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fMRI-Based Effective Connectivity in Surgical Remediable Epilepsies: A Pilot Study
Brain Topography ( IF 2.7 ) Pub Date : 2021-06-21 , DOI: 10.1007/s10548-021-00857-x
A E Vaudano 1, 2 , L Mirandola 2 , F Talami 2 , G Giovannini 1, 2 , G Monti 3 , P Riguzzi 4 , L Volpi 4 , R Michelucci 4 , F Bisulli 5, 6 , E Pasini 4 , P Tinuper 5, 6 , L Di Vito 5, 6 , G Gessaroli 1 , M Malagoli 7 , G Pavesi 2, 8 , F Cardinale 9 , L Tassi 9 , L Lemieux 10 , S Meletti 1, 2
Affiliation  

Simultaneous EEG-fMRI can contribute to identify the epileptogenic zone (EZ) in focal epilepsies. However, fMRI maps related to Interictal Epileptiform Discharges (IED) commonly show multiple regions of signal change rather than focal ones. Dynamic causal modeling (DCM) can estimate effective connectivity, i.e. the causal effects exerted by one brain region over another, based on fMRI data. Here, we employed DCM on fMRI data in 10 focal epilepsy patients with multiple IED-related regions of BOLD signal change, to test whether this approach can help the localization process of EZ. For each subject, a family of competing deterministic, plausible DCM models were constructed using IED as autonomous input at each node, one at time. The DCM findings were compared to the presurgical evaluation results and classified as: “Concordant” if the node identified by DCM matches the presumed focus, “Discordant” if the node is distant from the presumed focus, or “Inconclusive” (no statistically significant result). Furthermore, patients who subsequently underwent intracranial EEG recordings or surgery were considered as having an independent validation of DCM results. The effective connectivity focus identified using DCM was Concordant in 7 patients, Discordant in two cases and Inconclusive in one. In four of the 6 patients operated, the DCM findings were validated. Notably, the two Discordant and Invalidated results were found in patients with poor surgical outcome. Our findings provide preliminary evidence to support the applicability of DCM on fMRI data to investigate the epileptic networks in focal epilepsy and, particularly, to identify the EZ in complex cases.



中文翻译:

基于 fMRI 的可手术治疗癫痫有效连接:一项初步研究

同时 EEG-fMRI 有助于识别局灶性癫痫中的致痫区 (EZ)。然而,与发作间期癫痫样放电 (IED) 相关的 fMRI 图通常显示多个信号变化区域而不是焦点区域。动态因果模型 (DCM) 可以基于 fMRI 数据估计有效连接性,即一个大脑区域对另一个大脑区域施加的因果效应。在这里,我们对 10 名具有 BOLD 信号变化的多个 IED 相关区域的局灶性癫痫患者的 fMRI 数据使用 DCM,以测试这种方法是否有助于 EZ 的定位过程。对于每个主题,使用 IED 作为每个节点的自主输入构建了一系列相互竞争的确定性、合理的 DCM 模型,一次一个。将 DCM 结果与术前评估结果进行比较,并分类为:如果 DCM 识别的节点与假定的焦点匹配,则为“一致”,如果节点远离假定的焦点,则为“不一致”,或“不确定”(无统计显着性结果)。此外,随后接受颅内 EEG 记录或手术的患者被视为对 DCM 结果进行了独立验证。使用 DCM 确定的有效连接焦点在 7 例患者中是一致的,在 2 例中是不一致的,在 1 例中是不确定的。在 6 名接受手术的患者中,有 4 名证实了 DCM 的发现。值得注意的是,在手术结果不佳的患者中发现了不一致和无效的两个结果。我们的研究结果提供了初步证据,支持 DCM 对 fMRI 数据的适用性,以研究局灶性癫痫中的癫痫网络,特别是在复杂病例中识别 EZ。

更新日期:2021-06-21
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