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Purpose: The diagnosis of frontal lobe epilepsy may be compounded by poor electroclinical localization, due to distributed or rapidly propagating epileptiform activity. This study aimed at developing optimal procedures for localizing interictal epileptiform discharges (IEDs) of patients with localization related epilepsy in the frontal lobe. To this end the localization results obtained for magnetoencephalography (MEG) and electroencephalography (EEG) were compared systematically using automated analysis procedures.
Methods: Simultaneous recording of interictal EEG and MEG was successful for 18 out of the 24 patients studied. Visual inspection of these recordings revealed IEDs with varying morphology and topography. Cluster analysis was used to classify these discharges on the basis of their spatial distribution followed by equivalent dipole analysis of the cluster averages. The locations of the equivalent dipoles were compared with the location of the epileptogenic lesions of the patient or, if these were not visible at MRI with the location of the interictal onset zones identified by subdural electroencephalography.
Results: Generally IEDs were more abundantly in MEG than in the EEG recordings. Furthermore, the duration of the MEG spikes, measured from the onset till the spike maximum, was in most patients shorter than the EEG spikes. In most patients, distinct spike subpopulations were found with clearly different topographical field maps. Cluster analysis of MEG spikes followed by dipole localization was successful (n = 14) for twice as many patients as for EEG source analysis (n = 7), indicating that the localizability of interictal MEG is much better than of interictal EEG.
Conclusions: The automated procedures developed in this study provide a fast screening method for identifying the distinct categories of spikes and the brain areas responsible for these spikes. The results show that MEG spike yield and localization is superior compared with EEG. This finding is of importance for the diagnosis and preoperative evaluation of patients with frontal lobe epilepsy.
Patients with frontal lobe epilepsy (FLE) comprise about 20% of the group of patients with localization related epilepsy. For mesiotemporal lobe epilepsy, it has been reported (e.g., by Boon and D'Havé, 1995; Gilliam et al., 1997; Schultz et al., 2000; Sakamoto, 2004; Baldauf et al., 2006) that electroencephalography (EEG) studies including dipole localization and MRI hippocampal studies provide satisfactory localizing information in almost all cases. The causes of FLE are, however, more diverse, while the epileptiform activity in the EEG of these patients may show a more diffuse, less dipolar voltage field pattern because of the involvement of extended brain regions (Salanova et al., 1993), or the rapid propagation within the neocortex to deep structures of the brain (Laskowitz et al., 1995). Therefore, the electroclinical localization of FLE is thought to be poor, although this finding may depend on the specific areas of the frontal lobe from which the epilepsy originates (Kotagal and Arunkumar, 1998; Kellinghaus and Luders, 2004; Vadlamudi et al., 2004).
It has been shown that source analysis of interictal EEG spikes may be helpful for localizing the brain area that is responsible for FLE (Ossenblok et al., 1999; Stefan et al., 2000; Ochi et al., 2001). However, distributed or rapidly propagating epileptiform activity may lead to numerous morphologically distinct epileptiform EEG discharges with maximal amplitude at variable surface electrode locations (Engel, 1993; Lantz et al., 1998; Shiraishi et al., 2005). Therefore, the population of interictal spikes should be grouped into distinct categories before averaging and source reconstruction. Because visual inspection of spikes in prolonged high resolution recordings can become highly complex, in this study, we developed automated procedures in order to group the consecutive interictal epileptiform discharges (IEDs) occurring in these recordings.
A number of studies (e.g. Knowlton et al., 1997; Barkley, 2004; Baumgartner, 2004; Park et al., 2004) reported that magnetoencephalography (MEG) is superior to EEG with respect to sensitivity of spike detection and localization in case of extratemporal lobe epilepsy. However, until now only a few studies directly compared source localizations obtained from MEG and EEG in patients with extratemporal lobe epilepsy. These studies included either a small number of patients (Nakasato et al., 1994; Merlet et al., 1997; Shiraishi et al., 2001; Yoshinaga et al., 2002) or were dealing with presurgical assessment (Pataraia et al., 2002; Stefan et al., 2003). We compared the relative strengths of MEG and EEG of patients with a localization related epilepsy with a frontal onset, while dealing with clinically relevant sources of interictal epileptiform events.
