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刺激诱导的光谱反应的网络兴奋性有助于定位癫痫发作起始区。

Network excitability of stimulation-induced spectral responses helps localize the seizure onset zone.

机构信息

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

出版信息

Clin Neurophysiol. 2024 Oct;166:43-55. doi: 10.1016/j.clinph.2024.07.010. Epub 2024 Jul 24.

Abstract

OBJECTIVE

While evoked potentials elicited by single pulse electrical stimulation (SPES) may assist seizure onset zone (SOZ) localization during intracranial EEG (iEEG) monitoring, induced high frequency activity has also shown promising utility. We aimed to predict SOZ sites using induced cortico-cortical spectral responses (CCSRs) as an index of excitability within epileptogenic networks.

METHODS

SPES was conducted in 27 epilepsy patients undergoing iEEG monitoring and CCSRs were quantified by significant early (10-200 ms) increases in power from 10 to 250 Hz. Using response power as CCSR network connection strengths, graph centrality measures (metrics quantifying each site's influence within the network) were used to predict whether sites were within the SOZ.

RESULTS

Across patients with successful surgical outcomes, greater CCSR centrality predicted SOZ sites and SOZ sites targeted for surgical treatment with median AUCs of 0.85 and 0.91, respectively. We found that the alignment between predicted and targeted SOZ sites predicted surgical outcome with an AUC of 0.79.

CONCLUSIONS

These findings indicate that network analysis of CCSRs can be used to identify increased excitability of SOZ sites and discriminate important surgical targets within the SOZ.

SIGNIFICANCE

CCSRs may supplement traditional passive iEEG monitoring in seizure localization, potentially reducing the need for recording numerous seizures.

摘要

目的

虽然单脉冲电刺激诱发的诱发电位(SPES)可能有助于颅内脑电图(iEEG)监测期间的致痫区(SOZ)定位,但诱导的高频活动也显示出有希望的效用。我们旨在使用诱发性皮质-皮质光谱响应(CCSRs)作为癫痫网络兴奋性的指标来预测 SOZ 部位。

方法

对 27 名接受 iEEG 监测的癫痫患者进行 SPES,通过从 10 到 250 Hz 的功率显着早期(10-200 ms)增加来量化 CCSR。使用响应功率作为 CCSR 网络连接强度,图中心度测量(量化网络中每个站点的影响的指标)用于预测站点是否在 SOZ 内。

结果

在具有成功手术结果的患者中,更高的 CCSR 中心度预测了 SOZ 部位,针对手术治疗的 SOZ 部位的中位 AUC 分别为 0.85 和 0.91。我们发现,预测和靶向 SOZ 部位之间的一致性预测了手术结果,AUC 为 0.79。

结论

这些发现表明,CCSRs 的网络分析可用于识别 SOZ 部位的兴奋性增加,并区分 SOZ 内的重要手术靶标。

意义

CCSRs 可能补充传统的被动 iEEG 监测在癫痫定位,有可能减少记录大量癫痫发作的需要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d3e/11401764/94d52b0b48d4/nihms-2013862-f0001.jpg

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Stimulation to probe, excite, and inhibit the epileptic brain.刺激探针,激发和抑制癫痫大脑。
Epilepsia. 2023 Dec;64 Suppl 3(Suppl 3):S49-S61. doi: 10.1111/epi.17640. Epub 2023 May 18.
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Neural fragility as an EEG marker of the seizure onset zone.神经脆弱性作为癫痫发作起始区的脑电图标志物。
Nat Neurosci. 2021 Oct;24(10):1465-1474. doi: 10.1038/s41593-021-00901-w. Epub 2021 Aug 5.

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