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Background and ObjectivesCerebral 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.MethodsPatients 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–correctedp< 0.05, nonparametric testing over 5,000 permutations).ResultsWe 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.DiscussionWe 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 InformationClinicalTrails.govNCT02205424.

Background and ObjectivesFunctional 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.MethodsWe 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.ResultsWe 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 to −0.15,p< 0.001) and across multiple domains of function (β = −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).DiscussionWe 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.

Sensorimotor performance after stroke is strongly related to focal injury measures such as corticospinal tract lesion load. 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 sensorimotor outcomes. We hypothesized that stroke lesion damage would result in older brain age, which would in turn be associated with poorer sensorimotor outcomes. We also expected that brain age would mediate the impact of lesion damage on sensorimotor outcomes and that these relationships would be driven by post-stroke secondary atrophy (e.g., strongest in the ipsilesional hemisphere in chronic stroke). We further hypothesized that structural brain resilience, which we define in the context of stroke as the brain’s ability to maintain its global integrity despite focal lesion damage, would differentiate people with better versus worse outcomes.We analyzed cross-sectional high-resolution brain MRI and outcomes data from 963 people with stroke from 38 cohorts worldwide using robust linear mixed-effects regressions to examine the relationship between sensorimotor behavior, lesion damage, and brain age. We used a mediation analysis to examine whether brain age mediates the impact of lesion damage on stroke outcomes and if associations are driven by ipsilesional measures in chronic (≥180 days) stroke. We assessed the impact of brain resilience on sensorimotor outcome using logistic regression with propensity score matching on lesion damage.Stroke lesion damage was associated with older brain age, which in turn was associated with poorer sensorimotor outcomes. Brain age mediated the impact of corticospinal tract lesion load on sensorimotor outcomes most strongly in the ipsilesional hemisphere in chronic stroke. Greater brain resilience, as indexed by younger brain age, explained why people have better versus worse sensorimotor outcomes when lesion damage was fixed.We present novel evidence that global brain health is associated with superior post-stroke sensorimotor outcomes and modifies the impact of focal damage. This relationship appears to be due to post-stroke secondary degeneration. Brain resilience provides insight into why some people have better outcomes after stroke, despite similar amounts of focal injury. Inclusion of imaging-based assessments of global brain health may improve prediction of post-stroke sensorimotor outcomes compared to focal injury measures alone. This investigation is important because it introduces the potential to apply novel therapeutic interventions to prevent or slow brain aging from other fields (e.g., Alzheimer’s disease) to stroke.

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 < 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 < 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.

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.

Background Fatigue is associated with poor functional outcomes and increased mortality following stroke. Survivors identify fatigue as one of their key unmet needs. Despite the growing body of research into post-stroke fatigue, the specific neural mechanisms remain largely unknown. Aim This observational study aimed to identify resting state brain activity markers of post-stroke fatigue. Method Sixty-three stroke survivors (22 women; age 30–89 years; mean 67.5 ± 13.4 years) from the Cognition And Neocortical Volume After Stroke study, a cohort study examining cognition, mood, and brain volume in stroke survivors following ischemic stroke, underwent brain imaging three months post-stroke, including a 7-minute resting state functional magnetic resonance imaging. We calculated the fractional amplitude of low-frequency fluctuations, which is measured at the whole-brain level and can detect altered spontaneous neural activity of specific regions. Results Forty-five participants reported experiencing post-stroke fatigue as measured by an item on the Patient Health Questionnaire-9. Fatigued compared to non-fatigued participants demonstrated significantly lower resting-state activity in the calcarine cortex ( p FDR = 0.009, k = 63) and lingual gyrus ( p FDR = 0.025, k = 42) and significantly higher activity in the medial prefrontal cortex ( p FDR = 0.03, k = 45). Conclusions Post-stroke fatigue is associated with posterior hypoactivity and prefrontal hyperactivity reflecting dysfunction within large-scale brain systems such as fronto-striatal-thalamic and frontal-occipital networks. These systems in turn might reflect a relationship between post-stroke fatigue and abnormalities in executive and visual functioning. This whole-brain resting-state study provides new targets for further investigation of post-stroke fatigue beyond the lesion approach.

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.

The relationship between pain and depression is thought to be bidirectional and the underlying neurobiology ‘shared’ between the two conditions. However, these claims are often based on qualitative comparisons of brain regions implicated in pain or depression, while focused quantitative studies of the neurobiology of pain-depression comorbidity are lacking. Particularly, the direction of comorbidity, i.e., pain with depression vs. depression with pain, is rarely addressed. In this systematic review (PROSPERO registration CRD42020219876), we aimed to delineate brain correlates associated with primary pain with concomitant depression, primary depression with concurrent pain, and equal pain and depression comorbidity, using activation likelihood estimation (ALE) meta-analysis. Neuroimaging studies published in English until the 28th of September 2021 were evaluated using PRISMA guidelines. A total of 70 studies were included, of which 26 reported stereotactic coordinates and were analysed with ALE. All studies were assessed for quality by two authors, using the National Institute of Health Quality Assessment Tool. Our results revealed paucity of studies that directly investigated the neurobiology of pain-depression comorbidity. The ALE analysis indicated that pain with concomitant depression was associated with the right amygdala, while depression with concomitant pain was related primarily to the left dorsolateral prefrontal cortex (DLPFC). We provide evidence that pain and depression have a cumulative negative effect on a specific set of brain regions, distinct for primary diagnosis of depression vs. pain.

Introduction Hippocampal subfield volumes are more closely associated with cognitive impairment than whole hippocampal volume in many diseases. Both memory and whole hippocampal volume decline after stroke. Understanding the subfields’ temporal evolution could reveal valuable information about post‐stroke memory. Methods We sampled 120 participants (38 control, 82 stroke), with cognitive testing and 3T‐MRI available at 3 months and 3 years, from the Cognition and Neocortical Volume after Stroke (CANVAS) study. Verbal memory was assessed using the Hopkins Verbal Learning Test‐Revised. Subfields were delineated using FreeSurfer. We used partial Pearson's correlation to assess the associations between subfield volumes and verbal memory scores, adjusting for years of education, sex, and stroke side. Results The left cornu ammonis areas 2/3 and hippocampal tail volumes were significantly associated with verbal memory 3‐month post‐stroke. At 3 years, the associations became stronger and involved more subfields. Discussion Hippocampal subfield volumes may be a useful biomarker for post‐stroke cognitive impairment.