Source localization of ictal epileptic activity investigated by high resolution EEG and validated by SEEG
Introduction
Source localization techniques have been widely studied and validated for the study of interictal activity (Ebersole, 2000, Lantz et al., 2003, Michel et al., 2004a, Michel et al., 2004b, Gavaret et al., 2004, Gavaret et al., 2006, Gavaret et al., 2009). However, there have been few studies concerning ictal source localization (Lantz et al., 2001, Boon et al., 2002, Holmes et al., 2004, Beniczky et al., 2006, Ding et al., 2007). In addition, the relationship between the “irritative” zone (i.e. presenting interictal discharges) and epileptogenic zone remains poorly investigated (Talairach and Bancaud, 1966).
The small number of publications on this topic is largely due to the difficulty in recording epileptic seizures during high resolution electroencephalography (HR-EEG). This can be explained by the short recording time, due to demanding technical reasons (high number of sensors, high sampling rate, low impedances, comfort, etc.). Moreover, source modeling of seizures is much more complex than source modeling of spikes because of the low signal to noise ratio of some ictal pattern types, their frequent contamination by muscle artifacts, and propagation. Some studies have compared ictal surface EEG with intracranial EEG data (Assaf and Ebersole, 1997, Lantz et al., 1999, Lantz et al., 2001, Foldvary et al., 2001, Merlet and Gotman, 2001, Boon et al., 1997, Boon et al., 2002). Other authors have compared ictal surface EEG with anatomic lesions (Ding et al., 2007), epilepsy surgery (Boon et al., 1997, Lantz et al., 2001), or single photon-emission computed tomography (SPECT) (Mine et al., 1998, Beniczky et al., 2006). Due to poor temporal resolution, metabolic investigations are not suitable to study the temporal dynamics of seizures and cannot be used as a valid reference technique.
Different types of epilepsy (often temporal) and ictal patterns (mainly theta activity and spikes) were investigated in these studies, mainly using equivalent current dipole (ECD) and multiple signal classification (MUSIC) methods. Few studies (Worrell et al., 2000, Holmes et al., 2004) have used distributed source models (low resolution electromagnetic tomography (LORETA)) to localize ictal patterns. In these studies, the conditions of ictal surface EEG recordings were rarely adequate for source localization because of the low number of electrodes (30–40) or the use of a spherical head model.
Magnetoencephalography (MEG) recordings have been demonstrated to yield localizing information in epilepsy surgery candidates (Stefan et al., 2003, Fischer et al., 2005, Knowlton et al., 2006, Knowlton et al., 2009). Ictal activities have also been investigated by MEG in a few patients (Sutherling et al., 1987, Stefan et al., 1992, Eliashiv et al., 2002, Tanaka et al., 2009). In these studies, ictal magnetic source imaging was compared with the results of epilepsy surgery, intracranial recordings, and scalp EEGs. The authors concluded that the ictal magnetic source localizations were in close agreement with invasive and noninvasive preoperative studies. MEG ictal studies, like EEG ictal studies, concluded that imaging can help in the placement of invasive electrodes and in surgery planning. Despite fewer ergonomic constraints than MEG recordings (which require head immobility), EEG source localization studies of ictal activity are still rare. To date, no data have been published concerning source localization of ictal patterns in conditions of HR-EEG (at least 64 sensors and a high sampling rate) and few comparative studies exist with intracerebral EEG (Merlet and Gotman, 2001, Boon et al., 2002). Moreover, no study has compared dipolar and distributed source methods. It is also unclear what kind of scalp-EEG ictal patterns permit reliable source localization.
The main purpose of this study was to evaluate the accuracy of ictal source localization in distinct types of scalp-EEG ictal patterns, using stereoelectroencephalography (SEEG) as a validating method. The different source localization methods were also compared.
Section snippets
Subjects
Ten drug-resistant partial epilepsy patients underwent HR-EEG recording of seizures (six patients were investigated in the Clinical Neurophysiology Department of Timone Hospital, Marseille, and four in the Neurology Department of the University Hospital, Nancy). Each patient gave his informed consent and the study was approved by the ethics committee (CPP) of Marseille.
