8 research outputs found

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

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    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; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−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.S.-L.L. is supported by NIH K01 HD091283; NIH R01 NS115845. A.B. and M.S.K. are supported by National Health and Medical Research Council (NHMRC) GNT1020526, GNT1045617 (A.B.), GNT1094974, and Heart Foundation Future Leader Fellowship 100784 (A.B.). P.M.T. is supported by NIH U54 EB020403. L.A.B. is supported by the Canadian Institutes of Health Research (CIHR). C.M.B. is supported by NIH R21 HD067906. W.D.B. is supported by the Heath Research Council of New Zealand. J.M.C. is supported by NIH R00HD091375. A.B.C. is supported by NIH R01NS076348-01, Hospital Israelita Albert Einstein 2250-14, CNPq/305568/2016-7. A.N.D. is supported by funding provided by the Texas Legislature to the Lone Star Stroke Clinical Trial Network. Its contents are solely the responsibility of the authors and do not necessarily represent the of ficial views of the Government of the United States or the State of Texas. N.E.-B. is supported by Australian Research Council NIH DE180100893. W.F. is sup ported by NIH P20 GM109040. F.G. is supported by Wellcome Trust (093957). B.H. is funded by and NHMRC fellowship (1125054). S.A.K is supported by NIH P20 HD109040. F.B. is supported by Italian Ministry of Health, RC 20, 21. N.S. is supported by NIH R21NS120274. N.J.S. is supported by NIH/National Institute of General Medical Sciences (NIGMS) 2P20GM109040-06, U54-GM104941. S.R.S. is supported by European Research Council (ERC) (NGBMI, 759370). G.S. is supported by Italian Ministry of Health RC 18-19-20-21A. M.T. is sup ported by National Institute of Neurological Disorders and Stroke (NINDS) R01 NS110696. G.T.T. is supported by Temple University sub-award of NIH R24 –NHLBI (Dr Mickey Selzer) Center for Experimental Neurorehabilitation Training. N.J.S. is funded by NIH/National Institute of Child Health and Human Development (NICHD) 1R01HD094731-01A1

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

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    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 (β = 0.21; 95% CI 0.04-0.38, 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

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

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    Diffusion-weighted imaging has produced useful biomarkers of verbal fluency post-stroke but acquiring diffusion data is not always clinically feasible. Further, it has been demonstrated that subcortical regions may contribute to verbal fluency, though the predominant focus in the literature has been on cortical contributions to verbal fluency. Finally, the majority of recovery-oriented research on language in stroke has been cross-sectional, which does not allow for actual modelling of language change over time. Focusing on the contribution of subcortical and white matter structures to language recovery of individuals with ischaemic stroke, our present study, therefore, used the information of white matter disconnection and volumetric measurements obtained directly from non-diffusion-weighted anatomical images (T1, T2 and FLAIR), which are routinely acquired in clinical settings, to understand verbal fluency performance over time. We derived neuropsychological and anatomical neuroimaging data of individuals at 3- and 12-months post-stroke from the Cognition And Neocortical Volume After Stroke study, a longitudinal study of ischaemic stroke survivors and healthy stroke-free individuals. Cortical volumetric and thickness measurements were derived from FreeSurfer. White matter disconnection was quantified by two metrics based on BCBToolkit: Disconnection severity – the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability – the probability of the overlap between a subject’s lesion and a tract. Using the linear mixed multiple regression method based on 5-fold cross-validation, we correlated the semantic and phonemic fluency scores of participants with longitudinal measurements of subcortical grey matter volume and 22 literature-driven bilateral white matter tracts of interests, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness at both time points. Our results showed that the right subcortical grey matter volume was positively associated with phonemic fluency (p &lt; 0.05) from 3 months to 12 months post-stroke and the model predictions improved with cross-validation. The disconnection probability of the left superior longitudinal fasciculus II and the left posterior arcuate fasciculus was negatively correlated to semantic fluency (p &lt; 0.05) from 3 months to 12 months post-stroke, but this model did not generalize well following cross-validation. We conclude that subcortical grey matter volume is strongly related to phonemic fluency recovery after stroke, and that the association of white matter disruptions with semantic fluency recovery are strongly influenced by the specific lesion features of the stroke patients within the present study

    Fixel-based Analysis of Diffusion MRI: Methods, Applications, Challenges and Opportunities

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    Diffusion MRI has provided the neuroimaging community with a powerful tool to acquire in-vivo data sensitive to microstructural features of white matter, up to 3 orders of magnitude smaller than typical voxel sizes. The key to extracting such valuable information lies in complex modelling techniques, which form the link between the rich diffusion MRI data and various metrics related to the microstructural organisation. Over time, increasingly advanced techniques have been developed, up to the point where some diffusion MRI models can now provide access to properties specific to individual fibre populations in each voxel in the presence of multiple "crossing" fibre pathways. While highly valuable, such fibre-specific information poses unique challenges for typical image processing pipelines and statistical analysis. In this work, we review the "fixel-based analysis" (FBA) framework that implements bespoke solutions to this end, and has recently seen a stark increase in adoption for studies of both typical (healthy) populations as well as a wide range of clinical populations. We describe the main concepts related to fixel-based analyses, as well as the methods and specific steps involved in a state-of-the-art FBA pipeline, with a focus on providing researchers with practical advice on how to interpret results. We also include an overview of the scope of current fixel-based analysis studies (until August 2020), categorised across a broad range of neuroscientific domains, listing key design choices and summarising their main results and conclusions. Finally, we critically discuss several aspects and challenges involved with the fixel-based analysis framework, and outline some directions and future opportunities

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

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    Background and objectives: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. Here, we examined the impact of brain age, a measure of neurobiological aging derived from whole brain structural neuroimaging, on post-stroke 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 versus poor outcomes./ Methods: We conducted a cross-sectional observational study using a multi-site dataset of 3D brain structural MRIs and clinical measures from 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 three-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 versus 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 (β=0.21; 95% CI 0.04,0.38, P=0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (β=-0.28; 95% CI: -0.41,-0.15, P<0.001) and across multiple domains of function (β=-0.14; 95% CI: -0.22,-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 (OR=1.04, 95% CI: 1.01,1.08, P=0.004)./ Conclusions: We provide evidence that younger brain age is associated with superior post-stroke 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 post-stroke outcomes compared to focal injury measures alone, opening new possibilities for potential therapeutic targets.
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