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Accuracy of EEG source imaging of epileptic spikes in patients with large brain lesions
Clinical Neurophysiology 120 (2009) 679–685
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Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph
Accuracy of EEG source imaging of epileptic spikes in patients with large brain lesions Verena Brodbeck a,*, Agustina M. Lascano a, Laurent Spinelli b, Margitta Seeck b, Christoph M. Michel a a b
Functional Brain Mapping Laboratory, University Hospital Geneva, 24, Rue Micheli-du-Crest, CH-1211 Geneva, Switzerland Presurgical Evaluation Unit, Neurology Clinic, University Hospital Geneva, 24, Rue Micheli-du-Crest, CH-1211 Geneva, Switzerland
a r t i c l e
i n f o
Article history: Accepted 28 January 2009 Available online 5 March 2009 Keywords: EEG Electromagnetic source imaging Brain lesions Spike localization Epilepsy surgery
a b s t r a c t Objective: To test the accuracy of EEG source imaging in epilepsy patients with large cerebral lesions. It is hypothesized that lesions are most likely to change conductivity properties and to significantly impair the accuracy of electromagnetic source imaging (ESI) based on the EEG. This has, however, not been tested in patients’ EEG. Methods: Fourteen patients with focal epilepsy and large cerebral lesions underwent high-resolution (128–256 channels) interictal EEG recordings. Thirteen patients were operated, leading to seizure freedom in 12. The spike sources were localized with a distributed linear inverse solution (LAURA) and compared to the post-operative MRI or the results of other invasive or non-invasive exams. Results: In 12 patients ESI indicated the maximum source of the epileptic activity to be located within the epileptogenic zone (85%). One of the remaining cases was not seizure free after surgery. According to the ESI result, however, the focus was incompletely removed. Conclusion: High resolution ESI constrained to the individual anatomy identifies the epileptogenic focus in patients with volume relevant brain lesions with excellent accuracy, comparable to that of other noninvasive methods. Significance: Our results are of particular clinical importance, as they show that ESI can be extended to patients with large inhomogeneous lesions. Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
1. Introduction Surgical therapy is an important option in the treatment of partial epilepsy. In the presurgical evaluation of candidate patients it is crucial to define the epileptogenic area as precisely as possible and to delineate any adjacent eloquent areas. The decision making on whether a surgical intervention comes into question or whether further invasive diagnostic steps have to be taken, relies on a set of non-invasive diagnostic tools. Seizure semiology, ictal and interictal EEG, high resolution MRI, positron emission tomography (PET) and ictal and interictal single-photon emission computer tomography (SPECT) were incorporated into the presurgical workup in most epilepsy centres (Rosenow and Luders, 2001; Kim et al., 2004; Van Paesschen et al., 2007). With increasing availability of computational power the interest in electromagnetic source imaging (ESI) techniques is expanding. ESI has been shown to add important information on focus localization in the presurgical workup (Boon et al., 2002; Bast * Corresponding author. Tel.: +41 22 37 28339; fax: +41 22 37 28476. E-mail address: [email protected] (V. Brodbeck).
et al., 2006; Sperli et al., 2006) with precision rates comparable or even superior to standard diagnostic tools such as PET or SPECT (Michel et al., 2004a). Even though ESI still needs ultimate clinical validation through large prospective studies, the advantages of ESI compared to the traditional two dimensional clinical EEG is inarguable (Plummer et al., 2008). ESI can be performed with EEG or MEG recordings. Although the same neurophysiological processes generate the EEG and MEG signals, the recorded information is differing. While EEG has greater depth and greater orientation sensitivity than MEG, MEG is less susceptible to the conductivity variations of the head than the EEG (Wikswo et al., 1993; Malmivuo et al., 1997; Lopes da Silva, 2004; Lau et al., 2008). The fact that MEG is less influenced by irregularities of head geometry and less affected by intermediate tissue layers (scull, CSF) has been taken as argument that source localization with MEG in patients with volume relevant brain lesions is more trustworthy than with EEG (Williamson and Kaufman, 1987). Several simulation studies have addressed the question of how different conductivity properties influence the precision of EEG source localisation algorithms. It was noted that errors in dipole
1388-2457/$36.00 Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2009.01.011
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localization are larger in liquid as compared to solid lesions (Vatta et al., 2002) and larger if the source is in the peripheral brain tissue as compared to the centre of the head (Awada et al., 1998). These simulation studies were based on rather simple source and head models, and it was concluded that incorporation of correct tissue conductivities in the head models is needed for accurate source localization. However, another simulation study by Haueisen et al. (1997), using finite element volume conductor models and variable resistivity for 13 different tissue types concluded that knowledge of conductivities might only be necessary for modelling the field strength, but not for source localization. Others found negligible localization errors in few millimeter range for intracerebral cavities but large errors for skull defects (Benar and Gotman, 2002). While simulation studies have their undoubted value for systematic evaluation and quantification of the influence of conductivity changes in a model case, they cannot answer whether in case of real patients’ data with altered brain anatomy, accuracy of ESI is still in an acceptable range. This is of particular importance for the use of EEG ESI in epilepsy, as many of the patients that are addressed to presurgical evaluation suffer from lesional epilepsy. In the present study, we were interested to see if electrical source localization in patients with large brain lesions was too imprecise to be of use for clinical purposes. We selected 14 patients who had sufficiently extensive lesions to lead to conductivity inhomogeneity within the skull. We recorded high resolution EEG (128–256 channels) and used distributed source models with a standard three-shell head model but constrained to the individual grey matter of each patient. The precision of the focus localization was evaluated with respect to the surgical resection and surgical outcome. 