Owen Tom, Janiukstyte Vytene, Hall Gerard R, Chowdhury Fahmida A, Diehl Beate, McEvoy Andrew, Miserocchi Anna, de Tisi Jane, Duncan John S, Rugg-Gunn Fergus, Wang Yujiang, Taylor Peter Neal
CNNP Lab (www.cnnp-lab.com), Interdisciplinary Computing and Complex BioSystems Group, School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom.
UCL Queen Square Institute of Neurology, Queen Square, London, WC1N 3BG, United Kingdom.
ArXiv. 2023 Apr 11:arXiv:2304.05199v1.
Intracranial EEG (iEEG) is the gold standard technique for epileptogenic zone (EZ) localisation, but requires a preconceived hypothesis of the location of the epileptogenic tissue. This placement is guided by qualitative interpretations of seizure semiology, MRI, EEG and other imaging modalities, such as magnetoencephalography (MEG). Quantitative abnormality mapping using MEG has recently been shown to have potential clinical value. We hypothesised that if quantifiable MEG abnormalities were sampled by iEEG, then patients' post-resection seizure outcome may be better. Thirty-two individuals with refractory neocortical epilepsy underwent MEG and subsequent iEEG recordings as part of pre-surgical evaluation. Eyes-closed resting-state interictal MEG band power abnormality maps were derived from 70 healthy controls as a normative baseline. MEG abnormality maps were compared to iEEG electrode implantation, with the spatial overlap of iEEG electrode placement and cerebral MEG abnormalities recorded. Finally, we assessed if the implantation of electrodes in abnormal tissue, and subsequent resection of the strongest abnormalities determined by MEG and iEEG corresponded to surgical success. Intracranial electrodes were implanted in brain tissue with the most abnormal MEG findings - in individuals that were seizure-free post-operatively (T=3.9, p=0.003), but not in those who did not become seizure free. The overlap between MEG abnormalities and electrode placement distinguished surgical outcome groups moderately well (AUC=0.68). In isolation, the resection of the strongest abnormalities as defined by MEG and iEEG separated surgical outcome groups well, AUC=0.71, AUC=0.74 respectively. A model incorporating all three features separated surgical outcome groups best (AUC=0.80). Intracranial EEG is a key tool to delineate the EZ and help render individuals seizure-free post-operatively. We showed that data-driven abnormality maps derived from resting-state MEG recordings demonstrate clinical value and may help guide electrode placement in individuals with neocortical epilepsy. Additionally, our predictive model of post-operative seizure-freedom, which leverages both MEG and iEEG recordings, could aid patient counselling of expected outcome.
颅内脑电图(iEEG)是癫痫灶(EZ)定位的金标准技术,但需要对致痫组织的位置有一个预先设定的假设。这种放置是由发作症状学、MRI、脑电图和其他成像方式(如脑磁图(MEG))的定性解释来指导的。最近研究表明,使用MEG进行定量异常映射具有潜在的临床价值。我们假设,如果通过iEEG对可量化的MEG异常进行采样,那么患者术后的癫痫发作结果可能会更好。作为术前评估的一部分,32例难治性新皮质癫痫患者接受了MEG检查及随后的iEEG记录。闭眼静息期发作间期MEG频段功率异常图来自70名健康对照者,作为正常基线。将MEG异常图与iEEG电极植入情况进行比较,记录iEEG电极放置与脑MEG异常的空间重叠情况。最后,我们评估了在异常组织中植入电极以及随后切除由MEG和iEEG确定的最强异常是否与手术成功相关。颅内电极植入到MEG结果异常最明显的脑组织中——术后无癫痫发作的个体(T = 3.9,p = 0.003),但术后仍有癫痫发作的个体则未植入。MEG异常与电极放置之间的重叠在一定程度上能够区分手术结果组(曲线下面积[AUC]=0.68)。单独来看,切除由MEG和iEEG定义的最强异常能够很好地区分手术结果组,AUC分别为0.71和0.74。一个包含所有三个特征的模型区分手术结果组的效果最佳(AUC = 0.80)。颅内脑电图是描绘癫痫灶并帮助个体术后无癫痫发作的关键工具。我们表明,从静息态MEG记录中得出的数据驱动异常图具有临床价值,可能有助于指导新皮质癫痫患者的电极放置。此外,我们利用MEG和iEEG记录的术后无癫痫发作预测模型,可以辅助对患者预期结果的咨询。