Cargando…
Interictal high frequency background activity as a biomarker of epileptogenic tissue
High frequency oscillations (HFOs) are very brief events that are a well-established biomarker of the epileptogenic zone (EZ) but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency ‘background’ data, which has received little atten...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417455/ https://www.ncbi.nlm.nih.gov/pubmed/34704026 http://dx.doi.org/10.1093/braincomms/fcab188 |
_version_ | 1783748384404799488 |
---|---|
author | Stovall, Truman Hunt, Brian Glynn, Simon Stacey, William C Gliske, Stephen V |
author_facet | Stovall, Truman Hunt, Brian Glynn, Simon Stacey, William C Gliske, Stephen V |
author_sort | Stovall, Truman |
collection | PubMed |
description | High frequency oscillations (HFOs) are very brief events that are a well-established biomarker of the epileptogenic zone (EZ) but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency ‘background’ data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the EZ. We analysed intracranial EEG (30–500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63–307 h per subject), excluding all detected HFOs. We assessed association between each feature and the seizure onset zone (SOZ) and resected volume (RV) using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross-validation to avoid in-sample training. Association of the pathology score with the SOZ and RV was quantified using an asymmetry measure. Many features were associated with the SOZ: 23/38 features had odds ratios >1.3 or <0.7 and 17/38 had odds ratios different than zero with high significance (P < 0.001/39, logistic regression with Bonferroni Correction). The pathology score, the rate of HFOs, and their channel-wise product were each strongly associated with the SOZ [median asymmetry ≥0.44, good surgery outcome patients; median asymmetry ≥0.40, patients with other outcomes; 95% confidence interval (CI) > 0.27 in both cases]. The pathology score and the channel-wise product also had higher asymmetry with respect to the SOZ than the HFO rate alone (median difference in asymmetry ≥0.18, 95% CI >0.05). These results support that the high frequency background data contains useful information for determining the EZ, distinct and complementary to information from detected HFOs. The concordance between the high frequency activity pathology score and the rate of HFOs appears to be a better biomarker of epileptic tissue than either measure alone. |
format | Online Article Text |
id | pubmed-8417455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-84174552021-11-26 Interictal high frequency background activity as a biomarker of epileptogenic tissue Stovall, Truman Hunt, Brian Glynn, Simon Stacey, William C Gliske, Stephen V Brain Commun Original Article High frequency oscillations (HFOs) are very brief events that are a well-established biomarker of the epileptogenic zone (EZ) but are rare and comprise only a tiny fraction of the total recorded EEG. We hypothesize that the interictal high frequency ‘background’ data, which has received little attention but represents the majority of the EEG record, also may contain additional, novel information for identifying the EZ. We analysed intracranial EEG (30–500 Hz frequency range) acquired from 24 patients who underwent resective surgery. We computed 38 quantitative features based on all usable, interictal data (63–307 h per subject), excluding all detected HFOs. We assessed association between each feature and the seizure onset zone (SOZ) and resected volume (RV) using logistic regression. A pathology score per channel was also created via principle component analysis and logistic regression, using hold-out-one-patient cross-validation to avoid in-sample training. Association of the pathology score with the SOZ and RV was quantified using an asymmetry measure. Many features were associated with the SOZ: 23/38 features had odds ratios >1.3 or <0.7 and 17/38 had odds ratios different than zero with high significance (P < 0.001/39, logistic regression with Bonferroni Correction). The pathology score, the rate of HFOs, and their channel-wise product were each strongly associated with the SOZ [median asymmetry ≥0.44, good surgery outcome patients; median asymmetry ≥0.40, patients with other outcomes; 95% confidence interval (CI) > 0.27 in both cases]. The pathology score and the channel-wise product also had higher asymmetry with respect to the SOZ than the HFO rate alone (median difference in asymmetry ≥0.18, 95% CI >0.05). These results support that the high frequency background data contains useful information for determining the EZ, distinct and complementary to information from detected HFOs. The concordance between the high frequency activity pathology score and the rate of HFOs appears to be a better biomarker of epileptic tissue than either measure alone. Oxford University Press 2021-08-31 /pmc/articles/PMC8417455/ /pubmed/34704026 http://dx.doi.org/10.1093/braincomms/fcab188 Text en © The Author(s) (2021). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please email: journals.permissions@oup.com https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Article Stovall, Truman Hunt, Brian Glynn, Simon Stacey, William C Gliske, Stephen V Interictal high frequency background activity as a biomarker of epileptogenic tissue |
title | Interictal high frequency background activity as a biomarker of epileptogenic tissue |
title_full | Interictal high frequency background activity as a biomarker of epileptogenic tissue |
title_fullStr | Interictal high frequency background activity as a biomarker of epileptogenic tissue |
title_full_unstemmed | Interictal high frequency background activity as a biomarker of epileptogenic tissue |
title_short | Interictal high frequency background activity as a biomarker of epileptogenic tissue |
title_sort | interictal high frequency background activity as a biomarker of epileptogenic tissue |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8417455/ https://www.ncbi.nlm.nih.gov/pubmed/34704026 http://dx.doi.org/10.1093/braincomms/fcab188 |
work_keys_str_mv | AT stovalltruman interictalhighfrequencybackgroundactivityasabiomarkerofepileptogenictissue AT huntbrian interictalhighfrequencybackgroundactivityasabiomarkerofepileptogenictissue AT glynnsimon interictalhighfrequencybackgroundactivityasabiomarkerofepileptogenictissue AT staceywilliamc interictalhighfrequencybackgroundactivityasabiomarkerofepileptogenictissue AT gliskestephenv interictalhighfrequencybackgroundactivityasabiomarkerofepileptogenictissue |