Suppr超能文献

激光胼胝体切开术后快速双侧同步性癫痫发作侧别判断的颅内脑电图生物标志物

Intracranial EEG Biomarkers for Seizure Lateralization in Rapidly-Bisynchronous Epilepsy After Laser Corpus Callosotomy.

作者信息

Khuvis Simon, Hwang Sean T, Mehta Ashesh D

机构信息

Department of Neurosurgery, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Manhasset, NY, United States.

Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States.

出版信息

Front Neurol. 2021 Oct 8;12:696492. doi: 10.3389/fneur.2021.696492. eCollection 2021.

Abstract

It has been asserted that high-frequency analysis of intracranial EEG (iEEG) data may yield information useful in localizing epileptogenic foci. We tested whether proposed biomarkers could predict lateralization based on iEEG data collected prior to corpus callosotomy (CC) in three patients with bisynchronous epilepsy, whose seizures lateralized definitively post-CC. Lateralization data derived from algorithmically-computed ictal phase-locked high gamma (PLHG), high gamma amplitude (HGA), and low-frequency (filtered) line length (LFLL), as well as interictal high-frequency oscillation (HFO) and interictal epileptiform discharge (IED) rate metrics were compared against ground-truth lateralization from post-CC ictal iEEG. Pre-CC unilateral IEDs were more frequent on the more-pathologic side in all subjects. HFO rate predicted lateralization in one subject, but was sensitive to detection threshold. On pre-CC data, no ictal metric showed better predictive power than any other. All post-corpus callosotomy seizures lateralized to the pathological hemisphere using PLHG, HGA, and LFLL metrics. While quantitative metrics of IED rate and ictal HGA, PHLG, and LFLL all accurately lateralize based on post-CC iEEG, only IED rate consistently did so based on pre-CC data. Quantitative analysis of IEDs may be useful in lateralizing seizure pathology. More work is needed to develop reliable techniques for high-frequency iEEG analysis.

摘要

有人断言,对颅内脑电图(iEEG)数据进行高频分析可能会产生有助于定位致痫灶的信息。我们测试了所提出的生物标志物是否能够根据胼胝体切开术(CC)前收集的iEEG数据,对三名双侧同步癫痫患者的癫痫发作侧别进行预测,这三名患者在CC术后癫痫发作侧别明确。将通过算法计算得出的发作期锁相高伽马(PLHG)、高伽马振幅(HGA)、低频(滤波后)线长度(LFLL)以及发作间期高频振荡(HFO)和发作间期癫痫样放电(IED)率指标得出的侧别数据,与CC术后发作期iEEG的真实侧别进行比较。在所有受试者中,CC术前单侧IED在病变更严重的一侧更为常见。HFO率在一名受试者中预测了侧别,但对检测阈值敏感。在CC术前数据中,没有任何发作期指标显示出比其他指标更好的预测能力。使用PLHG、HGA和LFLL指标,胼胝体切开术后所有癫痫发作均定位于病变半球。虽然基于CC术后iEEG,IED率以及发作期HGA、PHLG和LFLL的定量指标均能准确确定侧别,但基于CC术前数据,只有IED率始终能做到这一点。IED的定量分析可能有助于确定癫痫发作的病变侧别。需要开展更多工作来开发可靠的高频iEEG分析技术。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7132/8531267/c9f20c5d608d/fneur-12-696492-g0001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验