2. Methods 2.1. Patients We searched our database for patients that had been addressed to our department for surgical work-up going back to the year 2000, matching the following inclusion criteria: (1) Examined with high density EEG (either 128 or 256 electrodes). (2) High frequency of spikes in the wake EEG (sufficiently enough epileptic discharges during 20–30 min EEG recording to perform the ESI analysis). (3) Large cerebral lesion identified in clinical MRI. (4) Underwent surgery. Thirteen patients matching these criteria were identified. Postoperatively, 12 patients were seizure-free (Engel class I) and one had a less favourable outcome (patient #3; Engel class III). One patient was added who was not operated but in whom several exams identified the same area as epileptogenic zone (patient #14). The clinical characteristics of all 14 patients are summarized in Table 1. Their age at examination ranged from 5 to 54 years (mean 15.9, median 11.5), the age at epilepsy onset ranged from 0 to 31 years (mean 6.6 years, median 3). Eight patients were female. Aetiologies of the brain lesion were variable. In four cases the lesion was due to a perinatal stroke. The subsequent aetiologies were present in one case each: congenital polymicrogyra, tuberous sclerosis, head trauma, residuum after postpartal meningitis, arterio-venous malformation, status after ruptured aneurysm and a gangliogliome with a large cystic lesion. Two patients had arachnoid cysts, in one of the two combined with schizencephaly. The location of the principal interictal epileptic activity was within or close to the lesion in all patients. Fig. 1 shows the patients’ preoperative MRI. The level of the slice is chosen so that the individual
lesion is best visible. In two patients (#3 and 13), invasive recording was performed prior to surgery. The locations of the intracranial electrodes and the ictal and interictal findings are given in Table 1. 2.2. High density EEG recordings High density EEG recording was performed in all patients, using 128 or 256 channel nets with interconnected electrodes (Electrical Geodesic, Inc., Eugene, OR, USA). The nets are soaked in saline water before they are put on the patient’s head. The electrodes are interconnected by thin rubber bands and each contains a small sponge that touches the patient’s head directly. The net was adjusted so that the electrodes over the Nasion, the Inion, the pre-auricular points, and Cz were correctly placed according to the international 10/10 system. The geodesic tension structure of the net assured that the remaining electrodes were then evenly distributed across the head and at approximately the same location across subjects. The whole net is applied at once and needs no skin abrasion. It has been demonstrated that with saline measures electrode bridging is negligible after around 10 min (Greischar et al., 2004). Nevertheless, we verified absence of electrolyte bridges using the methods described by Greischar et al. that are implemented in the recording software NetStation. Because of the high amplifier input impedance (200 MX) sensor impedance was required to be below 50 kX (Ferree et al., 2001). In reality, impedances below 20 kX were achieved easily. The net application and verification of good electrode-head contacts lasted 10 min or less. The patient was set up in a comfortable chair in a dimly lit room. The EEG was recorded continuously for at least 30 min, partly with eyes open and eyes closed leading to a total examination period of maximally 1 h (Michel et al. (2004a) for details of the protocol). The sampling rate was set to 500 Hz, filters were set to 0.1–100 Hz. The EEG was recorded against a vertex reference. 2.3. Data analysis 2.3.1. Spike selection and averaging The off-line analysis started with the visual selection of interictal spikes with artefact free surround EEG of ±500 ms. The spike was marked at the exact time point where it reached maximal negativity on the electrode trace where it showed highest amplitude and chosen when showing similar voltage map distribution. Within the single spike epochs, electrodes containing artefacts were interpolated using a three dimensional spline interpolation algorithm (Perrin et al., 1989) to keep the number of electrodes the same for all epochs. The average numbers of interpolated electrodes are given in Table 1. Cheek and neck electrodes were excluded leading to 204 and 111 electrodes. Spikes were then aligned to the Global Field Power Peak and averaged over epochs of ±500 ms around this peak. 2.4. EEG source imaging For the localization of the electrical activity in the brain we used the LAURA (local autoregressive average) algorithm, a distributed linear inverse solution comprising biophysical laws as constraints (Grave de Peralta Menendez et al., 2001, 2004) (see Michel et al. (2004b) for review). The solution space was restricted to the grey matter of the individual patient’s brain using a homemade semi-automatic segmentation tool. The lesions were thus excluded from the solution space. For the lead field calculation the SMAC method was applied (Spinelli et al., 2000; Phillips et al., 2005). This method first transforms the individual MRI to the best fitting sphere using homogeneous transformation opera-
Table 1 Clinical characteristics of all patients. The outcome after surgery is classified according to Engel’s Classification. Invasive recordings were performed in patients #3 and 13. The electrode types (grid, strip or depth electrodes), covered regions and the location of interictal activity and the number and regions of onset of ictal events are given. The last two columns contain the number of spikes averaged, the signal to noise ratio (maximal global field power divided by the average global field power of the 1 s spike epoch), the total number of electrodes and the average number of interpolated electrodes. (Abbreviations: d = day, m = month, w = week, R = right, L = left, F = frontal, T = temporal, P = parietal, O = occipital, lat = lateral, bas = basal, orb = orbital, HR = high resolution, N = number.) Patient No.
