Automatic detection of prominent interictal spikes in intracranial EEG: Validation of an algorithm and relationsip to the seizure onset zone

Acute intraoperative electrocorticography (ECoG) is a time-honoured technique to identify the relevant epileptogenic tissue (RET) and hence guide cortical resection to control medically refractory seizures. ECoG identifies the RET through careful analysis of pattern, morphology, frequency, and localization of interictal spikes recorded directly from the exposed cortical surface. Because the development and dissemination of chronic intracranial EEG recording techniques has put emphasis on ictal recordings (thus defining an ictal onset zone), acute ECoG is often considered unnecessary in surgical planning. The chapter describes limitations and advantages of acute ECoG to define the RET in comparison with more costly and risky procedures, particularly subdural grid and SEEG recording. Specifically, it shows how the integration of lesion type and sequentially recorded ECoG spikes during operation may provide a highly cost-effective approach to successful epilepsy surgery.

Download Full-text

Influence of Time-Series Normalization, Number of Nodes, Connectivity and Graph Measure Selection on Seizure-Onset Zone Localization from Intracranial EEG

Brain Topography ◽

10.1007/s10548-018-0646-7 ◽

2018 ◽

Vol 31 (5) ◽

pp. 753-766 ◽

Cited By ~ 5

Author(s):

Pieter van Mierlo ◽

Octavian Lie ◽

Willeke Staljanssens ◽

Ana Coito ◽

Serge Vulliémoz

Keyword(s):

Time Series ◽

Seizure Onset ◽

Intracranial Eeg ◽

Seizure Onset Zone ◽

Graph Measure

Download Full-text

Spatial variation in high-frequency oscillation rates and amplitudes in intracranial EEG

Neurology ◽

10.1212/wnl.0000000000004998 ◽

2018 ◽

Vol 90 (8) ◽

pp. e639-e646 ◽

Cited By ~ 23

Author(s):

Hari Guragain ◽

Jan Cimbalnik ◽

Matt Stead ◽

David M. Groppe ◽

Brent M. Berry ◽

...

Keyword(s):

High Frequency ◽

Anatomic Variation ◽

Brain Regions ◽

Brain Atlas ◽

Reproducible Research ◽

High Frequency Oscillation ◽

Seizure Onset ◽

Frequency Oscillation ◽

Intracranial Eeg ◽

Seizure Onset Zone

ObjectiveTo assess the variation in baseline and seizure onset zone interictal high-frequency oscillation (HFO) rates and amplitudes across different anatomic brain regions in a large cohort of patients.MethodsSeventy patients who had wide-bandwidth (5 kHz) intracranial EEG (iEEG) recordings during surgical evaluation for drug-resistant epilepsy between 2005 and 2014 who had high-resolution MRI and CT imaging were identified. Discrete HFOs were identified in 2-hour segments of high-quality interictal iEEG data with an automated detector. Electrode locations were determined by coregistering the patient's preoperative MRI with an X-ray CT scan acquired immediately after electrode implantation and correcting electrode locations for postimplant brain shift. The anatomic locations of electrodes were determined using the Desikan-Killiany brain atlas via FreeSurfer. HFO rates and mean amplitudes were measured in seizure onset zone (SOZ) and non-SOZ electrodes, as determined by the clinical iEEG seizure recordings. To promote reproducible research, imaging and iEEG data are made freely available (msel.mayo.edu).ResultsBaseline (non-SOZ) HFO rates and amplitudes vary significantly in different brain structures, and between homologous structures in left and right hemispheres. While HFO rates and amplitudes were significantly higher in SOZ than non-SOZ electrodes when analyzed regardless of contact location, SOZ and non-SOZ HFO rates and amplitudes were not separable in some lobes and structures (e.g., frontal and temporal neocortex).ConclusionsThe anatomic variation in SOZ and non-SOZ HFO rates and amplitudes suggests the need to assess interictal HFO activity relative to anatomically accurate normative standards when using HFOs for presurgical planning.