Patients first underwent a presurgical evaluation including careful history taking, neurologic examination, video–EEG recording
Patient classification according to scalp-EEG ictal pattern
For each patient, ictal source localizations were compared with the intracerebral epileptogenic zone as determined by SEEG. In the ictal spike group (four patients), signal to noise ratios ranged from 4–8 (Table 1), and spiking frequency was < 2 Hz. In the rhythmic activity group, one patient had TLE and one had PCE; signal to noise ratios ranged from 1.5–2. Rhythmic frequencies were in the delta and theta bands. In the paroxysmal fast activity group, one patient had TLE and one had FLE; signal
Discussion
The main objective of this study was to determine the best conditions for locating the epileptogenic zone with HR-EEG in distinct types of scalp-EEG ictal patterns, using SEEG as a validating method. Simultaneous EEG–SEEG recordings would be the best validation method for this kind of study. However, surgical constraints of SEEG (asepsis, presence of guiding screws …) did not allow using a high number of scalp-EEG sensors.
Ten drug-resistant partial epilepsy patients who underwent HR-EEG and
Acknowledgments
LK was supported by France Maintenance Biomedical and the French Ministry of Health (PHRC 17-05, 2009). The authors thank Prof. J. Regis, Prof. J.C. Peragut (Marseille), and Prof. J. Auque and Dr. S. Colnat-Coulbois (Nancy) for their neurosurgical contributions. The authors also thank P. Marquis for HR-EEG and SEEG data management.
References (56)
- et al.
Transitional sharp waves at ictal onset—a neocortical ictal pattern
Clin. Neurophysiol.
(2009) - et al.
Temporal and spatial determination of EEG-seizure onset in the frequency domain
Clin. Neurophysiol.
(2000) - et al.
Fractal analysis of electroencephalographic signals intracerebrally recorded during 35 epileptic seizures: evaluation of a new method for synoptic visualisation of ictal events
Electroencephalogr. Clin. Neurophysiol.
(1994) - et al.
Ictal source analysis: localization and imaging of causal interactions in humans
Neuroimage
(2007) - et al.
Analysis of mesial temporal seizure onset and propagation using the directed transfer function method
Electroencephalogr. Clin. Neurophysiol.
(1994) - et al.
Time–frequency analysis using the matching pursuit algorithm applied to seizures originating from the mesial temporal lobe
Electroencephalogr. Clin. Neurophysiol.
(1998) - et al.
Confidence limits of dipole source reconstruction results
Clin. Neurophysiol.
(2004) - et al.
Detection and evolution of rhythmic components in ictal EEG using short segment spectra and discriminant analysis
Electroencephalogr. Clin. Neurophysiol.
(1992) - et al.
Automatic localization of new scalp-recorded EEG sensors in MRI volume
NeuroImage
(2008) - et al.
Malformations of cortical development and epilepsy
Brain Dev.
(2001)
Frequency domain EEG source localization of ictal epileptiform activity in patients with partial complex epilepsy of temporal lobe origin
Clin. Neurophysiol.
Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity loss
Electroencephalogr. Clin. Neurophysiol.
A system for automatic artifact removal in ictal scalp EEG based on independent component analysis and Bayesian classification
Clin. Neurophysiol.
Combined SEEG and source localisation study of temporal lobe schizencephaly and polymicrogyria
Clin. Neurophysiol.
Dipole modeling of scalp electroencephalogram epileptic discharges: correlation with intracerebral fields
Clin. Neurophysiol.
Localization of the sources of EEG delta, theta, alpha and beta frequency bands using the FFT dipole approximation
Electroencephalogr. Clin. Neurophysiol.
EEG source imaging
Clin. Neurophysiol.
Ictal dipole source analysis based on a realistic scalp–skull–brain head model in localizing the epileptogenic zone
Neurosci. Res.
The five percent electrode system for high resolution EEG and ERP measurements
Clin. Neurophysiol.
Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain
Int. J. Psychophysiol.
Dynamic statistical parametric mapping for analyzing ictal magnetoencephalographic spikes in patients with intractable frontal lobe epilepsy
Epilepsy Res.
Bayesian model averaging in EEG/MEG imaging
Neuroimage
Continuous source imaging of scalp ictal rhythms in temporal lobe epilepsy
Epilepsia
Epileptogenicity of brain structures in human temporal lobe epilepsy: a quantified study from intracerebral EEG
Brain
Source analysis of epileptic discharges using multiple signal classification analysis
Neuroreport
Dipole modelling and intracranial EEG recording: correlation between dipole and ictal onset zone
Acta Neurochir. (Wien)
Ictal source localization in presurgical patients with refractory epilepsy
J. Clin. Neurophysiol.
A glossary of terms most commonly used by clinical electroencephalographers
Electroencephalogr. Clin. Neurophysiol.
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