The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke.

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

Atrophy of Ipsilesional Hippocampal Subfields Vary Over First Year After Ischemic Stroke.

BACKGROUND: The structural integrity of hippocampal subfields has been investigated in many neurological disorders and was shown to be better associated with cognitive performance than whole hippocampus. In stroke, hippocampal atrophy is linked to cognitive impairment, but it is unknown whether the hippocampal subfields atrophy differently. PURPOSE: To evaluate longitudinal hippocampal subfield atrophy in first year poststroke, in comparison with atrophy in healthy individuals. STUDY TYPE: Cohort. SUBJECTS: A total of 92 ischemic stroke (age: 67 ± 12 years, 63 men) and 39 healthy participants (age: 69 ± 7 years, 24 men). FIELD STRENGTH/SEQUENCE: A3 T/T1-MPRAGE, T2-SPACE, and T2-FLAIR. ASSESSMENT: FreeSurfer (6.0) was used to delineate 12 hippocampal subfields. Whole hippocampal volume was computed as sum of subfield volumes excluding hippocampal fissure volume. Separate assessments were completed for contralesional and ipsilesional hippocampi. STATISTICAL TESTS: A mixed-effect regression model was used to compare subfield volumes cross-sectionally between healthy and stroke groups and longitudinally between 3-month and 12-month timepoints. False discovery rate at 0.05 significance level was used to correct for multiple comparisons. Also, a receiver operating characteristic (ROC) curve analysis was performed to assess differentiation between healthy and stroke participants based on subfield volumes. RESULTS: There were no volume differences between groups at 3 months, but there was a significant difference (P = 0.027) in whole hippocampal volume reduction over time between control and stroke ipsilesionally. Thus, the ipsilesional whole hippocampal volume in stroke became significantly smaller (P = 0.035) at 12 months. The hippocampal tail was the highest single-region contributor (22.7%) to ipsilesional hippocampal atrophy (1.19%) over 9 months. The cornu ammonis areas (CA1) subfield volume reduction was minimal in controls and stroke contralesionally but significant ipsilesionally (P = 0.007). CA1 volume significantly outperformed whole hippocampal volume (P < 0.01) in discriminating between stroke participants and healthy controls in ROC curve analysis. DATA CONCLUSION: Greater stroke-induced effects were observed in the ipsilesional hippocampus anteriorly in CA1 and posteriorly in the hippocampal tail. Atrophy of CA1 and hippocampal tail may provide a better link to cognitive impairment than whole hippocampal atrophy. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3.

Imaging Markers of Brain Frailty and Outcome in Patients With Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: Functional outcome after stroke may be related to preexisting brain health. Several imaging markers of brain frailty have been described including brain atrophy and markers of small vessel disease. We investigated the association of these imaging markers with functional outcome after acute ischemic stroke. METHODS: We retrospectively studied patients with acute ischemic stroke enrolled in the AXIS-2 trial (AX200 in Ischemic Stroke Trial), a randomized controlled clinical trial of granulocyte colony-stimulating factor versus placebo. We assessed the ratio of brain parenchymal volume to total intracerebral volumes (ie, the brain parenchymal fraction) and total brain volumes from routine baseline magnetic resonance imaging data obtained within 9 hours of symptom onset using the unified segmentation algorithm in SPM12. Enlarged perivascular spaces, white matter hyperintensities, lacunes, as well as a small vessel disease burden, were rated visually. Functional outcomes (modified Rankin Scale score) at day 90 were determined. Logistic regression was used to test associations between brain imaging features and functional outcomes. RESULTS: We enrolled 259 patients with a mean age of 69±12 years and 46 % were female. Increased brain parenchymal fraction was associated with higher odds of excellent outcome (odds ratio per percent increase, 1.078 [95% CI, 1.008-1.153]). Total brain volumes and small vessel disease burden were not associated with functional outcome. An interaction between brain parenchymal fraction and large vessel occlusion on excellent outcome was not observed. CONCLUSIONS: Global brain health, as assessed by brain parenchymal fraction on magnetic resonance imaging, is associated with excellent functional outcome after ischemic stroke. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT00927836.

