| Literature DB >> 33372704 |
Qiang Xu1,2, Qirui Zhang1, Fang Yang3, Yifei Weng1,4, Xinyu Xie1, Jingru Hao1, Rongfeng Qi1, Valentina Gumenyuk5, Steven M Stufflebeam5, Boris C Bernhardt4, Guangming Lu1,2,6, Zhiqiang Zhang1,5,6.
Abstract
Generalized tonic-clonic seizures (GTCS) are the severest and most remarkable clinical expressions of human epilepsy. Cortical, subcortical, and cerebellar structures, organized with different network patterns, underlying the pathophysiological substrates of genetic associated epilepsy with GTCS (GE-GTCS) and focal epilepsy associated with focal to bilateral tonic-clonic seizure (FE-FBTS). Structural covariance analysis can delineate the features of epilepsy network related with long-term effects from seizure. Morphometric MRI data of 111 patients with GE-GTCS, 111 patients with FE-FBTS and 111 healthy controls were studied. Cortico-striato-thalao-cerebellar networks of structural covariance within the gray matter were constructed using a Winner-take-all strategy with five cortical parcellations. Comparisons of structural covariance networks were conducted using permutation tests, and module effects of disease duration on networks were conducted using GLM model. Both patient groups showed increased connectivity of structural covariance relative to controls, mainly within the striatum and thalamus, and mostly correlated with the frontal, motor, and somatosensory cortices. Connectivity changes increased as a function of epilepsy durations. FE-FBTS showed more intensive and extensive gray matter changes with volumetric loss and connectivity increment than GE-GTCS. Our findings implicated cortico-striato-thalamo-cerebellar network changes at a large temporal scale in GTCS, with FE-FBTS showing more severe network disruption. The study contributed novel imaging evidence for understanding the different epilepsy syndromes associated with generalized seizures.Entities:
Keywords: cortico-striato-thalamo-cerebellar network; epilepsy; generalized tonic-clonic seizures; morhpometric MRI; structural covariance connecvity
Mesh:
Year: 2020 PMID: 33372704 PMCID: PMC7856655 DOI: 10.1002/hbm.25279
Source DB: PubMed Journal: Hum Brain Mapp ISSN: 1065-9471 Impact factor: 5.399