Investigating the Relationship between Cerebral Blood Flow and Cognitive Function in Hemodialysis Patients.

BACKGROUND: The immediate and longer-term effects of hemodialysis on cerebral circulation, cerebral structure, and cognitive function are poorly understood. METHODS: In a prospective observational cohort study of 97 adults (median age 59 years) receiving chronic hemodialysis, we used transcranial Doppler ultrasound to measure cerebral arterial mean flow velocity (MFV) throughout dialysis. Using a well validated neuropsychological protocol, we assessed cognitive function during and off dialysis and after 12 months of treatment. We also used brain magnetic resonance imaging (MRI) to assess atrophy, white matter hyperintensities (WMHs), and diffusion parameters, and tested correlations between MFV, cognitive scores, and changes on MRI. RESULTS: MFV declined significantly during dialysis, correlating with ultrafiltrate volumes. Percentage of decline in MFV correlated with intradialytic decline in cognitive function, including global function, executive function, and verbal fluency. At follow-up, 73 patients were available for repeat testing, 34 of whom underwent repeat MRI. In a subgroup of patients followed for 12 months of continued dialysis, percentage of decline in MFV correlated significantly with lower global and executive function and with progression of WMH burden (a marker of small vessel disease). Twelve of 15 patients who received renal transplants during follow-up had both early and follow-up off-dialysis assessments. After transplant, patients' memory (on a delayed recall test) improved significantly; increased fractional anisotropy of white matter (a measure of cerebral diffusion) in these patients correlated with improving executive function. CONCLUSIONS: Patients undergoing hemodialysis experience transient decline in cerebral blood flow, correlating with intradialytic cognitive dysfunction. Progressive cerebrovascular disease occurred in those continuing dialysis, but not in transplanted patients. Cognitive function and cerebral diffusion improved after transplant.

Combining Neurovascular and Neurodegenerative Magnetic Resonance Imaging Measures in Stroke.

Background and Purpose- Individual markers of cerebral small vessel disease and cerebral atrophy explain a small proportion of variance in vascular risk factors and cognitive function. Combining these markers into a single measure of neurovascular and neurodegenerative disease may be more powerful. We assessed this using data contained in the Virtual International Stroke Trials Archive - Prevention sub-archive. Methods- We extracted white matter hyperintensities (WMH) and cerebrospinal fluid (CSF) volumes from 317 people with ischemic stroke or transient ischemic attack who had baseline magnetic resonance imaging. We assessed progression of volumes in 208 people who had 2-year follow-up magnetic resonance imaging. WMH and CSF volumes were segmented from fluid attenuated inversion recovery and T1 images. The combined neurovascular and neurodegenerative measure was the sum of WMH and CSF volume normalized by intracranial volume. We assessed (1) the relationship between baseline vascular risk factors and imaging markers; and (2) the relationship between baseline imaging markers and Mini-Mental State Examination score at follow-up using multiple linear regression. We also assessed implications for sample size calculations using n=208 participants with follow-up magnetic resonance imaging. Results- Vascular risk factors accounted for 7%, 11%, and 12% of the variance in WMH, CSF, and combined volume, respectively (all P<0.001). The association between baseline combined volume and 6-month follow-up Mini-Mental State Examination (ß=-0.442; SE, 0.07; P<0.0001) was 32% greater than WMH (ß=-0.302; SE, 0.06; P<0.0001) and 12% greater than CSF (ß=-0.391; SE, 0.07; P<0.0001) alone. The combined volume required between 207 and 3305 (20%) fewer patients per arm than WMH alone to detect reductions of 10% to 40% in volume progression over 2 years. Conclusions- A combined neurovascular and neurodegenerative magnetic resonance imaging measure including WMH and CSF volume was more closely related to vascular risk factors and cognitive function than either WMH or CSF volume alone. The combined volume may be a more sensitive measurement for clinical trials.

The Whole Picture: From Isolated to Global MRI Measures of Neurovascular and Neurodegenerative Disease.

