Suppr超能文献

儿童时间相关癫痫:脑磁图的连接组学分析。

Temporal-plus epilepsy in children: A connectomic analysis in magnetoencephalography.

机构信息

Program in Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, Ontario, Canada.

Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.

出版信息

Epilepsia. 2020 Aug;61(8):1691-1700. doi: 10.1111/epi.16591. Epub 2020 Jul 3.

Abstract

OBJECTIVE

Seizure recurrence following surgery for temporal lobe (TL) epilepsy may be related to extratemporal epileptogenic foci, so-called temporal-plus (TL+) epilepsy. Here, we sought to leverage whole brain connectomic profiling in magnetoencephalography (MEG) to identify neural networks indicative of TL+ epilepsy in children.

METHODS

Clinical and MEG data were analyzed for 121 children with TL and TL+ epilepsy spanning 20 years at the Hospital for Sick Children. Resting-state connectomes were derived using the weighted phase lag index from neuromagnetic oscillations. Multidimensional associations between patient connectomes, TL versus TL+ epilepsy, seizure freedom, and clinical covariates were performed using a partial least squares (PLS) analysis. Bootstrap resampling statistics were performed to assess statistical significance.

RESULTS

A single significant latent variable representing 66% of the variance in the data was identified with significant contributions from extent of epilepsy (TL vs TL+), duration of illness, and underlying etiology. This component was associated with significant bitemporal and frontotemporal connectivity in the theta, alpha, and beta bands. By extracting a brain score, representative of the observed connectivity profile, patients with TL epilepsy were dissociated from those with TL+, independent of their postoperative seizure outcome.

SIGNIFICANCE

By analyzing 121 connectomes derived from MEG data using a PLS approach, we find that connectomic profiling could dissociate TL from TL+ epilepsy. These findings may inform patient selection for resective procedures and guide decisions surrounding invasive monitoring.

摘要

目的

颞叶(TL)癫痫手术后的癫痫复发可能与所谓的颞叶加(TL +)癫痫的颞外致痫灶有关。在这里,我们试图利用磁共振脑磁图(MEG)中的全脑连接组学分析来识别儿童 TL + 癫痫的神经网络。

方法

对 SickKids 医院 20 年来 121 例 TL 和 TL +癫痫儿童的临床和 MEG 数据进行了分析。使用来自神经磁振荡的加权相位滞后指数得出静息状态连接组。使用偏最小二乘(PLS)分析对患者连接组、TL 与 TL +癫痫、无癫痫发作和临床协变量之间的多维关联进行了多维关联。通过bootstrap 重采样统计来评估统计显著性。

结果

识别出一个单一的显著潜在变量,代表数据中 66%的方差,其贡献来自癫痫的程度(TL 与 TL +)、疾病持续时间和潜在病因。该成分与θ、α和β频段的双侧颞叶和额颞叶连接显著相关。通过提取大脑评分,代表观察到的连接谱,TL 癫痫患者与 TL +患者区分开来,与他们术后癫痫发作结果无关。

意义

通过使用 PLS 方法分析来自 MEG 数据的 121 个连接组,我们发现连接组学分析可以将 TL 与 TL +癫痫区分开来。这些发现可能为手术治疗提供患者选择,并指导侵袭性监测决策。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验