Division of Neurology, Cincinnati Children's Hospital Medical Center, Cincinnati OH, USA; Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
Neurosciences and Mental Health, Hospital for Sick Children, Toronto, Canada; Department of Physiology, University of Toronto, Canada.
Clin Neurophysiol. 2022 Oct;142:199-208. doi: 10.1016/j.clinph.2022.07.506. Epub 2022 Aug 12.
To clinically validate the connectivity-based magnetoencephalography (MEG) analyses to identify seizure onset zone (SOZ) with comparing to equivalent current dipole (ECD).
The ECD cluster was quantitatively analyzed by calculating the centroid of the cluster and maximum distance (the largest distance between all dipoles). The "primary hub" was determined by the highest eigencentrality. The distribution of nodes in the top 5% of eigenvector centrality values was quantified by generating the convex hull between each node.
Thirty-one patients who underwent MEG, stereotactic-EEG, and focal surgery were included. The primary hub was significantly closer to the sEEG-defined SOZ compared to ECD (p = 0.009). The seizure freedom positive and negative predictive values of complete ECD cluster and primary hub resections did not significantly differ, although complete resection of the primary hub showed slightly better negative predictive value (ECD: 50.0% NPV, hub: 64.7% NPV). Both quantitative ECD and functional connectivity analyses suggested that spatially restricted dipole distributions and higher connectivity in a smaller region correlate with better seizure outcomes.
Our findings suggest that MEG network analysis could be a valuable complement to the ECD methods.
The results of this study are an important step towards using non-invasive neurophysiologic recordings to accurately define the epileptic network.
通过与等效电流偶极子(ECD)比较,对基于连通性的脑磁图(MEG)分析进行临床验证,以识别癫痫发作起始区(SOZ)。
通过计算簇的质心和最大距离(所有偶极子之间的最大距离)对 ECD 簇进行定量分析。通过计算最高特征值中心度来确定“主要枢纽”。通过在每个节点之间生成凸包,量化特征向量中心度值前 5%的节点分布。
纳入 31 例接受 MEG、立体定向 EEG 和局灶性手术的患者。与 ECD 相比,主要枢纽明显更接近 sEEG 定义的 SOZ(p=0.009)。尽管完全切除主要枢纽显示出略高的阴性预测值(ECD:50.0%NPV,枢纽:64.7%NPV),但完全切除 ECD 簇和主要枢纽的阳性和阴性预测值并无显著差异。两种定量 ECD 和功能连通性分析均表明,空间受限的偶极子分布和较小区域的更高连通性与更好的癫痫发作结果相关。
我们的发现表明,MEG 网络分析可能是 ECD 方法的有价值的补充。
这项研究的结果是朝着使用非侵入性神经生理记录来准确定义癫痫网络迈出的重要一步。