Structural magnetic resonance imaging (MRI) has been used to characterise the appearance of the brain in cerebral small vessel disease (SVD), ischaemic stroke, cognitive impairment, and dementia. SVD is a major cause of stroke and dementia; features of SVD include white matter hyperintensities (WMH) of presumed vascular origin, lacunes of presumed vascular origin, microbleeds, and perivascular spaces. Cognitive impairment and dementia have traditionally been stratified into subtypes of varying origin, e.g., vascular dementia versus dementia of the Alzheimer's type (Alzheimer's disease; AD). Vascular dementia is caused by reduced blood flow in the brain, often as a result of SVD, and AD is thought to have its genesis in the accumulation of tau and amyloid-beta leading to brain atrophy. But after early seminal studies in the 1990s found neurovascular disease features in around 30% of AD patients, it is becoming recognised that so-called "mixed pathologies" (of vascular and neurodegenerative origin) exist in many more patients diagnosed with stroke, only one type of dementia, or cognitive impairment. On the back of these discoveries, attempts have recently been made to quantify the full extent of degenerative and vascular disease in the brain in vivo on MRI. The hope being that these "global" methods may one day lead to better diagnoses of disease and provide more sensitive measurements to detect treatment effects in clinical trials. Indeed, the "Total MRI burden of cerebral small vessel disease", the "Brain Health Index" (BHI), and "MRI measure of degenerative and cerebrovascular pathology in Alzheimer disease" have all been shown to have stronger associations with clinical and cognitive phenotypes than individual brain MRI features. This chapter will review individual structural brain MRI features commonly seen in SVD, stroke, and dementia. The relationship between these features and differing clinical and cognitive phenotypes will be discussed along with developments in their measurement and quantification. The chapter will go on to review emerging methods for quantifying the collective burden of structural brain MRI findings and how these "whole picture" methods may lead to better diagnoses of neurovascular and neurodegenerative disorders.

Widespread associations between trait conscientiousness and thickness of brain cortical regions.

The neural correlates of human personality have been of longstanding interest; however, most studies in the field have relied on modest sample sizes and few replicable results have been reported to date. We investigated relationships between personality and brain gray matter in a sample of generally healthy, older (mean age 73 years) adults from Scotland drawn from the Lothian Birth Cohort 1936. Participants (N = 578) completed a brain MRI scan and self-reported Big Five personality trait measures. Conscientiousness trait scores were positively related to brain cortical thickness in a range of regions, including bilateral parahippocampal gyrus, bilateral fusiform gyrus, left cingulate gyrus, right medial orbitofrontal cortex, and left dorsomedial prefrontal cortex. These associations - most notably in frontal regions - were modestly-to-moderately attenuated by the inclusion of biomarker variables assessing allostatic load and smoking status. None of the other personality traits showed robust associations with brain cortical thickness, nor did we observe any personality trait associations with cortical surface area and gray matter volume. These findings indicate that brain cortical thickness is associated with conscientiousness, perhaps partly accounted for by allostatic load and smoking status.

Cognitive abilities, brain white matter hyperintensity volume, and structural network connectivity in older age.

OBJECTIVE: To assess brain structural connectivity in relation to cognitive abilities in healthy ageing, and the mediating effects of white matter hyper-intensity (WMH) volume. METHODS: MRI data were analysed in 558 members of the Lothian Birth Cohort 1936. Brains were segmented into 85 regions and combined with tractography to generate structural connectomes. WMH volume was quantified. Relationships between whole-brain connectivity, assessed using graph theory metrics, and four major domains of cognitive ability (visuospatial reasoning, verbal memory, information processing speed and crystallized ability) were investigated, as was the mediating effects of WMH volume on these relationships. RESULTS: Visuospatial reasoning was associated with network strength, mean shortest path length, and global efficiency. Memory was not associated with any network connectivity metric. Information processing speed and crystallized ability were associated with all network measures. Some relationships were lost when adjusted for mean network FA. WMH volume mediated 11%-15% of the relationships between most network measures and information processing speed, even after adjusting for mean network FA. CONCLUSION: Brain structural connectivity relates to visuospatial reasoning, information processing speed and crystallized ability, but not memory, in this relatively healthy age-homogeneous cohort of 73 year olds. When adjusted for mean FA across the network, most relationships are lost, except with information processing speed suggesting that the underlying topological network structure is related to this cognitive domain. Moreover, the connectome-processing speed relationship is partly mediated by WMH volume in this cohort. Hum Brain Mapp 39:622-632, 2018. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

A brain imaging repository of normal structural MRI across the life course: Brain Images of Normal Subjects (BRAINS).

