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Journal ArticleDOI

Cortical Thickness of Brain Areas Beyond Stroke Lesions and Sensory-Motor Recovery: A Systematic Review.

01 Jan 2021-Frontiers in Neuroscience (Frontiers Media SA)-Vol. 15, pp 764671
TL;DR: In this article, the effects of cerebral stroke on cortical thickness (CT) beyond the stroke lesion and its association with sensory-motor recovery were evaluated. But, the results of these studies were limited.
Abstract: Background: The clinical outcome of patients suffering from stroke is dependent on multiple factors. The features of the lesion itself play an important role but clinical recovery is remarkably influenced by the plasticity mechanisms triggered by the stroke and occurring at a distance from the lesion. The latter translate into functional and structural changes of which cortical thickness might be easy to quantify one of the main players. However, studies on the changes of cortical thickness in brain areas beyond stroke lesion and their relationship to sensory-motor recovery are sparse. Objectives: To evaluate the effects of cerebral stroke on cortical thickness (CT) beyond the stroke lesion and its association with sensory-motor recovery. Materials and Methods: Five electronic databases (PubMed, Embase, Web of Science, Scopus and the Cochrane Library) were searched. Methodological quality of the included studies was assessed with the Newcastle-Ottawa Scale for non-randomized controlled trials and the Risk of Bias Cochrane tool for randomized controlled trials. Results: The search strategy retrieved 821 records, 12 studies were included and risk of bias assessed. In most of the included studies, cortical thinning was seen at the ipsilesional motor area (M1). Cortical thinning can occur beyond the stroke lesion, typically in regions anatomically connected because of anterograde degeneration. Nonetheless, studies also reported cortical thickening of regions of the unaffected hemisphere, likely related to compensatory plasticity. Some studies revealed a significant correlation between changes in cortical thickness of M1 or somatosensory (S1) cortical areas and motor function recovery. Discussion and Conclusions: Following a stroke, changes in cortical thickness occur both in regions directly connected to the stroke lesion and in contralateral hemisphere areas as well as in the cerebellum. The underlying mechanisms leading to these changes in cortical thickness are still to be fully understood and further research in the field is needed. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020200539; PROSPERO 2020, identifier: CRD42020200539.
Citations
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TL;DR: In this paper , an association between cortical thickness and gamma synchrony was found for MRI-MEG scans. But the authors did not investigate the relationship between the thickness of the cortical cortex and the duration of gamma synchronization.

8 citations

Journal ArticleDOI
TL;DR: In this article , structural plastic changes underlying functional changes together with voxel-based morphometry (VBM) analysis of magnetic resonance imaging data and immunohistochemical analysis using SMI-32 antibody in a macaque model were investigated.
Abstract: Abstract Compensatory plastic changes in the remaining intact brain regions are supposedly involved in functional recovery following stroke. Previously, a compensatory increase in cortical activation occurred in the ventral premotor cortex (PMv), which contributed to the recovery of dexterous hand movement in a macaque model of unilateral internal capsular infarcts. Herein, we investigated the structural plastic changes underlying functional changes together with voxel-based morphometry (VBM) analysis of magnetic resonance imaging data and immunohistochemical analysis using SMI-32 antibody in a macaque model. Unilateral internal capsular infarcts were pharmacologically induced in 5 macaques, and another 5 macaques were used as intact controls for immunohistochemical analysis. Three months post infarcts, we observed significant increases in the gray matter volume (GMV) and the dendritic arborization of layer V pyramidal neurons in the contralesional rostral PMv (F5) as well as the primary motor cortex (M1). The histological analysis revealed shrinkage of neuronal soma and dendrites in the ipsilesional M1 and several premotor cortices, despite not always detecting GMV reduction by VBM analysis. In conclusion, compensatory structural changes occur in the contralesional F5 and M1 during motor recovery following internal capsular infarcts, and the dendritic growth of pyramidal neurons is partially correlated with GMV increase.
Journal ArticleDOI
TL;DR: In this paper , the authors re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from 2 independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender.
Abstract: Abstract Cortical thickness analyses have provided valuable insights into changes in cortical brain structure after stroke and their association with recovery. Across studies though, relationships between cortical structure and function show inconsistent results. Recent developments in diffusion-weighted imaging of the cortex have paved the way to uncover hidden aspects of stroke-related alterations in cortical microstructure, going beyond cortical thickness as a surrogate for cortical macrostructure. We re-analysed clinical and imaging data of 42 well-recovered chronic stroke patients from 2 independent cohorts (mean age 64 years, 4 left-handed, 71% male, 16 right-sided strokes) and 33 healthy controls of similar age and gender. Cortical fractional anisotropy and cortical thickness values were obtained for six key sensorimotor areas of the contralesional hemisphere. The regions included the primary motor cortex, dorsal and ventral premotor cortex, supplementary and pre-supplementary motor areas, and primary somatosensory cortex. Linear models were estimated for group comparisons between patients and controls and for correlations between cortical fractional anisotropy and cortical thickness and clinical scores. Compared with controls, stroke patients exhibited a reduction in fractional anisotropy in the contralesional ventral premotor cortex (P = 0.005). Fractional anisotropy of the other regions and cortical thickness did not show a comparable group difference. Higher fractional anisotropy of the ventral premotor cortex, but not cortical thickness, was positively associated with residual grip force in the stroke patients. These data provide novel evidence that the contralesional ventral premotor cortex might constitute a key sensorimotor area particularly susceptible to stroke-related alterations in cortical microstructure as measured by diffusion MRI and they suggest a link between these changes and residual motor output after stroke.
References
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Journal ArticleDOI
TL;DR: Moher et al. as mentioned in this paper introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses, which is used in this paper.
Abstract: David Moher and colleagues introduce PRISMA, an update of the QUOROM guidelines for reporting systematic reviews and meta-analyses

