Clinical Validation of the Champagne Algorithm for Evoked Response Source Localization in Magnetoencephalography.
Clinical Validation of the Champagne Algorithm for Evoked Response Source Localization in Magnetoencephalography.
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DOI：
10.1007/s10548-021-00850-4
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发表时间：
2022-01
期刊：
影响因子：
2.7
通讯作者：
Nagarajan SS
中科院分区：
文献类型：
--
作者：
Bhutada AS;Cai C;Mizuiri D;Findlay A;Chen J;Tay A;Kirsch HE;Nagarajan SS
脑磁图（Magnetoencephalography，MEG）是一种非侵入性的脑功能成像方法，具有良好的空间和时间分辨率。根据感觉诱发反应对功能标志进行MEG源定位的临床标准是等效电流偶极子（ECD）定位算法，已知该算法对初始化、噪声和偶极子数量的手动选择敏感。最近开发了许多自动化和鲁棒的算法，包括香槟算法，一种经验贝叶斯算法，具有强大的MEG源重建和时间过程估计能力（Wipf等人，2010; Owen等人，2012）。在这里，我们评估了自动香槟的性能，在肿瘤患者的临床人群中，有最小的失败定位感觉诱发反应，使用临床标准，ECD定位算法。采用香槟法分析21例脑肿瘤患者的听觉诱发电位和体感诱发电位的脑磁图（MEG）数据，并与等效电流偶极子（ECD）拟合结果进行比较。在体感和听觉诱发场定位，我们发现有一个强烈的协议之间的香槟和ECD定位在所有情况下。给定8 mm体素尺寸的分辨率，来自香槟的峰值源定位低于10 mm的ECD峰值源定位。香槟算法为手动ECD提供了一种强大的自动化替代方案，适合感觉诱发电位的临床定位，并有助于改善临床MEG数据处理工作流程。
Magnetoencephalography (MEG) is a robust method for non-invasive functional brain mapping of sensory cortices due to its exceptional spatial and temporal resolution. The clinical standard for MEG source localization of functional landmarks from sensory evoked responses is the equivalent current dipole (ECD) localization algorithm, known to be sensitive to initialization, noise, and manual choice of the number of dipoles. Recently many automated and robust algorithms have been developed, including the Champagne algorithm, an empirical Bayesian algorithm, with powerful abilities for MEG source reconstruction and time course estimation (Wipf et al. 2010; Owen et al. 2012). Here, we evaluate automated Champagne performance in a clinical population of tumor patients where there was minimal failure in localizing sensory evoked responses using the clinical standard, ECD localization algorithm. MEG data of auditory evoked potentials and somatosensory evoked potentials from 21 brain tumor patients were analyzed using Champagne, and these results were compared with equivalent current dipole (ECD) fit. Across both somatosensory and auditory evoked field localization, we found there was a strong agreement between Champagne and ECD localizations in all cases. Given resolution of 8mm voxel size, peak source localizations from Champagne were below 10mm of ECD peak source localization. The Champagne algorithm provides a robust and automated alternative to manual ECD fits for clinical localization of sensory evoked potentials and can contribute to improved clinical MEG data processing workflows.
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影响因子：
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作者：
Dalal SS;Zumer JM;Guggisberg AG;Trumpis M;Wong DD;Sekihara K;Nagarajan SS
通讯作者：
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作者：
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