Literature DB >> 30786048

High-Frequency Oscillation Networks and Surgical Outcome in Adult Focal Epilepsy.

Karina A González Otárula1,2, Nicolás von Ellenrieder1, Carolina Cuello-Oderiz1, François Dubeau1, Jean Gotman1.   

Abstract

OBJECTIVE: To investigate whether high-frequency oscillations (HFOs) show spatiotemporal propagation and assess the relevance of the earliest oscillations in relation to the seizure onset zone (SOZ) and postsurgical outcome.
METHODS: We retrospectively investigated the intracerebral electroencephalography (EEG) of patients who became seizure free after subsequent surgery. We marked HFOs during 1 hour of recordings. We calculated the time delay between pairs of channels as the median delay between their HFOs and constructed a time line of the delay of each channel with respect to the earliest channel (first source channel). A network was defined when a temporal order could be established among the channels based on the existence of statistically significant delays.
RESULTS: Fifteen patients with good surgical outcome were included. We found ripple networks in all patients, and fast ripple networks in 9. For ripples, first source channels were found in a higher proportion in the SOZ than the rest of the network channels (15 of 27 [56%] versus 93 of 262 [35%]; p = 0.04). For both ripples and fast ripples, first source channels were resected more often that the rest of the network channels (ripples: 13 of 27 [48%] versus 65 of 262 [25%]; p = 0.01; fast ripples: 8 of 9 [89%] versus 17 of 40 [43%]; p = 0.002); channels with the highest rates of ripples and fast ripples were resected in a similar proportion.
INTERPRETATION: These results demonstrate that interictal HFOs are organized in networks and indicate a possible need for the resection of first source channels. However, resecting them is not superior to resecting channels with highest rates of HFOs. Ann Neurol 2019;85:485-494.
© 2019 American Neurological Association.

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Mesh:

Year:  2019        PMID: 30786048     DOI: 10.1002/ana.25442

Source DB:  PubMed          Journal:  Ann Neurol        ISSN: 0364-5134            Impact factor:   10.422


  17 in total

Review 1.  Localizing the Epileptogenic Zone with Novel Biomarkers.

Authors:  Christos Papadelis; M Scott Perry
Journal:  Semin Pediatr Neurol       Date:  2021-08-20       Impact factor: 3.042

2.  Delineation of epileptogenic zones with high frequency magnetic source imaging based on kurtosis and skewness.

Authors:  Jing Xiang; Ellen Maue; Hisako Fujiwara; Francesco T Mangano; Hansel Greiner; Jeffrey Tenney
Journal:  Epilepsy Res       Date:  2021-03-08       Impact factor: 3.045

3.  Magnetoencephalography for epileptic focus localization based on Tucker decomposition with ripple window.

Authors:  Li-Juan Shi; Bo-Xuan Wei; Lu Xu; Yi-Cong Lin; Yu-Ping Wang; Ji-Cong Zhang
Journal:  CNS Neurosci Ther       Date:  2021-05-04       Impact factor: 5.243

4.  Ictal onset stereoelectroencephalography patterns in temporal lobe epilepsy: type, distribution, and prognostic value.

Authors:  Deqiu Cui; Runshi Gao; Cuiping Xu; Hao Yan; Xiaohua Zhang; Tao Yu; Guojun Zhang
Journal:  Acta Neurochir (Wien)       Date:  2022-01-18       Impact factor: 2.216

Review 5.  Epileptic Mechanisms Shared by Alzheimer's Disease: Viewed via the Unique Lens of Genetic Epilepsy.

Authors:  Jing-Qiong Kang
Journal:  Int J Mol Sci       Date:  2021-07-01       Impact factor: 5.923

6.  Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones.

Authors:  Jing Xiang; Ellen Maue; Han Tong; Francesco T Mangano; Hansel Greiner; Jeffrey Tenney
Journal:  Seizure       Date:  2021-05-04       Impact factor: 3.414

7.  Integrated Automatic Detection, Classification and Imaging of High Frequency Oscillations With Stereoelectroencephalography.

Authors:  Baotian Zhao; Wenhan Hu; Chao Zhang; Xiu Wang; Yao Wang; Chang Liu; Jiajie Mo; Xiaoli Yang; Lin Sang; Yanshan Ma; Xiaoqiu Shao; Kai Zhang; Jianguo Zhang
Journal:  Front Neurosci       Date:  2020-06-04       Impact factor: 4.677

8.  Learning to define an electrical biomarker of the epileptogenic zone.

Authors:  Jian Li; Olesya Grinenko; John C Mosher; Jorge Gonzalez-Martinez; Richard M Leahy; Patrick Chauvel
Journal:  Hum Brain Mapp       Date:  2019-10-14       Impact factor: 5.038

9.  Application of a convolutional neural network for fully-automated detection of spike ripples in the scalp electroencephalogram.

Authors:  Jessica K Nadalin; Uri T Eden; Xue Han; R Mark Richardson; Catherine J Chu; Mark A Kramer
Journal:  J Neurosci Methods       Date:  2021-06-04       Impact factor: 2.987

10.  Scalp ripples as prognostic biomarkers of epileptogenicity in pediatric surgery.

Authors:  Eleonora Tamilia; Matilde Dirodi; Michel Alhilani; P Ellen Grant; Joseph R Madsen; Steven M Stufflebeam; Phillip L Pearl; Christos Papadelis
Journal:  Ann Clin Transl Neurol       Date:  2020-02-25       Impact factor: 4.511

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