Literature DB >> 28160749

Interrater reliability of visually evaluated high frequency oscillations.

Aaron M Spring1, Daniel J Pittman2, Yahya Aghakhani3, Jeffrey Jirsch4, Neelan Pillay5, Luis E Bello-Espinosa6, Colin Josephson7, Paolo Federico8.   

Abstract

OBJECTIVE: High frequency oscillations (HFOs) and interictal epileptiform discharges (IEDs) have been shown to be markers of epileptogenic regions. However, there is currently no 'gold standard' for identifying HFOs. Accordingly, we aimed to formally characterize the interrater reliability of HFO markings to validate the current practices.
METHODS: A morphology detector was implemented to detect events (candidate HFOs, lower-threshold events, and distractors) from the intracranial EEG (iEEG) of ten patients. Six electroencephalographers visually evaluated these events for the presence of HFOs and IEDs. Interrater reliability was calculated using pairwise Cohen's Kappa (κ) and intraclass correlation coefficients (ICC).
RESULTS: The HFO evaluation distributions were significantly different for most pairs of reviewers (p<0.05; 11/15 pairs). Interrater reliability was poor for HFOs alone (κmean=0.403; ICC=0.401) and HFO+IEDs (κmean=0.568; ICC=0.570).
CONCLUSIONS: The current practice of using two visual reviewers to identify HFOs is prone to bias arising from the poor agreement between reviewers, limiting the extrinsic validity of studies using these markers. SIGNIFICANCE: The poor interrater reliability underlines the need for a framework to reconcile the important findings of existing studies. The present epoched design is an ideal candidate for the implementation of such a framework. Copyright Â
© 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  High frequency oscillations; Interictal epileptiform discharges; Interrater reliability; Interrater variability; Intracranial electroencephalography; Spikes

Mesh:

Year:  2016        PMID: 28160749     DOI: 10.1016/j.clinph.2016.12.017

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  17 in total

1.  Progress and Remaining Challenges in the Application of High Frequency Oscillations as Biomarkers of Epileptic Brain.

Authors:  Fatemeh Khadjevand; Jan Cimbalnik; Gregory A Worrell
Journal:  Curr Opin Biomed Eng       Date:  2017-09-22

2.  Harmonization of pipeline for detection of HFOs in a rat model of post-traumatic epilepsy in preclinical multicenter study on post-traumatic epileptogenesis.

Authors:  Cesar Santana-Gomez; Pedro Andrade; Matthew R Hudson; Tomi Paananen; Robert Ciszek; Gregory Smith; Idrish Ali; Brian K Rundle; Xavier Ekolle Ndode-Ekane; Pablo M Casillas-Espinosa; Riikka Immonen; Noora Puhakka; Nigel Jones; Rhys D Brady; Piero Perucca; Sandy R Shultz; Asla Pitkänen; Terence J O'Brien; Richard Staba
Journal:  Epilepsy Res       Date:  2019-03-15       Impact factor: 3.045

3.  Automatic vs. Manual Detection of High Frequency Oscillations in Intracranial Recordings From the Human Temporal Lobe.

Authors:  Aljoscha Thomschewski; Nathalie Gerner; Patrick B Langthaler; Eugen Trinka; Arne C Bathke; Jürgen Fell; Yvonne Höller
Journal:  Front Neurol       Date:  2020-10-19       Impact factor: 4.003

4.  Scalp EEG interictal high frequency oscillations as an objective biomarker of infantile spasms.

Authors:  Hiroki Nariai; Shaun A Hussain; Danilo Bernardo; Hirotaka Motoi; Masaki Sonoda; Naoto Kuroda; Eishi Asano; Jimmy C Nguyen; David Elashoff; Raman Sankar; Anatol Bragin; Richard J Staba; Joyce Y Wu
Journal:  Clin Neurophysiol       Date:  2020-09-03       Impact factor: 3.708

5.  The effect of increased intracranial EEG sampling rates in clinical practice.

Authors:  Kathryn A Davis; Seth P Devries; Abba Krieger; Temenuzhka Mihaylova; Daniela Minecan; Brian Litt; Joost B Wagenaar; William C Stacey
Journal:  Clin Neurophysiol       Date:  2017-11-16       Impact factor: 3.708

6.  Resection of high frequency oscillations predicts seizure outcome in the individual patient.

Authors:  Tommaso Fedele; Sergey Burnos; Ece Boran; Niklaus Krayenbühl; Peter Hilfiker; Thomas Grunwald; Johannes Sarnthein
Journal:  Sci Rep       Date:  2017-10-23       Impact factor: 4.379

7.  Identifying the Epileptogenic Zone With the Relative Strength of High-Frequency Oscillation: A Stereoelectroencephalography Study.

Authors:  Lei Qi; Xing Fan; Xiaorong Tao; Qi Chai; Kai Zhang; Fangang Meng; Wenhan Hu; Lin Sang; Xiaoli Yang; Hui Qiao
Journal:  Front Hum Neurosci       Date:  2020-06-09       Impact factor: 3.169

8.  Detection of anomalous high-frequency events in human intracranial EEG.

Authors:  Krit Charupanit; Indranil Sen-Gupta; Jack J Lin; Beth A Lopour
Journal:  Epilepsia Open       Date:  2020-05-20

9.  Utilization of independent component analysis for accurate pathological ripple detection in intracranial EEG recordings recorded extra- and intra-operatively.

Authors:  Shoichi Shimamoto; Zachary J Waldman; Iren Orosz; Inkyung Song; Anatol Bragin; Itzhak Fried; Jerome Engel; Richard Staba; Ashwini Sharan; Chengyuan Wu; Michael R Sperling; Shennan A Weiss
Journal:  Clin Neurophysiol       Date:  2017-10-25       Impact factor: 3.708

10.  Neural fragility as an EEG marker of the seizure onset zone.

Authors:  Jorge Gonzalez-Martinez; Sridevi V Sarma; Adam Li; Chester Huynh; Zachary Fitzgerald; Iahn Cajigas; Damian Brusko; Jonathan Jagid; Angel O Claudio; Andres M Kanner; Jennifer Hopp; Stephanie Chen; Jennifer Haagensen; Emily Johnson; William Anderson; Nathan Crone; Sara Inati; Kareem A Zaghloul; Juan Bulacio
Journal:  Nat Neurosci       Date:  2021-08-05       Impact factor: 24.884

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