Klovatch-Podlipsky Ilana, Gazit Tomer, Fahoum Firas, Tsirelson Boris, Kipervasser Svetlana, Kremer Uri, Ben-Zeev Bruria, Goldberg-Stern Hadassah, Eisenstein Orna, Harpaz Yuval, Levy Ory, Kirschner Adi, Neufeld Miriam Y, Fried Itzhak, Hendler Talma, Medvedovsky Mordekhay
Tel-Aviv Center for Brain Functions, Whol Institute for Advance Imaging, Tel Aviv Sourasky Medical Center, Israel.
Tel-Aviv Center for Brain Functions, Whol Institute for Advance Imaging, Tel Aviv Sourasky Medical Center, Israel.
Neuroimage. 2016 Nov 15;142:674-686. doi: 10.1016/j.neuroimage.2016.07.014. Epub 2016 Jul 9.
Although simultaneous recording of EEG and MRI has gained increasing popularity in recent years, the extent of its clinical use remains limited by various technical challenges. Motion interference is one of the major challenges in EEG-fMRI. Here we present an approach which reduces its impact with the aid of an MR compatible dual-array EEG (daEEG) in which the EEG itself is used both as a brain signal recorder and a motion sensor.
We implemented two arrays of EEG electrodes organized into two sets of nearly orthogonally intersecting wire bundles. The EEG was recorded using referential amplifiers inside a 3T MR-scanner. Virtual bipolar measurements were taken both along bundles (creating a small wire loop and therefore minimizing artifact) and across bundles (creating a large wire loop and therefore maximizing artifact). Independent component analysis (ICA) was applied. The resulting ICA components were classified into brain signal and noise using three criteria: 1) degree of two-dimensional spatial correlation between ICA coefficients along bundles and across bundles; 2) amplitude along bundles vs. across bundles; 3) correlation with ECG. The components which passed the criteria set were transformed back to the channel space. Motion artifact suppression and the ability to detect interictal epileptic spikes following daEEG and Optimal Basis Set (OBS) procedures were compared in 10 patients with epilepsy.
The SNR achieved by daEEG was 11.05±3.10 and by OBS was 8.25±1.01 (p<0.00001). In 9 of 10 patients, more spikes were detected after daEEG than after OBS (p<0.05).
daEEG improves signal quality in EEG-fMRI recordings, expanding its clinical and research potential.
尽管近年来脑电图(EEG)与磁共振成像(MRI)同步记录越来越普遍,但其临床应用范围仍受到各种技术挑战的限制。运动干扰是EEG - fMRI中的主要挑战之一。在此,我们提出一种方法,借助与磁共振兼容的双阵列脑电图(daEEG)来减少其影响,其中EEG本身既用作脑信号记录器,又用作运动传感器。
我们实现了两个EEG电极阵列,它们被组织成两组几乎正交相交的线束。在3T磁共振扫描仪内使用参考放大器记录EEG。沿着线束(形成一个小的线环,从而使伪影最小化)和跨线束(形成一个大的线环,从而使伪影最大化)进行虚拟双极测量。应用独立成分分析(ICA)。使用三个标准将所得的ICA成分分为脑信号和噪声:1)沿着线束和跨线束的ICA系数之间的二维空间相关性程度;2)沿着线束与跨线束的幅度;3)与心电图(ECG)的相关性。通过设定标准的成分被转换回通道空间。在10例癫痫患者中比较了daEEG和最佳基集(OBS)程序后的运动伪影抑制以及检测发作间期癫痫棘波的能力。
daEEG实现的信噪比为11.05±3.10,OBS为8.25±1.01(p<0.00001)。在10例患者中的9例中,daEEG后检测到的棘波比OBS后更多(p<0.05)。
daEEG提高了EEG - fMRI记录中的信号质量,扩展了其临床和研究潜力。