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

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

Seizure Onset Zone Localization from Ictal High-Density EEG in Refractory Focal Epilepsy

Brain Topography ◽

10.1007/s10548-016-0537-8 ◽

2016 ◽

Vol 30 (2) ◽

pp. 257-271 ◽

Cited By ~ 29

Author(s):

Willeke Staljanssens ◽

Gregor Strobbe ◽

Roel Van Holen ◽

Gwénaël Birot ◽

Markus Gschwind ◽

...

Keyword(s):

Focal Epilepsy ◽

High Density ◽

Seizure Onset ◽

Seizure Onset Zone

Download Full-text

Synchrony in Normal and Focal Epileptic Brain: The Seizure Onset Zone is Functionally Disconnected

Journal of Neurophysiology ◽

10.1152/jn.00368.2010 ◽

2010 ◽

Vol 104 (6) ◽

pp. 3530-3539 ◽

Cited By ~ 101

Author(s):

Christopher P. Warren ◽

Sanqing Hu ◽

Matt Stead ◽

Benjamin H. Brinkmann ◽

Mark R. Bower ◽

...

Keyword(s):

Focal Epilepsy ◽

Brain Regions ◽

Seizure Onset ◽

Neuronal Synchrony ◽

Seizure Onset Zone ◽

Paradoxical Finding ◽

Eeg Recordings ◽

Learning And Cognition ◽

Patients With Epilepsy ◽

And Control

Synchronization of local and distributed neuronal assemblies is thought to underlie fundamental brain processes such as perception, learning, and cognition. In neurological disease, neuronal synchrony can be altered and in epilepsy may play an important role in the generation of seizures. Linear cross-correlation and mean phase coherence of local field potentials (LFPs) are commonly used measures of neuronal synchrony and have been studied extensively in epileptic brain. Multiple studies have reported that epileptic brain is characterized by increased neuronal synchrony except possibly prior to seizure onset when synchrony may decrease. Previous studies using intracranial electroencephalography (EEG), however, have been limited to patients with epilepsy. Here we investigate neuronal synchrony in epileptic and control brain using intracranial EEG recordings from patients with medically resistant partial epilepsy and control subjects with intractable facial pain. For both epilepsy and control patients, average LFP synchrony decreases with increasing interelectrode distance. Results in epilepsy patients show lower LFP synchrony between seizure-generating brain and other brain regions. This relative isolation of seizure-generating brain underlies the paradoxical finding that control patients without epilepsy have greater average LFP synchrony than patients with epilepsy. In conclusion, we show that in patients with focal epilepsy, the region of epileptic brain generating seizures is functionally isolated from surrounding brain regions. We further speculate that this functional isolation may contribute to spontaneous seizure generation and may represent a clinically useful electrophysiological signature for mapping epileptic brain.

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

Ictal EEG source imaging and connectivity to localize the seizure onset zone in extratemporal lobe epilepsy

Seizure ◽

10.1016/j.seizure.2020.03.001 ◽

2020 ◽

Vol 78 ◽

pp. 18-30 ◽

Cited By ~ 1

Author(s):

Simone Vespa ◽

Amir G. Baroumand ◽

Susana Ferrao Santos ◽

Pascal Vrielynck ◽

Marianne de Tourtchaninoff ◽

...

Keyword(s):

Seizure Onset ◽

Source Imaging ◽

Seizure Onset Zone ◽

Ictal Eeg ◽

Eeg Source Imaging

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

Clinical Validation of the Champagne Algorithm for Epilepsy Spike Localization

Frontiers in Human Neuroscience ◽

10.3389/fnhum.2021.642819 ◽

2021 ◽

Vol 15 ◽

Author(s):

Chang Cai ◽

Jessie Chen ◽

Anne M. Findlay ◽

Danielle Mizuiri ◽

Kensuke Sekihara ◽

...

