F. Moeller and J. Moehring contributed equally to this work.
EEG-fMRI in atypical benign partial epilepsy
Article first published online: 12 JUN 2013
Wiley Periodicals, Inc. © 2013 International League Against Epilepsy
Volume 54, Issue 8, pages e103–e108, August 2013
How to Cite
Moeller, F., Moehring, J., Ick, I., Steinmann, E., Wolff, S., Jansen, O., Boor, R., Stephani, U. and Siniatchkin, M. (2013), EEG-fMRI in atypical benign partial epilepsy. Epilepsia, 54: e103–e108. doi: 10.1111/epi.12243
- Issue published online: 30 JUL 2013
- Article first published online: 12 JUN 2013
- Manuscript Accepted: 1 MAY 2013
- German Research Foundation. Grant Number: 1419/2-1
- Gerok Grant from the Christian-Albrechts-University Kiel
- Atypical benign partial epilepsy;
- Pseudo-Lennox syndrome
Atypical benign partial epilepsy (ABPE) is a subgroup among the idiopathic focal epilepsies of childhood. Aim of this study was to investigate neuronal networks underlying ABPE and compare the results with previous electroencephalography (EEG)–functional magnetic resonance imaging (fMRI) studies of related epilepsy syndromes. Ten patients with ABPE underwent simultaneous EEG-fMRI recording. In all 10 patients several types of interictal epileptiform discharges (IEDs) were recorded. Individual IED-associated blood oxygen level–dependent (BOLD) signal changes were analyzed in a single subject analysis for each IED type (33 studies). A group analysis was also performed to determine common BOLD signal changes across the patients. IED-associated BOLD signal changes were found in 31 studies. Focal BOLD signal changes concordant with the spike field (21 studies) and distant cortical and subcortical BOLD signal changes (31 studies) were detected. The group analysis revealed a thalamic activation. This study demonstrated that ABPE is characterized by patterns similar to studies in rolandic epilepsy (focal BOLD signal changes in the spike field) as well as patterns observed in continuous spikes and waves during slow sleep (CSWS) (distant BOLD signal changes in cortical and subcortical structures), thereby underscoring that idiopathic focal epilepsies of childhood form a spectrum of overlapping syndromes.
The idiopathic focal epilepsies of childhood comprise a broad spectrum of phenotypes ranging from benign childhood epilepsy with centrotemporal spikes (BECTS) to more severe seizure disorders such as atypical benign partial epilepsy (ABPE), continuous spikes and waves during slow sleep (CSWS) and Landau-Kleffner syndrome (LKS). Patients with ABPE show some clinical and electrophysiologic overlap with patients with BECTS (rolandic seizures, focal sharp slow waves) but in addition present with different seizure types such as atonic drop attacks, atypical absences, generalized tonic–clonic seizures (GTCS), and myoclonic seizures, and may develop mental retardation (Doose et al., 2001; Hahn et al., 2001). Moreover, patients with ABPE may have a pronounced activation of epileptic discharges during sleep with features common to patients with CSWS. Because the clinical picture with frequent drop attacks and cognitive impairment exhibits similarities to the Lennox-Gastaut syndrome, the term pseudo-Lennox syndrome was proposed (Doose et al., 2001).
Electroencephalography–functional magnetic resonance imaging (EEG-fMRI) studies have detected underlying neuronal networks in BECTS (Archer et al., 2003; Boor et al., 2003, 2007; Lengler et al., 2007; Siniatchkin et al., 2007; Masterton et al., 2010, 2013) and CSWS (Siniatchkin et al., 2010). The aim of this study was to investigate hemodynamic changes in patients with ABPE using EEG-fMRI, and to compare the results with previous EEG-fMRI studies of related epilepsy syndromes to better understand the spectrum of idiopathic focal epilepsies of childhood.
Subjects and Methods
Ten patients with the diagnosis of ABPE without CSWS were recruited from the Department of Neuropediatrics at the University Hospital Schleswig Holstein, Campus Kiel and the Northern German Epilepsy Center for Children and Adolescents, Raisdorf. The inclusion criteria for ABPE were based on Hahn et al., 2001 and included seizure semiology (atonic drop attacks and/or atypical absences and/or myoclonic seizures), and multifocal sharp waves in the EEG of a type characteristic of rolandic epilepsy with activation during sleep. Because CSWS-related blood oxygen level–dependent (BOLD) signal changes have been reported before (Siniatchkin et al., 2010), patients with a sleep aggravation of sharp waves of 85% or more were excluded. Patients included in our study showed spike-wave discharges of 10–70% in preceding routine sleep EEG recordings. The clinical characteristics of all included patients are summarized in Table 1. Except for patient 5, all patients showed cognitive impairment, ranging from learning disabilities to mental retardation. The study was performed according to the Declaration of Helsinki and approved by the local ethics committee of the University of Kiel. The parents gave written informed consent prior to the experiment.
