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

机译:金属伪影过滤对MEG信号的影响,用于在发作间期癫痫样活动期间进行源定位

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摘要

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.
机译:医学上顽固性癫痫是一种常见病,会影响40%的癫痫患者,这些患者通常必须接受切除手术。磁脑描记术(MEG)已被越来越多地用于通过等效电流偶极(ECD)建模来识别癫痫灶,这是获得准确定位小儿癫痫样放电(IED)的最广泛接受的方法之一。建模要求对MEG信号进行适当的预处理以减少干扰,这项任务已通过使用盲源分离(BSS)方法得到了极大改善。 MEG记录对颅内植入的颅内电极,假牙等源自头部的金属干扰非常敏感,这些干扰也来自诸如起搏器或迷走神经刺激器等外部来源。为了减少这些伪像,最近开发并验证了一种基于BSS的全自动程序,该方法可有效减少模拟信号和真实信号中的金属伪像(Migliorelli等人,2015 J. Neural Eng。12 046001)。这项研究的主要目的是评估其在局灶性癫痫和金属干扰患者的IEDs和ECD模型检测中的作用。方法。比较了ECD的最终位置:不消除金属干扰;仅拒绝具有较大金属伪影的通道;以及基于BSS的还原后。定义了ECD的分散度和距离的量度,以分析结果。主要结果。伪影信号比与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。结果表明,使用基于BSS的还原程序可大大降低分散度,与其他两种方法相比,可产生ECD可行的位置。意义。可以将基于BSS的自动方法应用于受金属伪影影响的MEG数据集,作为改善癫痫灶定位的处理步骤。

著录项

  • 来源
    《Journal of neural engineering》 |2016年第2期|026029.1-026029.12|共12页
  • 作者单位

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

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

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

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

    Magnetoencephalography Unit, Hospital Quiron Teknon, Barcelona, Spain;

    Epilepsy Unit, Hospital Quiron Teknon, Barcelona, Spain;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    magnetoencephalography; metallic artifact; automatic artifact reduction; blind source separation; epilepsy; IEDs;

    机译:脑磁图金属制品自动减少伪像;盲源分离癫痫;简易爆炸装置;

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