Sex
Age (years) Phase I
Age of onset (years)
Seizures frequency
MRI
Ictal onset in clinical EEG
Invasive recordings
Interictal focus in HR-EEG
OP Resected zone
Out come
Number of spikes/ signal to noise ratio
HREEG
Congenital left hemispheric lesion of unknown origin Perinatal left hemispheric stroke
0–6/d
TPO L lesion with polymicrogyria O and parasag Cortex and periventricular gliosis L hemispheric atrophy Pachygyrie and Microgyria of L hemisphere, predominant P L + dysplastic insula and paarasagittal cortex, slight hippocampus atrophy Haemorrhage T R Porencephalie and periventricular gliosis,
TPO L
–
PO L
Lesionectomie PO L
1
62/2.95
204
Slowing Hemisphere R
–
TL
Periinsular Hemispherotomie L
1
30/3.98
109
PT R
Grid PT R depth T bilat, F orb R interictal: TPJ R ictal: 4/7 TPJ, 3/7 undefined –
PR
T R Resection
3
25/2.47
204
FL
Polectomie FT L
1
26/4.67
204
1
F
9
6
2
M
9
2
3
M
11
8
Postnatal Strep B Sepsis with right temp. haemorrhage
0–7/d
4
M
54
31
3–5/m
Posthaemorhagic lesion F >T L
FL
5
F
34
15
10/m
Posttraumatic lesion with perilesional leucoencephalopathy F L>R, T R T L
Bilateral predominantly paramedian F R
–
FC
Lobectomie F R
1
45/3.90
204
6
F
26
17
8/d–1/w
–
FR
45/3.30
111
6
OL
–
OL
Lobectomie Anterior T R + AmygdaloHippocampectomie R Partial lobectomie PO L
1
F
Arterio-venous malformation T R, first OP 1997 thereafter haematome T R, cortico subcortical atrophy T R Large cystic lesion O L
TR
7
1
23/2.67
111
8
F
15
4
Rupture of aneurisma a. communicans anterior Head trauma with subdural haematome right hemisphere mainly bi-F and T right Arterio-venous malformation T Right Ganliogliome TPO Left Lesion F right of unknown origin
Large multicystic lesion F R
.
FR
Lesionectomie F R
1
22/2.73
111
9
F
5
0
Perinatal stroke left hemisphere
2–8/d
Porencephalic cyst T post-L, Hippocampus atrophy L
–
Continuous T L, TP L TO L
Disconnection TPO L
1
28/3.09
111
10
M
6
3
Perinatal stroke left hemisphere
4–5/d
–
Continuous mainly F R
Hemispherectomie L
1
29/3.24
111
11
M
8
3
>10/week
FL
Hemispherectomie L
1
18/3.94
111
F
13
1
0–5/d
No seizures registered FC L
–
12
–
FL
Resection of Dysplasia F L
1
31/4.58
204
13
F
15
0
Perinatal stroke of left a. cerebri media Dysplasia F left of unknown origin Tuberous Sclerosis Bourneville
Voluminous ischaemic lesion sylvian territory L Hemiatrophy L Hemisphere orbito-F and T Severe atrophy of hemiphere L, large infarcted area in ACM teritoy Dysplasia F C L
Generalised spikes F R predominance Variable, mainly background flattening PL
>5/d
Tuber TP L (largest of many)
Posterior L
TO L
Tuberectomie + Corticotomie TP L
1
38/3.33
204
14
M
12
3
0.3–3/ month
Large cyst, schizencephaly FT R
TR
Grid TP L, strips L: F, T lat + bas, O interictal TP L ictal: 14/15 TP L –
TP R
–
–
37/3.21
204
0.5
Nocturnal/ sublicinical 5–8/d
681
Congenital arachnoid cyst, schizencephaly FT right
30–40/d
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Origin of symptomatic focal epilepsy
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Fig. 1. Anatomical pre-OP-MRI of lesions. The slices shown here are the preoperative MRI of all 14 patients. The level of the slices are indicated by red bars on the sagital view and chosen so that the individual lesion is best visible. Lesions of patients #2, 9, 10 and 11 are caused by perinatal stroke. Patients #8 and 14 have arachnoid cysts, in patient #14 combined with a schizencephaly. Patient #1 has a congenital polymicrogyria, #3 a residuum after postpartal meningitis, #4 had a ruptured aneurysm, #5 has a posttraumatic lesion, #6 a arterio-venous malformation, #7 a cystic lesion after resection of a gangliogliome, #12 a congenital dysplasia and #13 a tuberous sclerosis. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this paper.)
tors. It then determines a regular grid of around 4000 solution points in the grey matter of this spherical MRI and computes the lead field matrix using the known analytical solution for a spherical head model with three shells of different conductivities as defined by Ary et al. (1981). Possible differences in the conductivities due to the large lesions were thus not considered in the model. The two same electrode positions (128/256) were used for all subjects as derived from the mean of positions measured in 20 healthy subjects with a three dimensional digitizer and projected to a best fitting sphere. The co-registration between the spherical MRI and the spherical electrode positions was achieved by marking the landmarks (Nasion, Inion), pre-auricular points and Cz on the individual 3D MRI and matching them with the corresponding electrode positions. 2.5. Defining the accuracy of ESI focus localization The average map of the spikes was analysed and the time point of 50% rising phase (50% global field power peak) was subjected to the source localization procedure. It has been demonstrated that the ESI of the rising phase of the average spike represents most reliable the actual source of the epileptic activity (Scherg et al., 1999; Lantz et al., 2003; Lau et al., 2008). In all patients who were seizure free after surgery, the focus localization was stated to be correct when it fell within the resected area. For seven of the 12 operated patients a post-OP MRI was available. In six patients the quality of the post-OP MRI was sufficient to superimpose the MRI, the resected area and the ESI identified focus (Fig. 2). One patient’s (#5) post-OP MRI was of bad quality due to movement artefacts and not unequivocally usable for comparison with the pre-OP MRI. We renounced on a post-operative MRI in patients who underwent a hemispherotomy (#2, 10, 11) and/or were seizure-free and too young to undergo a post-op MRI procedure without sedation (#9). For the non-operated patient #14, we coregistered the spike triggered fMRI with the spike ESI results.
