Source localization of the seizure onset zone from ictal EEG/MEG data

Pellegrino, Giovanni; Hedrich, Tanguy; Chowdhury, Rasheda Arman; Hall, Jeffery A.; Lina, Jean‐Marc; Dubeau, François; Kobayashi, Eliane; Grova, Christophe

doi:10.1002/hbm.23191

Cited by 92 publications

(95 citation statements)

References 90 publications

(177 reference statements)

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“… A cluster map was assessed as concordant with the CR whenever the vertex of the cluster map exhibiting the maximum source amplitude (source maximum) was inside the CR. A cluster map was assessed as sublobar concordant with the CR whenever the source maximum was within the sublobar region of the CR. We identified 10 sublobar regions per hemisphere based on anatomical atlas (Agirre‐Arrizubieta, Huiskamp, Ferrier, van Huffelen, & Leijten, ; de Gooijer‐van de Groep, Leijten, Ferrier, & Huiskamp, ; Heers et al, ; Pellegrino et al, ). The sublobar region classifications were based on the anatomical atlas proposed in (Agirre‐Arrizubieta et al, ), which consisted of subdivisions of the different lobes, resulting in a total of 10 regions per hemisphere.…”

Section: Methodsmentioning

confidence: 99%

“…The central, occipital, and parietal lobes were not further subdivided (de Gooijer‐van de Groep et al, ). Such a qualitative evaluation was made visually using anatomical landmarks as used in two of our previous studies (Heers et al, ; Pellegrino et al, ). A cluster map was assessed as discordant with the CR whenever the source maximum was outside the sublobar region.…”

Section: Methodsmentioning

confidence: 99%

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Reproducibility of EEG‐MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Chowdhury

Pellegrino

Aydın

et al. 2017

Human Brain Mapping

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Fusion of electroencephalography (EEG) and magnetoencephalography (MEG) data using maximum entropy on the mean method (MEM-fusion) takes advantage of the complementarities between EEG and MEG to improve localization accuracy. Simulation studies demonstrated MEM-fusion to be robust especially in noisy conditions such as single spike source localizations (SSSL). Our objective was to assess the reliability of SSSL using MEM-fusion on clinical data. We proposed to cluster SSSL results to find the most reliable and consistent source map from the reconstructed sources, the so-called consensus map. Thirty-four types of interictal epileptic discharges (IEDs) were analyzed from 26 patients with well-defined epileptogenic focus. SSSLs were performed on EEG, MEG, and fusion data and consensus maps were estimated using hierarchical clustering. Qualitative (spike-to-spike reproducibility rate, SSR) and quantitative (localization error and spatial dispersion) assessments were performed using the epileptogenic focus as clinical reference. Fusion SSSL provided significantly better results than EEG or MEG alone. Fusion found at least one cluster concordant with the clinical reference in all cases. This concordant cluster was always the one involving the highest number of spikes. Fusion yielded highest reproducibility (SSR EEG = 55%, MEG = 71%, fusion = 90%) and lowest localization error. Also, using only few channels from either modality (21EEG + 272MEG or 54EEG + 25MEG) was sufficient to reach accurate fusion. MEM-fusion with consensus map approach provides an objective way of finding the most reliable and concordant generators of IEDs. We, therefore, suggest the pertinence of SSSL using MEM-fusion as a valuable clinical tool for presurgical evaluation of epilepsy.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Reproducibility of EEG‐MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Chowdhury

Pellegrino

Aydın

et al. 2017

Human Brain Mapping

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“…The earliest electrophysiological change distinct from the BGA was identified as ictal onset using simultaneous MEG and EEG according to standard methods outlined in the literature. 6,8 Baseline was defined as the 4-second period that antecedes 10 minutes distant from any seizure or artifact. Initial ictal rhythms in the buildup of all seizures remained focal for a minimum of 4 seconds and later propagated to the ipsilateral/contralateral hemisphere.…”

Section: Mri and Meg Acquisitionmentioning

confidence: 99%

Magnetoencephalographic imaging of ictal high‐frequency oscillations (80‐200 Hz) in pharmacologically resistant focal epilepsy

et al. 2017

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SummaryObjective: Specificity of ictal high-frequency oscillations (HFOs) in identifying epileptogenic abnormality is significant, compared to the spikes and interictal HFOs. The objectives of the study were to detect and to localize ictal HFOs by magnetoencephalography (MEG) for identifying the seizure onset zone (SOZ), evaluate the cortical excitability from preictal to ictal transition, and establish HFO concordance rates with other modalities and postsurgical resection. Methods: Sixty-seven patients with drug-resistant epilepsy had at least 1 spontaneous seizure each during MEG acquisition, and analysis was carried out on 20 seizures from 20 patients. Ictal MEG data were bandpass filtered (80-200 Hz) to visualize, review, and analyze the HFOs co-occurring with ictal spikes. Source montages were generated on both hemispheres, mean fast Fourier transform was computed on virtual time series for determining the preictal to ictal spectral power transition, and source reconstruction was performed with sLORETA and beamformers. The concordance rates of ictal MEG HFOs (SOZ) was estimated with 4 reference epileptogenic regions. Results: In each subject, transient bursts of high-frequency oscillatory cycles, distinct from the background activity, were observed in the periictal continuum.Time-frequency analysis showed significant spectral power surge (85-160 Hz) during ictal state (P < .05) compared to preictal state, but there was no variation in the peak HFO frequencies (P > .05) for each subgroup and at each source montage. HFO source localization was consistent between algorithms (k = 0.857 AE 0.138), with presumed epileptogenic zone (EZ) comparable to other modalities. In patients who underwent surgery (n = 6), MEG HFO SOZ was concordant with the presumed EZ and the surgical resection site (100%), and all were seizure-free during follow-up. Significance: HFOs could be detected in the MEG periictal state, and its sources were accurately localized. During preictal to ictal transition, HFOs exhibited

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“…NOTE: The MEM is an efficient technique that has been successfully used to determine the location and extent of sources of epileptic activity [62][63][64] . The wMEM is an extension of MEM that has been developed for localizing oscillatory activity as evaluated with realistic simulations 65 .…”

Section: Hfo Source Localization At Both Eeg and Meg Using The Wavelementioning

confidence: 99%

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

Papadelis

Tamilia

Stufflebeam

et al. 2016

JoVE

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Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery.The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy.

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Source localization of the seizure onset zone from ictal EEG/MEG data

Abstract: wMEM allows non-invasive localization of the SOZ from ictal MEG and EEG. MSI-SOZ performs better than ESI-SOZ. MSI/ESI-SOZ can provide important additional information to MSI/ESI-Spikes during presurgical evaluation. Hum Brain Mapp 37:2528-2546, 2016. © 2016 Wiley Periodicals, Inc.

Cited by 92 publications

References 90 publications

Reproducibility of EEG‐MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Reproducibility of EEG‐MEG fusion source analysis of interictal spikes: Relevance in presurgical evaluation of epilepsy

Magnetoencephalographic imaging of ictal high‐frequency oscillations (80‐200 Hz) in pharmacologically resistant focal epilepsy

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

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