Progressive topological disorganization of brain network in focal epilepsy
Graph theory is a mathematical tool that allows for the analysis and quantification of a brain network.1 It takes into account the full network structure by providing a simple model of the underlying brain connectome, represented by a collection of nodes and edges.1 By reducing the complex network structure of the brain into a set of parameters that characterize specific topological properties of the network, it enables the study of individual nodes and the network as a whole.1 This approach has made a considerable impact on recent studies of brain network, and small‐world architectures have been found in the human brain network.2 The small‐world network is characterized by a high level of integration and segregation.6
Recently, there has also been an emerging role of graph theory in the research of epilepsy,2 and various modalities have been used to evaluate the topological properties, such as electroencephalography (EEG),7 magnetoencephalography (MEG),8 resting state‐functional magnetic resonance imaging (rs‐fMRI),9 cortical thickness or volumes,4 and diffusion tensor image (DTI).11 However, of these modalities, the DTI has been rarely used to investigate the connectivity in patients with focal epilepsy,12 despite the reproducibility of graph theory metrics from structural connectomes based on DTI being remarkably accurate.16 Compared to DTI study, studies of functional connectivity based on EEG, MEG, and rs‐fMRI have dynamic properties over time and a level of within‐subject variability that is caused by changes in signal transmission time delay and local interactions between cells.17 In addition, they are highly modulated by attention, medications, and cognitive state.19 On the other hands, the study based on cortical thickness or volumes can indirectly evaluate structural association using statistical dependence or correlation, whereas DTI study can focus on the quantification of intuitive measurements of axonal fibers, revealing direct structural reorganization and connection. Only a few studies investigated graph theoretical analysis in patients with focal epilepsy based on DTI, and most of them recruited patients with mesial temporal lobe epilepsy.12
Previous studies in patients with focal epilepsy using graph theory analysis have revealed various results, including both a more regular4 and a more random network topology.21 These discrepancies across studies may originate from the differences in the modality of connectivity measures but are likely also influenced by epilepsy‐related factors, such as duration of epilepsy. Thus, studies considering the influences of duration of epilepsy are needed. In addition, the influence of duration of epilepsy on the topological organization of brain network has not been determined.
We aimed to evaluate the influences of the duration of epilepsy on the topological organization of the brain network in focal epilepsy patients with normal MRI using the graph theoretical analysis based on DTI. In addition, we investigated topological organization of brain network in focal epilepsy patients with normal MRI compared with healthy subjects. Our hypothesis was that the topological characteristics were altered in focal epilepsy patients, even with normal MRI, and they were different according to the duration of epilepsy.