<scp>MEG</scp> abnormalities and mechanisms of surgical failure in neocortical epilepsy

Owen, Thomas W; Schroeder, Gabrielle M; Vytene, Janiukstyte,; Hall, Gerard R; McEvoy, Andrew W.; Miserocchi, Anna; Tisi, Jane de; Duncan, John; Rugg‐Gunn, Fergus; Wang, Yujiang; Taylor, Peter Neal

doi:10.1111/epi.17503

Cited by 14 publications

(25 citation statements)

References 59 publications

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“…Beyond invasive iEEG recordings, our results hint at the possibility that noninvasive electrophysiological abnormality maps (e.g., based on scalp EEG, MEG) are likely also relatively stable over time. This hypothesis is supported by a recent MEG study mapping abnormalities across multiple epochs 8 …”

Section: Discussionsupporting

confidence: 59%

“…This hypothesis is supported by a recent MEG study mapping abnormalities across multiple epochs. 8 Our findings are encouraging, especially when compared to other traditional interictal markers of epileptogenic tissue such as interictal spikes. Apart from the previously demonstrated added value of band power abnormality compared to interictal spikes in our cohort, 6 our results here also seem to suggest that band power abnormality is temporally stable enough as a biomarker.…”

Section: Interictal and Peri-ictal Time Windows Perform Similarly At ...mentioning

confidence: 53%

“…Finally, information from multiple modalities may also guide implantation of iEEG electrodes, allowing for more relevant spatial sampling and better subsequent surgical planning. 31 In summary, using continuously recorded iEEG, we have demonstrated that band power abnormality maps are temporally stable in terms of their localizing information, despite brain state and seizure-related changes throughout the recording. This finding is an important cornerstone in establishing the feasibility of band power abnormality mapping to aid localization for presurgical evaluation.…”

Section: Interictal and Peri-ictal Time Windows Perform Similarly At ...mentioning

confidence: 68%

“…However, other measures besides

D_{RS}

may need to be considered, especially given the abovementioned possibility of nonepileptogenic abnormalities and the patient‐specific spatial sampling in iEEG. Other possibilities include measures that only focus on the abnormality of the resected tissue or the proportion of resected abnormalities (see, e.g., Owen et al 8 ).…”

Section: Discussionmentioning

confidence: 99%

“…Instead, the normative distribution is derived from recordings from postulated nonepileptic brain areas across a large cohort of patients 3–5 . The subsequently derived band power abnormalities have recently been shown by multiple independent studies to contain localizing information 6–8 . However, those studies used short segments of EEG or magnetoencephalographic (MEG) recordings of approximately 1 min far away from seizures.…”

Section: Introductionmentioning

confidence: 99%

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Temporal stability of intracranial electroencephalographic abnormality maps for localizing epileptogenic tissue

et al. 2023

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ObjectiveIdentifying abnormalities on interictal intracranial electroencephalogram (iEEG), by comparing patient data to a normative map, has shown promise for the localization of epileptogenic tissue and prediction of outcome. The approach typically uses short interictal segments of approximately 1 min. However, the temporal stability of findings has not been established.MethodsHere, we generated a normative map of iEEG in nonpathological brain tissue from 249 patients. We computed regional band power abnormalities in a separate cohort of 39 patients for the duration of their monitoring period (.92–8.62 days of iEEG data, mean = 4.58 days per patient, >4800 hours recording). To assess the localizing value of band power abnormality, we computed —a measure of how different the surgically resected and spared tissue was in terms of band power abnormalities—over time.ResultsIn each patient, the value was relatively consistent over time. The median of the entire recording period separated seizure‐free (International League Against Epilepsy [ILAE] = 1) and not‐seizure‐free (ILAE 1) patients well (area under the curve [AUC] = .69). This effect was similar interictally (AUC = .69) and peri‐ictally (AUC = .71).SignificanceOur results suggest that band power abnormality D_RS, as a predictor of outcomes from epilepsy surgery, is a relatively robust metric over time. These findings add further support for abnormality mapping of neurophysiology data during presurgical evaluation.

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Section: Discussionsupporting

confidence: 59%

Section: Interictal and Peri-ictal Time Windows Perform Similarly At ...mentioning

confidence: 53%

Section: Interictal and Peri-ictal Time Windows Perform Similarly At ...mentioning

confidence: 68%

“…However, other measures besides

D_{RS}

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Temporal stability of intracranial electroencephalographic abnormality maps for localizing epileptogenic tissue

et al. 2023

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Identifying epileptogenic abnormalities through spatial clustering of MEG interictal band power

et al. 2023

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Successful epilepsy surgery depends on localizing and resecting cerebral abnormalities and networks that generate seizures. Abnormalities, however, may be widely distributed across multiple discontiguous areas. We propose spatially constrained clusters as candidate areas for further investigation and potential resection. We quantified the spatial overlap between the abnormality cluster and subsequent resection, hypothesizing a greater overlap in seizure‐free patients. Thirty‐four individuals with refractory focal epilepsy underwent pre‐surgical resting‐state interictal magnetoencephalography (MEG) recording. Fourteen individuals were totally seizure‐free (ILAE 1) after surgery and 20 continued to have some seizures post‐operatively (ILAE 2+). Band power abnormality maps were derived using controls as a baseline. Patient abnormalities were spatially clustered using the k‐means algorithm. The tissue within the cluster containing the most abnormal region was compared with the resection volume using the dice score. The proposed abnormality cluster overlapped with the resection in 71% of ILAE 1 patients. Conversely, an overlap only occurred in 15% of ILAE 2+ patients. This effect discriminated outcome groups well (AUC = 0.82). Our novel approach identifies clusters of spatially similar tissue with high abnormality. This is clinically valuable, providing (a) a data‐driven framework to validate current hypotheses of the epileptogenic zone localization or (b) to guide further investigation.

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