scholarly journals Tracking multi-site seizure propagation using ictal high frequency activity

2020 ◽  
Author(s):  
Steven Tobochnik ◽  
Lisa M. Bateman ◽  
Cigdem I. Akman ◽  
Deepti Anbarasan ◽  
Carl W. Bazil ◽  
...  
Keyword(s):  
High Frequency ◽  
Spatial Clustering ◽  
Spatial Clusters ◽  
Prognostic Information ◽  
Spatial Overlap ◽  
High Frequency Oscillations ◽  
Depth Electrodes ◽  
Seizure Termination ◽  
High Frequency Activity

Objective: Characterization of progressive multi-site seizure recruitment using high frequency oscillations. Methods: Ictal and interictal high frequency oscillations were identified in a series of 13 patients with 72 seizures recorded by stereotactic depth electrodes, using previously validated methods. Channels with ictal high frequency oscillations were assigned to distinct spatial clusters, and seizure hubs were identified by stereotypically recruited non-overlapping clusters. Clusters were correlated with asynchronous seizure terminations to provide supportive evidence for independent seizure activity at these sites. The spatial overlap of ictal and interictal high frequency oscillations were compared. Results: Ictal high frequency oscillations were detected in 71% of seizures and 10% of implanted contacts, enabling tracking of contiguous and noncontiguous seizure recruitment. Multiple seizure hubs were identified in 54% of cases, including 43% of patients thought preoperatively to have unifocal epilepsy. Noncontiguous recruitment was associated with asynchronous seizure termination (Odds Ratio=10, 95% CI 2.9-41, p<0.001). Interictal high frequency oscillations demonstrated greater spatial overlap with ictal high frequency oscillations in cases with single seizure hubs than in those with multiple hubs (100% vs 66% per patient, p=0.03). Significance: Analysis of ictal high frequency oscillations can serve as a useful adjunctive technique to distinguish contiguous seizure spread from propagation to remote seizure sites. This study demonstrated that multiple seizure hubs were commonly identified by spatial clustering of ictal high frequency oscillations, including in cases that were considered unifocal. The distinction between initially activated and delayed seizure hubs was not evident based on interictal high frequency analysis, but may provide important prognostic information.

scholarly journals Detection of High-Frequency Oscillations by Hybrid Depth Electrodes in Standard Clinical Intracranial EEG Recordings

2014 ◽  
Vol 5 ◽  
Author(s):  
Efstathios D. Kondylis ◽  
Thomas A. Wozny ◽  
Witold J. Lipski ◽  
Alexandra Popescu ◽  
Vincent J. DeStefino ◽  
...  
Keyword(s):  
High Frequency ◽  
Intracranial Eeg ◽  
High Frequency Oscillations ◽  
Depth Electrodes ◽  
Eeg Recordings

scholarly journals Blinded study: prospectively defined high frequency oscillations predict seizure outcome in individual patients

2020 ◽  
Author(s):  
V Dimakopoulos ◽  
P Mégevand ◽  
E Boran ◽  
S Momjian ◽  
M Seeck ◽  
...  
Keyword(s):  
Epilepsy Surgery ◽  
High Frequency ◽  
Dwell Time ◽  
Nrem Sleep ◽  
Seizure Outcome ◽  
Seizure Freedom ◽  
University Hospitals ◽  
High Frequency Oscillations ◽  
Depth Electrodes

AbstractBackgroundInterictal high frequency oscillations (HFO) are discussed as biomarkers for epileptogenic brain tissue that should be resected in epilepsy surgery to achieve seizure freedom. The prospective classification of tissue sampled by individual electrode contacts remains a challenge. We have developed an automated, prospective definition of clinically relevant HFO in intracranial EEG (iEEG) from MNI Montreal and tested it in iEEG from Zurich. We here validate the algorithm on iEEG recorded in an independent epilepsy center so that HFO analysis was blinded to seizure outcome.MethodsWe selected consecutive patients from Geneva University Hospitals who underwent resective epilepsy surgery with postsurgical follow-up > 12 months. We analyzed long-term iEEG recordings during non-rapid eye movement (NREM) sleep that we segmented into intervals of 5 min. HFOs were defined in the ripple (80-250 Hz) and the fast ripple (FR, 250-500 Hz) frequency band. Contacts with the highest rate of ripples co-occurring with FR (FRandR) designated the HFO area. If the HFO area was not fully resected and the patient suffered from recurrent seizures (ILAE 2-6), this was classified as a true positive (TP) prediction.ResultsWe included iEEG recordings from 16 patients (median age 32 y, range [18-53]) with stereotactic depth electrodes and/or with subdural electrode grids (median follow-up 27 mo, range [12-55]). The HFO area had high test-retest reliability across intervals (median dwell time 95%). We excluded two patients with dwell time < 50% from further analysis.The HFO area was fully included in the resected volume in 2/4 patients who achieved postoperative seizure freedom (ILAE 1, specificity 50%) and was not fully included in 9/10 patients with recurrent seizures (ILAE > 1, sensitivity 90%), leading to an accuracy of 79%.ConclusionsWe validated the automated procedure to delineate the clinical relevant HFO area in individual patients of an independently recorded dataset and achieved the same good accuracy as in our previous studies.SignificanceThe reproducibility of our results across datasets is promising for a multicienter study testing the clinical application of HFO detection to guide epilepsy surgery.

