Interictal high frequency oscillations as non-invasive biomarkers of epileptogenicity in pediatric patients

项目摘要 癫痫手术成功的关键是有一个强大的术前生物标记物来识别 致痫带(EZ)。完全切除EZ可能会导致药物治疗和癫痫发作缓解。自.以来 Ez不能直接测量，它的位置是根据来自多个区域的一致数据间接估计的 非侵入性测试。然而，这些测试的结果往往不够一致或不确定。 脑电图(IEEG)是描述癫痫发作的金标准 区域(SOZ)。然而，SOZ并不总是预测手术结果，它的描述需要 多天的记录以捕捉临床癫痫发作。IEEG记录的高频振荡(HFO) 是极有希望的EZ发作间期生物标志物。然而，它们在癫痫手术中的临床价值仍然存在争议。 HFO的产生区域通常相对较大，其完全切除可能与口才区域重叠。 这通常归因于生理性HFO在非致痫区域的存在。在我们最近的iEEG中 研究表明，发作间期的HFO是由发病发生器启动的，并扩散到其他脑区。 时间到了。这个生成器构成了一个有希望的癫痫发作间期生物标志物，因为它的切除与 手术效果良好。尽管有大量关于HFO的文献，但HFO在外科手术中的临床价值 仅使用iEEG进行研究，由于其侵袭性和局限性，显示出严重的局限性。 空间采样。这项应用旨在无创地定位发作间期高密度的HFO 难治性脑病患儿的脑电和脑磁图检查 癫痫(MRE)，区分病理和生理性HFO，并评估无创性定位 与手术切除和患者预后有关的HFO发病因素。我们的假设是 HD-EEG和MEG可以无创性地区分病理性和生理性HFO，并能定位 HfO发病的发电机，其切除导致的手术结果比切除面积更好 二次扩散。为了验证我们的假设，我们的具体目标是：(I)评估HD-EEG和MEG的能力 定位HFO；(Ii)使用无监督的方法区分生理性(NHFO)和病理性(PHFOS)HFO 机器学习；(Iii)对HFO发病发生器进行无创定位，并与临床金进行比较 切除量身定做的标准，即iEEG定义的SOZ；以及(Iv)评估HFO的预测价值- 在手术结果方面的起病诱因。为了实现这些目标，我们将记录HD-EEG和MEG数据 来自50名患有MRE的儿童(0-18岁)和50名典型发育期(TD)儿童。此应用程序 结合使用尖端的儿科神经成像仪器、3D打印技术和创新 信号处理工具，以及丰富的儿童神经成像经验。我们的研究将会有 对患有MRE的儿童的生活产生直接影响，因为它将提供一种新的EZ非侵入性生物标志物， 将限制侵入性的长期监测，增加术前计划，并改善手术结果。

Project Summary Crucial to the success of epilepsy surgery is the availability of a robust presurgical biomarker to identify the epileptogenic zone (EZ). Complete resection of the EZ may lead to medication and seizure freedom. Since the EZ cannot be measured directly, its location is estimated indirectly based on concordant data from a multitude of noninvasive tests. Yet, the results of these tests are often insufficiently concordant or inconclusive. Intracranial electroencephalography (iEEG) serves as the gold standard for the delineation of the seizure onset zone (SOZ). However, the SOZ does not always predict the surgical outcome, and its delineation requires many days of recordings to capture clinical seizures. High-frequency oscillations (HFOs), recorded with iEEG are promising interictal biomarkers of the EZ. Yet, their clinical value for epilepsy surgery is still debated since the HFO-generating area is often relatively large and its complete resection may overlap with eloquent areas. This is often attributed to the presence of physiological HFOs in non-epileptogenic areas. In our recent iEEG study, we showed that interictal HFOs are initiated by an onset generator and spread to other brain areas over time. This generator constitutes a promising interictal biomarker of the EZ since its resection is associated with good surgical outcome. Despite the copious literature on HFOs, the clinical value of HFOs for surgery has been only investigated using iEEG, which presents serious limitations due to its invasiveness and its limited spatial sampling. This application aims to noninvasively localize interictal HFOs with high-density electroencephalography (HD-EEG) and magnetoencephalography (MEG) in children with medically refractory epilepsy (MRE), distinguish pathological from physiological HFOs, and assess the noninvasive localization of the HFO-onset generator with respect to the surgical resection and patients’ outcome. Our hypothesis is that HD-EEG and MEG can distinguish pathological from physiological HFOs non-invasively and can localize the HFO-onset generator whose removal leads to better surgical outcome than the removal of the area of secondary spread. To test our hypothesis, we specifically aim to: (i) assess the ability of HD-EEG and MEG to localize HFOs; (ii) differentiate physiological (nHFOs) from pathological (pHFOs) HFOs using unsupervised machine learning; (iii) localize noninvasively the HFO-onset generator and compare it with the clinical gold standard for resection tailoring, i.e. the iEEG-defined SOZ; and (iv) assess the predictive value of the HFO- onset generator in terms of surgical outcome. To pursue these aims, we will record HD-EEG and MEG data from 50 children (0-18 years old) with MRE and 50 typically developing (TD) children. This application combines the use of cutting-edge pediatric neuroimaging instruments, 3D printing technology, and innovative signal processing tools together with extensive neuroimaging experience with children. Our research will have a direct impact on the life of children with MRE since it will provide a new noninvasive biomarker of the EZ that would limit invasive long-term monitoring, augment presurgical planning, and improve the surgical outcome.