Widespread interictal epileptic discharge more likely than focal discharges to unveil the seizure onset zone in EEG-fMRI

Yamazoe, Tomohiro; Ellenrieder, Nicolás von; Khoo, Hui Ming; Huang, Yao-Hsien; Zazubovits, Natalja; Dubeau, François; Gotman, Jean

doi:10.1016/j.clinph.2018.12.014

Cited by 15 publications

(13 citation statements)

References 21 publications

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“…Non-focal IEDs on icEEG with wider topographic and field distribution (Regional, Widespread, and Non-contiguous) showed BOLD clusters in surgical resection volume more commonly, compared to focal IEDs on icEEG. This finding is similar to a recent scalp EEG-fMRI study (66) in which widespread epileptic discharges were more likely to show BOLD activation in seizure onset areas. The significance of this finding raises interesting questions about the BOLD effect, for example: is there a spatial scale of neural activity below which the strength of the BOLD change reflects only the local intensity of that activity, in contrast to its spatial extent?…”

Section: Neurophysiological and Neurobiological Significancesupporting

confidence: 90%

“…This suggests the possibility of common underlying brain areas or networks recruited as propagation nodes or even generators for different IED classes ( 50 , 51 , 61 – 63 ), or these widespread BOLD changes may be secondary to extensive underlying pathology ( 64 ). We suggest that BOLD changes in cortex and other brain areas remote from the surgical resection volume (i.e., confirmed EZ) may represent propagated epileptic activity in agreement with scalp EEG-fMRI ( 16 , 22 , 24 , 65 , 66 ) and electric source imaging studies ( 67 ). Also, this propagated epileptic activity in remote cortical or other brain areas such as precuneus, medial frontal, cuneus, and thalamus may represent an interaction with resting-state networks in line with previous scalp EEG-fMRI studies ( 55 , 56 ), which can have implications on level of cognition and consciousness ( 55 , 68 ) at some level and grants further research.…”

Section: Discussionsupporting

confidence: 72%

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Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

et al. 2021

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Background: Potentially curative epilepsy surgery can be offered if a single, discrete epileptogenic zone (EZ) can be identified. For individuals in whom there is no clear concordance between clinical localization, scalp EEG, and imaging data, intracranial EEG (icEEG) may be needed to confirm a predefined hypothesis regarding irritative zone (IZ), seizure onset zone (SOZ), and EZ prior to surgery. However, icEEG has limited spatial sampling and may fail to reveal the full extent of epileptogenic network if predefined hypothesis is not correct. Simultaneous icEEG-fMRI has been safely acquired in humans and allows exploration of neuronal activity at the whole-brain level related to interictal epileptiform discharges (IED) captured intracranially.Methods: We report icEEG-fMRI in eight patients with refractory focal epilepsy who had resective surgery and good postsurgical outcome. Surgical resection volume in seizure-free patients post-surgically reflects confirmed identification of the EZ. IEDs on icEEG were classified according to their topographic distribution and localization (Focal, Regional, Widespread, and Non-contiguous). We also divided IEDs by their location within the surgical resection volume [primary IZ (IZ1) IED] or outside [secondary IZ (IZ2) IED]. The distribution of fMRI blood oxygen level-dependent (BOLD) changes associated with individual IED classes were assessed over the whole brain using a general linear model. The concordance of resulting BOLD map was evaluated by comparing localization of BOLD clusters with surgical resection volume. Additionally, we compared the concordance of BOLD maps and presence of BOLD clusters in remote brain areas: precuneus, cuneus, cingulate, medial frontal, and thalamus for different IED classes.Results: A total of 38 different topographic IED classes were identified across the 8 patients: Focal (22) and non-focal (16, Regional = 9, Widespread = 2, Non-contiguous = 5). Twenty-nine IEDs originated from IZ1 and 9 from IZ2. All IED classes were associated with BOLD changes. BOLD maps were concordant with the surgical resection volume for 27/38 (71%) IED classes, showing statistical global maximum BOLD cluster or another cluster in the surgical resection volume. The concordance of BOLD maps with surgical resection volume was greater (p < 0.05) for non-focal (87.5%, 14/16) as compared to Focal (59%, 13/22) IED classes. Additionally, BOLD clusters in remote cortical and deep brain areas were present in 84% (32/38) of BOLD maps, more commonly (15/16; 93%) for non-focal IED-related BOLD maps.Conclusions: Simultaneous icEEG-fMRI can reveal BOLD changes at the whole-brain level for a wide range of IEDs on icEEG. BOLD clusters within surgical resection volume and remote brain areas were more commonly seen for non-focal IED classes, suggesting that a wider hemodynamic network is at play.

