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Epilepsia
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Epilepsia
Article . 2023 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Article . 2023
License: CC BY NC ND
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Permutation entropy‐derived parameters to estimate the epileptogenic zone network

Authors: Bratu, Ionuț‐Flavius; Makhalova, Julia; Garnier, Elodie; Villalon, Samuel Medina; Jegou, Aude; Bonini, Francesca; Lagarde, Stanislas; +6 Authors

Permutation entropy‐derived parameters to estimate the epileptogenic zone network

Abstract

AbstractObjectiveQuantification of the epileptogenic zone network (EZN) most frequently implies analysis of seizure onset. However, important information can also be obtained from the postictal period, characterized by prominent changes in the EZN. We used permutation entropy (PE), a measure of signal complexity, to analyze the peri‐ictal stereoelectroencephalography (SEEG) signal changes with emphasis on the postictal state. We sought to determine the best PE‐derived parameter (PEDP) for identifying the EZN.MethodsSeveral PEDPs were computed retrospectively on SEEG‐recorded seizures of 86 patients operated on for drug‐resistant epilepsy: mean baseline preictal entropy, minimum ictal entropy, maximum postictal entropy, the ratio between the maximum postictal and the minimum ictal entropy, and the ratio between the maximum postictal and the baseline preictal entropy. The performance of each biomarker was assessed by comparing the identified epileptogenic contacts or brain regions against the EZN defined by clinical analysis incorporating the Epileptogenicity Index and the connectivity epileptogenicity index methods (EZNc), using the receiver‐operating characteristic and precision‐recall.ResultsThe ratio between the maximum postictal and the minimum ictal entropy (defined as the Permutation Entropy Index [PEI]) proved to be the best‐performing PEDP to identify the EZNC. It demonstrated the highest area under the curve (AUC) and F1 score at the contact level (AUC 0.72; F1 0.39) and at the region level (AUC 0.78; F1 0.47). PEI values gradually decreased between the EZN, the propagation network, and the non‐involved regions. PEI showed higher performance in patients with slow seizure‐onset patterns than in those with fast seizure‐onset patterns. The percentage of resected epileptogenic regions defined by PEI was significantly correlated with surgical outcome.SignificancePEI is a promising tool to improve the delineation of the EZN. PEI combines ease and robustness in a routine clinical setting with high sensitivity for seizures without fast activity at seizure onset.

Country
France
Keywords

[SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, Seizures, Entropy, Humans, Brain, [NLIN] Nonlinear Sciences [physics], Electroencephalography, Retrospective Studies

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green
hybrid