Investigating the microstructural properties of normal-appearing white matter (NAWM) preceding conversion to white matter hyperintensities (WMHs) in stroke survivors.

Using advanced diffusion MRI, we aimed to assess the microstructural properties of normal-appearing white matter (NAWM) preceding conversion to white matter hyperintensities (WMHs) using 3-tissue diffusion signal compositions in ischemic stroke. Data were obtained from the Cognition and Neocortical Volume After Stroke (CANVAS) study. Diffusion-weighted MR and high-resolution structural brain images were acquired 3- (baseline) and 12-months (follow-up) post-stroke. WMHs were automatically segmented and longitudinal assessment at 12-months was used to retrospectively delineate NAWM voxels at baseline converting to WMHs. NAWM voxels converting to WMHs were further dichotomized into either: "growing" WMHs if NAWM adhered to existing WMH voxels, or "isolated de-novo" WMHs if NAWM was unconnected to WMH voxels identified at baseline. Microstructural properties were assessed using 3-tissue diffusion signal compositions consisting of white matter-like (WM-like: TW), gray matter-like (GM-like: TG), and cerebrospinal fluid-like (CSF-like: TC) signal fractions. Our findings showed that NAWM converting to WMHs already exhibited similar changes in tissue compositions at baseline to WMHs with lower TW and increased TC (fluid-like, i.e. free-water) and TG compared to persistent NAWM. We also found that microstructural properties of persistent NAWM were related to overall WMH burden with greater free-water content in patients with high WMH load. These findings suggest that NAWM preceding conversion to WMHs are accompanied by greater fluid-like properties indicating increased tissue water content. Increased GM-like properties may indicate a more isotropic microstructure of tissue reflecting a degree of hindered diffusion in NAWM regions vulnerable to WMH development. These results support the usefulness of microstructural compositions as a sensitive marker of NAWM vulnerability to WMH pathogenesis.

Dynamic Regional Brain Atrophy Rates in the First Year After Ischemic Stroke.

BACKGROUND AND PURPOSE: Brain atrophy can be regarded as an end-organ effect of cumulative cardiovascular risk factors. Accelerated brain atrophy is described following ischemic stroke, but it is not known whether atrophy rates vary over the poststroke period. Examining rates of brain atrophy allows the identification of potential therapeutic windows for interventions to prevent poststroke brain atrophy. METHODS: We charted total and regional brain volume and cortical thickness trajectories, comparing atrophy rates over 2 time periods in the first year after ischemic stroke: within 3 months (early period) and between 3 and 12 months (later period). Patients with first-ever or recurrent ischemic stroke were recruited from 3 Melbourne hospitals at 1 of 2 poststroke time points: within 6 weeks (baseline) or 3 months. Whole-brain 3T magnetic resonance imaging was performed at 3 time points: baseline, 3 months, and 12 months. Eighty-six stroke participants completed testing at baseline; 125 at 3 months (76 baseline follow-up plus 49 delayed recruitment); and 113 participants at 12 months. Their data were compared with 40 healthy control participants with identical testing. We examined 5 brain measures: hippocampal volume, thalamic volume, total brain and hemispheric brain volume, and cortical thickness. We tested whether brain atrophy rates differed between time points and groups. A linear mixed-effect model was used to compare brain structural changes, including age, sex, years of education, a composite cerebrovascular risk factor score, and total intracranial volume as covariates. RESULTS: Atrophy rates were greater in stroke than control participants. Ipsilesional hemispheric, hippocampal, and thalamic atrophy rates were 2 to 4 times greater in the early versus later period. CONCLUSIONS: Regional atrophy rates vary over the first year after stroke. Rapid brain volume loss in the first 3 months after stroke may represent a potential window for intervention. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02205424.

