Blood pressure variability and leukoaraiosis in acute ischemic stroke

Higher blood pressure, blood pressure variability, and leukoaraiosis are risk factors for early adverse events and poor functional outcome after ischemic stroke, but prior studies differed on whether leukoaraiosis was associated with blood pressure variability, including in ischemic stroke. In the Third International Stroke Trial, blood pressure was measured in the acute phase of ischemic stroke immediately prior to randomization, and at 0.5, 1, and 24 h after randomization. Masked neuroradiologists rated index infarct, leukoaraiosis, and atrophy on CT using validated methods. We characterized blood pressure variation by coefficient of variance and three other standard methods. We measured associations between blood pressure, blood pressure variability, and leukoaraiosis using generalized estimating equations, adjusting for age, and a number of covariates related to treatment and stroke type/severity. Among 3017 patients, mean (±SD) systolic and diastolic blood pressure decreased from 155(±24)/82(±15) mmHg pre-randomization to 146(±23)/78(±14) mmHg 24 h later ( P < 0.005). Mean within-subject coefficient of variance was 0.09 ± 0.05 for systolic and 0.11 ± 0.06 for diastolic blood pressure. Patients with most leukoaraiosis were older and had higher blood pressure than those with least ( P < 0.0001). Although statistically significant in simple pairwise comparisons, no measures of blood pressure variability were associated with leukoaraiosis when adjusting for confounding variables ( P > 0.05), e.g. age. Our results suggest that blood pressure variability is not a potential mechanism to explain the association between leukoaraiosis and poor outcome after acute stroke

Rationale, design and methodology of the image analysis protocol for studies of patients with cerebral small vessel disease and mild stroke

Rationale: Cerebral small vessel disease (SVD) is common in ageing and patients with dementia and stroke. Its manifestations on magnetic resonance imaging (MRI) include white matter hyperintensities, lacunes, microbleeds, perivascular spaces, small subcortical infarcts, and brain atrophy. Many studies focus only on one of these manifestations. A protocol for the differential assessment of all these features is, therefore, needed. Aims: To identify ways of quantifying imaging markers in research of patients with SVD and operationalize the recommendations from the STandards for ReportIng Vascular changes on nEuroimaging guidelines. Here, we report the rationale, design, and methodology of a brain image analysis protocol based on our experience from observational longitudinal studies of patients with nondisabling stroke. Design: The MRI analysis protocol is designed to provide quantitative and qualitative measures of disease evolution including: acute and old stroke lesions, lacunes, tissue loss due to stroke, perivascular spaces, microbleeds, macrohemorrhages, iron deposition in basal ganglia, substantia nigra and brain stem, brain atrophy, and white matter hyperintensities, with the latter separated into intense and less intense. Quantitative measures of tissue integrity such as diffusion fractional anisotropy, mean diffusivity, and the longitudinal relaxation time are assessed in regions of interest manually placed in anatomically and functionally relevant locations, and in others derived from feature extraction pipelines and tissue segmentation methods. Morphological changes that relate to cognitive deficits after stroke, analyzed through shape models of subcortical structures, complete the multiparametric image analysis protocol. Outcomes: Final outcomes include guidance for identifying ways to minimize bias and confounds in the assessment of SVD and stroke imaging biomarkers. It is intended that this information will inform the design of studies to examine the underlying pathophysiology of SVD and stroke, and to provide reliable, quantitative outcomes in trials of new therapies and preventative strategies

Clinical relevance and practical implications of trials of perfusion and angiographic imaging in patients with acute ischaemic stroke:a multicentre cohort imaging study

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The Brain Health Index: Towards a combined measure of neurovascular and neurodegenerative structural brain injury