Keyword(s):

Refractory Epilepsy ◽

Focal Epilepsy ◽

Epileptiform Activity ◽

Consecutive Series ◽

Source Reconstruction ◽

Seizure Onset ◽

Current Dipole ◽

Seizure Onset Zone ◽

Complementary Techniques ◽

Epilepsy Localization

Magnetoencephalography (MEG) is increasingly used for presurgical planning in people with medically refractory focal epilepsy. Localization of interictal epileptiform activity, a surrogate for the seizure onset zone whose removal may prevent seizures, is challenging and depends on the use of multiple complementary techniques. Accurate and reliable localization of epileptiform activity from spontaneous MEG data has been an elusive goal. One approach toward this goal is to use a novel Bayesian inference algorithm—the Champagne algorithm with noise learning—which has shown tremendous success in source reconstruction, especially for focal brain sources. In this study, we localized sources of manually identified MEG spikes using the Champagne algorithm in a cohort of 16 patients with medically refractory epilepsy collected in two consecutive series. To evaluate the reliability of this approach, we compared the performance to equivalent current dipole (ECD) modeling, a conventional source localization technique that is commonly used in clinical practice. Results suggest that Champagne may be a robust, automated, alternative to manual parametric dipole fitting methods for localization of interictal MEG spikes, in addition to its previously described clinical and research applications.

Download Full-text

Delta rhythm in wakefulness: evidence from intracranial recordings in human beings

Journal of Neurophysiology ◽

10.1152/jn.00249.2015 ◽

2015 ◽

Vol 114 (2) ◽

pp. 1248-1254 ◽

Cited By ~ 24

Author(s):

Robert N. S. Sachdev ◽

Nicolas Gaspard ◽

Jason L. Gerrard ◽

Lawrence J. Hirsch ◽

Dennis D. Spencer ◽

...

Keyword(s):

High Frequency ◽

Nonhuman Primates ◽

Human Beings ◽

Seizure Onset ◽

Intracranial Eeg ◽

Quiet Wakefulness ◽

Delta Rhythm ◽

Eeg Recordings ◽

Low Amplitude ◽

Intracranial Recordings

A widely accepted view is that wakefulness is a state in which the entire cortical mantle is persistently activated, and therefore desynchronized. Consequently, the EEG is dominated by low-amplitude, high-frequency fluctuations. This view is currently under revision because the 1–4 Hz delta rhythm is often evident during “quiet” wakefulness in rodents and nonhuman primates. Here we used intracranial EEG recordings to assess the occurrence of delta rhythm in 18 awake human beings. Our recordings reveal rhythmic delta during wakefulness at 10% of all recording sites. Delta rhythm could be observed in a single cortical lobe or in multiple lobes. Sites with high delta could flip between high and low delta power or could be in a persistently high delta state. Finally, these sites were rarely identified as the sites of seizure onset. Thus rhythmic delta can dominate the background operation and activity of some neocortical circuits in awake human beings.

Download Full-text

Statistical Features in High-Frequency Bands of Interictal iEEG Work Efficiently in Identifying the Seizure Onset Zone in Patients with Focal Epilepsy

Entropy ◽

10.3390/e22121415 ◽

2020 ◽

Vol 22 (12) ◽

pp. 1415

Author(s):

Most. Sheuli Akter ◽

Md. Rabiul Islam ◽

Toshihisa Tanaka ◽

Yasushi Iimura ◽

Takumi Mitsuhashi ◽

...

Keyword(s):

High Frequency ◽

State Of The Art ◽

Focal Epilepsy ◽

Epileptic Seizures ◽

Gradient Boosting ◽

Statistical Features ◽

Seizure Onset ◽

Seizure Onset Zone ◽

Frequency Components ◽

Final Score

The design of a computer-aided system for identifying the seizure onset zone (SOZ) from interictal and ictal electroencephalograms (EEGs) is desired by epileptologists. This study aims to introduce the statistical features of high-frequency components (HFCs) in interictal intracranial electroencephalograms (iEEGs) to identify the possible seizure onset zone (SOZ) channels. It is known that the activity of HFCs in interictal iEEGs, including ripple and fast ripple bands, is associated with epileptic seizures. This paper proposes to decompose multi-channel interictal iEEG signals into a number of subbands. For every 20 s segment, twelve features are computed from each subband. A mutual information (MI)-based method with grid search was applied to select the most prominent bands and features. A gradient-boosting decision tree-based algorithm called LightGBM was used to score each segment of the channels and these were averaged together to achieve a final score for each channel. The possible SOZ channels were localized based on the higher value channels. The experimental results with eleven epilepsy patients were tested to observe the efficiency of the proposed design compared to the state-of-the-art methods.

Download Full-text