Pervasive White Matter Fiber Degeneration in Ischemic Stroke.

Background and Purpose- We examined if ischemic stroke is associated with white matter degeneration predominantly confined to the ipsi-lesional tracts or with widespread bilateral axonal loss independent of lesion laterality. Methods- We applied a novel fixel-based analysis, sensitive to fiber tract-specific differences within a voxel, to assess axonal loss in stroke (N=104, 32 women) compared to control participants (N=40, 15 women) across the whole brain. We studied microstructural differences in fiber density and macrostructural (morphological) changes in fiber cross-section. Results- In participants with stroke, we observed significantly lower fiber density and cross-section in areas adjacent, or connected, to the lesions (eg, ipsi-lesional corticospinal tract). In addition, the changes extended beyond directly connected tracts, independent of the lesion laterality (eg, corpus callosum, bilateral inferior fronto-occipital fasciculus, right superior longitudinal fasciculus). Conclusions- We conclude that ischemic stroke is associated with extensive neurodegeneration that significantly affects white matter integrity across the whole brain. These findings expand our understanding of the mechanisms of brain volume loss and delayed cognitive decline in stroke.

Three-tissue compositional analysis reveals in-vivo microstructural heterogeneity of white matter hyperintensities following stroke.

White matter hyperintensities (WMHs) are frequently observed on brain scans of older individuals and are associated with cognitive impairment and vascular brain burden. Recent studies have shown that WMHs may only represent an extreme end of a diffuse pathological spectrum of white matter (WM) degeneration. The present study investigated the microstructural characteristics of WMHs using an advanced diffusion MRI modelling approach known as Single-Shell 3-Tissue Constrained Spherical Deconvolution (SS3T-CSD), which provides information on different tissue compartments within each voxel. The SS3T-CSD method may provide complementary information in the interpretation of pathological tissue through the tissue-specific microstructural compositions of WMHs. Data were obtained from stroke patients enrolled in the Cognition and Neocortical Volume After Stroke (CANVAS) study, a study examining brain volume and cognition after stroke. WMHs were segmented using an automated method, based on fluid attenuated inversion recovery (FLAIR) images. Automated tissue segmentation was used to identify normal-appearing white matter (NAWM). WMHs were classified into juxtaventricular, periventricular and deep lesions, based on their distance from the ventricles (3-10 â€‹mm). We aimed to compare in stroke participants the microstructural composition of the different lesion classes of WMHs and compositions of NAWM to assess the in-vivo heterogeneity of these lesions. Results showed that the 3-tissue composition significantly differed between WMHs classes and NAWM. Specifically, the 3-tissue compositions for juxtaventricular and periventricular WMHs both exhibited a relatively greater fluid-like (free water) content, which is compatible with a presence of interstitial fluid accumulation, when compared to deep WMHs. These findings provide evidence of microstructural heterogeneity of WMHs in-vivo and may support new insights for understanding the role of WMH development in vascular neurodegeneration.

Modulation of the Association Between Corticospinal Tract Damage and Outcome After Stroke by White Matter Hyperintensities.

