Differential alterations of structural network in temporal lobe epilepsy with different seizure types are associated with cognitive and psychiatric status

Xuemei Chen; Xiao Zhang; Bailing Qin; Dongying Huang; Cuimi Luo; Huachun Huang; Qin Zhou; Zirong Chen; Jinou Zheng

doi:10.1016/j.yebeh.2024.110228

Differential alterations of structural network in temporal lobe epilepsy with different seizure types are associated with cognitive and psychiatric status

Epilepsy Behav. 2024 Dec 26:163:110228. doi: 10.1016/j.yebeh.2024.110228. Online ahead of print.

Authors

Xuemei Chen¹, Xiao Zhang¹, Bailing Qin¹, Dongying Huang¹, Cuimi Luo¹, Huachun Huang¹, Qin Zhou¹, Zirong Chen¹, Jinou Zheng²

Affiliations

¹ Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
² Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China. Electronic address: [email protected].

PMID: 39729685
DOI: 10.1016/j.yebeh.2024.110228

Abstract

Background: The fundamental pathophysiologic understanding of different seizure types in Temporal lobe epilepsy (TLE) remains unclear. This study aimed to assess the distinct alterations of structural network in TLE patients with different seizure types and their relationships with cognitive and psychiatric symptoms.

Methods: Seventy-three patients with unilateral TLE, including 25 with uncontrolled focal to bilateral tonic-clonic seizures (FBTCS), 25 with controlled FBTCS and 23 with focal impaired awareness seizures (FIAS), as well as 26 healthy controls (HC), underwent the diffusion tensor imaging (DTI) scan. Network-based statistic (NBS) and graph theory analyses were employed to investigate the structural network and its topological properties. Partial correlation analyses were conducted to examine the relationships between clinical variables and disrupted network characteristics. Additionally, the support vector machine (SVM) algorithm was utilized for the classification of controlled and uncontrolled FBTCS.

Results: Compared to HC, TLE seizure type subgroups presented differently aberrant SC within the frontostriatal network. Additionally, alterations in the rich club organization and global network metrics were observed only in FBTCS. Notably, a significant decrease in all nodal metrics of the right amygdala were observed within the uncontrolled FBTCS group compared to the other three groups. Additionally, the disrupted nodal properties were significantly correlated with the age of onset, duration of epilepsy and psychiatric symptoms in FBTCS. Furthermore, the classifier achieved notably high accuracy (98%) in distinguishing between controlled and uncontrolled FBTCS.

Conclusions: Our findings may contribute to elucidating the neuropathological mechanisms of different seizure types in TLE and their impacts on cognitive and psychiatric status. SVM algorithm combined with nodal properties holds promise for predicting the poor seizure control of FBTCS.

Keywords: Diffusion tensor imaging; Focal impaired awareness seizures; Focal to bilateral tonic-clonic seizures; Psychiatric symptoms; Support vector machine; Tractography.