Altered Structural Connectome in Temporal Lobe Epilepsy

Abstract

Purpose:To study differences in the whole-brain structural connectomes of patients with left temporal lobe epilepsy (TLE) and healthy control subjects. Materials and Methods:This study was approved by the institutional review board, and all individuals gave signed informed consent. Sixtydirection diffusion-tensor imaging and magnetizationprepared rapid acquisition gradient-echo (MP-RAGE) magnetic resonance imaging volumes were analyzed in 24 patients with left TLE and in 24 healthy control subjects. MP-RAGE volumes were segmented into 1015 regions of interest (ROIs) spanning the entire brain. Deterministic white matter tractography was performed after voxelwise tensor calculation. Weighted structural connectivity matrices were generated by using the pairwise density of connecting fibers between ROIs. Graph theoretical measures of connectivity networks were compared between groups by using linear models with permutation testing. Results:Patients with TLE had 22%-45% reduced (P , .01) distant connectivity in the medial orbitofrontal cortex, temporal cortex, posterior cingulate cortex, and precuneus, compared with that in healthy subjects. However, local connectivity, as measured by means of network efficiency, was increased by 85%-270% (P , .01) in the medial and lateral frontal cortices, insular cortex, posterior cingulate cortex, precuneus, and occipital cortex in patients with TLE as compared with healthy subjects. Conclusion:This study suggests that TLE involves altered structural connectivity in a network that reaches beyond the temporal lobe, especially in the default mode network.q RSNA, 2013

Machine Learning of DTI Structural Brain Connectomes for Lateralization of Temporal Lobe Epilepsy

“…They are also in line with those of previous reports utilizing graph analyses to assess the DTI structural connectome. [11][12][13][14][15] We did not observe the reported paradoxical increase in clustering coefficient or local efficiency, 12,13 and there has been some variation in the reported alteration of the clustering coefficient in patients with TLE. 28 One possible explanation for this discrepancy is that the clustering coefficient depends on the stage of disease; indeed, it has been reported to increase during most of the sclerotic process and decrease in the final stages of disease.…”

“…Several studies have analyzed DTI-based structural connectomes in TLE; the majority have reported altered connectivity to be most prominent within the ipsilateral temporal lobe. [11][12][13][14][15] In recent years, several studies have investigated the performance of machine learning algorithms, such as that of the support vector machine (SVM), for automatic localization of epileptogenic foci using MR voxel-based morphometry (VBM) 2,3 and fMRI. 5 Because graph theory metrics use a subset of numeric parameters to summarize the characteristic properties of huge and complex brain networks, they are mathematically good candidates for a machine learning approach to identify the multivariate feature combinations that best predict an outcome of interest.…”

The brain connectome as a personalized biomarker of seizure outcomes after temporal lobectomy

“…In this context, this goal and methodology is different from regional abnormalities demonstrated from previous groupwise studies from our group and others, indicating groupwise white matter loss, 23,24 connectivity abnormalities, [25][26][27][28][29][30] and neural network rearrangement in patients with TLE. 20,31,32 We assessed the area under the curve (AUC) for the receiver operating characteristic (ROC) curve for each possible connectome link (including only connections from the temporal to extratemporal regions, as described in e-Methods). This was performed to compare seizure-free vs not seizure-free patients, using linkwise Z scores representing the relative distance of the patient's link weight, compared with the weight distribution in controls for that same link.…”

Disrupted Global and Regional Structural Networks and Subnetworks in Children with Localization-Related Epilepsy

“…Differences in findings could be related to different populations of FLE, with our patient population having a wider age range and possibly more severe epilepsy relative to the patients in the study by Vaessen et al 10 Disruption in the global structural network has also been identified in childhood absence epilepsy 28 and adults with TLE. 29,30 Patients with localization-related epilepsy showed reduced regional efficiency affecting multiple regions in the frontal, temporal, and occipital lobes. Liu et al 30 also found that adult patients with left mesial TLE have significantly reduced regional efficiency in multiple regions in the temporal, frontal, and parietal lobes.…”

“…Adult patients with TLE have also shown reduced structural connectivity between the temporal and frontal cortices, including the orbitofrontal cortex. 29,30 The WM tracts connecting the frontal lobe to the temporal and occipital lobes have demonstrated smaller volumes in children with FLE compared with controls, 34 indicating impaired structural connections between the frontal and temporal and occipital lobes. Vaessen et al 4 found that the clustering coefficient was significantly positively correlated with IQ, and path length was negatively correlated with IQ in adults with cryptogenic localizationrelated epilepsy.…”