BACKGROUND AND OBJECTIVES: Motor outcomes after stroke relate to corticospinal tract (CST) damage. The brain leverages surviving neural pathways to compensate for CST damage and mediate motor recovery. Thus, concurrent age-related damage from white matter hyperintensities (WMHs) might affect neurologic capacity for recovery after CST injury. The role of WMHs in post-stroke motor outcomes is unclear. In this study, we evaluated whether WMHs modulate the relationship between CST damage and post-stroke motor outcomes. METHODS: We used data from the multisite ENIGMA Stroke Recovery Working Group with T1 and T2/fluid-attenuated inversion recovery imaging. CST damage was indexed with weighted CST lesion load (CST-LL). WMH volumes were extracted with Freesurfer's SAMSEG. Mixed-effects beta-regression models were fit to test the impact of CST-LL, WMH volume, and their interaction on motor impairment, controlling for age, days after stroke, and stroke volume. RESULTS: A total of 223 individuals were included. WMH volume related to motor impairment above and beyond CST-LL (ß = 0.178, 95% CI 0.025-0.331, p = 0.022). Relationships varied by WMH severity (mild vs moderate-severe). In individuals with mild WMHs, motor impairment related to CST-LL (ß = 0.888, 95% CI 0.604-1.172, p < 0.001) with a CST-LL × WMH interaction (ß = -0.211, 95% CI -0.340 to -0.026, p = 0.026). In individuals with moderate-severe WMHs, motor impairment related to WMH volume (ß = 0.299, 95% CI 0.008-0.590, p = 0.044), but did not significantly relate to CST-LL or a CST-LL × WMH interaction. DISCUSSION: WMHs relate to motor outcomes after stroke and modify relationships between motor impairment and CST damage. WMH-related damage may be under-recognized in stroke research as a factor contributing to variability in motor outcomes. Our findings emphasize the importance of brain structural reserve in motor outcomes after brain injury.

Changes in White Matter Microstructure Over 3 Years in People With and Without Stroke.

BACKGROUND AND OBJECTIVES: Cerebral white matter health can be estimated by MRI-derived indices of microstructure. White matter dysfunction is increasingly recognized as a contributor to neurodegenerative disorders affecting cognition and to functional outcomes after stroke. Reduced indices of white matter microstructure have been demonstrated cross-sectionally in stroke survivors compared with stroke-free participants, but longitudinal changes in the structure of white matter after stroke remain largely unexplored. We aimed to characterize white matter micro- and macrostructure over 3 years after stroke and study associations with white matter metrics and cognitive functions. METHODS: Patients with first-ever or recurrent ischemic stroke of any etiology in any vascular territory were compared with stroke-free age- and sex-matched controls. Those diagnosed with hemorrhagic stroke, TIA, venous infarction, or significant medical comorbidities, psychiatric and neurodegenerative disorders, substance abuse, or history of dementia were excluded. Diffusion-weighted MRI data at 3, 12, and 36 months were analyzed using a longitudinal fixel-based analysis, sensitive to fiber tract-specific differences within a voxel. It was used to examine whole-brain white matter degeneration in stroke compared with control participants. We studied microstructural differences in fiber density and macrostructural changes in fiber-bundle cross-section, in relation to cognitive performance. Analyses were performed controlling for age, intracranial volume, and education (family-wise error-corrected p < 0.05, nonparametric testing over 5,000 permutations). RESULTS: We included 71 participants with stroke (age 66 ± 12 years, 22 women) and 36 controls (age 69 ± 5 years, 13 women). We observed extensive white matter structural degeneration across the whole brain, particularly affecting the thalamic, cerebellar, striatal, and superior longitudinal tracts and corpus callosum. Importantly, follow-up regression analyses in 72 predefined tracts showed that the decline in fiber density and cross-section from 3 months to 3 years was associated with worse cognitive performance at 3 years after stroke, especially affecting visuospatial processing, processing speed, language, and recognition memory. DISCUSSION: We conclude that white matter neurodegeneration in ipsi- and contralesional thalamic, striatal, and cerebellar tracts continues to be greater in stroke survivors compared with stroke-free controls. White matter degeneration persists even years after stroke and is associated with poststroke cognitive impairment. TRIAL REGISTRATION INFORMATION: ClinicalTrails.gov NCT02205424.

Neural correlates of verbal fluency revealed by longitudinal T1, T2 and FLAIR imaging in stroke.