Download Full-text

Identification of seizure onset zone using automatically detected spike and high-frequency oscillation in human intracranial EEG

2016 24th Signal Processing and Communication Application Conference (SIU) ◽

10.1109/siu.2016.7496221 ◽

2016 ◽

Author(s):

Su Liu ◽

Zhiyi Sha ◽

Aviva Abosch ◽

Thomas Henry ◽

Nuri Firat Ince

Keyword(s):

High Frequency ◽

High Frequency Oscillation ◽

Seizure Onset ◽

Frequency Oscillation ◽

Intracranial Eeg ◽

Seizure Onset Zone

Download Full-text

The Irritative Zone and Seizure Onset Zone in Subdural EEG

Invasive Studies of the Human Epileptic Brain ◽

10.1093/med/9780198714668.003.0008 ◽

2018 ◽

pp. 98-105

Author(s):

Sebastian Bauer ◽

Felix Rosenow

Keyword(s):

Temporal Lobe Epilepsy ◽

Temporal Lobe ◽

Surgical Outcome ◽

Prognostic Value ◽

High Sensitivity ◽

Interictal Spikes ◽

Seizure Onset ◽

Seizure Onset Zone ◽

Cortical Dysplasias ◽

Definition Of

Subdural EEG has a high sensitivity for detecting interictal spikes. The irritative zone is usually more extended than the seizure onset zone. Removal of the entire irritative zone improves outcome in extratemporal as well as neocortical and tumour-related temporal lobe epilepsy, but not in mesial TLE. Quantification of spike features like amplitude, frequency, or latency may help differentiate the localizing and prognostic value of different spike populations. Although EEG patterns are not aetiology, some pathologies such as focal cortical dysplasias are frequently associated with typical EEG patterns, in which case intraoperative electrocorticography should be applied to tailor resections. Presence of a focal seizure onset zone and slow propagation are associated with good surgical outcome. Definition of a sound hypothesis about location of the seizure onset zone from pre-invasive findings is a crucial prerequisite for the success of subdural recordings. Concordance of interictal and ictal recordings is highly predictive of outcomes.

Download Full-text

Contribution of ictal source imaging for localizing seizure onset zone in patients with focal epilepsy patients

Neurology ◽

10.1212/wnl.0000000000011109 ◽

2020 ◽

pp. 10.1212/WNL.0000000000011109

Author(s):

Shuai Ye ◽

Lin Yang ◽

Yunfeng Lu ◽

Michal T. Kucewicz ◽

Benjamin Brinkmann ◽

...

Keyword(s):

Surgical Resection ◽

Focal Epilepsy ◽

High Density ◽

Concordance Rate ◽

Added Value ◽

Seizure Onset ◽

Source Imaging ◽

Intracranial Eeg ◽

Seizure Onset Zone ◽

Eeg Recordings

ObjectiveTo determine whether seizure onset zone can be accurately localized prior to surgical planning in focal epilepsy patients, we performed non-invasive EEG recordings and source localization analyses on 39 patients.MethodsIn a total of 39 focal epilepsy patients, we recorded and extracted 138 seizures and 1,325 interictal epileptic discharges using high-density EEG. We have investigated a novel approach for directly imaging sources of seizures and interictal spikes from high density EEG recordings, and rigorously validated it for noninvasive localization of seizure onset zone (SOZ) determined from intracranial EEG findings and surgical resection volume. Conventional source imaging analyses were also performed for comparison.ResultsIctal source imaging showed a concordance rate of 95% when compared to intracranial EEG or resection results. The average distance from estimation to seizure onset (intracranial) electrodes is 1.35 cm in patients with concordant results, and 0.74 cm to surgical resection boundary in patients with successful surgery. About 41% of the patients were found to have multiple types of interictal activities; coincidentally, a lower concordance rate and a significantly worse performance in localizing SOZ were observed in these patients.ConclusionNoninvasive ictal source imaging with high-density EEG recording can provide highly concordant results with clinical decisions obtained by invasive monitoring or confirmed by resective surgery. By means of direct seizure imaging using high-density scalp EEG recordings, the added value of ictal source imaging is particularly high in patients with complex interictal activity patterns, who may represent the most challenging cases with poor prognosis.