|Patient||Age/age at onset/gender||Seizure types||AED||Spikes during fMRI (no.)||fMRI results activation||fMRI results deactivation|
Atonic drop attacks
|ESM||F3 (651)||Frontal L, caudate L, cingulate gyrus||Occipital B|
|F4 (299)||Frontal R, precuneus, frontoparietal L,||–|
|Fz (325)||Frontomesial B, cingulate gyrus; parietal R||–|
|O2 (327)||Parietal B, frontal R||–|
|2a||6/2/m||Atonic drop attacksb||STM||F3 (55)||Frontal B, precentral R, parietal B||Cingulate gyrus, parietal B|
|VPA||P3 (498)||Parietal L, thalamus, frontal L, occipital B||Default mode|
Atonic drop attacks
|C4 (400)||Central R, parietal R||–|
|T8 (230)||Occipital B||Frontal L|
Bilateral myoclonic jerks
Atonic drop attacks
|STM||C3 (218)||–||Central B, temporal B, frontomesial|
|C4 (53)||Parietal R||–|
|Cz (23)||Centromesial, thalamus, caudate B, frontal B||–|
|Fz (290)||Ventricles, cerebellum||Frontomesial, central B, brainstem, thalamus, caudate B, occipital B|
|F4 (89)||Frontal B, occipital B, cingulate gyrus,|
|None||C3 (22)||–||Occipital B, frontal R,|
|C4 (62)||Frontal R, cerebellum||Central R|
|Fz (24)||Caudate L||–|
|P7 (28)||Parietal B, occipital L||–|
|6a,c||6/3/m||Atypical absencesb|| |
|Cz (722)||Centromesial, thalamus, precuneus||Temporal L|
|T8 (82)||Thalamus||Temporal R, frontal L|
|STM||C4 (21)||Occipital R||–|
|P4 (14)||–||Cerebellum L|
Atonic drop attacks
|LTG||F4 (643)||–||Frontal R, occipital R|
|Fp1 (228)||Central L||Frontal L, parietal|
|P4 (63)||Parietal R, pons||–|
|T7 (33)||Parietal R||Parietal R, cerebellum R, frontal R|
|STM||Fp1 (36)||Frontal L||Parietal R|
|Fp2 (15)||Parietal B, frontal mesial and L||–|
|Pz (7)||Temporal L, occipital L||–|
Atonic drop attacks
|VPA||F3 (136)||Frontal B, occipital B, central B, thalamus||–|
|Fp1 (62)||Frontal L, frontomesial||Frontal R, parietal|
|Fpz (506)||Frontal B, frontomesial, thalamus||Parietal B, precuneus|
All patients were investigated at rest. Seven patients were sedated with chloral hydrate (75 mg/kg, maximal dose 2,000 mg) 30 min before MRI scanning, and the EEG-fMRI recordings were performed when the children were asleep. A pediatrician was present throughout the examination, and the children's pulse and oxygen saturation were monitored throughout the recording.
The EEG was continuously recorded during fMRI from 30 scalp sites (“EasyCap,” Falk-Minow Services, Herrsching-Breitbrunn, Germany; MR-compatible EEG recording system “BrainAmp-MR,” Brainproducts Co., Munich, Germany, for detailed description see Siniatchkin et al., 2010).
BOLD-sensitive MRI was performed with a 3-Tesla MR scanner (Philips Achieva; Philips, Best, The Netherlands) and a standard, 8-channel head coil. A single-shot T2*-weighted, gradient-echo planar imaging sequence was used for fMRI (repetition time [TR] = 2,250 msec, echo time [TE] = 45 msec, 30 slices, 64 × 64 matrix, slice thickness = 3.5 mm, field of view [FOV] = 200 mm, flip angle = 90 degrees). Five hundred and forty brain volumes were acquired during the 20-min fMRI session. fMRI measurements were complemented by a structural MRI using a T1-weighted, three-dimensional multiplanar reconstruction sequence (1 mm slice thickness, 208 × 208 matrix, 150 contiguous slices, FOV = 208 mm, TE = 3.6 msec, TR = 7.8 msec, flip angle = 8 degrees, number of signal averages = 2).
