinical outcome after stroke based on the best predictors from patient characteristics and CT imaging will be developed and validated. Methods/design: The DUST is a prospective multi-centre cohort study in 1500 patients with suspected acute ischaemic stroke. All patients undergo non-contrast CT, CT perfusion and CT angiography within 9 hours after onset of the neurological deficits, and, if possible, follow-up imaging after 3 days. The primary outcome is a dichotomised score on the modified Rankin Scale, assessed at 90 days. A score of 0-2 represents good outcome, and a score of 3-6 represents poor outcome. Three logistic regression models will be developed, including patient characteristics and non-contrast CT (model A), with addition of CT angiography (model B), and CT perfusion parameters (model C). Model derivation will be performed in 60% of the study population, and model validation in the remaining 40% of the patients. Additional prognostic value of the models will be determined with the area under the curve (AUC) from the receiver operating characteristic (ROC) curve, calibration plots, assessment of goodness-of-fit, and likelihood ratio tests. Discussion: This study will provide insight in the added prognostic value of CTP and CTA parameters in outcome prediction of acute stroke patients. The prediction models that will be developed in this study may help guide future treatm