The Brain Images of Normal Subjects (BRAINS) Imagebank (http://www.brainsimagebank.ac.uk) is an integrated repository project hosted by the University of Edinburgh and sponsored by the Scottish Imaging Network: A Platform for Scientific Excellence (SINAPSE) collaborators. BRAINS provide sharing and archiving of detailed normal human brain imaging and relevant phenotypic data already collected in studies of healthy volunteers across the life-course. It particularly focusses on the extremes of age (currently older age, and in future perinatal) where variability is largest, and which are under-represented in existing databanks. BRAINS is a living imagebank where new data will be added when available. Currently BRAINS contains data from 808 healthy volunteers, from 15 to 81years of age, from 7 projects in 3 centres. Additional completed and ongoing studies of normal individuals from 1st to 10th decades are in preparation and will be included as they become available. BRAINS holds several MRI structural sequences, including T1, T2, T2* and fluid attenuated inversion recovery (FLAIR), available in DICOM (http://dicom.nema.org/); in future Diffusion Tensor Imaging (DTI) will be added where available. Images are linked to a wide range of 'textual data', such as age, medical history, physiological measures (e.g. blood pressure), medication use, cognitive ability, and perinatal information for pre/post-natal subjects. The imagebank can be searched to include or exclude ranges of these variables to create better estimates of 'what is normal' at different ages.

Improving data availability for brain image biobanking in healthy subjects: Practice-based suggestions from an international multidisciplinary working group.

Brain imaging is now ubiquitous in clinical practice and research. The case for bringing together large amounts of image data from well-characterised healthy subjects and those with a range of common brain diseases across the life course is now compelling. This report follows a meeting of international experts from multiple disciplines, all interested in brain image biobanking. The meeting included neuroimaging experts (clinical and non-clinical), computer scientists, epidemiologists, clinicians, ethicists, and lawyers involved in creating brain image banks. The meeting followed a structured format to discuss current and emerging brain image banks; applications such as atlases; conceptual and statistical problems (e.g. defining 'normality'); legal, ethical and technological issues (e.g. consents, potential for data linkage, data security, harmonisation, data storage and enabling of research data sharing). We summarise the lessons learned from the experiences of a wide range of individual image banks, and provide practical recommendations to enhance creation, use and reuse of neuroimaging data. Our aim is to maximise the benefit of the image data, provided voluntarily by research participants and funded by many organisations, for human health. Our ultimate vision is of a federated network of brain image biobanks accessible for large studies of brain structure and function.

Metric to quantify white matter damage on brain magnetic resonance images.

PURPOSE: Quantitative assessment of white matter hyperintensities (WMH) on structural Magnetic Resonance Imaging (MRI) is challenging. It is important to harmonise results from different software tools considering not only the volume but also the signal intensity. Here we propose and evaluate a metric of white matter (WM) damage that addresses this need. METHODS: We obtained WMH and normal-appearing white matter (NAWM) volumes from brain structural MRI from community dwelling older individuals and stroke patients enrolled in three different studies, using two automatic methods followed by manual editing by two to four observers blind to each other. We calculated the average intensity values on brain structural fluid-attenuation inversion recovery (FLAIR) MRI for the NAWM and WMH. The white matter damage metric is calculated as the proportion of WMH in brain tissue weighted by the relative image contrast of the WMH-to-NAWM. The new metric was evaluated using tissue microstructure parameters and visual ratings of small vessel disease burden and WMH: Fazekas score for WMH burden and Prins scale for WMH change. RESULTS: The correlation between the WM damage metric and the visual rating scores (Spearman ρ > =0.74, p < 0.0001) was slightly stronger than between the latter and WMH volumes (Spearman ρ > =0.72, p < 0.0001). The repeatability of the WM damage metric was better than WM volume (average median difference between measurements 3.26% (IQR 2.76%) and 5.88% (IQR 5.32%) respectively). The follow-up WM damage was highly related to total Prins score even when adjusted for baseline WM damage (ANCOVA, p < 0.0001), which was not always the case for WMH volume, as total Prins was highly associated with the change in the intense WMH volume (p = 0.0079, increase of 4.42 ml per unit change in total Prins, 95%CI [1.17 7.67]), but not with the change in less-intense, subtle WMH, which determined the volumetric change. CONCLUSION: The new metric is practical and simple to calculate. It is robust to variations in image processing methods and scanning protocols, and sensitive to subtle and severe white matter damage.