3. Results In average 27 spikes were selected in each subject. The mean signal to noise ratio was 3.4. The exact values for each patient are given in Table 1. Fig. 1 displays the anatomical MRI of all patients, with the level of the slice chosen to show best the extension of the individual patient’s lesion. Fig. 3 shows the slices with the maximal ESI activity. For those patients in whom the postoperative MRI was available we demonstrate a superimposed display of the resected area (red) and the ESI result (blue) as 3D volumes (Fig. 2). The identified maximum source of the epileptic activity fell within the epileptogenic zone in all but 2 of the 13 operated patients. In patients #2, 10 and 11 a hemispherotomy was carried out. Given that in all cases the focus lied in the affected hemisphere, the correctness of the solution is assumed. Since these patients are usually not candidates for intracranial EEG monitoring or extensive preoperative corticography, no further verification was obtained. However, in all 3 patients, PET results suggested predominantly frontal dysfunctions and thus corroborate the ESI findings in these patients (Figs. 2 and 3). In the remaining 9 operated patients with outcome class I (#1, 4, 5, 6, 7, 8, 9, 12, 13), in all except one patient (#5) the source of the focus was found in the resection brain area. In patient #5, the work-up indicated a right mesial frontal focus, whereas ESI located the principal focus in the right insula-temporal cortex (Fig. 3). Resection of the right frontal tissue resulted in seizure freedom; however, post-operatively the patient suffered from several complications (bleeding, hydrocephalus). In patient #3 seizures persisted, albeit with reduced frequency, despite resection of most of the presumed epileptogenic zone. However, ESI suggests an incomplete resection, because the focus was only partially removed, i.e. situated more anterior, overlying the somato-motor cortex.
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Fig. 2. Resection zone and superimposed ESI results of all patients. The resected areas are displayed in red within the post-OP MRI in patients #1, 2, 3, 7, 12 and 13 and manually indicated and approximated within the pre-OP MRI according to surgery reports for patients #4, 5, 6, 8, 9, 10 and 11. The ESI result is displayed in blue. For patient #3 we added a 3D display of the subdural grid position (electrodes as blue circles) in which the electrodes of seizure onset are highlighted in yellow. Patient #14 is the one non-operated case in which we show the focus localization according to spike triggered fMRI (green) and the high resolution EEG recording (in blue).
Patient #14 was not operated given that seizures disappeared with improved drug treatment and because there was a major neurosurgical risk associated to an intervention. He underwent EEGtriggered fMRI, PET and SPECT imaging. All 3 modalities were concordant with respect to the focus localization as determined by ESI, i.e. in the inferior and posterior aspect of a highly dysplastic insula. It can reasonably be assumed that the source solution is correct despite absence of a post-operative MRI. 4. Discussion Our results suggest that ESI based on high density EEG is able to identify the epileptogenic focus with excellent accuracy in most patients despite volume relevant brain lesions that most likely
changed conductivity properties within the skull. In 12 of 14 patients (85%) ESI was correct, a yield that is comparable to similar studies in patients without significant brain malformations (Michel et al., 2004a; Sperli et al., 2006). In the 2 cases with incorrect localization, the accuracy – or inaccuracy – of ESI is difficult to determine: the remaining seizures after incomplete resection of the focus in patient #3, as determined by ESI, may speak in favour for the superiority of ESI over the intracranial data. In contrast to the other patients, a large portion of the active area as identified with ESI was outside the lesion in the surrounding tissue. However, due to its vicinity to vital sensory-motor cortex and because of the intracranial EEG, which suggested more posterior and caudal onset (yellow circles in Fig. 2), the resection zone was not extended. In this patient, ESI also proposed an addi-
Fig. 3. Anatomical pre-OP MRI with ESI maximum. In each patients MRI the maximum of the estimated source of the average interictal spike (LAURA) is indicated in red. Note that the level of maximal source activity does not necessarily correspond to the level of maximal extent of the lesion shown in Fig. 1.
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tional independent source in the temporal lobe remote from the resected area. Careful inspection of the temporal dynamics indicated that this temporal source dominated at the beginning of the spike and that the parietal source was activated later during the rising phase of the spike. This observation suggests the onset of the epileptogenic activity in the temporal lobe followed by fast propagation to the parietal lobe. However, the intracranial recordings with electrodes covering both brain regions (Fig. 2) did not speak in favour of such a sequential activation, albeit not all regions of the lateral aspect of the temporal lobe were covered. This case also raises the question of the correspondence of ictal and interical activity and the detection of fast propagation. A recent study with simultaneous intracranial and scalp EEG indicated that source analysis of scalp spikes at their initial rising phase, as done in this study, might provide more focal localizing information than the analysis of seizure origin or spike peaks because of fast propagation of the epileptic activity (Ray et al., 2007). In patient #5, ESI localized incorrectly to the insula temporal cortex, because resection of right mesial frontal cortical tissue led to seizure freedom. However, the post-operative complications, in particular bleeding into the right frontal cavity, might also have lesioned the insula-temporal cortex and that this additional lesion has led to seizure freedom. Our study evaluated the influence of