Diffusion-weighted imaging has been widely used in the research on post-stroke verbal fluency but acquiring diffusion data is not always clinically feasible. Achieving comparable reliability for detecting brain variables associated with verbal fluency impairments, based on more readily available anatomical, non-diffusion images (T1, T2 and FLAIR), enables clinical practitioners to have complementary neurophysiological information at hand to facilitate diagnosis and treatment of language impairment. Meanwhile, although the predominant focus in the stroke recovery literature has been on cortical contributions to verbal fluency, it remains unclear how subcortical regions and white matter disconnection are related to verbal fluency. Our study thus utilized anatomical scans of ischaemic stroke survivors (n = 121) to identify longitudinal relationships between subcortical volume, white matter tract disconnection, and verbal fluency performance at 3- and 12-months post-stroke. Subcortical grey matter volume was derived from FreeSurfer. We used an indirect probabilistic approach to quantify white matter disconnection in terms of disconnection severity, the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability, the probability of the overlap between the stroke lesion and a tract. These disconnection variables of each subject were identified based on the disconnectome map of the BCBToolkit. Using a linear mixed multiple regression method with 5-fold cross-validations, we correlated the semantic and phonemic fluency scores with longitudinal measurements of subcortical grey matter volume and 22 bilateral white matter tracts, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness. The results showed that the right subcortical grey matter volume was positively correlated with phonemic fluency averaged over 3 months and 12 months. The finding generalized well on the test data. The disconnection probability of left superior longitudinal fasciculus II and left posterior arcuate fasciculus was negatively associated with semantic fluency only on the training data, but the result aligned with our previous study using diffusion scans in the same clinical population. In sum, our results presented evidence that routinely acquired anatomical scans can serve as a reliable source for deriving neural variables of post-stroke verbal fluency performance. The use of this method might provide an ecologically valid and more readily implementable analysis tool.

Optimizing automated white matter hyperintensity segmentation in individuals with stroke.

White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.

White matter hyperintensities modify relationships between corticospinal tract damage and motor outcomes after stroke.

Motor outcomes after stroke relate to corticospinal tract (CST) damage. Concurrent damage from white matter hyperintensities (WMHs) might impact neurological capacity for recovery after CST injury. Here, we evaluated if WMHs modulate the relationship between CST damage and post-stroke motor impairment outcome. We included 223 individuals from the ENIGMA Stroke Recovery Working Group. CST damage was indexed with weighted CST lesion load (CST-LL). Mixed effects beta-regression models were fit to test the impact of CST-LL, WMH volume, and their interaction on motor impairment. WMH volume related to motor impairment above and beyond CST-LL (ß = 0.178, p = 0.022). We tested if relationships varied by WMH severity (mild vs. moderate-severe). In individuals with mild WMHs, motor impairment related to CST-LL (ß = 0.888, p < 0.001) with a CST-LL x WMH interaction (ß = -0.211, 0.026). In individuals with moderate-severe WMHs, motor impairment related to WMH volume (ß = 0.299, p = 0.044), but did not significantly relate to CST-LL or a CST-LL x WMH interaction. WMH-related damage may be under-recognised in stroke research as a factor contributing to variability in motor outcomes. Our findings emphasize the importance of brain structural reserve in motor outcomes after brain injury.

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke.

BACKGROUND AND OBJECTIVES: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. METHODS: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage. RESULTS: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (ß = 0.21; 95% CI 0.04-0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (ß = -0.28; 95% CI -0.41 to -0.15, p < 0.001) and across multiple domains of function (ß = -0.14; 95% CI -0.22 to -0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%-58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01-1.08, p = 0.004). DISCUSSION: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets.

White matter microstructure and verbal fluency.

