Gray Matter Atrophy: The Impacts of Resective Surgery and Vagus Nerve Stimulation in Drug-Resistant Epilepsy

灰质萎缩:切除手术和迷走神经刺激对药物难治性癫痫的影响

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Abstract

BACKGROUND: There is great concern for cognitive function after resective temporal lobe surgery for drug-resistant epilepsy. However, few studies have investigated postoperative anatomical changes, and the downstream effects of surgery are poorly understood. This study investigated volumetric changes after resective surgery and vagus nerve stimulation (VNS) for epilepsy. METHODS: Preoperative and latest postoperative (mean, 28 months) structural T1 magnetic resonance imaging scans were retrospectively obtained for 43 patients: 27 temporal lobe resections (TLRs), 6 extratemporal lobe resections, and 10 VNS, undergoing surgery for drug-resistant epilepsy between 2012 and 2017. Automated volumetric analyses of predefined cortical gray matter and subcortical structures were performed. Preoperative and postoperative volumes were compared, and the effects of age, gender, operation type, resection laterality, selectivity, time since surgery, and seizure outcome on volumetric changes were analyzed. RESULTS: After TLRs, there were reductions in contralateral hemispheric gray matter, temporal lobe, entorhinal cortex, parahippocampal, superior temporal, middle temporal, inferior temporal (P = 0.02), lingual, fusiform, precentral, paracentral, postcentral, pericalcarine gyri, and ipsilateral superior parietal gyrus. After VNS, there was bilateral atrophy in the thalamus, putamen, cerebellum, rostral anterior cingulate, posterior cingulate, medial orbitofrontal, paracentral, fusiform, and transverse temporal gyri. There was a significant effect of surgery type but no effect of age, gender, operation type, resection laterality, selectivity, time since surgery, and seizure outcome on contralateral hippocampal gray matter change. CONCLUSION: This is the first study to demonstrate volumetric decreases in temporal and connected regions after TLRs and VNS. These results provide interesting insight into functional network changes.

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