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发作间期癫痫样活动期间金属伪影滤波对用于源定位的脑磁图信号的影响。

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity.

作者信息

Migliorelli Carolina, Alonso Joan F, Romero Sergio, Mañanas Miguel A, Nowak Rafał, Russi Antonio

机构信息

Department of Automatic Control (ESAII), Biomedical Engineering Research Center (CREB), Universitat Politènica de Catalunya (UPC), Barcelona, Spain. Biomedical Research Networking center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Spain.

出版信息

J Neural Eng. 2016 Apr;13(2):026029. doi: 10.1088/1741-2560/13/2/026029. Epub 2016 Mar 2.

Abstract

OBJECTIVE

Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference.

APPROACH

A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results.

MAIN RESULTS

The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches.

SIGNIFICANCE

The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.

摘要

目的

药物难治性癫痫是一种常见病症,影响40%的癫痫患者,这些患者通常必须接受切除性手术。脑磁图(MEG)已越来越多地用于通过等效电流偶极子(ECD)建模来识别致痫灶,这是获得发作间期癫痫样放电(IED)准确定位的最常用方法之一。建模要求对MEG信号进行充分预处理以减少干扰,而使用盲源分离(BSS)方法极大地改进了这项任务。MEG记录对由植入的颅内电极、假牙等在头部内部产生的金属干扰以及来自起搏器或迷走神经刺激器等外部源的干扰高度敏感。为减少这些伪迹,最近开发并验证了一种基于BSS的全自动程序,该程序在模拟信号和真实信号中均有效减少了金属伪迹(Migliorelli等人,2015年,《神经工程学杂志》12卷,046001)。本研究的主要目的是评估其对局灶性癫痫和金属干扰患者的IED检测及ECD建模的影响。

方法

对ECD的最终位置进行了比较:不消除金属干扰;仅剔除具有大金属伪迹的通道;以及在基于BSS进行减少之后。定义了ECD的离散度和距离测量指标来分析结果。

主要结果

伪迹与信号比率和ECD拟合之间的关系表明,较高的金属干扰值会产生高度分散的偶极子。结果显示,使用基于BSS的减少程序可显著降低离散度,与其他两种方法相比,能得出可行的ECD位置。

意义

基于BSS的自动方法可作为一个处理步骤应用于受金属伪迹影响的MEG数据集,以改善癫痫灶的定位。

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