conductivity changes due to large lesions in the real case, if these changes are not specifically considered in the source localization procedure. We used standard conductivity values for the three compartments of the head (brain, CSF, skull) without taking into account the possible changes induced by the lesions. However, we restricted the source space to the remaining grey matter of the individual brain of the patient, excluding potential sources within the lesion. We also took advantage of recent hard- and software developments by using high-resolution EEG recordings (128–256 channels) and distributed inverse solutions that do not a priori assume a limited amount of sources. Our results indicate that the influence of conductivity variations due to large brain lesions is negligible with respect to the capability of high-resolution ESI to accurately localize epileptic foci. From a theoretical point of view, EEG-based source imaging should be of limited use in large brain lesions, because the EEG is affected by the changes in conductivity properties induced by such lesions. Simulation studies partly supported this assumption: Vatta and colleagues (Vatta et al., 2002) evaluated 64 different simulated pathology situations and showed highest errors in dipole estimations for liquid filled lesions, whereas solid, calcified lesions show negligible sensitivity to uncertainties in conductivity assignment. Localization errors were also tolerable (smaller than 0.5 cm) when source and lesions were far apart from each other. The authors propose correction procedures to identify and incorporate lesion-induced conductivity changes in the source localization estimation. Awada et al. (1998) examined errors in dipole source localization when wrong conductivity values for different brain tissues were assumed, and conclude that the localization error generally increases as the dipole moves away from the centre of the head toward the boundary. However, their simulations were restricted to two-dimensional, transaxial cross-sections of the head. The authors themselves state that the estimation errors are likely to be less extensive for 3D calculations. The simulation study by Haueisen and Ramon on the influence of tissue resistivity changes on the neuromagnetic field and the electric scalp potential (Haueisen et al., 1997) showed that both, EEG and MEG signal are affected by changes of the resistivity of the tissue that surrounds the source (grey matter), but that only the EEG signal is influenced by changes close to the electrodes as well. However, it is the magnitude (strength) of the magnetic field and the electric scalp potential that is affected rather than their topography. Our results corroborate this hypothesis and the results of Benar and Gotman (2002) that
indicate that the accuracy of source localization procedures is affected only to a negligible extent by brain tissue changes. Advances in computer power make it now possible to use boundary element head models (BEM) to precisely model the shape of the different isotropic homogeneous head compartments in the individual brain (Fuchs et al., 2002). We did not use such advanced headmodels in this study but relied on a simpler head model reconstruction based on spherical deformation of the individual grey matter. This fast SMAC method has successfully been used in different clinical and experimental studies (Michel et al., 2004a; Phillips et al., 2005; Sperli et al., 2006); for review see Michel et al. (2004b). The results presented here demonstrate that it leads to adequate localization of epileptic foci in the individual brain. Nevertheless, since the individual gray matter is needed for the source space constraints segmentation of the individual cortex in the SMAC method, the application of BEM models would be straightforward in cases where greater spatial resolution is required. A final point concerns the number of electrodes for adequate source imaging in epilepsy. In this study high resolution EEG was used in all patients (128–256 channels). In a previous study (Sperli et al., 2006)we showed that even with standard clinical EEG systems of around 30 electrodes, correct localization on a lobar level is achieved in over 90% of the cases, including some with large brain lesions. However, for sublobar precision, higher numbers of electrodes are needed, as shown in Sperli et al. (2006) as well as by Lantz et al. (2003). In this latter study data originally recorded from 123 electrodes were downsampled to 63 and 31 electrodes. It was shown that localization precision with respect to distance of the source maximum to the resected area increased in average from 6 to 22 mm when sampling with 123 and 31 electrodes, respectively. 5. Conclusions Our retrospective study shows excellent accuracy of electrical source localization in patients with large brain lesions, comparable to the accuracy obtained in non-lesional epilepsy patients and to other non-invasive localization methods (Lantz et al., 1999; Michel et al., 2004a; Zumsteg et al., 2006) (for review see Plummer et al. (2008)). Even though a prospective study with a larger number of patients would be necessary to doubtless verify our results, our finding is of important clinical relevance as it increases the confidence in source localization procedures and extends their application to surgical candidate patients with lesioned brains. Acknowledgments The data were analyzed with the Cartool software (http://brainmapping.unige.ch/Cartool.php) which is developed by Denis Brunet, from the Functional Brain Mapping Laboratory, Geneva, supported by the Center for Biomedical Imaging (CIBM), Geneva and Lausanne, Switzerland. The work was also supported by the Swiss National Science by the Grant No. 3200-113766 to M.S. and No. 3200-111783 to C.M. References Ary JP, Klein SA, Fender DH. Location of sources of evoked scalp potentials: corrections for skull and scalp thicknesses. IEEE Trans Biomed Eng 1981;28(6):447–52. Awada KA, Jackson DR, Baumann SB, Williams JT, Wilton DR, Fink PW, et al. Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model. IEEE Trans Biomed Eng 1998;45(9):1135–45.
