Cuspineda-Bravo Elena R, Martínez-Montes Eduardo, Farach-Fumero Miguel, Machado-Curbelo Calixto
Havana Institute of Neurology and Neurosurgery, Havana, Cuba
Neuroinformatics Department, Cuban Neuroscience Center, Havana, Cuba.
Clin EEG Neurosci. 2015 Apr;46(2):153-68. doi: 10.1177/1550059414522231. Epub 2014 May 29.
The combination of recently developed methods for electroencephalographic (EEG) space-time-frequency analysis can provide noninvasive functional neuroimages necessary for obtaining an accurate localization of the epileptogenic zone. The aim of this study was to determine if time-frequency (TF) analysis, followed by EEG source localization, would improve the detection and identification of epileptogenic and related activity. Seventeen patients with refractory frontal lobe epilepsy (FLE) were studied using video EEG recording. TF analysis identified the first epileptogenic EEG changes. Using the Bayesian model averaging (BMA) approach, we compared brain electromagnetic tomographic (BET) images, constructed from the TF domain, with BET images constructed from the time domain only. We determined if the localization identified by BET images was concordant with the localization from medical history and video EEG recording. TF analysis provided a clear display of subtle EEG features, including EEG lateralization, and more concordant and delimited epileptogenic zones, compared with time-domain source analysis. In conclusion, EEG TF analysis improves source localization. After a thorough validation, this methodology could become a useful noninvasive tool for localizing the epileptogenic zone in clinical practice.
最近开发的脑电图（EEG）时空频率分析方法相结合，可以提供获得癫痫发作起始区准确定位所需的无创功能神经影像。本研究的目的是确定时频（TF）分析，随后进行EEG源定位，是否会改善癫痫发作起始及相关活动的检测和识别。使用视频EEG记录对17例难治性额叶癫痫（FLE）患者进行了研究。TF分析确定了首次癫痫发作的EEG变化。使用贝叶斯模型平均（BMA）方法，我们将从TF域构建的脑电磁断层扫描（BET）图像与仅从时域构建的BET图像进行了比较。我们确定BET图像识别的定位是否与病史和视频EEG记录的定位一致。与时域源分析相比，TF分析能够清晰显示细微的EEG特征，包括EEG的偏侧化，以及更一致且界限更明确的癫痫发作起始区。总之，EEG TF分析可改善源定位。经过全面验证后，该方法可能成为临床实践中定位癫痫发作起始区的有用无创工具。