Progression of White Matter Disease and Cortical Thinning Are Not Related in Older Community-Dwelling Subjects.

BACKGROUND AND PURPOSE: We assessed cross-sectional and longitudinal relationships between whole brain white matter hyperintensity (WMH) volume and regional cortical thickness. METHODS: We measured WMH volume and regional cortical thickness on magnetic resonance imaging at ≈73 and ≈76 years in 351 community-dwelling subjects from the Lothian Birth Cohort 1936. We used multiple linear regression to calculate cross-sectional and longitudinal associations between regional cortical thickness and WMH volume controlling for age, sex, Mini Mental State Examination, education, intelligence quotient at age 11, and vascular risk factors. RESULTS: We found cross-sectional associations between WMH volume and cortical thickness within and surrounding the Sylvian fissure at 73 and 76 years (rho=-0.276, Q=0.004). However, we found no significant longitudinal associations between (1) baseline WMH volume and change in cortical thickness; (2) baseline cortical thickness and change in WMH volume; or (3) change in WMH volume and change in cortical thickness. CONCLUSIONS: Our results show that WMH volume and cortical thinning both worsen with age and are associated cross-sectionally within and surrounding the Sylvian fissure. However, changes in WMH volume and cortical thinning from 73 to 76 years are not associated longitudinally in these relatively healthy older subjects. The underlying cause(s) of WMH growth and cortical thinning have yet to be fully determined.

Brain volumetric changes and cognitive ageing during the eighth decade of life.

Later-life changes in brain tissue volumes--decreases in the volume of healthy grey and white matter and increases in the volume of white matter hyperintensities (WMH)--are strong candidates to explain some of the variation in ageing-related cognitive decline. We assessed fluid intelligence, memory, processing speed, and brain volumes (from structural MRI) at mean age 73 years, and at mean age 76 in a narrow-age sample of older individuals (n = 657 with brain volumetric data at the initial wave, n = 465 at follow-up). We used latent variable modeling to extract error-free cognitive levels and slopes. Initial levels of cognitive ability were predictive of subsequent brain tissue volume changes. Initial brain volumes were not predictive of subsequent cognitive changes. Brain volume changes, especially increases in WMH, were associated with declines in each of the cognitive abilities. All statistically significant results were modest in size (absolute r-values ranged from 0.114 to 0.334). These results build a comprehensive picture of macrostructural brain volume changes and declines in important cognitive faculties during the eighth decade of life.

Differentiation of calcified regions and iron deposits in the ageing brain on conventional structural MR images.

PURPOSE: In the human brain, minerals such as iron and calcium accumulate increasingly with age. They typically appear hypointense on T2*-weighted MRI sequences. This study aims to explore the differentiation and association between calcified regions and noncalcified iron deposits on clinical brain MRI in elderly, otherwise healthy subjects. MATERIALS AND METHODS: Mineral deposits were segmented on co-registered T1- and T2*-weighted sequences from 100 1.5 Tesla MRI datasets of community-dwelling individuals in their 70s. To differentiate calcified regions from noncalcified iron deposits we developed a method based on their appearance on T1-weighted images, which was validated with a purpose-designed phantom. Joint T1- and T2*-weighted intensity histograms were constructed to measure the similarity between the calcified and noncalcified iron deposits using a Euclidean distance based metric. RESULTS: We found distinct distributions for calcified regions and noncalcified iron deposits in the cumulative joint T1- and T2*-weighted intensity histograms across all subjects (correlations ranging from 0.02 to 0.86; mean = 0.26 ± 0.16; t = 16.93; P < 0.001) consistent with differences in iron and calcium signal in the phantom. The mean volumes of affected tissue per subject for calcified and noncalcified deposits were 236.74 ± 309.70 mm(3) and 283.76 ± 581.51 mm(3); respectively. There was a positive association between the mineral depositions (ß = 0.32, P < 0.005), consistent with existing literature reports. CONCLUSION: Calcified mineral deposits and noncalcified iron deposits can be distinguished from each other by signal intensity changes on conventional 1.5T T1-weighted MRI and are significantly associated in brains of elderly, otherwise healthy subjects.

