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磁源估计与颅内脑电图、切除面积和癫痫发作结果的比较。

Comparison of magnetic source estimation to intracranial EEG, resection area, and seizure outcome.

机构信息

Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, U.S.A.

出版信息

Epilepsia. 2014 Nov;55(11):1854-63. doi: 10.1111/epi.12822. Epub 2014 Oct 13.

Abstract

OBJECTIVES

Magnetoencephalography (MEG) is used to guide intracranial electroencephalography (ICEEG) monitoring and determine areas for resection. The purpose of this retrospective cross-sectional study was to report our experience using dipole modeling/dipole scanning, current density reconstructions, and beam-forming methods in a large cohort of pediatric patients with intractable epilepsy.

METHODS

Source localization results for each algorithm and seizure-onset zone, defined by ICEEG, were described by three blinded reviewers according to five location criteria. The accuracy of each algorithm was then compared to ICEEG. The relationships between the accuracy of these algorithms (discordant, lobar concordant, sublobar concordant) and long-term seizure outcome was calculated using positive and negative predictive values.

RESULTS

Thirty-two patients (mean age ± SD, 10.8 ± 5 years) were included in this retrospective review. No algorithms had sublobar concordance with ICEEG in all patients, including when algorithms were grouped by type (dipole modeling/dipole scanning, current density reconstruction, beam forming). Synthetic aperture magnetometry (SAM) with excess kurtosis tended to be the most accurate, but there were no significant differences between algorithms. When comparing the source modeling with ICEEG findings, significantly more patients with a seizure-free outcome were found to have lobar or sublobar concordance of multiple signal classification (MUSIC) (61.1%) and standardized low resolution brain electromagnetic tomography (sLORETA) (52.9%). Positive predictive values were highest for MUSIC (61.9%) and equivalent current dipole (ECD) (57.1%). Negative predictive values were highest for SAM(g2 )-VS (83%), minimum norm estimate (MNE) (75%), MUSIC (73.7%), and ECD (73.5%).

SIGNIFICANCE

This study describes the use of multiple MEG source estimation techniques and demonstrates that all algorithms have similar rates of concordance with ICEEG. Also, the concordance or discordance of MUSIC with ICEEG was the best predictor of long-term seizure outcome.

摘要

目的

脑磁图(MEG)用于指导颅内脑电图(ICEEG)监测并确定切除区域。本回顾性横断面研究的目的是报告我们在一组患有难治性癫痫的儿科患者中使用偶极子建模/偶极子扫描、电流密度重建和波束形成方法的经验。

方法

根据五个位置标准,由三名盲审员描述每个算法和由 ICEEG 定义的痫性发作起始区的源定位结果。然后将每种算法的准确性与 ICEEG 进行比较。使用正预测值和负预测值计算这些算法的准确性(不一致、叶性一致、亚叶性一致)与长期癫痫发作结果之间的关系。

结果

共纳入 32 例患者(平均年龄±标准差,10.8±5 岁)进行回顾性分析。在所有患者中,没有一种算法与 ICEEG 具有亚叶性一致性,包括按类型(偶极子建模/偶极子扫描、电流密度重建、波束形成)分组的算法。具有超峰度的合成孔径磁强计(SAM)往往是最准确的,但算法之间没有显著差异。当将源模型与 ICEEG 结果进行比较时,发现无癫痫发作结果的患者中,多个信号分类(MUSIC)(61.1%)和标准化低分辨率脑电磁层析成像(sLORETA)(52.9%)的叶性或亚叶性一致性明显更高。MUSIC(61.9%)和等效电流偶极子(ECD)(57.1%)的阳性预测值最高。SAM(g2)-VS(83%)、最小范数估计(MNE)(75%)、MUSIC(73.7%)和 ECD(73.5%)的阴性预测值最高。

意义

本研究描述了多种 MEG 源估计技术的应用,并表明所有算法与 ICEEG 的一致性相似。此外,MUSIC 与 ICEEG 的一致性或不一致性是长期癫痫发作结果的最佳预测因素。

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