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Section: Neurophysiological and Neurobiological Significancesupporting

confidence: 90%

Section: Discussionsupporting

confidence: 72%

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

et al. 2021

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“…Regarding the relations between IEDs and SOZ, Yamazoe et al (163) hypothesized that the number of IEDs and their spatial extent could contribute to revealing the SOZ. To test this hypothesis, 157 types of IED grouped by spatial distribution were extracted clinically from the EEG-fMRI data of 64 patients with refractory localization-related epilepsy.…”

Section: The Relations Between Ieds and Sozmentioning

confidence: 99%

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

et al. 2021

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Combining functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) enables a non-invasive investigation of the human brain function and evaluation of the correlation of these two important modalities of brain activity. This paper explores recent reports on using advanced simultaneous EEG–fMRI methods proposed to map the regions and networks involved in focal epileptic seizure generation. One of the applications of EEG and fMRI combination as a valuable clinical approach is the pre-surgical evaluation of patients with epilepsy to map and localize the precise brain regions associated with epileptiform activity. In the process of conventional analysis using EEG–fMRI data, the interictal epileptiform discharges (IEDs) are visually extracted from the EEG data to be convolved as binary events with a predefined hemodynamic response function (HRF) to provide a model of epileptiform BOLD activity and use as a regressor for general linear model (GLM) analysis of the fMRI data. This review examines the methodologies involved in performing such studies, including techniques used for the recording of EEG inside the scanner, artifact removal, and statistical analysis of the fMRI signal. It then discusses the results reported for patients with primary generalized epilepsy and patients with different types of focal epileptic disorders. An important matter that these results have brought to light is that the brain regions affected by interictal epileptic discharges might not be limited to the ones where they have been generated. The developed methods can help reveal the regions involved in or affected by a seizure onset zone (SOZ). As confirmed by the reviewed literature, EEG–fMRI provides information that comes particularly useful when evaluating patients with refractory epilepsy for surgery.

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“…Most importantly, we have not included surface‐based morphology metrics (Ahmed et al, 2014; Whelan et al, 2018) or T1/T2 intensity alterations metrics (Noth et al, 2020; Shultz, O'Brien, Stefanidou, & Kuzniecky, 2014). We also did not include simultaneous EEG–fMRI methods due to a lack of IED in almost all EEG data acquired during fMRI sessions (Pardoe & Kuzniecky, 2014; Yamazoe et al, 2019). All these methods might improve classification accuracy or could render some classes to be specific to any pathology.…”

Section: Discussionmentioning

confidence: 99%

Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging

Mareček

Říha

Bartoňová

et al. 2021

Human Brain Mapping

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Many methods applied to data acquired by various imaging modalities have been evaluated for their benefit in localizing lesions in magnetic resonance (MR) negative epilepsy patients. No approach has proven to be a stand‐alone method with sufficiently high sensitivity and specificity. The presented study addresses the potential benefit of the automated fusion of results of individual methods in presurgical evaluation. We collected electrophysiological, MR, and nuclear imaging data from 137 patients with pharmacoresistant MR‐negative/inconclusive focal epilepsy. A subgroup of 32 patients underwent surgical treatment with known postsurgical outcomes and histopathology. We employed a Gaussian mixture model to reveal several classes of gray matter tissue. Classes specific to epileptogenic tissue were identified and validated using the surgery subgroup divided into two disjoint sets. We evaluated the classification accuracy of the proposed method at a voxel‐wise level and assessed the effect of individual methods. The training of the classifier resulted in six classes of gray matter tissue. We found a subset of two classes specific to tissue located in resected areas. The average classification accuracy (i.e., the probability of correct classification) was significantly higher than the level of chance in the training group (0.73) and even better in the validation surgery subgroup (0.82). Nuclear imaging, diffusion‐weighted imaging, and source localization of interictal epileptic discharges were the strongest methods for classification accuracy. We showed that the automatic fusion of results can identify brain areas that show epileptogenic gray matter tissue features. The method might enhance the presurgical evaluations of MR‐negative epilepsy patients.

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Widespread interictal epileptic discharge more likely than focal discharges to unveil the seizure onset zone in EEG-fMRI

Cited by 15 publications

References 21 publications

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

Mapping Epileptic Networks Using Simultaneous Intracranial EEG-fMRI

Localization of Epileptic Foci Based on Simultaneous EEG–fMRI Data

Automated fusion of multimodal imaging data for identifying epileptogenic lesions in patients with inconclusive magnetic resonance imaging

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