We used MEG in addition to EEG because it is generally assumed that solutions to the inverse problem are more accurate with MEG. This is primarily because magnetic fields, compared with electric potentials, are less attenuated or distorted by intervening tissue layers between the brain and recording sensors (Hämäläinen and Sarvas, 1989). Furthermore, it is typical for patients with FLE that the epileptiform activity propagates rapidly from a localized area, related e.g. to an epileptogenic lesion, to distant and more deep lying structures of the brain (Ossenblok et al., 1999). MEG is less sensitive to activity of deep lying sources then EEG (De Jongh et al., 2005). This typical feature of MEG may result in MEG spikes clearly distinguishable from ongoing background activities, whereas the corresponding EEG spike onset may be masked by the activity due to propagation. Thus, suppressing activity from deeper structures may provide more discernable MEG spikes and more discrete localization of cortical phenomena. In this article, we describe the results of the comparison of spike sensitivity and localizability of the underlying sources of the interictal MEG and EEG of patients with FLE, using automated methods for focus localization.
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The primary aim of this study was to evaluate whether MEG yields additional information compared with EEG for identifying clinically relevant sources of epileptiform events of patients with FLE. To this end, we compared systematically the MEG and EEG datasets consisting of expert-selected and confirmed IEDs of 18 well-documented patients with FLE. It was found that MEG spikes are far more often present than EEG spikes and generally have a sharper appearance. The higher spike yield of MEG compared with EEG is in accordance with a model that predicts higher SNRs for MEG than EEG in the frontal lobes, thus explaining that MEG spikes appear to be more distinguishable from the background activity than EEG spikes (De Jongh et al., 2005). The same model predicted similar spike yields for MEG and EEG in patients with temporal lobe epilepsy, which is consistent with the findings of Leijten et al. (2003) and Iwisaki et al. (2005) for patients with temporal lobe epilepsy. These authors regarded the relative insensitivity of MEG to deep lying sources as a disadvantage, especially because epileptiform activity generated in mesial temporal lobe regions might not be recorded by MEG. That MEG shows a significantly higher sensitivity than EEG for a patient with lateral frontal lobe epilepsy, but not for a patient with basal temporal epilepsy was also previously shown by Oishi et al. (2002), by comparing the interictal EEG and MEG spikes with spikes in the electrocorticogram. Furthermore, in a study of Fernandes et al. (2005) a computer-based algorithm was applied to extract parameters that could be used to quantitatively describe the morphology of the epileptiform transients. It appeared that EEG and MEG coincident spike events were statistically different with respect to several morphologic characteristics, such as duration, sharpness, and shape. These topographic and morphologic differences are the consequence of volume propagation through the tissues with different conductivities that surround the brain and affect EEG but not MEG, and of the difference in sensitivity of MEG and EEG to the orientation of the underlying dipolar sources.
The localizability of MEG versus EEG
The comparison of the MEG and EEG cluster analysis results followed by dipole localization raises the question why EEG based analysis failed for twice as many patients as MEG based analysis. For some of the patients the interspike variability was too high for clustering and reliable localization. However, diffuse field distributions due to overlap of primary (onset) and secondary source activity may be another reason for failure of source localization of EEG spikes, e.g., for patient H. Equivalent dipole fitting at an epoch centered around the maximum of each single interictal EEG event of this patient followed by clustering of these dipoles resulted in a single widely distributed cluster of dipoles covering the right temporal and frontobasal area (Fig. 5, bottom right). Cluster analysis of the equivalent dipoles fitted at an epoch centered around the maximum of each single MEG spike of this patient indicated, in accordance to the spatiotemporal cluster analysis results published by Van't Ent et al. (2003), 2 plausible clusters of dipoles, located at the right temporal lobe (red dots), and a second cluster located at the right frontobasal area (dark brown dots) (Fig. 5, upper right). Thus, the interictal MEG of patient H enabled the discrimination between clearly delineated primary and secondary epileptic active areas, probably as a direct result of the MEG feature being less sensitive to distributed and deep lying sources. The EEG sharp waves of this patient, on the other hand, corresponded to a distributed area of activity, probably resulting from the rapid propagation of the epileptiform activity along the right temporal lobe to the right frontal basal area (see Fig. 5, bottom right).