Validation of the brain health index in the European Prevention of Alzheimer's Dementia cohort.

Background: Brain Health Index (BHI) assimilates various MRI sequences, giving a quantitative measure of brain health. To date, BHI validation has been cross-sectional and limited to selected populations. Further large-scale validation and assessment of temporal change is required to understand its clinical utility. Aim: Assess 1) relationships between variables associated with cognitive decline and BHI 2) associations between BHI and measures of cognition and 3) longitudinal changes in BHI and relationship with cognitive function. Methods: BHI computation involved Gaussian mixture-model cluster analysis of T1, T2, T2*, and T2 FLAIR MRI data from participants within the European Prevention of Alzheimer's Dementia (EPAD) cohort. Group differences (gender- and health-based) were evaluated using independent samples Welch's t-tests. Relationships between BHI, age and cognitive tests used linear regression. Longitudinal analysis (12/24 months) utilised mixed linear regression models to examine BHI changes, and paired BHI/cognition associations. Results: Data from N = 1496 predominantly Caucasian participants (50-88 years old, 43.32% male) were used. BHI scores were lower in those with diabetes (p < 0.001, d = 0.419), hypertension (p < 0.001, d = 0.375), hypercholesterolemia (p < 0.001, d = 0.193) and stroke (p < 0.05, d = 0.512). APOE was not significantly related to BHI scores. After correction for age, cross-sectional BHI scores were significantly associated with all measures of cognitive function in males, but only the Four Mountains Test (4MT) in females. Longitudinal change in BHI and cognition were not consistently related. Conclusions: BHI is a valid marker of cognitive decline and relatively stable over 1-2 year follow-up periods. Further work should assess temporal changes over a longer duration and determine relationships between BHI and cognition in more diverse populations.

Allopurinol and blood pressure variability following ischemic stroke and transient ischemic attack: a secondary analysis of XILO-FIST.

Blood Pressure Variability (BPV) is associated with cardiovascular risk and serum uric acid level. We investigated whether BPV was lowered by allopurinol and whether it was related to neuroimaging markers of cerebral small vessel disease (CSVD) and cognition. We used data from a randomised, double-blind, placebo-controlled trial of two years allopurinol treatment after recent ischemic stroke or transient ischemic attack. Visit-to-visit BPV was assessed using brachial blood pressure (BP) recordings. Short-term BPV was assessed using ambulatory BP monitoring (ABPM) performed at 4 weeks and 2 years. Brain MRI was performed at baseline and 2 years. BPV measures were compared between the allopurinol and placebo groups, and with CSVD and cognition. 409 participants (205 allopurinol; 204 placebo) were included in the visit-to-visit BPV analyses. There were no significant differences found between placebo and allopurinol groups for any measure of visit-to-visit BPV. 196 participants were included in analyses of short-term BPV at week 4. Two measures were reduced by allopurinol: the standard deviation (SD) of systolic BP (by 1.30 mmHg (95% confidence interval (CI) 0.18-2.42, p = 0.023)); and the average real variability (ARV) of systolic BP (by 1.31 mmHg (95% CI 0.31-2.32, p = 0.011)). There were no differences in other measures at week 4 or in any measure at 2 years, and BPV was not associated with CSVD or cognition. Allopurinol treatment did not affect visit-to-visit BPV in people with recent ischemic stroke or TIA. Two BPV measures were reduced at week 4 by allopurinol but not at 2 years.

