The sixth sense: how much does interictal intracranial EEG add to determining the focality of epileptic networks?

IF 4.1 Q1 CLINICAL NEUROLOGY
Brain communications Pub Date : 2024-09-27 eCollection Date: 2024-01-01 DOI:10.1093/braincomms/fcae320
Ryan S Gallagher, Nishant Sinha, Akash R Pattnaik, William K S Ojemann, Alfredo Lucas, Joshua J LaRocque, John M Bernabei, Adam S Greenblatt, Elizabeth M Sweeney, Iahn Cajigas, H Isaac Chen, Kathryn A Davis, Erin C Conrad, Brian Litt
{"title":"The sixth sense: how much does interictal intracranial EEG add to determining the focality of epileptic networks?","authors":"Ryan S Gallagher, Nishant Sinha, Akash R Pattnaik, William K S Ojemann, Alfredo Lucas, Joshua J LaRocque, John M Bernabei, Adam S Greenblatt, Elizabeth M Sweeney, Iahn Cajigas, H Isaac Chen, Kathryn A Davis, Erin C Conrad, Brian Litt","doi":"10.1093/braincomms/fcae320","DOIUrl":null,"url":null,"abstract":"<p><p>Intracranial EEG is used for two main purposes: to determine (i) if epileptic networks are amenable to focal treatment and (ii) where to intervene. Currently, these questions are answered qualitatively and differently across centres. There is a need to quantify the focality of epileptic networks systematically, which may guide surgical decision-making, enable large-scale data analysis and facilitate multi-centre prospective clinical trials. We analysed interictal data from 101 patients with drug-resistant epilepsy who underwent pre-surgical evaluation with intracranial EEG at a single centre. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. Sixty-five patients had unifocal seizure onset on intracranial EEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal intracranial EEG abnormalities for each patient. We compared these measures against the '5 Sense Score,' a pre-implant prediction of the likelihood of focal seizure onset, assessed the ability to predict unifocal seizure onset by combining these metrics and evaluated how predicted focality relates to subsequent treatment and outcomes. The spatial dispersion of intracranial EEG electrodes predicted network focality with similar performance to the 5-SENSE score [area under the receiver operating characteristic curve = 0.68 (95% confidence interval 0.57, 0.78)], indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5-SENSE score and the spatial dispersion of interictal intracranial EEG abnormalities significantly improved this prediction [area under the receiver operating characteristic curve = 0.79 (95% confidence interval 0.70, 0.88); <i>P</i> < 0.05]. Predictions from this combined model differed between surgical- from device-treated patients with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.68, 0.85) and between patients with good and poor post-surgical outcome at 2 years with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval 0.56, 0.85). Spatial measures of interictal intracranial EEG abnormality significantly improved upon pre-implant predictions of network focality by area under the receiver operating characteristic curve and increased sensitivity in a single-centre study. Quantified focality predictions related to ultimate treatment strategy and surgical outcomes. While the 5-SENSE score weighed for specificity in their multi-centre validation to prevent unnecessary implantation, sensitivity improvement found in our single-centre study by including intracranial EEG may aid the decision on whom to perform the focal intervention. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.