Emilio Werden

Cortical thickness estimation in longitudinal stroke studies: A comparison of 3 measurement methods

There is considerable controversy about the causes of cognitive decline after stroke, with evidence for both the absence and coexistence of Alzheimer pathology. A reduction in cortical thickness has been shown to be an important biomarker for the progression of many neurodegenerative diseases, including Alzheimers disease (AD). However, brain volume changes following stroke are not well described. Cortical thickness estimation presents an ideal way to detect regional and global post-stroke brain atrophy. In this study, we imaged a group of patients in the first month after stroke and at 3 months. We compared three methods of estimating cortical thickness on unmasked images: one surface-based (FreeSurfer) and two voxel-based methods (a Laplacian method and a registration method, DiRecT). We used three benchmarks for our analyses: accuracy of segmentation (especially peri-lesional performance), reproducibility, and biological validity. We found important differences between these methods in cortical thickness values and performance in high curvature areas and peri-lesional regions, but similar reproducibility metrics. FreeSurfer had less reliance on manual boundary correction than the other two methods, while reproducibility was highest in the Laplacian method. A discussion of the caveats for each method and recommendations for use in a stroke population is included. We conclude that both surface- and voxel-based methods are valid for estimating cortical thickness in stroke populations.

Charting cognitive and volumetric trajectories after stroke: protocol for the Cognition And Neocortical Volume After Stroke (CANVAS) study

Rationale Globally, stroke and dementia are leading causes of disability and mortality. More than one third of stroke patients will develop dementia, but mechanisms are unclear. Aims The study aims to establish whether brain volume change is associated with poststroke dementia, and to elucidate potential causal mechanisms, including genetic markers, amyloid deposition and vascular risk factors. An understanding of whether – and in whom – stroke is neurodegenerative is critical for the strategic use of potential disease-modifying therapies. Hypotheses That stroke patients will exhibit greater brain volume loss than comparable cohorts of stroke-free controls; and that those who develop dementia will exhibit greater brain volume loss than those who do not. Design Advanced brain imaging techniques are used to longitudinally measure brain volume and cortical thickness in 135 stroke patients. Concurrent neuropsychological testing will correlate clinical profile with these measures. Primary outcomes Primary imaging end-point is brain volume change between three-months and three-years poststroke; primary clinical outcome is the presence of dementia at three-years. Secondary outcomes We will examine the correlations with the following variables: dementia subtype; physical activity levels; behavioral dysfunction as measured by patient and caregiver-reported scales; structural and functional brain connectivity disruption; apolipoprotein E; and specific neuropsychological test scores. Discussion Magnetic resonance imaging markers of structural brain aging and performance on neuropsychological tests are powerful predictors of dementia. We need to understand the trajectory of regional brain volume change and cognitive decline in patients after stroke. This will allow future risk stratification for prognostic counseling, service planning, and early therapeutic intervention.

Structural MRI markers of brain aging early after ischemic stroke

Objective: To examine associations between ischemic stroke, vascular risk factors, and MRI markers of brain aging. Methods: Eighty-one patients (mean age 67.5 ± 13.1 years, 31 left-sided, 61 men) with confirmed first-ever (n = 66) or recurrent (n = 15) ischemic stroke underwent 3T MRI scanning within 6 weeks of symptom onset (mean 26 ± 9 days). Age-matched controls (n = 40) completed identical testing. Multivariate regression analyses examined associations between group membership and MRI markers of brain aging (cortical thickness, total brain volume, white matter hyperintensity [WMH] volume, hippocampal volume), normalized against intracranial volume, and the effects of vascular risk factors on these relationships. Results: First-ever stroke was associated with smaller hippocampal volume (p = 0.025) and greater WMH volume (p = 0.004) relative to controls. Recurrent stroke was in turn associated with smaller hippocampal volume relative to both first-ever stroke (p = 0.017) and controls (p = 0.001). These associations remained significant after adjustment for age, sex, education, and, in stroke patients, infarct volume. Total brain volume was not significantly smaller in first-ever stroke patients than in controls (p = 0.056), but the association became significant after further adjustment for atrial fibrillation (p = 0.036). Cortical thickness and brain volumes did not differ as a function of stroke type, infarct volume, or etiology. Conclusions: Brain structure is likely to be compromised before ischemic stroke by vascular risk factors. Smaller hippocampal and total brain volumes and increased WMH load represent proxies for underlying vascular brain injury.