62,157 citations

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TL;DR: The quality assessment of non-randomized studies is an important component of a thorough meta-analysis of non randomized studies and can dramatically influence the interpretation of meta-analyses, and can even reverse conclusions regarding the effectiveness of an intervention.
Abstract: The quality assessment of non-randomized studies is an important component of a thorough meta-analysis of nonrandomized studies. Low quality studies can lead to a distortion of the summary effect estimate. Recent guidelines for the reporting of meta-analyses of observational studies recommend the assessment of the study quality (MOOSE) [1]. In principal, three categories of quality assessments tools are available: scales, simple checklists, or checklists with a summary judgment (for details see Sanderson et al. 2007 [2]). The results of the quality assessment can be used in several ways such as forming inclusion criteria for the meta-analysis, informing a sensitivity analysis or metaregression, weighting studies, or highlighting areas of methodological quality poorly addressed by the included studies [3]. It has been criticized that the use of summary scores involve inherent weighting of component items including items that may not be related to the validity of the study findings [2]. Sanderson et al. [2] recently identified overall 86 tools for assessing the quality of non-randomized studies. Their review "highlighted the lack of a single obvious candidate tool for assessing quality of observational epidemiological studies" [2]. In the field of randomized trials, it has been shown that the choice of quality scale can dramatically influence the interpretation of meta-analyses, and can even reverse conclusions regarding the effectiveness of an intervention [4]. Wells et al. [5] proposed a scale for assessing the quality of published non-randomized studies in meta-analyses,

10,420 citations

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TL;DR: A set of automated procedures for obtaining accurate reconstructions of the cortical surface are described, which have been applied to data from more than 100 subjects, requiring little or no manual intervention.

9,599 citations

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TL;DR: The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users.
Abstract: Synthesis of multiple randomized controlled trials (RCTs) in a systematic review can summarize the effects of individual outcomes and provide numerical answers about the effectiveness of interventions. Filtering of searches is time consuming, and no single method fulfills the principal requirements of speed with accuracy. Automation of systematic reviews is driven by a necessity to expedite the availability of current best evidence for policy and clinical decision-making. We developed Rayyan ( http://rayyan.qcri.org ), a free web and mobile app, that helps expedite the initial screening of abstracts and titles using a process of semi-automation while incorporating a high level of usability. For the beta testing phase, we used two published Cochrane reviews in which included studies had been selected manually. Their searches, with 1030 records and 273 records, were uploaded to Rayyan. Different features of Rayyan were tested using these two reviews. We also conducted a survey of Rayyan’s users and collected feedback through a built-in feature. Pilot testing of Rayyan focused on usability, accuracy against manual methods, and the added value of the prediction feature. The “taster” review (273 records) allowed a quick overview of Rayyan for early comments on usability. The second review (1030 records) required several iterations to identify the previously identified 11 trials. The “suggestions” and “hints,” based on the “prediction model,” appeared as testing progressed beyond five included studies. Post rollout user experiences and a reflexive response by the developers enabled real-time modifications and improvements. The survey respondents reported 40% average time savings when using Rayyan compared to others tools, with 34% of the respondents reporting more than 50% time savings. In addition, around 75% of the respondents mentioned that screening and labeling studies as well as collaborating on reviews to be the two most important features of Rayyan. As of November 2016, Rayyan users exceed 2000 from over 60 countries conducting hundreds of reviews totaling more than 1.6M citations. Feedback from users, obtained mostly through the app web site and a recent survey, has highlighted the ease in exploration of searches, the time saved, and simplicity in sharing and comparing include-exclude decisions. The strongest features of the app, identified and reported in user feedback, were its ability to help in screening and collaboration as well as the time savings it affords to users. Rayyan is responsive and intuitive in use with significant potential to lighten the load of reviewers.

7,527 citations

Journal ArticleDOI
TL;DR: All-cause age-standardised YLD rates decreased by 3·9% from 1990 to 2017; however, the all-age YLD rate increased by 7·2% while the total sum of global YLDs increased from 562 million (421–723) to 853 million (642–1100).

7,419 citations