EEG data processing
EEG recordings were processed offline (gradient artifact correction, high-pass filter 0.03 Hz, low-pass filter 75 Hz, down-sampling to 250 Hz, ballistocardiographic artifacts correction) using the BRAINVISION Analyser software (Brainproducts Co). Interictal epileptiform discharges (IEDs) were independently marked by two experienced neurophysiologists (FM and MS). Consensus was achieved by comparing and discussing the results of these independently identified IEDs.
MRI data analysis
Individual MRI data sets were analyzed using SPM5 software (Wellcome Department of Imaging Neurosciences, University College London, United Kingdom, http://www.fil.ion.ucl.ac.uk/spm). Images were slice time corrected, realigned, spatially normalized to the Montreal Neurological Institute (MNI) template supplied by statistical parametric mapping (SPM) and smoothed (6 mm). The preprocessed fMRI time series were statistically analyzed at an individual level using separate sets of regressors for each type of IED in one model. Each event was represented as a stick function, convolved with a canonical hemodynamic response function as implemented in SPM5. Motion parameters obtained from realignment were included as confounds.
In each individual, one-tailed t-tests were applied to test for regional IED-related BOLD increases or decreases. As in previous studies by Carney et al. (2012) no correction for multiple comparisons was performed. In addition, we applied an extent threshold of 10 contiguous voxels to reduce the likelihood of an accidental activation/deactivation of a voxel. For the group level, a random effect group analysis (one sample t-test) of all IED studies from the single-subject analysis was performed with the threshold set at p < 0.001 (noncorrected) and a cluster extent of 10 voxels.
In all 10 patients we recorded several types of IEDs (two to five types) per patient. Compared with the EEG recorded outside the scanner, the IEDs selected during scanning were similar for every patient.
Table 1 summarizes the EEG-fMRI results for all patients. In total, 33 IED types were analyzed; BOLD signal changes were detected in 31 of 33 studies. In 21 of 31 studies the BOLD signal changes corresponded with the spike topography of the IEDs; in 15 of 21 studies the corresponding BOLD signal changes were activations. In addition, BOLD signal changes in distant brain areas were detected in all studies. Distant BOLD signal changes were detected in subcortical structures in 17 of 31 studies: in 7 studies in the thalamus (six activations), in 4 studies in the caudate nucleus (three activations), in 4 studies in the cerebellum (two activations), and in one study in the brainstem (deactivation). In Fig. 1 three examples of individual BOLD responses with BOLD signal changes in areas of the spike topography and in distant areas are presented.
For the group analysis, all 33 IED-related studies from the single-subject analyses were included. The group analysis revealed an activation of the medial thalamus (noncorrected, 23 voxel, t = 4.03, coordinates x = −3, y = −15, z = 9). No negative BOLD signal changes were observed. The results are shown in Figure 1.
Although not included in the international classification of epilepsies and epileptic syndromes, ABPE is considered as a subgroup among idiopathic focal epilepsies of childhood with an overlap with BECTS, CSWS, and LKS (Hahn et al., 2001). Because of these similarities, common pathogenic mechanisms in ABPE and other idiopathic focal epilepsies have been proposed, but they have not yet been described.
In patients with BECTS, EEG-fMRI studies have revealed focal spike-associated BOLD signal changes in the sensorimotor cortex, well corresponding to IED localization and the typical seizure semiology with paresthesia and jerking of the mouth, face, and hand (Archer et al., 2003; Boor et al., 2003, 2007; Lengler et al., 2007; Siniatchkin et al., 2007; Masterton et al., 2010, 2013). In patients with CSWS, a consistent neuronal network including both cortical and subcortical structures was described with positive BOLD signal changes in the perisylvian region, insula, cingulate cortex, and thalamus, and negative BOLD signal changes in the default mode network areas and caudate nucleus (Siniatchkin et al., 2010). In this study, patients with ABPE presented with BOLD signal changes in cortical brain areas concordant with the IED topography as well as in cortical and subcortical areas distant to the spike topography. The results underscore that idiopathic focal epilepsies of childhood form a continuum of different overlapping phenotypes: whereas BECTS is characterized by focal BOLD signal changes in the area of the spike field, both ABPE and CSWS show both focal BOLD signal changes in the area of the spike field but also distant cortical and subcortical BOLD signal changes. The group analysis in patients with ABPE revealed an activation of the medial thalamus. Previous EEG-fMRI studies in BECTS did not show an involvement of the thalamus (Archer et al., 2003; Boor et al., 2003, 2007; Lengler et al., 2007; Siniatchkin et al., 2007; Masterton et al., 2010, 2013). However, because rolandic spikes are increased during sleep, sleep-regulating thalamic nuclei may play a role in their generation. This