Figure 5. A single epileptiform event occurring simultaneously in the MEG (black) and EEG (red) of patient H (left). The arrows indicate the epoch centered around the maximum of the single spikes that were used for dipole fitting. The equivalent dipoles obtained for 71 single MEG and 62 single EEG epileptiform events are projected for MEG at the sagittal and axial MR scan of the patient (upper right) and for EEG at the sagittal MR scan (bottom right). The strength of the equivalent dipoles is color coded and is maximal in red.
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The results of equivalent dipole fitting of single spikes, as shown in Fig. 5, indicate that one has to be careful when localizing average spikes. This finding was also reported by Chitoku et al. (2003), who showed discrepancies of single interictal spike localization and localization of average spike clusters in case of extratemporal lobe epilepsy. Equivalent dipole analysis of single spikes instead of spike subaverages is, however, in most of the cases not feasible, because of insufficient SNR of single spikes. Therefore, in this study spike clusters are localized assuming that averaging of spikes with similar spatiotemporal patterns yields a more accurate localization, because of the increased SNR of the average spike.
Accuracy of MEG versus EEG localizations
An indication for accuracy might be inferred from the site of the main dipole cluster relative to the lesion, because neuropathology is most of the time directly related to the lesion (Genow et al., 2004). Assuming that the area at the margins of the structural lesion is related to the epileptogenic zone the accuracy of EEG versus MEG localizations was estimated as the distance of the irritative zone to the border of the lesion (Table 1). We did, however, not find a systematic relationship between the distances of the EEG versus MEG localizations. We sometimes found the centre of the dipole cluster located within the lesional area, which is probably due to the widely distributed area involved in the epilepsy of the patient, while it still contained intact neuronal cells. It is well known that in case of a tumor, like for patient I, the epileptogenic lesion may be located at a remote distance of the lesion (Zaatreh et al., 2003). Furthermore, for the EEG, holes in the skull can lead to very large errors in the inverse solution (Oostenveld and Oostendorp, 2002), but not for the MEG. Although, the location errors due to underestimating skull conductivity—which is unknown for the individual patient—are typically higher than those found due to neglecting a hole in the skull (Vanrumste et al., 2000). We found for three out of four of the patients with a hole in the skull, that the differences of MEG and EEG in location relative to the lesion were falling within the localization error inherent to inverse solutions for EEG and MEG (Leahy et al., 1998).
It has been reported that the combined analysis of MEG and EEG may yield a better accuracy than a separate analysis of these modalities (Diekman et al., 1998). In practice, however, a combined analysis is hampered by the large differences that can be observed in both the morphology and topography of the MEG versus EEG spikes of our group of patients.
The diagnostic value of the localization procedures
Evaluation of epilepsy improves with yield of interictal epileptiform activity, with neurophysiologic SNRs of such activity and with the localization of the full range of interictal IEDs. In this study, we successfully applied algorithms for the characterization of the single spike events with varying morphology and topography occurring in prolonged M/EEG recordings of patients with FLE. The automated clustering and localization of these spike events indicated distinct spike clusters within a widely distributed epileptogenic region surrounding a lesion (e.g. patient W in Fig. 4) or corresponding to distinct brain areas involved during the IEDs (e.g patient H). For the latter patient, additional research—including spatiotemporal analysis of the MEG spikes, ECoG, and successful surgical intervention that rendered the patient seizure free—pointed to a primary onset zone in the right temporal lobe with secondary involvement of the right frontal lobe. Thus, the results presented here support the hypothesis that the spike clusters located within the epileptogenic region, as defined by an epileptogenic lesion or ECoG, correspond to the irritative zone, whereas others only represent the propagation of the epileptiform activity (see also Ossenblok et al., 1999). This finding is in accordance with the results of Ossadtchi et al. (2004), who reported multiple spike clusters with some of them located in the vicinity of the area that subsequently was resectioned (for three of the four patients studied), while the other remaining “spurious clusters” might correspond to secondary epileptic areas because of propagation.
The generally higher spike yield of MEG and the generally sharper profiles of the spikes is of importance for deciding whether the patient has epilepsy or not. Furthermore, because localization of MEG is possible in more patients on basis of MEG than of EEG, MEG might result in a better treatment and prognoses based on a more accurate diagnosis and localization of the epilepsy of the patient. These findings are in support of the conclusion of Baumgartner and Pataraia (2006), who stated: “In extratemporal lobe epilepsy MEG provides unique information in nonlesional cases and helps to define the relationship of epileptic activity with respect to lesions and eloquent cortex.”