Close correlation between quantitative and qualitative assessments of white matter lesions.

BACKGROUND: White matter lesions (WML) increase with age and are associated with stroke, cognitive decline and dementia. They can be visually rated or computationally assessed. METHODS: We compared WML Fazekas visual rating scores and volumes, determined using a validated multispectral image-fusion technique, in Magnetic Resonance Imaging from 672 participants of the Lothian Birth Cohort 1936 and sought explanations for subjects in whom the correlation (Spearman's ρ) between the total Fazekas score (summed deep and periventricular ratings, 0-6) and WML volume did not concur (z-score difference >1). Infarcts were identified separately. RESULTS: The median WML Fazekas score was 2 [inter-quartile range (IQR): 2], median WML volume 7.7 ml (IQR: 13.6 ml) and median infarct volume (n = 95) 0.98 ml. Score and volume were highly correlated (Spearman's ρ = 0.78, p < 0.001). Infarcts did not alter the correlation. Minor discordance occurred in 94/672 (14%) subjects, most with total Fazekas score of 1 (n = 20, WML volume = 4.5-14.8 ml) or 2 (n = 50, WML volume = 0.1-34.4 ml). The main reasons were: subtle WML identified visually but omitted from the volume; prominent ventricular caps but thin body lining giving a periventricular score of 1/2 but large WML volume, and small deep focal lesions which increase the score disproportionally when beginning to coalesce with little change in WML volume. CONCLUSIONS: WML rating scores and volumes provide near-equivalent estimates of WML burden, therefore either can be used depending on research circumstances. Even closer agreement could result from improved computational detection of subtle WML and modified visual ratings to differentiate prominent ventricular caps from thin periventricular linings, and small non-coalescent from early coalescent deep WML.

Vagus Nerve Stimulation Paired With Mobility Training in Chronic Ischemic Stroke: A Case Report.

OBJECTIVE: The purpose of this case report is to describe pairing vagus nerve stimulation (VNS) with mobility training in an individual after stroke. METHODS: A 53-year-old man with left hemiparesis 14.2 months after an ischemic stroke participated in a pilot study investigating the safety and feasibility of VNS paired with upper limb rehabilitation. In addition to upper limb impairment, the participant had impaired gait and wanted to improve his mobility. A single-subject design investigation of VNS paired with self-directed mobility training was conducted. Following the conclusion of the pilot study, the participant was instructed to complete daily sessions of self-activated VNS paired with walking or stationary biking. The 10-Meter Walk Test and timed distance (6-Minute Walk Test) were assessed at 4 baseline points and at 3 to 41 months after mobility training. RESULTS: The participant had stable baseline values and was classified as a household ambulator with a quad cane. After VNS-paired mobility training, statistically significant improvements were observed in all measures, with the greatest improvements at 9 months exceeding the minimal detectable change: self-selected gait speed from 0.34 (standard deviation [SD] = 0.01) to 0.60 meters/second, fast gait speed from 0.37 (SD = 0.03) to 0.79 meters/second, and 6-Minute Walk Test distance from 106.91 (SD = 6.38) to 179.83 meters. The participant reported increased confidence and balance when walking. No falls or adverse events were reported. CONCLUSION: The participant demonstrated improved gait speed and timed distance after VNS-paired mobility training. Randomized, blinded trials are needed to determine treatment efficacy. IMPACT: This is the first documented case of VNS-paired mobility training in an individual with chronic poststroke gait impairments. VNS paired with mobility training may improve poststroke gait impairments.

Sleep quality, perivascular spaces and brain health markers in ageing - A longitudinal study in the Lothian Birth Cohort 1936.