Download Full-text

F90. Efficacy of simultaneous scalp and intracranial EEG in detecting seizure onset zone

Clinical Neurophysiology ◽

10.1016/j.clinph.2018.04.253 ◽

2018 ◽

Vol 129 ◽

pp. e100-e101

Author(s):

Ying Sun ◽

Arun Antony ◽

Julie Pan ◽

Alexandra Urban ◽

Joanna Fong ◽

...

Keyword(s):

Seizure Onset ◽

Intracranial Eeg ◽

Seizure Onset Zone

Download Full-text

More Than Spikes: On the Added Value of Non-linear Intracranial EEG Analysis for Surgery Planning in Temporal Lobe Epilepsy

Frontiers in Neurology ◽

10.3389/fneur.2021.741450 ◽

2022 ◽

Vol 12 ◽

Author(s):

Michael Müller ◽

Martijn Dekkers ◽

Roland Wiest ◽

Kaspar Schindler ◽

Christian Rummel

Keyword(s):

Temporal Lobe Epilepsy ◽

Temporal Lobe ◽

Quantitative Eeg ◽

Eeg Analysis ◽

Seizure Onset ◽

Intracranial Eeg ◽

Seizure Onset Zone ◽

Quantitative Eeg Analysis ◽

Non Linear ◽

Epileptiform Events

Epilepsy surgery can be a very effective therapy in medication refractory patients. During patient evaluation intracranial EEG is analyzed by clinical experts to identify the brain tissue generating epileptiform events. Quantitative EEG analysis increasingly complements this approach in research settings, but not yet in clinical routine. We investigate the correspondence between epileptiform events and a specific quantitative EEG marker. We analyzed 99 preictal epochs of multichannel intracranial EEG of 40 patients with mixed etiologies. Time and channel of occurrence of epileptiform events (spikes, slow waves, sharp waves, fast oscillations) were annotated by a human expert and non-linear excess interrelations were calculated as a quantitative EEG marker. We assessed whether the visually identified preictal events predicted channels that belonged to the seizure onset zone, that were later resected or that showed strong non-linear interrelations. We also investigated whether the seizure onset zone or the resection were predicted by channels with strong non-linear interrelations. In patients with temporal lobe epilepsy (32 of 40), epileptic spikes and the seizure onset zone predicted the resected brain tissue much better in patients with favorable seizure control after surgery than in unfavorable outcomes. Beyond that, our analysis did not reveal any significant associations with epileptiform EEG events. Specifically, none of the epileptiform event types did predict non-linear interrelations. In contrast, channels with strong non-linear excess EEG interrelations predicted the resected channels better in patients with temporal lobe epilepsy and favorable outcome. Also in the small number of patients with seizure onset in the frontal and parietal lobes, no association between epileptiform events and channels with strong non-linear excess EEG interrelations was detectable. In contrast to patients with temporal seizure onset, EEG channels with strong non-linear excess interrelations did neither predict the seizure onset zone nor the resection of these patients or allow separation between patients with favorable and unfavorable seizure control. Our study indicates that non-linear excess EEG interrelations are not strictly associated with epileptiform events, which are one key concept of current clinical EEG assessment. Rather, they may provide information relevant for surgery planning in temporal lobe epilepsy. Our study suggests to incorporate quantitative EEG analysis in the workup of clinical cases. We make the EEG epochs and expert annotations publicly available in anonymized form to foster similar analyses for other quantitative EEG methods.

Download Full-text

Neural Fragility as an EEG Marker of the Seizure Onset Zone

10.1101/862797 ◽

2019 ◽

Author(s):

Adam Li ◽

Chester Huynh ◽

Zachary Fitzgerald ◽

Iahn Cajigas ◽

Damian Brusko ◽

...