</p>","PeriodicalId":93915,"journal":{"name":"Brain communications","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11495218/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/braincomms/fcae320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Intracranial EEG is used for two main purposes: to determine (i) if epileptic networks are amenable to focal treatment and (ii) where to intervene. Currently, these questions are answered qualitatively and differently across centres. There is a need to quantify the focality of epileptic networks systematically, which may guide surgical decision-making, enable large-scale data analysis and facilitate multi-centre prospective clinical trials. We analysed interictal data from 101 patients with drug-resistant epilepsy who underwent pre-surgical evaluation with intracranial EEG at a single centre. We chose interictal data because of its potential to reduce the morbidity and cost associated with ictal recording. Sixty-five patients had unifocal seizure onset on intracranial EEG, and 36 were non-focal or multi-focal. We quantified the spatial dispersion of implanted electrodes and interictal intracranial EEG abnormalities for each patient. We compared these measures against the '5 Sense Score,' a pre-implant prediction of the likelihood of focal seizure onset, assessed the ability to predict unifocal seizure onset by combining these metrics and evaluated how predicted focality relates to subsequent treatment and outcomes. The spatial dispersion of intracranial EEG electrodes predicted network focality with similar performance to the 5-SENSE score [area under the receiver operating characteristic curve = 0.68 (95% confidence interval 0.57, 0.78)], indicating that electrode placement accurately reflected pre-implant information. A cross-validated model combining the 5-SENSE score and the spatial dispersion of interictal intracranial EEG abnormalities significantly improved this prediction [area under the receiver operating characteristic curve = 0.79 (95% confidence interval 0.70, 0.88); P < 0.05]. Predictions from this combined model differed between surgical- from device-treated patients with an area under the receiver operating characteristic curve of 0.81 (95% confidence interval 0.68, 0.85) and between patients with good and poor post-surgical outcome at 2 years with an area under the receiver operating characteristic curve of 0.70 (95% confidence interval 0.56, 0.85). Spatial measures of interictal intracranial EEG abnormality significantly improved upon pre-implant predictions of network focality by area under the receiver operating characteristic curve and increased sensitivity in a single-centre study. Quantified focality predictions related to ultimate treatment strategy and surgical outcomes. While the 5-SENSE score weighed for specificity in their multi-centre validation to prevent unnecessary implantation, sensitivity improvement found in our single-centre study by including intracranial EEG may aid the decision on whom to perform the focal intervention. We present this study as an important step in building standardized, quantitative tools to guide epilepsy surgery.

第六感:发作间期颅内脑电图对确定癫痫网络病灶的作用有多大?
颅内脑电图主要用于两个目的:确定(i) 癫痫网络是否适合病灶治疗;(ii) 在何处进行干预。目前,各中心对这些问题的回答都是定性的,而且各不相同。有必要对癫痫网络的病灶性进行系统量化,从而为手术决策提供指导,实现大规模数据分析,促进多中心前瞻性临床试验。我们分析了 101 名耐药性癫痫患者的发作间期数据,这些患者在一个中心接受了手术前颅内脑电图评估。我们选择发作间期数据是因为它有可能降低发作期记录的发病率和成本。65 名患者的颅内脑电图显示为单灶发作,36 名为非灶或多灶发作。我们量化了每位患者植入电极的空间分散性和发作间期颅内脑电图异常。我们将这些指标与 "5 Sense Score"(一种植入前预测局灶性癫痫发作可能性的指标)进行了比较,评估了通过结合这些指标预测单灶性癫痫发作的能力,并评估了预测的局灶性与后续治疗和预后的关系。颅内脑电图电极的空间散布预测网络病灶的性能与5-SENSE评分相似[接收器操作特征曲线下面积=0.68(95%置信区间0.57, 0.78)],表明电极位置准确反映了植入前的信息。将 5-SENSE 评分与发作间期颅内脑电图异常的空间弥散相结合的交叉验证模型显著改善了这一预测结果[接收器操作特征曲线下面积 = 0.79(95% 置信区间 0.70,0.88);P < 0.05]。该综合模型的预测结果在接受手术治疗和接受器械治疗的患者之间存在差异,接收者操作特征曲线下面积为 0.81(95% 置信区间为 0.68,0.85);在手术后 2 年结果良好和不佳的患者之间也存在差异,接收者操作特征曲线下面积为 0.70(95% 置信区间为 0.56,0.85)。在一项单中心研究中,对发作间期颅内脑电图异常的空间测量通过接收器操作特征曲线下面积显著改善了植入前的网络聚焦预测,并提高了灵敏度。量化的病灶预测与最终治疗策略和手术结果有关。虽然 5-SENSE 评分在多中心验证中权衡了特异性以防止不必要的植入,但在我们的单中心研究中,通过纳入颅内脑电图发现灵敏度的提高可能有助于决定对谁进行病灶干预。我们将这项研究视为建立标准化定量工具以指导癫痫手术的重要一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.00
自引率
0.00%
发文量
0
审稿时长
6 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信