Medial temporal lobe epilepsy is associated with neuronal fibre loss and paradoxical increase in structural connectivity of limbic structures

Abstract

Background: It has been hypothesised that seizure induced neuronal loss and axonal damage in medial temporal lobe epilepsy (MTLE) may lead to the development of aberrant connections between limbic structures and eventually result in the reorganisation of the limbic network. In this study, limbic structural connectivity in patients with MTLE was investigated, using diffusion tensor MRI, probabilistic tractography and graph theory based network analysis.

Methods: 12 patients with unilateral MTLE and hippocampal sclerosis (five left and seven right MTLE) and 26 healthy controls were studied. The connectivity of 10 bilateral limbic regions of interest was mapped with probabilistic tractography, and the probabilistic fibre density between each pair of regions was used as the measure of their weighted structural connectivity. Binary connectivity matrices were then obtained from the weighted connectivity matrix using a range of fixed density thresholds. Graph theory based properties of nodes (degree, local efficiency, clustering coefficient and betweenness centrality) and the network (global efficiency and average clustering coefficient) were calculated from the weight and binary connectivity matrices of each subject and compared between patients and controls.

Results: MTLE was associated with a regional reduction in fibre density compared with controls. Paradoxically, patients exhibited (1) increased limbic network clustering and (2) increased nodal efficiency, degree and clustering coefficient in the ipsilateral insula, superior temporal region and thalamus. There was also a significant reduction in clustering coefficient and efficiency of the ipsilateral hippocampus, accompanied by increased nodal degree.

Conclusions: These results suggest that MTLE is associated with reorganisation of the limbic system. These results corroborate the concept of MTLE as a network disease, and may contribute to the understanding of network excitability dynamics in epilepsy and MTLE.

Figure 1

Locations of the regions of interest employed in this study overlaid onto a T1 weighted template in standard space.

Figure 2

Results from probabilistic tractography obtained from different regions of interest (ROIs) averaged over all subjects. Each three-dimensional brain rendering illustrates the voxel-wise probabilistic map of connectivity from one ROI (from left to right: left anterior cingulate, left inferior orbital region, left hippocampus and left thalamus).

Figure 3

Regional brain connectivity, as depicted by weighted connectivity matrices for controls and patients, and the ensuing matrix of statistical differences. The connectivity matrices for patients and controls illustrate the weight of connection between regions, whereby each cell entry represents a corrected weight of connection between the region depicted on the y and x axes. The scale (0–100) represents the average voxel-wise number of probabilistic defined fibre counts between regions. To facilitate visualisation, regions are number from 1 to 20, representing the numbering adopted in table 1 (with left representing ipsilateral and right contralateral). The difference matrix illustrates the p values obtained from a two sample t test performed between connectivity matrices, showing areas with higher connectivity in controls compared with patients with medial temporal lobe epilepsy.

Figure 4

Results from analyses related to the whole network. The y axis represents the value for the network measure and the x axis represents the fixed density threshold utilised to define a binary matrix. MTLE, medial temporal lobe epilepsy.

Figure 5

Results from the node properties graphical analyses. For each graph, the y axis represents the network measure. The x axis represents the fixed density threshold utilised to define a binary matrix. Each column demonstrates the results for a particular anatomical structure. MTLE, medial temporal lobe epilepsy.