BACKGROUND: Sleep is thought to play a major role in brain health and general wellbeing. However, few longitudinal studies have explored the relationship between sleep habits and imaging markers of brain health, particularly markers of brain waste clearance such as perivascular spaces (PVS), of neurodegeneration such as brain atrophy, and of vascular disease, such as white matter hyperintensities (WMH). We explore these associations using data collected over 6 years from a birth cohort of older community-dwelling adults in their 70s. METHOD: We analysed brain MRI data from ages 73, 76 and 79 years, and self-reported sleep duration, sleep quality and vascular risk factors from community-dwelling participants in the Lothian Birth Cohort 1936 (LBC1936) study. We calculated sleep efficiency (at age 76), quantified PVS burden (at age 73), and WMH and brain volumes (age 73 to 79), calculated the white matter damage metric, and used structural equation modelling (SEM) to explore associations and potential causative pathways between indicators related to brain waste cleaning (i.e., sleep and PVS burden), brain and WMH volume changes during the 8th decade of life. RESULTS: Lower sleep efficiency was associated with a reduction in normal-appearing white matter (NAWM) volume (ß = 0.204, P = 0.009) from ages 73 to 79, but not concurrent volume (i.e. age 76). Increased daytime sleep correlated with less night-time sleep (r = -0.20, P < 0.001), and with increasing white matter damage metric (ß = -0.122, P = 0.018) and faster WMH growth (ß = 0.116, P = 0.026). Shorter night-time sleep duration was associated with steeper 6-year reduction of NAWM volumes (ß = 0.160, P = 0.011). High burden of PVS at age 73 (volume, count, and visual scores), was associated with faster deterioration in white matter: reduction of NAWM volume (ß = -0.16, P = 0.012) and increasing white matter damage metric (ß = 0.37, P < 0.001) between ages 73 and 79. On SEM, centrum semiovale PVS burden mediated 5% of the associations between sleep parameters and brain changes. CONCLUSION: Sleep impairments, and higher PVS burden, a marker of impaired waste clearance, were associated with faster loss of healthy white matter and increasing WMH in the 8th decade of life. A small percentage of the effect of sleep in white matter health was mediated by the burden of PVS consistent with the proposed role for sleep in brain waste clearance.

Xanthine oxidase inhibition and white matter hyperintensity progression following ischaemic stroke and transient ischaemic attack (XILO-FIST): a multicentre, double-blinded, randomised, placebo-controlled trial.

Background: People who experience an ischaemic stroke are at risk of recurrent vascular events, progression of cerebrovascular disease, and cognitive decline. We assessed whether allopurinol, a xanthine oxidase inhibitor, reduced white matter hyperintensity (WMH) progression and blood pressure (BP) following ischaemic stroke or transient ischaemic attack (TIA). Methods: In this multicentre, prospective, randomised, double-blinded, placebo-controlled trial conducted in 22 stroke units in the United Kingdom, we randomly assigned participants within 30-days of ischaemic stroke or TIA to receive oral allopurinol 300 mg twice daily or placebo for 104 weeks. All participants had brain MRI performed at baseline and week 104 and ambulatory blood pressure monitoring at baseline, week 4 and week 104. The primary outcome was the WMH Rotterdam Progression Score (RPS) at week 104. Analyses were by intention to treat. Participants who received at least one dose of allopurinol or placebo were included in the safety analysis. This trial is registered with ClinicalTrials.gov, NCT02122718. Findings: Between 25th May 2015 and the 29th November 2018, 464 participants were enrolled (232 per group). A total of 372 (189 with placebo and 183 with allopurinol) attended for week 104 MRI and were included in analysis of the primary outcome. The RPS at week 104 was 1.3 (SD 1.8) with allopurinol and 1.5 (SD 1.9) with placebo (between group difference -0.17, 95% CI -0.52 to 0.17, p = 0.33). Serious adverse events were reported in 73 (32%) participants with allopurinol and in 64 (28%) with placebo. There was one potentially treatment related death in the allopurinol group. Interpretation: Allopurinol use did not reduce WMH progression in people with recent ischaemic stroke or TIA and is unlikely to reduce the risk of stroke in unselected people. Funding: The British Heart Foundation and the UK Stroke Association.

Do brain image databanks support understanding of normal ageing brain structure? A systematic review.