scholarly journals Kurtosis-Based Detection of Intracranial High-Frequency Oscillations for the Identification of the Seizure Onset Zone

2018 ◽  
Vol 28 (07) ◽  
pp. 1850001 ◽  
Author(s):  
Lucia Rita Quitadamo ◽  
Roberto Mai ◽  
Francesca Gozzo ◽  
Veronica Pelliccia ◽  
Francesco Cardinale ◽  
...  
Keyword(s):  
High Frequency ◽  
Computational Time ◽  
Seizure Onset ◽  
Time Frequency ◽  
High Frequency Oscillations ◽  
Epileptiform Discharges ◽  
Seizure Onset Zone ◽  
Potential Biomarker ◽  
Eeg Data

Pathological High-Frequency Oscillations (HFOs) have been recently proposed as potential biomarker of the seizure onset zone (SOZ) and have shown superior accuracy to interictal epileptiform discharges in delineating its anatomical boundaries. Characterization of HFOs is still in its infancy and this is reflected in the heterogeneity of analysis and reporting methods across studies and in clinical practice. The clinical approach to HFOs identification and quantification usually still relies on visual inspection of EEG data. In this study, we developed a pipeline for the detection and analysis of HFOs. This includes preliminary selection of the most informative channels exploiting statistical properties of the pre-ictal and ictal intracranial EEG (iEEG) time series based on spectral kurtosis, followed by wavelet-based characterization of the time–frequency properties of the signal. We performed a preliminary validation analyzing EEG data in the ripple frequency band (80–250 Hz) from six patients with drug-resistant epilepsy who underwent pre-surgical evaluation with stereo-EEG (SEEG) followed by surgical resection of pathologic brain areas, who had at least two-year positive post-surgical outcome. In this series, kurtosis-driven selection and wavelet-based detection of HFOs had average sensitivity of 81.94% and average specificity of 96.03% in identifying the HFO area which overlapped with the SOZ as defined by clinical presurgical workup. Furthermore, the kurtosis-based channel selection resulted in an average reduction in computational time of 66.60%.

scholarly journals High-frequency bioelectrical activity of the brain in the diagnosis of epilepsy

2018 ◽  
Vol 10 (3) ◽  
pp. 6-13 ◽  
Author(s):  
N. D. Sorokina ◽  
S. S. Pertsov ◽  
G. V. Selitsky
Keyword(s):  
High Frequency ◽  
Epileptiform Activity ◽  
Gamma Activity ◽  
Epileptic Focus ◽  
Bioelectrical Activity ◽  
Seizure Onset ◽  
High Frequency Oscillations ◽  
Gamma Rhythm ◽  
High Frequency Activity ◽  
The Brain

Recent studies show that the brain gamma activity includes both the gamma rhythm (standard EEG) and high frequency (100-1000 Hz) as well as super-high (>1000 Hz) frequency oscillations, as recorded by electrocorticography. As reported in the literature, the high-frequency oscillations (80-500 Hz) are highly informative markers of an epileptic focus. In this review, we analyze features of high-frequency activity associated with the epileptiform activity, and its relation to the seizure onset range. Further study of high-frequency bioelectric activity of the brain is of interest to researchers and clinicians, and may improve the EEG differential diagnosis of epilepsy.

scholarly journals Spatiotemporal patterns of high-frequency activity (80-170 Hz) in long-term intracranial EEG

2020 ◽  
Author(s):  
Zhuying Chen ◽  
David B. Grayden ◽  
Anthony N. Burkitt ◽  
Udaya Seneviratne ◽  
Wendyl J. D’Souza ◽  
...  
Keyword(s):  
Circadian Rhythms ◽  
High Frequency ◽  
Focal Epilepsy ◽  
Patient Specific ◽  
Intracranial Eeg ◽  
Electrode Implantation ◽  
High Frequency Oscillations ◽  
Total Data ◽  
High Frequency Activity