Poor performance on verbal fluency tasks is associated with an increased risk of post-stroke cognitive impairment. Grey matter regions supporting verbal fluency have been identified via lesion-symptom mapping, but the links between verbal fluency and white matter structure remain less well described. We examined white matter correlates of semantic (Category Fluency Animals) and phonemic or lexical fluency (COWAT FAS) after stroke, accounting for stroke severity measured with the National Institutes of health Stroke Scale (NIHSS), age, sex, and level of education. White matter fibre density and cross-section measures were automatically extracted from 72 tracts, using MRtrix and TractSeg software in 72 ischaemic stroke survivors assessed 3 months after their event. We conducted regression analyses separately for phonemic and semantic fluency for each tract. Worse semantic fluency was associated with lower fibre density in several tracts, including the arcuate fasciculus, superior longitudinal fasciculus, inferior occipito-frontal fasciculus, inferior longitudinal fasciculus, optic radiation, striato-occipital, thalamo-occipital tracts, and inferior cerebellar peduncle. Our stroke sample was heterogenous with largely non-overlapping and predominantly right-lateralised lesions (lesion distribution: left N = 27, right N = 43, bilateral N = 2), dissimilar to previous studies of verbal fluency. Yet, the tracts we identified as correlates of semantic fluency were all left-lateralised. No associations between phonemic fluency performance and fibre density metrics in any of the white matter tracts we extracted survived correction for multiple comparisons, possibly due to the limitations in the selection of tracts and sample characteristics. We conclude that when accounting for the effects of stroke severity, sex, age, and education, semantic fluency is associated with white matter microstructure in the left arcuate fasciculus, superior longitudinal fasciculus, and several occipital tracts, possibly reflecting the disconnection in the sagittal stratum. Our results obtained with fixel-based analysis, complement previous findings obtained with lesions-symptom mapping and neurodegenerative approaches.

Neonatal EEG seizure detection using a new signal structural complexity measure based on matching pursuit decomposition with nonstationary dictionary.

BACKGROUND AND OBJECTIVE: In newborns, it is often difficult to accurately differentiate between seizure and non-seizure based solely on clinical manifestations. This highlights the importance of electroencephalogram (EEG) in the recognition and management of neonatal seizures. This paper proposes an effective algorithm for the detection of neonatal seizure using multichannel EEG. METHODS: Neonatal EEG changes morphology as it alternates between seizure and non-seizure states. A new signal complexity measure based on matching pursuit (MP) decomposition is proposed and used to detect transitions between these two states. The new measure, referred to as weighted structural complexity (WSC), was used for the detection of seizures in 30 newborn EEG records. Multiple IIR filters and an MP-based filter were designed and used to remove artifacts from the EEG data. Geometrical correlation between the EEG data channels was applied to reduce the number of false detections caused by remnant artifacts. The seizure detector's performance was assessed using several epoch-based (e.g., accuracy) and event-based (GDR = good detection rate and FD/h = false detections per hour) metrics. RESULTS: Compared to the neurologist marking, the proposed detector was able to detect EEG seizures with 94% accuracy, 90.9% GDR, and 0.14 FD/h (95% CI: [0.06, 0.34]). CONCLUSIONS: The high performance of the MP-based detector may have significant implications for the accurate diagnosis of neonatal seizures and the appropriate use of anticonvulsants and ongoing clinical assessment and care of the newborn.

Grey and white matter atrophy 1 year after stroke aphasia.

Dynamic whole-brain changes occur following stroke, and not just in association with recovery. We tested the hypothesis that the presence of a specific behavioural deficit after stroke would be associated with structural decline (atrophy) in the brain regions supporting the affected function, by examining language deficits post-stroke. We quantified whole-brain structural volume changes longitudinally (3-12 months) in stroke participants with (N = 32) and without aphasia (N = 59) as assessed by the Token Test at 3 months post-stroke, compared with a healthy control group (N = 29). While no significant difference in language decline rates (change in Token Test scores from 3 to 12 months) was observed between groups and some participants in the aphasic group improved their scores, stroke participants with aphasia symptoms at 3 months showed significant atrophy (>2%, P = 0.0001) of the left inferior frontal gyrus not observed in either healthy control or non-aphasic groups over the 3-12 months period. We found significant group differences in the inferior frontal gyrus volume, accounting for age, sex, stroke severity at baseline, education and total intracranial volume (Bonferroni-corrected P = 0.0003). In a subset of participants (aphasic N = 14, non-aphasic N = 36, and healthy control N = 25) with available diffusion-weighted imaging data, we found significant atrophy in the corpus callosum and the left superior longitudinal fasciculus in the aphasic compared with the healthy control group. Language deficits at 3 months post-stroke are associated with accelerated structural decline specific to the left inferior frontal gyrus, highlighting that known functional brain reorganization underlying behavioural improvement may occur in parallel with atrophy of brain regions supporting the language function.