hypothesis is supported by the observation that BECTS-associated discharges during sleep show a high positive correlation with spindle activity (Nobili et al., 1999). According to Avanzini et al. (2012) BECTS might be caused by a dysfunction of the thalamocortical part of the somatosensory system. The authors proposed the term “system epilepsy” in this context supporting the hypothesis that some types of epilepsy may depend on the dysfunction of a specific brain system. Previous EEG-fMRI studies have indicated that the thalamus is not primarily involved in BECTS (Archer et al., 2003; Boor et al., 2003, 2007; Lengler et al., 2007; Siniatchkin et al., 2007; Masterton et al., 2010, 2013) but given that IEDs during sleep show a high positive correlation with spindle activity one might assume that the thalamus could facilitate IED (Nobili et al., 1999). The involvement of the thalamus has been demonstrated previously in patients with CSWS and currently in patients with ABPE. It seems likely that the thalamus plays an important role in the spectrum of idiopathic focal epilepsies of childhood. According to the “system epilepsy” approach one might assume that idiopathic focal epilepsies of childhood are characterized by a variable degree of dysfunction within the somatosensory network (Avanzini et al., 2012). It can be suggested that with severity of epilepsy more structures of this susceptible somatosensory network and the thalamus get involved. A similar tendency has been observed in patients with the photoparoxysmal responses (PPRs). There is no involvement of the thalamus in the epileptic network underlying PPR if PPR is not associated with a seizure. However, if PPR triggers a seizure, the thalamus contributes significantly to the generation of hypersynchronous activity (Moeller et al., 2009a,b). Thalamic involvement is not specific for ABPE or CSWS: It is well known that the thalamus plays a substantial role in patients with idiopathic generalized epilepsy (Gotman et al., 2005) and might also be involved in the generation of photic-induced seizures (Moeller et al., 2009b). EEG-fMRI studies have also detected thalamic involvement in patients with Lennox-Gastaut syndrome (Siniatchkin et al., 2011) and in patients with frontal lobe epilepsy (Fahoum et al., 2012). In their study Fahoum et al. (2012) performed group analyses in patients with temporal lobe epilepsy, frontal lobe epilepsy, and posterior quadrant epilepsy and detected widespread epileptic networks. In contrast, the group analysis in our study revealed only an activation of the thalamus. The discrepancy with the study of Fahoum et al. may be explained by the fact that the patients in our study showed multifocal IEDs, and individual widespread BOLD signal changes were not consistent across the group. Moreover, the use of multiple hemodynamic response function in the study by Fahoum et al. as well as different etiologies (idiopathic localization-related epilepsy versus lesional epilepsy) and seizure activity (six of our patients were seizure free during the time of scanning) may have additionally contributed to differences between our study and study of Fahoum et al. (2012). Furthermore the results presented in this study were not corrected for multiple comparisons. Therefore, these preliminary results need to be confirmed in a larger group of patients.
As mentioned before, different subgroups of idiopathic focal epilepsy in childhood show a considerable overlap with each other, and even in one patient the diagnosis might shift during the course of the disease (Kanemura et al., 2012). In our study we tried to exclude patients with CSWS, since CSWS-specific patterns were analyzed in a separate study (Siniatchkin et al., 2010). None of the patients had shown CSWS (>85% of spike-wave discharges) during preceding routine sleep recordings. However, no whole night recordings were performed. Therefore, it cannot be entirely excluded that patients included in the current study might have shown CSWS at some point. Furthermore the patients received chloral hydrate for sedation, which might have influenced the amount of spike and wave discharges during the EEG-fMRI investigation. The influence of chloral hydrate on the BOLD signal change is not known. Because BOLD signal changes did not differ between sedated and nonsedated patients in a previous study (Moeller et al. 2008), we infer that sedation had no substantial effect on IED-associated BOLD signal changes. This view is supported by a study on epileptiform discharges in children with symptomatic epilepsy in which there were no differences in BOLD signal changes between patients who were sedated using chloral hydrate or prothipendyl (Jacobs et al., 2007).
In conclusion, the current study in patients with ABPE closes the gap between EEG-fMRI studies in BECTS and CSWS and supports the concept of a continuum of idiopathic focal epilepsies in childhood.
Study funding: supported by the German Research Foundation (DFG) grant SI 1419/2-1 and a Gerok Grant from the Christian-Albrechts-University Kiel.
None of the authors has any conflict of interest to disclose. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this report is consistent with those guidelines.
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