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Malmivuo J, Suihko V, Eskola H. Sensitivity distributions of EEG and MEG measurements. IEEE Trans Biomed Eng 1997;44(3):196–208. Michel CM, Lantz G, Spinelli L, De Peralta RG, Landis T, Seeck M. 128-channel EEG source imaging in epilepsy: clinical yield and localization precision. J Clin Neurophysiol 2004a;21(2):71–83. Michel CM, Murray MM, Lantz G, Gonzalez S, Spinelli L, Grave de Peralta R. EEG source imaging. Clin Neurophysiol 2004b;115(10):2195–222. Perrin F, Pernier J, Bertrand O, Echallier JF. Spherical splines for scalp potential and current density mapping. Electroencephalogr Clin Neurophysiol 1989;72(2):184–7. Phillips C, Mattout J, Rugg MD, Maquet P, Friston KJ. An empirical Bayesian solution to the source reconstruction problem in EEG. Neuroimage 2005;24(4):997–1011. Plummer C, Harvey AS, Cook M. EEG source localization in focal epilepsy: where are we now? Epilepsia 2008;49(2):201–18. Ray A, Tao JX, Hawes-Ebersole SM, Ebersole JS. Localizing value of scalp EEG spikes: a simultaneous scalp and intracranial study. Clin Neurophysiol 2007;118(1):69–79. Rosenow F, Luders H. Presurgical evaluation of epilepsy. Brain 2001;124(Pt 9):1683–700. Scherg M, Bast T, Berg P. Multiple source analysis of interictal spikes: goals, requirements, and clinical value. J Clin Neurophysiol 1999;16(3):214–24. Sperli F, Spinelli L, Seeck M, Kurian M, Michel CM, Lantz G. EEG source imaging in pediatric epilepsy surgery: a new perspective in presurgical workup. Epilepsia 2006;47(6):981–90. Spinelli L, Andino SG, Lantz G, Seeck M, Michel CM. Electromagnetic inverse solutions in anatomically constrained spherical head models. Brain Topogr 2000;13(2):115–25. Van Paesschen W, Dupont P, Sunaert S, Goffin K, Van Laere K. The use of SPECT and PET in routine clinical practice in epilepsy. Curr Opin Neurol 2007;20(2):194–202. Vatta F, Bruno P, Inchingolo P. Improving lesion conductivity estimate by means of EEG source localization sensitivity to model parameter. J Clin Neurophysiol 2002;19(1):1–15. Wikswo Jr JP, Gevins A, Williamson SJ. The future of the EEG and MEG. Electroencephalogr Clin Neurophysiol 1993;87(1):1–9. Williamson SJ, Kaufman L. Analysis of Neuromagnetic Signals. In: Gevins AS, Rémond A, editors. Handbook of electroencephalography and clinical neurophysiology. Amsterdam: Elsevier; 1987. p. 405–48. Zumsteg D, Andrade DM, Wennberg RA. Source localization of small sharp spikes: low resolution electromagnetic tomography (LORETA) reveals two distinct cortical sources. Clin Neurophysiol 2006;117(6):1380–7.
Contents lists available at ScienceDirect
Clinical Neurophysiology journal homepage: www.elsevier.com/locate/clinph
Accuracy of EEG source imaging of epileptic spikes in patients with large brain lesions Verena Brodbeck a,*, Agustina M. Lascano a, Laurent Spinelli b, Margitta Seeck b, Christoph M. Michel a a b
Functional Brain Mapping Laboratory, University Hospital Geneva, 24, Rue Micheli-du-Crest, CH-1211 Geneva, Switzerland Presurgical Evaluation Unit, Neurology Clinic, University Hospital Geneva, 24, Rue Micheli-du-Crest, CH-1211 Geneva, Switzerland
a r t i c l e
i n f o
Article history: Accepted 28 January 2009 Available online 5 March 2009 Keywords: EEG Electromagnetic source imaging Brain lesions Spike localization Epilepsy surgery
a b s t r a c t Objective: To test the accuracy of EEG source imaging in epilepsy patients with large cerebral lesions. It is hypothesized that lesions are most likely to change conductivity properties and to significantly impair the accuracy of electromagnetic source imaging (ESI) based on the EEG. This has, however, not been tested in patients’ EEG. Methods: Fourteen patients with focal epilepsy and large cerebral lesions underwent high-resolution (128–256 channels) interictal EEG recordings. Thirteen patients were operated, leading to seizure freedom in 12. The spike sources were localized with a distributed linear inverse solution (LAURA) and compared to the post-operative MRI or the results of other invasive or non-invasive exams. Results: In 12 patients ESI indicated the maximum source of the epileptic activity to be located within the epileptogenic zone (85%). One of the remaining cases was not seizure free after surgery. According to the ESI result, however, the focus was incompletely removed. Conclusion: High resolution ESI constrained to the individual anatomy identifies the epileptogenic focus in patients with volume relevant brain lesions with excellent accuracy, comparable to that of other noninvasive methods. Significance: Our results are of particular clinical importance, as they show that ESI can be extended to patients with large inhomogeneous lesions. Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
1. Introduction Surgical therapy is an important option in the treatment of partial epilepsy. In the presurgical evaluation of candidate patients it is crucial to define the epileptogenic area as precisely as possible and to delineate any adjacent eloquent areas. The decision making on whether a surgical intervention comes into question or whether further invasive diagnostic steps have to be taken, relies on a set of non-invasive diagnostic tools. Seizure semiology, ictal and interictal EEG, high resolution MRI, positron emission tomography (PET) and ictal and interictal single-photon emission computer tomography (SPECT) were incorporated into the presurgical workup in most epilepsy centres (Rosenow and Luders, 2001; Kim et al., 2004; Van Paesschen et al., 2007). With increasing availability of computational power the interest in electromagnetic source imaging (ESI) techniques is expanding. ESI has been shown to add important information on focus localization in the presurgical workup (Boon et al., 2002; Bast * Corresponding author. Tel.: +41 22 37 28339; fax: +41 22 37 28476. E-mail address: [email protected] (V. Brodbeck).
