Laboratory for Epilepsy Research, UZ Leuven & KU Leuven, Leuven, Belgium; Medical Imaging Research Center, UZ Leuven & KU Leuven, Leuven, Belgium.
Epilepsia. 2014 Dec;55(12):2048-58. doi: 10.1111/epi.12841. Epub 2014 Nov 6.
A prerequisite for the implementation of interictal electroencephalography-correlated functional magnetic resonance imaging (EEG-fMRI) in the presurgical work-up for epilepsy surgery is straightforward processing. We propose a new semi-automatic method as alternative for the challenging and time-consuming visual spike identification.
Our method starts from a patient-specific spike-template, built by averaging spikes recorded on the EEG outside the scanner. Spatiotemporal cross-correlations between the template and the EEG measured during fMRI were calculated. To minimize false-positive detections, this time course of cross-correlations was binarized by means of a spike-template-specific threshold determined in healthy controls. To inform our model for statistical parametric mapping, this binarized regressor was convolved with the canonical hemodynamic response function. We validated our "template-based" method in 21 adult patients with refractory focal epilepsy with a well-defined epileptogenic zone and interictal spikes during EEG-fMRI. Sensitivity and specificity for detecting the epileptogenic zone were calculated and represented in receiver operating characteristic (ROC) curves. Our approach was compared with a previously proposed semiautomatic "topography-based" method that used the topographic amplitude distribution of spikes as a starting point for correlation-based fitting.
Good diagnostic performance could be reached with our template-based method. The optimal area under the ROC curve was 0.77. Diagnostic performance of the topography-based method was overall low.
Our new template-based method is more standardized and time-saving than visual spike identification on intra-scanner EEG recordings, and preserves good diagnostic performance for detecting the epileptogenic zone.
在癫痫手术的术前评估中实施发作间期脑电图相关功能磁共振成像(EEG-fMRI)的前提是进行简单的处理。我们提出了一种新的半自动方法,作为对具有挑战性和耗时的视觉棘波识别的替代方法。
我们的方法从患者特异性的棘波模板开始,该模板通过对扫描仪外记录的棘波进行平均构建。在 fMRI 期间测量的模板和 EEG 之间的时空互相关进行计算。为了最小化假阳性检测,通过在健康对照中确定的棘波模板特异性阈值对该互相关时间过程进行二值化。为了告知我们的统计参数映射模型,将此二值化回归器与典型的血液动力学响应函数卷积。我们在 21 例具有明确致痫区和 EEG-fMRI 期间发作间期棘波的难治性局灶性癫痫成人患者中验证了我们的“基于模板”方法。计算并在接收者操作特征(ROC)曲线中表示检测致痫区的敏感性和特异性。我们的方法与先前提出的半自动“基于地形图”方法进行了比较,该方法使用棘波的地形幅度分布作为相关拟合的起点。
我们的基于模板的方法可以达到良好的诊断性能。ROC 曲线下的最佳面积为 0.77。基于地形图的方法的诊断性能总体较低。
我们的新基于模板的方法比在扫描仪内 EEG 记录上进行视觉棘波识别更标准化和省时,并且保留了检测致痫区的良好诊断性能。