scholarly journals Epilepsy Surgery for Refractory Focal Epilepsy based on the Analysis of High Frequency Oscillations with Intracranial Electroencephalography : A Case Report

2015 ◽  
Vol 24 (1) ◽  
pp. 32-39
Author(s):  
Akihiko Kondo ◽  
Tomoyuki Akiyama ◽  
Takashi Agari ◽  
Makio Oka ◽  
Yoshinori Kobayashi ◽  
...  
2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Ece Boran ◽  
Johannes Sarnthein ◽  
Niklaus Krayenbühl ◽  
Georgia Ramantani ◽  
Tommaso Fedele

Abstract High-frequency oscillations (HFO) are promising EEG biomarkers of epileptogenicity. While the evidence supporting their significance derives mainly from invasive recordings, recent studies have extended these observations to HFO recorded in the widely accessible scalp EEG. Here, we investigated whether scalp HFO in drug-resistant focal epilepsy correspond to epilepsy severity and how they are affected by surgical therapy. In eleven children with drug-resistant focal epilepsy that underwent epilepsy surgery, we prospectively recorded pre- and postsurgical scalp EEG with a custom-made low-noise amplifier (LNA). In four of these children, we also recorded intraoperative electrocorticography (ECoG). To detect clinically relevant HFO, we applied a previously validated automated detector. Scalp HFO rates showed a significant positive correlation with seizure frequency (R2 = 0.80, p < 0.001). Overall, scalp HFO rates were higher in patients with active epilepsy (19 recordings, p = 0.0066, PPV = 86%, NPV = 80%, accuracy = 84% CI [62% 94%]) and decreased following successful epilepsy surgery. The location of the highest HFO rates in scalp EEG matched the location of the highest HFO rates in ECoG. This study is the first step towards using non-invasively recorded scalp HFO to monitor disease severity in patients affected by epilepsy.


2017 ◽  
Vol 2 (2) ◽  
pp. 267-272 ◽  
Author(s):  
Su Liu ◽  
Michael M. Quach ◽  
Daniel J. Curry ◽  
Monika Ummat ◽  
Elaine Seto ◽  
...  

Epilepsia ◽  
2021 ◽  
Author(s):  
Nicole E. C. Klink ◽  
Willemiek J. E. M. Zweiphenning ◽  
Cyrille H. Ferrier ◽  
Peter H. Gosselaar ◽  
Kai J. Miller ◽  
...  

2012 ◽  
Vol 123 (1) ◽  
pp. 100-105 ◽  
Author(s):  
Luciana Andrade-Valença ◽  
Francesco Mari ◽  
Julia Jacobs ◽  
Maeike Zijlmans ◽  
André Olivier ◽  
...  

2017 ◽  
Vol 128 (5) ◽  
pp. 858-866 ◽  
Author(s):  
M.A. van 't Klooster ◽  
N.E.C. van Klink ◽  
D. van Blooijs ◽  
C.H. Ferrier ◽  
K.P.J. Braun ◽  
...  

2020 ◽  
Vol 134 ◽  
pp. 104618 ◽  
Author(s):  
Carlos Cepeda ◽  
Simon Levinson ◽  
Hiroki Nariai ◽  
Vannah-Wila Yazon ◽  
Conny Tran ◽  
...  

Brain ◽  
2018 ◽  
Vol 141 (3) ◽  
pp. 713-730 ◽  
Author(s):  
Su Liu ◽  
Candan Gurses ◽  
Zhiyi Sha ◽  
Michael M Quach ◽  
Altay Sencer ◽  
...  

Abstract High-frequency oscillations in local field potentials recorded with intracranial EEG are putative biomarkers of seizure onset zones in epileptic brain. However, localized 80–500 Hz oscillations can also be recorded from normal and non-epileptic cerebral structures. When defined only by rate or frequency, physiological high-frequency oscillations are indistinguishable from pathological ones, which limit their application in epilepsy presurgical planning. We hypothesized that pathological high-frequency oscillations occur in a repetitive fashion with a similar waveform morphology that specifically indicates seizure onset zones. We investigated the waveform patterns of automatically detected high-frequency oscillations in 13 epilepsy patients and five control subjects, with an average of 73 subdural and intracerebral electrodes recorded per patient. The repetitive oscillatory waveforms were identified by using a pipeline of unsupervised machine learning techniques and were then correlated with independently clinician-defined seizure onset zones. Consistently in all patients, the stereotypical high-frequency oscillations with the highest degree of waveform similarity were localized within the seizure onset zones only, whereas the channels generating high-frequency oscillations embedded in random waveforms were found in the functional regions independent from the epileptogenic locations. The repetitive waveform pattern was more evident in fast ripples compared to ripples, suggesting a potential association between waveform repetition and the underlying pathological network. Our findings provided a new tool for the interpretation of pathological high-frequency oscillations that can be efficiently applied to distinguish seizure onset zones from functionally important sites, which is a critical step towards the translation of these signature events into valid clinical biomarkers. 5721572971001 awx374media1 5721572971001


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