Microstructural features of the cerebral cortex: Implications for predicting epilepsy relapse after drug withdrawal
Ge Tan1, Xiuli Li2, Running Niu2
1From the Epilepsy Center, Department of Neurology, West China Hospital, Sichuan University, No. 37, Guoxue Road, Chengdu 610041, Sichuan Province, China.
Abstract:
A considerable portion of patients with well-controlled seizures and visually normal brain structures experience seizure recurrence after anti-seizure medication is withdrawn. Microstructural abnormalities of the cortex may play an essential role in epilepsy relapse. Patients with idiopathic/cryptogenic epilepsy were registered. At the follow-up endpoint, 18 patients with relapse (PR+ group), 20 patients without relapse (PR- group), and 30 healthy controls were included. High-resolution T1-weighted images were obtained at the time of drug withdrawal. Microstructural features including cortical thickness, surface area, cortical volume and mean curvature in 68 cortical areas were calculated. A general linear model was applied to investigate intergroup differences, and then post hoc analysis was performed. Additionally, factor analysis was conducted to extract components from imaging measures showing a difference between PR- and PR+ groups, and independent associations between components and epilepsy relapse were assessed using a logistic regression model. Cortical thickness of the left paracentral lobule, left temporal pole and right superior frontal gyrus; surface area of the bilateral lingual gyrus and bilateral pericalcarine cortex; and cortical volume of the bilateral pericalcarine cortex had significant intergroup differences (false discovery rate correction, P < 0.05). All measures, except for cortical thickness of the left temporal pole, showed differences between PR- and PR+ groups. Two dominant components were extracted from these measures, and both were independently associated with epilepsy relapse. In conclusion, epilepsy patients with relapse presented distinct microstructural features of cortex at the time of drug withdrawal, which may serve as a potential biomarker for predicting seizure recurrence.
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