Tan Ge, Li Xiuli, Jiang Ping, Lei Du, Liu Fangzhou, Xu Yingchun, Cheng Bochao, Gong Qiyong, Liu Ling
Epilepsy Center, Department of Neurology, West China Hospital of Sichuan University, Chengdu, China.
Mental Health Center, West China Hospital of Sichuan University, Chengdu, China.
Neurol Sci. 2025 May;46(5):2235-2248. doi: 10.1007/s10072-024-07958-y. Epub 2025 Jan 11.
This study intents to detect graphical network features associated with seizure relapse following antiseizure medication (ASM) withdrawal. Twenty-four patients remaining seizure-free (SF-group) and 22 experiencing seizure relapse (SR-group) following ASM withdrawal as well as 46 matched healthy participants (Control) were included. Individualized morphological similarity network was constructed using T1-weighted images, and graphic metrics were compared between groups. Relative to the Control, the SF-group exhibited lower local efficiency, while the SR-group displayed lower global and local efficiency and longer characteristic path length. Both patient groups displayed reduced centrality in certain subcortical and cortical nodes than the Control, with a more pronounced reduction in the SR-group. Additionally, the SR-group exhibited lower centrality of the right pallidum than the SF-group. Decreased subcortical-cortical connectivity was found in both patient groups than the Control, with a more extensive decrease in the SR-group. Furthermore, an edge connecting the right pallidum and left middle temporal gyrus exhibited decreased connectivity in the SR-group than in the SF-group. A weaker small-worldization network upon medication withdrawal, potentially underpinned by node decentralization and subcortical-cortical decoupling, may elevate the risk of seizure relapse.
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