et al., 2006; Sperli et al., 2006) with precision rates comparable or even superior to standard diagnostic tools such as PET or SPECT (Michel et al., 2004a). Even though ESI still needs ultimate clinical validation through large prospective studies, the advantages of ESI compared to the traditional two dimensional clinical EEG is inarguable (Plummer et al., 2008). ESI can be performed with EEG or MEG recordings. Although the same neurophysiological processes generate the EEG and MEG signals, the recorded information is differing. While EEG has greater depth and greater orientation sensitivity than MEG, MEG is less susceptible to the conductivity variations of the head than the EEG (Wikswo et al., 1993; Malmivuo et al., 1997; Lopes da Silva, 2004; Lau et al., 2008). The fact that MEG is less influenced by irregularities of head geometry and less affected by intermediate tissue layers (scull, CSF) has been taken as argument that source localization with MEG in patients with volume relevant brain lesions is more trustworthy than with EEG (Williamson and Kaufman, 1987). Several simulation studies have addressed the question of how different conductivity properties influence the precision of EEG source localisation algorithms. It was noted that errors in dipole
1388-2457/$36.00 Ó 2009 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.clinph.2009.01.011
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localization are larger in liquid as compared to solid lesions (Vatta et al., 2002) and larger if the source is in the peripheral brain tissue as compared to the centre of the head (Awada et al., 1998). These simulation studies were based on rather simple source and head models, and it was concluded that incorporation of correct tissue conductivities in the head models is needed for accurate source localization. However, another simulation study by Haueisen et al. (1997), using finite element volume conductor models and variable resistivity for 13 different tissue types concluded that knowledge of conductivities might only be necessary for modelling the field strength, but not for source localization. Others found negligible localization errors in few millimeter range for intracerebral cavities but large errors for skull defects (Benar and Gotman, 2002). While simulation studies have their undoubted value for systematic evaluation and quantification of the influence of conductivity changes in a model case, they cannot answer whether in case of real patients’ data with altered brain anatomy, accuracy of ESI is still in an acceptable range. This is of particular importance for the use of EEG ESI in epilepsy, as many of the patients that are addressed to presurgical evaluation suffer from lesional epilepsy. In the present study, we were interested to see if electrical source localization in patients with large brain lesions was too imprecise to be of use for clinical purposes. We selected 14 patients who had sufficiently extensive lesions to lead to conductivity inhomogeneity within the skull. We recorded high resolution EEG (128–256 channels) and used distributed source models with a standard three-shell head model but constrained to the individual grey matter of each patient. The precision of the focus localization was evaluated with respect to the surgical resection and surgical outcome. 2. Methods 2.1. Patients We searched our database for patients that had been addressed to our department for surgical work-up going back to the year 2000, matching the following inclusion criteria: (1) Examined with high density EEG (either 128 or 256 electrodes). (2) High frequency of spikes in the wake EEG (sufficiently enough epileptic discharges during 20–30 min EEG recording to perform the ESI analysis). (3) Large cerebral lesion identified in clinical MRI. (4) Underwent surgery. Thirteen patients matching these criteria were identified. Postoperatively, 12 patients were seizure-free (Engel class I) and one had a less favourable outcome (patient #3; Engel class III). One patient was added who was not operated but in whom several exams identified the same area as epileptogenic zone (patient #14). The clinical characteristics of all 14 patients are summarized in Table 1. Their age at examination ranged from 5 to 54 years (mean 15.9, median 11.5), the age at epilepsy onset ranged from 0 to 31 years (mean 6.6 years, median 3). Eight patients were female. Aetiologies of the brain lesion were variable. In four cases the lesion was due to a perinatal stroke. The subsequent aetiologies were present in one case each: congenital polymicrogyra, tuberous sclerosis, head trauma, residuum after postpartal meningitis, arterio-venous malformation, status after ruptured aneurysm and a gangliogliome with a large cystic lesion. Two patients had arachnoid cysts, in one of the two combined with schizencephaly. The location of the principal interictal epileptic activity was within or close to the lesion in all patients. Fig. 1 shows the patients’ preoperative MRI. The level of the slice is chosen so that the individual
lesion is best visible. In two patients (#3 and 13), invasive recording was performed prior to surgery. The locations of the intracranial electrodes and the ictal and interictal findings are given in Table 1. 2.2. High density EEG recordings High density EEG recording was performed in all patients, using 128 or 256 channel nets with interconnected electrodes (Electrical Geodesic, Inc., Eugene, OR, USA). The nets are soaked in saline water before they are put on the patient’s head. The electrodes are interconnected by thin rubber bands and each contains a small sponge that touches the patient’s head directly. The net was adjusted so that the electrodes over the Nasion, the Inion, the pre-auricular points, and Cz were correctly placed according to the international 10/10 system. The geodesic tension structure of the net assured that the remaining electrodes were then evenly distributed across the head and at approximately the same location across subjects. The whole net is applied at once and needs no skin abrasion. It has been demonstrated that with saline measures electrode bridging is negligible after around 10 min (Greischar et al., 2004). Nevertheless, we verified absence of electrolyte bridges using the methods described by Greischar et al. that are implemented in the recording software NetStation. Because of the high amplifier input impedance (200 MX) sensor impedance was required to be below 50 kX (Ferree et al., 2001). In reality, impedances below 20 kX were achieved easily. The net application and verification of good electrode-head contacts lasted 10 min or less. The patient was set up in a comfortable chair in a dimly lit room. The EEG was recorded continuously for at least 30 min, partly with eyes open and eyes closed leading to a total examination period of maximally 1 h (Michel et al. (2004a) for details of the protocol). The sampling rate was set to 500 Hz, filters were set to 0.1–100 Hz. The EEG was recorded against a vertex reference. 2.3. Data analysis 2.3.1. Spike selection and averaging The off-line analysis started with the visual selection of interictal spikes with artefact free surround EEG of ±500 ms. The spike was marked at the exact time point where it reached maximal negativity on the electrode trace where it showed highest amplitude and chosen when showing similar voltage map distribution. Within the single spike epochs, electrodes containing artefacts were interpolated using a three dimensional spline interpolation algorithm (Perrin et al., 1989) to keep the number of electrodes the same for all epochs. The average numbers of interpolated electrodes are given in Table 1. Cheek and neck electrodes were excluded leading to 204 and 111 electrodes. Spikes were then aligned to the Global Field Power Peak and averaged over epochs of ±500 ms around this peak. 2.4. EEG source imaging For the localization of the electrical activity in the brain we used the LAURA (local autoregressive average) algorithm, a distributed linear inverse solution comprising biophysical laws as constraints (Grave de Peralta Menendez et al., 2001, 2004) (see Michel et al. (2004b) for review). The solution space was restricted to the grey matter of the individual patient’s brain using a homemade semi-automatic segmentation tool. The lesions were thus excluded from the solution space. For the lead field calculation the SMAC method was applied (Spinelli et al., 2000; Phillips et al., 2005). This method first transforms the individual MRI to the best fitting sphere using homogeneous transformation opera-
Table 1 Clinical characteristics of all patients. The outcome after surgery is classified according to Engel’s Classification. Invasive recordings were performed in patients #3 and 13. The electrode types (grid, strip or depth electrodes), covered regions and the location of interictal activity and the number and regions of onset of ictal events are given. The last two columns contain the number of spikes averaged, the signal to noise ratio (maximal global field power divided by the average global field power of the 1 s spike epoch), the total number of electrodes and the average number of interpolated electrodes. (Abbreviations: d = day, m = month, w = week, R = right, L = left, F = frontal, T = temporal, P = parietal, O = occipital, lat = lateral, bas = basal, orb = orbital, HR = high resolution, N = number.) Patient No.