Background: A structural magnetic resonance imaging measure of combined neurovascular and neurodegenerative burden may be useful as these features often coexist in older people, stroke and dementia. Aim: We aimed to develop a new automated approach for quantifying visible brain injury from small vessel disease and brain atrophy in a single measure, the brain health index. Materials and methods: We computed brain health index in N = 288 participants using voxel-based Gaussian mixture model cluster analysis of T1, T2, T2*, and FLAIR magnetic resonance imaging. We tested brain health index against a validated total small vessel disease visual score and white matter hyperintensity volumes in two patient groups (minor stroke, N = 157; lupus, N = 51) and against measures of brain atrophy in healthy participants (N = 80) using multiple regression. We evaluated associations with Addenbrooke’s Cognitive Exam Revised in patients and with reaction time in healthy participants. Results: The brain health index (standard beta = 0.20–0.59, P < 0.05) was significantly and more strongly associated with Addenbrooke’s Cognitive Exam Revised, including at one year follow-up, than white matter hyperintensity volume (standard beta = 0.04–0.08, P > 0.05) and small vessel disease score (standard beta = 0.02–0.27, P > 0.05) alone in both patient groups. Further, the brain health index (standard beta = 0.57–0.59, P < 0.05) was more strongly associated with reaction time than measures of brain atrophy alone (standard beta = 0.04–0.13, P > 0.05) in healthy participants. Conclusions: The brain health index is a new image analysis approach that may usefully capture combined visible brain damage in large-scale studies of ageing, neurovascular and neurodegenerative disease

The National Institute for Health Research Hyperacute Stroke Research Centres and the ENCHANTED trial: the impact of enhanced research infrastructure on trial metrics and patient outcomes

Background The English National Institute for Health Research Clinical Research Network first established Hyperacute Stroke Research Centres (HSRCs) in 2010 to support multicentre hyperacute (< 9 h) and complex stroke research. We assessed the impact of this investment on research performance and patient outcomes in a post-hoc analysis of country-specific data from a large multicentre clinical trial. Methods Comparisons of baseline, outcome and trial metric data were made for participants recruited to the alteplase-dose arm of the international Enhanced Control of Hypertension and Thrombolysis Stroke study (ENCHANTED) at National Institute for Health Research Clinical Research Network HSRCs and non-HSRCs between June 2012 and October 2015. Results Among 774 ENCHANTED United Kingdom participants (41% female; mean age 72 years), 502 (64.9%) were recruited from nine HSRCs and 272 (35.1%) from 24 non-HSRCs. HSRCs had higher monthly recruitment rates (median 1.5, interquartile interval 1.4–2.2 vs. 0.7, 0.5–1.3; p = 0.01) and shorter randomisation-to-treatment times (2.6 vs. 3.1 min; p = 0.01) compared to non-HSRCs. HSRC participants were younger and had milder stroke severity, but clinically important between-group differences in 90-day death or disability outcomes remained after adjustment for minimisation criteria and important baseline variables at randomisation, whether defined by ordinal modified Rankin scale score shift (adjusted OR 0.82, 95% CI 0.62–1.08; p = 0.15), scores 2 to 6 (adjusted OR 0.71, 95% CI 0.50–1.01; p = 0.05), or scores 3 to 6 (adjusted OR 0.82, 95% CI 0.57–1.17; p = 0.27). There was no significant difference in symptomatic intracerebral haemorrhage, nor heterogeneity in the comparative treatment effects between low- and standard-dose alteplase by HSRCs or non-HSRCs. Conclusions Infrastructure investment in HSRCs was associated with improved research performance metrics, particularly recruitment and time to treatment with clinically important, though not statistically significant, improvements in patient outcomes

The relation between total cerebral small vessel disease burden and gait impairment in patients with minor stroke

Acknowledgements We thank the patients and their families, and the staff of the Brain Research Imaging Centre, Edinburgh, where MRI scanning was performed. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Mild Stroke Study-2 follow up study at three years was funded by Chest Heart Stroke Scotland. The original MSS-2 study was funded by the Wellcome Trust (ref. 088134/Z/09/A) and Row Fogo Charitable Trust. The imaging was performed at the Brain Research Imaging Centre Edinburgh, which is supported by the SINAPSE collaboration and the Chief Scientist Office of the Scottish Government (http://www.bric.ed.ac.uk/). The work was supported by European Union Horizon 2020 (EU H2020), PHC03-15, project No 666881, ’SVDs@Target’, and the Fondation Leducq Transatlantic Network of Excellence for Study of Perivascular Spaces in Small Vessel Disease, ref no. 16 CVD 05. The work reflects the views of the authors and not of the funders. CMJL was supported by the Dutch Alzheimer Foundation and VC holds a NHS Research Scotland Fellowship. The work was performed in the Edinburgh Dementia Research Centre in the UK DementiaResearch InitiativePeer reviewedPublisher PD

Brain age predicts mortality

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N = 2001), then tested in the Lothian Birth Cohort 1936 (N = 669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death