Poststroke White Matter Hyperintensities and Physical Activity: A CANVAS Study Exploratory Analysis.

PURPOSE: White matter hyperintensities (WMHs) are associated with poststroke cognitive decline and mortality. Physical activity (PA) may decrease WMH risk by reducing vascular risk factors and promoting cerebral perfusion. However, the association between poststroke PA and WMH progression remains unclear. We examined the association between PA and WMH volume 12 months after stroke, and between PA and change in WMH volume between 3 and 12 months after stroke. METHODS: We included ischemic stroke survivors from the Cognition And Neocortical Volume After Stroke cohort with available brain magnetic resonance imaging and objective PA data. Total, periventricular, and deep WMH volumes (in milliliters) were estimated with manually edited, automated segmentations (Wisconsin White Matter Hyperintensities Segmentation toolbox). Moderate-to-vigorous intensity PA (MVPA) was estimated using the SenseWear® Armband. Participants with MVPA ≥30 min·d -1 were classified as "meeting PA guidelines." We used quantile regression to estimate the associations between PA (MVPA and meeting PA guidelines) with WMH volume at 12 months and change in WMH volume between 3 and 12 months after stroke. RESULTS: A total of 100 participants were included (median National Institutes of Health Stroke Scale 2; interquartile range, 1-4). MVPA was not associated with WMH volume. In univariable analysis, meeting PA guidelines was associated with lower total, periventricular, and deep WMH volumes by 3.0 mL (95% confidence interval (CI), 0.5-9.7 mL), 2.8 mL (95% CI, 0.5-7.1 mL), and 0.9 mL (95% CI, 0.1-3.0 mL), respectively. However, in multivariable analysis, meeting PA guidelines was not associated with WMH volume, and older age was associated with greater WMH volume at 12 months. PA was not associated with change in WMH volume. CONCLUSIONS: Meeting PA guidelines was associated with lower WMH volume at 12 months in univariable analysis, but not in multivariable analysis. Age consistently predicted greater WMH volume.

Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis.

Background Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper-limb sensorimotor impairment. We investigated associations between non-lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results Cross-sectional T1-weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta-Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA-UE (Fugl-Meyer Assessment of Upper Extremity). Robust mixed-effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni-corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; ß=0.16) but not contralesional (P=0.96; ß=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; ß=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; ß=-0.26) and contralesional (P=0.006; ß=-0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; ß=-0.21) and extent of sensorimotor damage (P=0.003; ß=-0.15). Conclusions The present study identifies novel associations between chronic poststroke sensorimotor impairment and ipsilesional hippocampal volume that are not caused by lesion size and may be stronger in women.

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research.

Hippocampal Volume and Amyloid PET Status Three Years After Ischemic Stroke: A Pilot Study.

Hippocampal atrophy is seen in many neurodegenerative disorders and may be a cardinal feature of vascular neurodegeneration. We examined hippocampal volume (HV) in a group of ischemic stroke survivors with amyloid 18F-NAV4694 PET imaging three years after stroke. We compared HV between the amyloid-positive (n = 4) and amyloid-negative (n = 29) groups, and associations with co-morbidities using Charlson Comorbidity Indices and multi-way ANOVA. Amyloid status was not associated with verbal or visual delayed free recall memory indices or cognitive impairment. We found no association between amyloid status and HV in this group of ischemic stroke survivors.