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Cross-modal Consistency of Epileptogenic Network in SEEG and Resting-state fMRI

机译:奇基脲基网络在奇基和休息状态FMRI中的跨型模态一致性

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Electrophysiological recording and metabolic imaging are two complimentary techniques in preoperative evaluation of epilepsy surgery. High frequency electrical brain activity has been increasingly used in localizing seizure onset zone (SOZ) owing to the development of stereo-EEG (SEEG) technique. However, SEEG recording has no capacity of whole brain coverage as functional MRI. In this study, we performed cross-modal validation of epileptogenic network defined by SEEG and that by resting-state fMRI on individual brain of epilepsy patients. Epileptogenicity index (EI) based on abnormal high frequency SEEG signals was employed to define the epileptogenic network in electrophysiology. Meanwhile, taking the SEEG sites with highest EI as the seed, resting-state functional MRI and connectivity analysis were used to define the epileptogenic network in hemodynamics. The spatial consistency of these two networks was measured by ROC, and the average AUC reached 0.87, which proved a good consistency between electrophysiological and hemodynamic networks in epileptic brain. The difference part in resting-state fMRI network may supplement the SEEG electrode coverage, to reveal more information about epileptic network.
机译:电生理记录和代谢成像是癫痫手术术前评价的两种互补技术。由于立体脑电图(SEEG)技术的发展,高频电脑活动越来越多地用于本地化癫痫发作区域(SOZ)。然而,Seeg记录没有全脑覆盖的能力作为功能MRI。在这项研究中,我们对Seeg定义的癫痫型网络进行了跨越模态验证,并且通过休息状态FMRI对癫痫患者的个体脑。基于异常高频跷跷板信号的癫痫发生指数(EI)用于定义电生理学中的癫痫型网络。同时,使用与种子最高的eI,休息状态的官能MRI和连接分析以血流动力学定义血流动力学中的癫痫型网络。通过ROC测量这两个网络的空间一致性,平均AUC达到0.87,这证明了癫痫大脑中电生理学和血液动力学网络之间的良好一致性。休息状态FMRI网络中的差异部分可以补充跷跷板电极覆盖,以揭示关于癫痫网络的更多信息。

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