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Structural brain networks and functional motor outcome after stroke-a prospective cohort study.

ABSTRACT: The time course of topological reorganization that occurs in the structural connectome after an ischaemic stroke is currently not well understood. We aimed to determine the evolution of structural brain networks in stroke patients with motor deficits and relate changes in their global topology to residual symptom burden and functional impairment. In this prospective cohort study, ischaemic stroke patients with supratentorial infarcts and motor symptoms were assessed longitudinally by advanced diffusion MRI and detailed clinical testing of upper extremity motor function at four time points from the acute to the chronic stage. For each time point, structural connectomes were reconstructed, and whole-hemisphere global network topology was quantified in terms of integration and segregation parameters. Using non-linear joint mixed-effects regression modelling, network evolution was related to lesion volume and clinical outcome. Thirty patients were included for analysis. Graph-theoretical analysis demonstrated that, over time, brain networks became less integrated and more segregated with decreasing global efficiency and increasing modularity. Changes occurred in both stroke and intact hemispheres and, in the latter, were positively associated with lesion volume. Greater change in topology was associated with larger residual symptom burden and greater motor impairment 1, 3 and 12 months after stroke. After ischaemic stroke, brain networks underwent characteristic changes in both ipsi- and contralesional hemispheres. Topological network changes reflect the severity of damage to the structural network and are associated with functional outcome beyond the impact of lesion volume.

SUBMITTER: Schlemm E

PROVIDER: S-EPMC7425342 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Structural brain networks and functional motor outcome after stroke-a prospective cohort study.

Schlemm Eckhard E Schulz Robert R Bönstrup Marlene M Krawinkel Lutz L Fiehler Jens J Gerloff Christian C Thomalla Götz G Cheng Bastian B

Brain communications 20200110 1

The time course of topological reorganization that occurs in the structural connectome after an ischaemic stroke is currently not well understood. We aimed to determine the evolution of structural brain networks in stroke patients with motor deficits and relate changes in their global topology to residual symptom burden and functional impairment. In this prospective cohort study, ischaemic stroke patients with supratentorial infarcts and motor symptoms were assessed longitudinally by advanced di ...[more]

PMID: 32954275

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Project description:Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post-stroke structural brain imaging.

Project description:Background and purposeA majority of people with stroke remain impaired in their functional mobility. The aim of the study was to determine longitudinal changes in functional mobility after stroke.MethodsThe study was of a longitudinal and prospective design. The functional mobility was assessed using the Timed Up-and-Go test on 5 different occasions: 5 days after onset, within 24 hours after discharge, 1 month after discharge, 3 months, and 1 year poststroke. Stroke severity was stratified based on impairments and activity limitations using a baseline cluster analysis. A multilevel model was developed to predict longitudinal progression in functional mobility based on stroke severity.ResultsOne-hundred-thirty-five patients were included at baseline. Two distinct subgroups (moderate stroke [52%] and mild stroke [48%]) were identified based on impairments and activity limitations using clustering. Ninety-one patients were included in the longitudinal analysis. After controlling for age and cognition, significant improvements in functional mobility were found in the moderate stroke group between baseline and 1 year poststroke (mean difference in Timed Up-and-Go test time, -6.4 s, adjusted P<0.001). Patients with moderate stroke had a maximum rate of improvement in functional mobility during the first 3 months poststroke and then declined significantly at 1 year (12% increase in Timed Up-and-Go test time, adjusted P=0.025). Younger patients had better functional mobility. Although there was also a slight improvement in the mild stroke group, it was not statistically significant.ConclusionsThe recovery of functional mobility differs between mild and moderate stroke. Patients with moderate stroke improved their functional mobility during the first 3 months, after which it decreased significantly. These findings suggest that long-term rehabilitation is desirable to maintain and perhaps increase the gained functional mobility. Older patients and those with moderate impairments and activity limitations have particular needs. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01622205.

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Project description:ObjectiveTo investigate structural and functional neural organization in amyotrophic lateral sclerosis (ALS), primary lateral sclerosis (PLS), and progressive muscular atrophy (PMA).MethodsA total of 173 patients with sporadic ALS, 38 patients with PLS, 28 patients with PMA, and 79 healthy controls were recruited from 3 Italian centers. Participants underwent clinical, neuropsychological, and brain MRI evaluations. Using graph analysis and connectomics, global and lobar topologic network properties and regional structural and functional brain connectivity were assessed. The association between structural and functional network organization and clinical and cognitive data was investigated.ResultsCompared with healthy controls, patients with ALS and patients with PLS showed altered structural global network properties, as well as local topologic alterations and decreased structural connectivity in sensorimotor, basal ganglia, frontal, and parietal areas. Patients with PMA showed preserved global structure. Patient groups did not show significant alterations of functional network topologic properties relative to controls. Increased local functional connectivity was observed in patients with ALS in the precentral, middle, and superior frontal areas, and in patients with PLS in the sensorimotor, basal ganglia, and temporal networks. In patients with ALS and patients with PLS, structural connectivity alterations correlated with motor impairment, whereas functional connectivity disruption was closely related to executive dysfunction and behavioral disturbances.ConclusionsThis multicenter study showed widespread motor and extramotor network degeneration in ALS and PLS, suggesting that graph analysis and connectomics might represent a powerful approach to detect upper motor neuron degeneration, extramotor brain changes, and network reorganization associated with the disease. Network-based advanced MRI provides an objective in vivo assessment of motor neuron diseases, delivering potential prognostic markers.

Dataset Information

Structural brain networks and functional motor outcome after stroke-a prospective cohort study.

Publications

Structural brain networks and functional motor outcome after stroke-a prospective cohort study.

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