OBJECTIVE: To document accessible magnetic resonance (MR) brain images, metadata and statistical results from normal older subjects that may be used to improve diagnoses of dementia. METHODS: We systematically reviewed published brain image databanks (print literature and Internet) concerned with normal ageing brain structure. RESULTS: From nine eligible databanks, there appeared to be 944 normal subjects aged ≥60 years. However, many subjects were in more than one databank and not all were fully representative of normal ageing clinical characteristics. Therefore, there were approximately 343 subjects aged ≥60 years with metadata representative of normal ageing, but only 98 subjects were openly accessible. No databank had the range of MR image sequences, e.g. T2*, fluid-attenuated inversion recovery (FLAIR), required to effectively characterise the features of brain ageing. No databank supported random subject retrieval; therefore, manual selection bias and errors may occur in studies that use these subjects as controls. Finally, no databank stored results from statistical analyses of its brain image and metadata that may be validated with analyses of further data. CONCLUSION: Brain image databanks require open access, more subjects, metadata, MR image sequences, searchability and statistical results to improve understanding of normal ageing brain structure and diagnoses of dementia. KEY POINTS: • We reviewed databanks with structural MR brain images of normal older people. • Among these nine databanks, 98 normal subjects ≥60 years were openly accessible. • None had all the required sequences, random subject retrieval or statistical results. • More access, subjects, sequences, metadata, searchability and results are needed. • These may improve understanding of normal brain ageing and diagnoses of dementia.

Contribution of white matter hyperintensities to ventricular enlargement in older adults.

Lateral ventricles might increase due to generalized tissue loss related to brain atrophy. Alternatively, they may expand into areas of tissue loss related to white matter hyperintensities (WMH). We assessed longitudinal associations between lateral ventricle and WMH volumes, accounting for total brain volume, blood pressure, history of stroke, cardiovascular disease, diabetes and smoking at ages 73, 76 and 79, in participants from the Lothian Birth Cohort 1936, including MRI data from all available time points. Lateral ventricle volume increased steadily with age, WMH volume change was more variable. WMH volume decreased in 20% and increased in remaining subjects. Over 6 years, lateral ventricle volume increased by 3% per year of age, 0.1% per mm Hg increase in blood pressure, 3.2% per 1% decrease of total brain volume, and 4.5% per 1% increase of WMH volume. Over time, lateral ventricle volumes were 19% smaller in women than men. Ventricular and WMH volume changes are modestly associated and independent of general brain atrophy, suggesting that their underlying processes do not fully overlap.

Cortical thickness, white matter hyperintensities, and cognition after stroke.

BACKGROUND: A thinner cerebral cortex is associated with higher white matter hyperintensity burden and cognitive impairment in community-dwelling and dementia cohorts. It is important to assess these associations in people with ischemic stroke because their cerebrovascular disease profiles are different to these cohorts. AIMS: We aimed to determine whether cortical thickness was related to white matter hyperintensity burden and cognition after ischemic stroke. METHODS: We measured cortical thickness using advanced normalization tools' "KellyKapowski" function in 244 patients with ischemic stroke or transient ischemic attack from the Virtual International Stroke Trials Archive. We measured white matter hyperintensity burden via quantitative volumes and Fazekas score. We extracted data on vascular risk factors at baseline and Mini Mental State Examination scores at one year. We assessed associations between imaging and clinical data using correlation and multiple linear regression. RESULTS: Pairwise correlation showed that higher white matter hyperintensity Fazekas score was associated with a thinner cortex (rho = -0.284, P < 0.0001). White matter hyperintensities were generally distributed adjacent to and above the lateral ventricles. Voxel-wise analyses showed statistically significant negative associations between cortical thickness and white matter hyperintensities across fronto-temporal and inferior parietal cortical regions. Mean cortical thickness was positively related to Mini Mental State Examination in pair-wise correlation (r = 0.167, P = 0.0088) but there was no independent association after adjustment for age and white matter hyperintensities (beta = 0.016, P = 0.7874). CONCLUSIONS: Cortical thickness was not an independent predictor of cognition after ischemic stroke. Further work is required to understand how white matter hyperintensities are associated with a thinner cortex in temporal regions but less so in more superior regions where white matter hyperintensities are generally found in people with stroke.