AbstractObjectiveTo assess the variability in the rates and locations of high-frequency activity (HFA) and epileptiform spikes after electrode implantation, and to examine the long-term patterns of HFA using ambulatory intracranial EEG (iEEG) recordings.MethodsContinuous iEEG recordings obtained over an average of 1.4 years from 15 patients with drug-resistant focal epilepsy were used in this study. HFA was defined as high-frequency events with amplitudes clearly larger than the background, which was automatically detected using a custom algorithm. High-frequency oscillations (HFOs) were also visually annotated by three neurologists in randomly sampled segments of the total data. The automatically detected HFA was compared with the visually marked HFOs. The variations of HFA rates were compared with spikes and seizures on patient-specific and electrode-specific bases.ResultsHFA was a more general event that encompassed HFOs manually annotated by different reviewers. HFA and spike rates had high amounts of intra- and inter-patient variability. The rates and locations of HFA and spikes took up to weeks to stabilize after electrode implantation in some patients. Both HFA and spike rates showed strong circadian rhythms in all patients and some also showed multiday cycles. Furthermore, the circadian patterns of HFA and spike rates had patient-specific correlations with seizures, which tended to vary across electrodes.ConclusionsAnalysis of HFA and epileptiform spikes should account for post-implantation variability. Like seizures, HFA and epileptiform spikes show circadian rhythms. However, the circadian profiles can vary spatially within patients and their correlations to seizures are patient-specific.

scholarly journals Channel-Wise Characterization of High Frequency Oscillations for Automated Identification of the Seizure Onset Zone

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 45531-45543 ◽  
Author(s):  
Dakun Lai ◽  
Xinyue Zhang ◽  
Wenjing Chen ◽  
Heng Zhang ◽  
Tongzhou Kang ◽  
...  
Keyword(s):  
High Frequency ◽  
Automated Identification ◽  
Seizure Onset ◽  
High Frequency Oscillations ◽  
Seizure Onset Zone

scholarly journals Spatial characterization of interictal high frequency oscillations in epileptic neocortex

Brain ◽  
2009 ◽  
Vol 132 (11) ◽  
pp. 3047-3059 ◽  
Author(s):  
C. A. Schevon ◽  
A. J. Trevelyan ◽  
C. E. Schroeder ◽  
R. R. Goodman ◽  
G. McKhann ◽  
...  
Keyword(s):  
High Frequency ◽  
Spatial Characterization ◽  
High Frequency Oscillations

Intracranial EEG Monitoring

2017 ◽  
Author(s):  
Margitta Seeck ◽  
Donald L. Schomer
Keyword(s):  
High Frequency ◽  
Good Prognosis ◽  
Intracranial Eeg ◽  
High Frequency Oscillations ◽  
Depth Electrodes ◽  
Seizure Onset Zone ◽  
Potential Biomarker ◽  
Eeg Recordings ◽  
Intracranial Electroencephalography ◽  
Intracranial Recordings

Intracranial electroencephalography (iEEG) is used to localize the focus of seizures and determine vital adjacent cortex before epilepsy surgery. The two most commonly used electrode types are subdural and depth electrodes. Foramen ovale electrodes are less often used. Combinations of electrode types are possible. The choice depends on the presumed focus site. Careful planning is needed before implantation, taking into account the results of noninvasive studies. While subdural recordings allow better mapping of functional cortex, depth electrodes can reach deep structures. There are no guidelines on how to read ictal intracranial EEG recordings, but a focal onset (<5 contacts) and a high-frequency onset herald a good prognosis. High-frequency oscillations have been described as a potential biomarker of the seizure onset zone. Intracranial recordings provide a focal but magnified view of the brain, which is also exemplified by the use of microelectrodes, which allow the recording of single-unit or multi-unit activity.

scholarly journals Periodic discharges with high frequency oscillations recorded from a cerebellar gangliocytoma in an epileptic infant

2021 ◽  
Vol 12 ◽  
pp. 98
Author(s):  
Nobutaka Mukae ◽  
Takato Morioka ◽  
Michiko Torio ◽  
Yasunari Sakai ◽  
Takafumi Shimogawa ◽  
...  
Keyword(s):  
High Frequency ◽  
Male Infant ◽  
Subtotal Resection ◽  
Supportive Evidence ◽  
Periodic Discharges ◽  
High Frequency Oscillations ◽  
Depth Electrodes ◽  
Japanese Male ◽  
Old Japanese ◽  
Drug Resistant Epilepsy

Background: Subcortical epilepsies associated with developmental tumors in the cerebellum are rarely experienced. As supportive evidence of the intrinsic epileptogenicity of cerebellar tumors, previous electroencephalogram (EEG) studies with intratumoral depth electrodes demonstrated epileptiform or ictal discharges. Recent studies have demonstrated that high frequency oscillations (HFOs) can be regarded as a new biomarker of epileptogenesis and ictogenesis; however, there are few evidence about HFOs in cases of epilepsy associated with cerebellar tumors. Case Description: A 6-month-old Japanese male infant presented to our hospital with drug resistant epilepsy. We underwent subtotal resection of a cerebellar gangliocytoma and obtained good seizure outcomes. Intraoperative EEG in the tumor depicted HFOs in the form of ripples, riding on periodic discharges. Conclusion: Our findings provide further supportive evidence for the intrinsic epileptogenicity of cerebellar tumors.

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