NREM sleep is the state of vigilance that best identifies the epileptogenic zone in the interictal electroencephalogram

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68081731%3A_____%2F19%3A00535709" target="_blank" >RIV/68081731:_____/19:00535709 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14110/19:00113177 RIV/00159816:_____/19:00072897

Result on the web

<a href="https://onlinelibrary.wiley.com/doi/abs/10.1111/epi.16377" target="_blank" >https://onlinelibrary.wiley.com/doi/abs/10.1111/epi.16377</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1111/epi.16377" target="_blank" >10.1111/epi.16377</a>

Result language

angličtina

Original language name

NREM sleep is the state of vigilance that best identifies the epileptogenic zone in the interictal electroencephalogram

Original language description

Interictal epileptiform anomalies such as epileptiform discharges or high-frequency oscillations show marked variations across the sleep-wake cycle. This study investigates which state of vigilance is the best to localize the epileptogenic zone (EZ) in interictal intracranial electroencephalography (EEG). Thirty patients with drug-resistant epilepsy undergoing stereo-EEG (SEEG)/sleep recording and subsequent open surgery were included, 13 patients (43.3%) had good surgical outcome (Engel class I). Sleep was scored following standard criteria. Multiple features based on the interictal EEG (interictal epileptiform discharges, high-frequency oscillations, univariate and bivariate features) were used to train a support vector machine (SVM) model to classify SEEG contacts placed in the EZ. The performance of the algorithm was evaluated by the mean area under the receiver-operating characteristic (ROC) curves (AUCs) and positive predictive values (PPVs) across 10-minute sections of wake, non-rapid eye movement sleep (NREM) stages N2 and N3, REM sleep, and their combination. Highest AUCs were achieved in NREM sleep stages N2 and N3 compared to wakefulness and REM (P <.01). There was no improvement when using a combination of all four states (P >.05), the best performing features in the combined state were selected from NREM sleep. There were differences between good (Engel I) and poor (Engel II-IV) outcomes in PPV (P <.05) and AUC (P <.01) across all states. The SVM multifeature approach outperformed spikes and high-frequency oscillations (P <.01) and resulted in results similar to those of the seizure-onset zone (SOZ, P >.05). Sleep improves the localization of the EZ with best identification obtained in NREM sleep stages N2 and N3. Results based on the multifeature classification in 10 minutes of NREM sleep were not different from the results achieved by the SOZ based on 12.7 days of seizure monitoring. This finding might ultimately result in a more time-efficient intracranial presurgical investigation of focal epilepsy.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20601 - Medical engineering

Project

<a href="/en/project/LTAUSA18056" target="_blank" >LTAUSA18056: Seizure onset zone localization and advanced analysis of high-frequency intracranial EEG</a><br>

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Epilepsia

ISSN

0013-9580

e-ISSN

—

Volume of the periodical

60

Issue of the periodical within the volume

12

Country of publishing house

US - UNITED STATES

Number of pages

12

Pages from-to

2404-2415

UT code for WoS article

000545973100008

EID of the result in the Scopus database

2-s2.0-85074825684