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Protocol for multicentre comparison of interictal high-frequency oscillations as a predictor of seizure freedom

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F22%3A00077781" target="_blank" >RIV/00159816:_____/22:00077781 - isvavai.cz</a>

  • Result on the web

    <a href="https://academic.oup.com/braincomms/article/4/3/fcac151/6604800?login=true" target="_blank" >https://academic.oup.com/braincomms/article/4/3/fcac151/6604800?login=true</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1093/braincomms/fcac151" target="_blank" >10.1093/braincomms/fcac151</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Protocol for multicentre comparison of interictal high-frequency oscillations as a predictor of seizure freedom

  • Original language description

    In drug-resistant focal epilepsy, interictal high-frequency oscillations (HFOs) recorded from intracranial EEG (iEEG) may provide clinical information for delineating epileptogenic brain tissue. The iEEG electrode contacts that contain HFO are hypothesized to delineate the epileptogenic zone; their resection should then lead to postsurgical seizure freedom. We test whether our prospective definition of clinically relevant HFO is in agreement with postsurgical seizure outcome. The algorithm is fully automated and is equally applied to all data sets. The aim is to assess the reliability of the proposed detector and analysis approach. We use an automated data-independent prospective definition of clinically relevant HFO that has been validated in data from two independent epilepsy centres. In this study, we combine retrospectively collected data sets from nine independent epilepsy centres. The analysis is blinded to clinical outcome. We use iEEG recordings during NREM sleep with a minimum of 12 epochs of 5 min of NREM sleep. We automatically detect HFO in the ripple (80-250 Hz) and in the fast ripple (250-500 Hz) band. There is no manual rejection of events in this fully automated algorithm. The type of HFO that we consider clinically relevant is defined as the simultaneous occurrence of a fast ripple and a ripple. We calculate the temporal consistency of each patient&apos;s HFO rates over several data epochs within and between nights. Patients with temporal consistency &lt;50% are excluded from further analysis. We determine whether all electrode contacts with high HFO rate are included in the resection volume and whether seizure freedom (ILAE 1) was achieved at &gt;= 2 years follow-up. Applying a previously validated algorithm to a large cohort from several independent epilepsy centres may advance the clinical relevance and the generalizability of HFO analysis as essential next step for use of HFO in clinical practice. High-frequency oscillations (HFOs) have long been discussed as biomarkers for epileptogenic tissue. Dimakopoulos et al. propose a prospective multicentre study to validate whether HFOs in intracranial EEG recorded during sleep may serve to predict the seizure outcome after epilepsy surgery.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30210 - Clinical neurology

Result continuities

  • Project

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2022

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    BRAIN COMMUNICATIONS

  • ISSN

    2632-1297

  • e-ISSN

    2632-1297

  • Volume of the periodical

    4

  • Issue of the periodical within the volume

    3

  • Country of publishing house

    GB - UNITED KINGDOM

  • Number of pages

    8

  • Pages from-to

    nestrankovano

  • UT code for WoS article

    000816825400001

  • EID of the result in the Scopus database