Physical Activity After Stroke Is Associated With Increased Interhemispheric Connectivity of the Dorsal Attention Network

Background. Attention is frequently impaired after stroke, and its impairment is associated with poor quality of life. Physical activity benefits attention in healthy populations and has also been associated with recovery after brain injury. Objective. We investigated the relationship between objectively measured daily physical activity, attention network connectivity, and attention task performance after stroke. We hypothesized that increased daily physical activity would be associated with improved attention network function. Methods. Stroke patients (n = 62; mean age = 67 years, SD = 12.6 years) and healthy controls (n = 27; mean age = 68 years, SD = 6 years) underwent cognitive testing and 7 minutes of functional magnetic resonance imaging in the resting-state. Patients were tested 3 months after ischemic stroke. Physical activity was monitored with an electronic armband worn for 7 days. Dorsal and ventral attention network function was examined using seed-based connectivity analyses. Results. Greater daily physical activity was associated with increased interhemispheric connectivity of the superior parietal lobule in the dorsal attention network (DAN; P < .05, false discovery rate corrected). This relationship was not explained by stroke lesion volume. Importantly, stronger connectivity in this region was related to faster reaction time in 3 attention tasks, as revealed by robust linear regression. The relationship remained after adjusting for age, gray matter volume, and white matter hyperintensity load. Conclusions. Daily physical activity was associated with increased resting interhemispheric connectivity of the DAN. Increased connectivity was associated with faster attention performance, suggesting a cognitive correlate to increased network connectivity. Attentional modulation by physical activity represents a key focus for intervention studies.

Default mode network neurodegeneration reveals the remote effects of ischaemic stroke

Dementia is estimated to occur in 15%–30% patients after ischaemic stroke.1 Stroke may initiate or accelerate neurodegeneration associated with cognitive impairment.1 Brain atrophy is an important marker of neurodegeneration, preceding the emergence of cognitive symptoms in Alzheimer’s disease (AD).2 Atrophy occurs in distributed regions that collectively mirror known brain networks, including the default mode network (DMN). Atrophy and dysfunction within the DMN is evident in healthy ageing, accelerated in pathological ageing2 and evident in acute and subacute stroke.3 Lesion location rarely predicts long-term outcome in stroke. Network-wide changes may better explain neurodegeneration and conversion to dementia after stroke. Atrophy after stroke has not been well investigated and has been limited to cross-sectional studies and regional volume changes. Structural covariance is an increasingly popular method of examining network-wide correlations in morphometric estimates of brain structure, such as cortical thickness or grey matter volume. There is a close relationship between estimates of network-based structural covariance and intrinsic functional network architecture.4 Structural covariance can be tracked over time to reveal changes in brain organisation, either developmental or degenerative, via cross-sectional comparisons within and between groups.4 Cross-sectional differences can be difficult to detect when there is normal variability across individuals.5 Longitudinal imaging has the benefit of overcoming interindividual differences in cortical morphology by using each individual as their own control.5 Longitudinal imaging also provides an opportunity for more direct examination of atrophy within networks by looking at correlations in the rate of cortical atrophy (see figure 1 in the online Supplementary file 1) across the brain, rather than just correlations in the morphometric measure itself. Atrophy across the brain can also be examined by …

STROKOG (stroke and cognition consortium): An international consortium to examine the epidemiology, diagnosis, and treatment of neurocognitive disorders in relation to cerebrovascular disease

The Stroke and Cognition consortium (STROKOG) aims to facilitate a better understanding of the determinants of vascular contributions to cognitive disorders and help improve the diagnosis and treatment of vascular cognitive disorders (VCD).

A comparison of automated segmentation and manual tracing in estimating hippocampal volume in ischemic stroke and healthy control participants

Manual quantification of the hippocampal atrophy state and rate is time consuming and prone to poor reproducibility, even when performed by neuroanatomical experts. The automation of hippocampal segmentation has been investigated in normal aging, epilepsy, and in Alzheimers disease. Our first goal was to compare manual and automated hippocampal segmentation in ischemic stroke and to, secondly, study the impact of stroke lesion presence on hippocampal volume estimation. We used eight automated methods to segment T1-weighted MR images from 105 ischemic stroke patients and 39 age-matched controls sampled from the Cognition And Neocortical Volume After Stroke (CANVAS) study. The methods were: AdaBoost, Atlas-based Hippocampal Segmentation (ABHS) from the IDeALab, Computational Anatomy Toolbox (CAT) using 3 atlas variants (Hammers, LPBA40 and Neuromorphometics), FIRST, FreeSurfer v5.3, and FreeSurfer v6.0-Subfields. A number of these methods were employed to re-segment the T1 images for the stroke group after the stroke lesions were masked (i.e., removed). The automated methods were assessed on eight measures: process yield (i.e. segmentation success rate), correlation (Pearsons R and Shrouts ICC), concordance (Lins RC and Kandalls W), slope ‘a’ of best-fit line from correlation plots, percentage of outliers from Bland-Altman plots, and significance of control−stroke difference. We eliminated the redundant measures after analysing between-measure correlations using Spearmans rank correlation. We ranked the automated methods based on the sum of the remaining non-redundant measures where each measure ranged between 0 and 1. Subfields attained an overall score of 96.3%, followed by AdaBoost (95.0%) and FIRST (94.7%). CAT using the LPBA40 atlas inflated hippocampal volumes the most, while the Hammers atlas returned the smallest volumes overall. FIRST (p = 0.014), FreeSurfer v5.3 (p = 0.007), manual tracing (p = 0.049), and CAT using the Neuromorphometics atlas (p = 0.017) all showed a significantly reduced hippocampal volume mean for the stroke group compared to control at three months. Moreover, masking of the stroke lesions prior to segmentation resulted in hippocampal volumes which agreed less with manual tracing. These findings recommend an automated segmentation without lesion masking as a more reliable procedure for the estimation of hippocampal volume in ischemic stroke.

