The structural connectome and motor recovery after stroke: predicting natural recovery

Stroke patients vary considerably in terms of outcomes: some patients present ‘natural’ recovery proportional to their initial impairment (fitters), while others do not (non-fitters). Thus, a key challenge in stroke rehabilitation is to identify individual recovery potential to make personalized decisions for neuro-rehabilitation, obviating the ‘one-size-fits-all’ approach. This goal requires (i) the prediction of individual courses of recovery in the acute stage; and (ii) an understanding of underlying neuronal network mechanisms. ‘Natural’ recovery is especially variable in severely impaired patients, underscoring the special clinical importance of prediction for this subgroup. Fractional anisotropy connectomes based on individual tractography of 92 patients were analysed 2 weeks after stroke (TA) and their changes to 3 months after stroke (TC − TA). Motor impairment was assessed using the Fugl-Meyer Upper Extremity (FMUE) scale. Support vector machine classifiers were trained to separate patients with natural recovery from patients without natural recovery based on their whole-brain structural connectomes and to define their respective underlying network patterns, focusing on severely impaired patients (FMUE

Whole-brain structural connectivity in temporal lobe epilepsy: a Diffusion Spectrum Imaging study

Alessandro Daducci, Alessandra Griffa, François Lazeyras, Alia Lemkaddem, Jean-Philippe Thiran

Introduction: Medial Temporal Lobe Epilepsy (mTLE) with hippocampal sclerosis is the most frequent cause of drug-resistant focal epilepsy in adults. These patients suffer from widespread subtle white matter abnormalities and abnormal functional connectivity extending beyond the affected lobe, as revealed by Diffusion Tensor Imaging and functional MRI studies. Diffusion spectrum imaging (DSI) is a new diffusion imaging technique with high angular resolution for improving the mapping of white matter tracts [1]. In this study, we used DSI to investigate the whole brain effect of TLE as reflected by topological measures of the structural connectivity network. Methods: Eight patients with right-sided mTLE and hippocampal sclerosis and 25 controls underwent our DSI protocol at 3T using a 32 channel coil: DSI (voxel size 2.2x2.2x3mm; 44 slices, 257 diffusion directions; max b-value = 6400 s/mm2), 3D T1-weighted MPRAGE and 3D T2-weighted images. The analysis was performed using the Connectome Mapper. The cortical and subcortical grey matters were parcellated into 86 Regions of Interest (ROI) with anatomical landmarks using Freesurfer 5.0. The ROIs were coregistered to the diffusion data by using a nonlinear registration between T1 and T2, then T2 to the diffusion space. The Diffusion Tool Kit was used for the reconstruction of the diffusion Orientation Distribution Function in each voxel. Streamline fibre-tracking was then performed from each voxel in the white matter areas using an in-house streamline-based algorithm. Two scalar maps, the Fractional Anisotropy and the Generalized Fractional Anisotropy were calculated. For each patient, the connectivity between every region pair was estimated was used to construct a connectivity matrix (the adjacency matrix of the structural network). Finally we used topological measures in order to reduce the data and obtain whole-brain characteristics of the network [2]: characteristic Path Length (L), Clustering Coefficient (C) and Small Worldness (S) where S=(C/Crand)/(L/ Lrand) with Crand and Lrand are computed for a random network. Significant differences between the mTLE and control groups were assessed using a Wilcoxon rank-sum test. Results: In patients, we found a higher characteristic path length (0.0288), with a lower clustering coefficient (0.0079) and reduced small-worldness (p=0.000058) compared to controls. Network nodes that contributed significantly to these alterations were located within as well as outside the temporal lobe in both hemispheres, although with a predominance for the ipsilateral hemisphere and bilateral limbic structures. The pattern of significant nodes showed concordance with brain regions known to be involved in epileptic networks in patients with mTLE. Conclusions: Our results show a reduced efficiency of structural brain networks and altered connectivity patterns that are concordant with the mapping of functional epileptic networks [3] and altered functional connectivity [4] in patients with mTLE. Therefore, the network in mTLE is less segregated than in controls with reduced global interactions between the nodes and reduced specialised communities. Further studies are needed to establish the relevance of these findings with respect to the propagation of epileptic activity, cognitive deficits in mTLE and outcome of epilepsy surgery in individual patients.

2012

Whole-brain structural connectivity in temporal lobe epilepsy: a Diffusion Spectrum Imaging study

Alessandro Daducci, Alessandra Griffa, François Lazeyras, Alia Lemkaddem, Jean-Philippe Thiran

2012