High-Density Electroencephalography Detects Spatiotemporal Abnormalities in Brain Networks in Patients With Glioma-Related Epilepsy

IF 4.8 1区医学 Q1 NEUROSCIENCES

CNS Neuroscience & Therapeutics Pub Date : 2025-04-18 DOI:10.1111/cns.70396

Jiajia Liu, Jiawei Shi, Ke Li, Lei Wang, Gan You, Yinyan Wang, Xing Fan, Tao Jiang, Hui Qiao

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Abstract

Aims

The current study aimed to investigate brain network abnormalities in glioma-related epilepsy (gre) patients through high-density electroencephalography (eeg) data analysis.

Methods

The study included 35 patients with newly diagnosed frontal gliomas. All participants underwent 128-channel resting-state EEG recordings before surgery. Afterward, graph theory and microstate analyses were performed, and the resulting metrics were compared between patients with GRE and those without GRE.

Results

The network topology analysis demonstrated that the GRE group had a higher clustering coefficient, global efficiency, and local efficiency; a lower characteristic path length; and a higher small-worldness coefficient than the non-GRE group (adjusted p < 0.05 for all). Additionally, the microstate analysis indicated that the GRE group had lower occurrence and global explained variance of microstate E and higher global explained variance of microstate D (adjusted p < 0.05 for all). Moreover, the occurrence of microstate D was significantly negatively correlated with the maximum tumor diameter in the non-GRE group (r = −0.542, p = 0.009).

Conclusion

The current study revealed specific brain network abnormalities in GRE patients based on graph theory and microstate analyses of resting-state high-density EEG data. These findings can enhance our comprehension of the mechanisms behind GRE and offer potential biomarkers for improving individualized management of glioma patients.

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高密度脑电图检测神经胶质瘤相关癫痫患者脑网络的时空异常

目的通过高密度脑电图（eeg）数据分析胶质瘤相关性癫痫（gre）患者的脑网络异常。方法对35例新诊断的额叶胶质瘤患者进行研究。所有参与者在手术前进行128通道静息状态脑电图记录。随后，进行图论和微观状态分析，并将结果指标在GRE患者和未GRE患者之间进行比较。结果网络拓扑分析表明，GRE组具有较高的聚类系数、全局效率和局部效率；较低的特征路径长度；小世界系数高于非gre组（调整p <； 0.05）。此外，微状态分析显示，GRE组微状态E的发生率和整体解释方差较低，微状态D的整体解释方差较高（均校正p <； 0.05）。非gre组微状态D的发生与最大肿瘤直径呈显著负相关（r = - 0.542, p = 0.009）。结论基于图论和静息状态高密度脑电图数据的微态分析，本研究揭示了GRE患者脑网络的特异性异常。这些发现可以增强我们对GRE背后机制的理解，并为改善胶质瘤患者的个性化管理提供潜在的生物标志物。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

CNS Neuroscience & Therapeutics 医学-神经科学

CiteScore

7.30

自引率

12.70%

发文量

240

审稿时长

2 months

期刊介绍： CNS Neuroscience & Therapeutics provides a medium for rapid publication of original clinical, experimental, and translational research papers, timely reviews and reports of novel findings of therapeutic relevance to the central nervous system, as well as papers related to clinical pharmacology, drug development and novel methodologies for drug evaluation. The journal focuses on neurological and psychiatric diseases such as stroke, Parkinson’s disease, Alzheimer’s disease, depression, schizophrenia, epilepsy, and drug abuse.