9 research outputs found

    Altered Topological Organization of White Matter Structural Networks in Patients with Neuromyelitis Optica

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    <div><h3>Objective</h3><p>To investigate the topological alterations of the whole-brain white-matter (WM) structural networks in patients with neuromyelitis optica (NMO).</p> <h3>Methods</h3><p>The present study involved 26 NMO patients and 26 age- and sex-matched healthy controls. WM structural connectivity in each participant was imaged with diffusion-weighted MRI and represented in terms of a connectivity matrix using deterministic tractography method. Graph theory-based analyses were then performed for the characterization of brain network properties. A multiple linear regression analysis was performed on each network metric between the NMO and control groups.</p> <h3>Results</h3><p>The NMO patients exhibited abnormal small-world network properties, as indicated by increased normalized characteristic path length, increased normalized clustering and increased small-worldness. Furthermore, largely similar hub distributions of the WM structural networks were observed between NMO patients and healthy controls. However, regional efficiency in several brain areas of NMO patients was significantly reduced, which were mainly distributed in the default-mode, sensorimotor and visual systems. Furthermore, we have observed increased regional efficiency in a few brain regions such as the orbital parts of the superior and middle frontal and fusiform gyri.</p> <h3>Conclusion</h3><p>Although the NMO patients in this study had no discernible white matter T2 lesions in the brain, we hypothesize that the disrupted topological organization of WM networks provides additional evidence for subtle, widespread cerebral WM pathology in NMO.</p> </div

    Brain regions with significant group effects in nodal efficiency between control and NMO groups.

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    <p>Note: The FN-weighted WM network for each participant was constructed under the threshold T = 3. The comparisons of nodal efficiency were performed between groups for each brain region. <i>p</i><0.05 (uncorrected) was considered significant.</p

    Group differences in global measures of WM structural networks were quantified between control and NMO groups.

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    <p>The FN-weighted network of each subject was constructed with different thresholds (T = 1,2,3,4,5). The threshold (horizontal axis) determined the minimum number of streamlines that needed to interconnect a pair of nodes for a connection to be assumed. Data points marked with a star indicate a significant difference (<i>p</i><0.05) between groups. Significant group effects in normalized path length and normalized clustering were observed for all thresholds considered. A trend of increased small-worldness was also observed in NMO patients versus controls.</p

    Comparisons of global network measures between controls and NMO patients.

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    <p>Note: The WM network with different connectivity metrics (FN-weighted, FA-weighted and binary networks) for each participant was constructed under the threshold T = 3.</p>*<p><i>p</i><0.05 was considered significant. NS: not significant.</p

    A flowchart for the construction of WM structural network by DTI.

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    <p>(1) The rigid coregistration from the T1-weighted structural MRI (b) to DTI native space (a) (DTI color-coded map; red: left to right; green: anterior to posterior; blue: inferior to superior) for each subject. (2) The nonlinear registration from the resultant structural MRI to the ICBM152 T1 template in the MNI space (c), resulting in a nonlinear transformation (T). (3) The application of the inverse transformation (T<sup>−1</sup>) to the AAL template in the MNI space (e), resulting in the subject-specific AAL mask in the DTI native space (f). All registrations were implemented in the SPM8 package. (4) The reconstruction of all of the WM fibers (d) in the whole brain using DTI deterministic tractography in DTIstudio. (5) The weighted networks of each subject (g) were created by computing the fiber numbers (FN-weighted) and the mean FA values (FA-weighted) of the fiber bundles that connected each pair of brain regions. The binary network was created by considering the existence/absence of fiber bundles between two regions. The matrices and 3D representations (lateral view) of the three kinds of WM structural networks of a representative healthy subject were shown in the bottom panel. The nodes are located according to their centroid stereotaxic coordinates, and the edges are coded according to their connection weights. For details, see the Materials and Methods section.</p

    The brain regions with significant group differences in nodal efficiency between control and NMO groups at <i>p</i><0.05 (uncorrected).

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    <p>The node sizes indicate the significance of between-group differences in the regional efficiency. The network shown here was constructed by averaging the WM connection matrices of all healthy controls and thresholded with the sparsity of 10%. The nodal regions are located according to their centroid stereotaxic coordinates. Nodes in blue showed the regions have reduced efficiency in NMO patients versus controls. Nodes in green showed the regions have increased efficiency in NMO patients versus controls. For the abbreviations of nodes, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048846#pone-0048846-t002" target="_blank">Table 2</a>.</p

    Hub Regions of WM networks in control and NMO groups.

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    <p>The hub regions were identified if E<sub>nodal</sub>(i) was at least one SD greater than the mean nodal efficiency of the network (i.e., E<sub>nodal</sub>(i) > mean±SD). The hubs are sorted by the mean normalized nodal efficiency (divided by the mean of all nodes) in each group. The cortical regions are classified as primary, association and paralimibic <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0048846#pone.0048846-Mesulam1" target="_blank">[42]</a>.</p
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