Left ventricular hypertrophy and cognitive function: a systematic review

Cognitive impairment is common in patients with hypertension. Left ventricular hypertrophy (LVH) is recognised as a marker of hypertension-related organ damage and is a strong predictor of coronary artery disease, heart failure and stroke. There is evidence that LVH is independently associated with cognitive impairment, even after adjustment for the presence of hypertension. We conducted a systematic review that examined cognitive impairment in adults with LVH. Independent searches were performed in Ovid MEDLINE, Ovid psycInfo and PubMed with the terms left ventricular hypertrophy and cognition. Seventy-three studies were identified when both searches were combined. After limiting the search to studies that were: (1) reported in English; (2) conducted in humans; (3) in adults aged 50 years and older; and (4) investigated the relationship between LVH and cognitive performance, nine papers were included in this systematic review. The majority of studies found an association between LVH and cognitive performance. Inspection of results indicated that individuals with LVH exhibited a lower performance in cognitive tests, when compared to individuals without LVH. Memory and executive functions were the cognitive domains that showed a specific vulnerability to the presence of LVH. A possible mechanism for the relationship between LVH and cognition is the presence of cerebral white matter damage. White matter lesions occur frequently in patients with LVH and may contribute to cognitive dysfunction. Together, the results of this review suggest that memory impairment and executive dysfunction are the cognitive domains that showed a particular association with the presence of LVH.

The Post Ischaemic Stroke Cardiovascular Exercise Study: Protocol for a randomised controlled trial of fitness training for brain health

Introduction Compared to healthy individuals, stroke patients have five times the rate of dementia diagnosis within three years. Aerobic exercise may induce neuroprotective mechanisms that help to preserve, and even increase, brain volume and cognition. We seek to determine whether aerobic fitness training helps to protect brain volume and cognitive function after stroke compared to an active, non-aerobic control. Methods In this Phase IIb, single blind, randomised controlled trial, 100 ischaemic stroke participants, recruited at two months post-stroke, will be randomly allocated to either the intervention (aerobic and strength exercise) or active control (stretching and balance training). Participants will attend one-hour, individualised exercise sessions, three days-per-week for eight weeks. Assessments at two months (baseline), four months (post-intervention), and one year (follow-up) post-stroke will measure brain volume, cognition, mood, cardiorespiratory fitness, physical activity, blood pressure and blood biomarkers. Study outcome: Our primary outcome measure is hippocampal volume at four months after stroke. We hypothesise that participants who undertake the prescribed intervention will have preserved hippocampal volume at four months compared to the control group. We also hypothesise that this group will have preserved total brain volume and cognition, better mood, fitness, and higher levels of physical activity, than those receiving stretching and balance training. Discussion The promise of exercise training to prevent, or slow, the accelerated rates of brain atrophy and cognitive decline experienced by stroke survivors needs to be tested. Post Ischaemic Stroke Cardiovascular Exercise Study has the potential, if proven efficacious, to identify a new treatment that could be readily translated to the clinic.

IMAGING VASCULAR NEURODEGENERATION: REGIONAL BRAIN ATROPHY IN THE FIRST YEAR AFTER ISCHEMIC STROKE

genetic study of data-driven AD subtypes identified an association between a limbic-predominant atrophy pattern and rs2479124. This variant is located upstream of TCF7L2, a known risk gene for type 2 diabetes (T2D) [Grant 2006]. Interestingly, subjects with diabetes mellitus have been reported to exhibit more hippocampal and amygdalar atrophy, regardless of vascular pathology, compared to non-diabetic individuals [den Heijer 2003]. Furthermore, variation in TCF7L2 is associated with smaller amygdalar volume in diabetic patients [Ganmore 2017]. We speculate that this novel candidate variant might exert a pleiotropic effect, jointly influencing the phenotypes of T2D and the limbic-predominant AD subtype.