Keyword(s):

Surgical Outcomes ◽

Predictive Power ◽

Biological Marker ◽

Complete Removal ◽

Drug Resistant ◽

Success Rates ◽

Seizure Onset ◽

Intracranial Eeg ◽

Seizure Onset Zone ◽

Drug Resistant Epilepsy

AbstractOver 15 million epilepsy patients worldwide do not respond to drugs. Successful surgical treatment requires complete removal, or disconnection of the seizure onset zone (SOZ), brain region(s) where seizures originate. Unfortunately, surgical success rates vary between 30%-70% because no clinically validated biological marker of the SOZ exists. We develop and retrospectively validate a new EEG marker - neural fragility. We validate this new marker in a retrospective analysis of 91 patients by using neural fragility of the annotated SOZ as a metric to predict surgical outcomes. Fragility predicts 43/47 surgical failures with an overall prediction accuracy of 76%, compared to the accuracy of clinicians being 48% (successful outcomes). In failed outcomes, we identify fragile regions that were untreated. When compared to 20 EEG features proposed as SOZ markers, fragility outperformed in predictive power and interpretability suggesting neural fragility as an EEG fingerprint of the SOZ.One Sentence SummaryNeural fragility, an intracranial EEG biomarker for the seizure onset zone in drug-resistant epilepsy, predicts surgical outcomes with high accuracy.

Download Full-text

Distinction of Physiologic and Epileptic Ripples: An Electrical Stimulation Study

Brain Sciences ◽

10.3390/brainsci11050538 ◽

2021 ◽

Vol 11 (5) ◽

pp. 538

Author(s):

Jan Schönberger ◽

Anja Knopf ◽

Kerstin Alexandra Klotz ◽

Matthias Dümpelmann ◽

Andreas Schulze-Bonhage ◽

...

Keyword(s):

Electrical Stimulation ◽

Slow Wave Sleep ◽

Focal Epilepsy ◽

Epileptic Activity ◽

Interictal Spikes ◽

Seizure Onset ◽

Receiver Operating Characteristic Curves ◽

Seizure Onset Zone ◽

Intracranial Electroencephalography ◽

Better Than

Ripple oscillations (80–250 Hz) are a promising biomarker of epileptic activity, but are also involved in memory consolidation, which impairs their value as a diagnostic tool. Distinguishing physiologic from epileptic ripples has been particularly challenging because usually, invasive recordings are only performed in patients with refractory epilepsy. Here, we identified ‘healthy’ brain areas based on electrical stimulation and hypothesized that these regions specifically generate ‘pure’ ripples not coupled to spikes. Intracranial electroencephalography (EEG) recorded with subdural grid electrodes was retrospectively analyzed in 19 patients with drug-resistant focal epilepsy. Interictal spikes and ripples were automatically detected in slow-wave sleep using the publicly available Delphos software. We found that rates of spikes, ripples and ripples coupled to spikes (‘spike–ripples’) were higher inside the seizure-onset zone (p < 0.001). A comparison of receiver operating characteristic curves revealed that spike–ripples slightly delineated the seizure-onset zone channels, but did this significantly better than spikes (p < 0.001). Ripples were more frequent in the eloquent neocortex than in the remaining non-seizure onset zone areas (p < 0.001). This was due to the higher rates of ‘pure’ ripples (p < 0.001; median rates 3.3/min vs. 1.4/min), whereas spike–ripple rates were not significantly different (p = 0.87). ‘Pure’ ripples identified ‘healthy’ channels significantly better than chance (p < 0.001). Our findings suggest that, in contrast to epileptic spike–ripples, ‘pure’ ripples are mainly physiological. They may be considered, in addition to electrical stimulation, to delineate eloquent cortex in pre-surgical patients. Since we applied open source software for detection, our approach may be generally suited to tackle a variety of research questions in epilepsy and cognitive science.

Download Full-text