Sex
Age (years) Phase I
Age of onset (years)
Seizures frequency
MRI
Ictal onset in clinical EEG
Invasive recordings
Interictal focus in HR-EEG
OP Resected zone
Out come
Number of spikes/ signal to noise ratio
HREEG
Congenital left hemispheric lesion of unknown origin Perinatal left hemispheric stroke
0–6/d
TPO L lesion with polymicrogyria O and parasag Cortex and periventricular gliosis L hemispheric atrophy Pachygyrie and Microgyria of L hemisphere, predominant P L + dysplastic insula and paarasagittal cortex, slight hippocampus atrophy Haemorrhage T R Porencephalie and periventricular gliosis,
TPO L
–
PO L
Lesionectomie PO L
1
62/2.95
204
Slowing Hemisphere R
–
TL
Periinsular Hemispherotomie L
1
30/3.98
109
PT R
Grid PT R depth T bilat, F orb R interictal: TPJ R ictal: 4/7 TPJ, 3/7 undefined –
PR
T R Resection
3
25/2.47
204
FL
Polectomie FT L
1
26/4.67
204
1
F
9
6
2
M
9
2
3
M
11
8
Postnatal Strep B Sepsis with right temp. haemorrhage
0–7/d
4
M
54
31
3–5/m
Posthaemorhagic lesion F >T L
FL
5
F
34
15
10/m
Posttraumatic lesion with perilesional leucoencephalopathy F L>R, T R T L
Bilateral predominantly paramedian F R
–
FC
Lobectomie F R
1
45/3.90
204
6
F
26
17
8/d–1/w
–
FR
45/3.30
111
6
OL
–
OL
Lobectomie Anterior T R + AmygdaloHippocampectomie R Partial lobectomie PO L
1
F
Arterio-venous malformation T R, first OP 1997 thereafter haematome T R, cortico subcortical atrophy T R Large cystic lesion O L
TR
7
1
23/2.67
111
8
F
15
4
Rupture of aneurisma a. communicans anterior Head trauma with subdural haematome right hemisphere mainly bi-F and T right Arterio-venous malformation T Right Ganliogliome TPO Left Lesion F right of unknown origin
Large multicystic lesion F R
.
FR
Lesionectomie F R
1
22/2.73
111
9
F
5
0
Perinatal stroke left hemisphere
2–8/d
Porencephalic cyst T post-L, Hippocampus atrophy L
–
Continuous T L, TP L TO L
Disconnection TPO L
1
28/3.09
111
10
M
6
3
Perinatal stroke left hemisphere
4–5/d
–
Continuous mainly F R
Hemispherectomie L
1
29/3.24
111
11
M
8
3
>10/week
FL
Hemispherectomie L
1
18/3.94
111
F
13
1
0–5/d
No seizures registered FC L
–
12
–
FL
Resection of Dysplasia F L
1
31/4.58
204
13
F
15
0
Perinatal stroke of left a. cerebri media Dysplasia F left of unknown origin Tuberous Sclerosis Bourneville
Voluminous ischaemic lesion sylvian territory L Hemiatrophy L Hemisphere orbito-F and T Severe atrophy of hemiphere L, large infarcted area in ACM teritoy Dysplasia F C L
Generalised spikes F R predominance Variable, mainly background flattening PL
>5/d
Tuber TP L (largest of many)
Posterior L
TO L
Tuberectomie + Corticotomie TP L
1
38/3.33
204
14
M
12
3
0.3–3/ month
Large cyst, schizencephaly FT R
TR
Grid TP L, strips L: F, T lat + bas, O interictal TP L ictal: 14/15 TP L –
TP R
–
–
37/3.21
204
0.5
Nocturnal/ sublicinical 5–8/d
681
Congenital arachnoid cyst, schizencephaly FT right
30–40/d
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Origin of symptomatic focal epilepsy
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Fig. 1. Anatomical pre-OP-MRI of lesions. The slices shown here are the preoperative MRI of all 14 patients. The level of the slices are indicated by red bars on the sagital view and chosen so that the individual lesion is best visible. Lesions of patients #2, 9, 10 and 11 are caused by perinatal stroke. Patients #8 and 14 have arachnoid cysts, in patient #14 combined with a schizencephaly. Patient #1 has a congenital polymicrogyria, #3 a residuum after postpartal meningitis, #4 had a ruptured aneurysm, #5 has a posttraumatic lesion, #6 a arterio-venous malformation, #7 a cystic lesion after resection of a gangliogliome, #12 a congenital dysplasia and #13 a tuberous sclerosis. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this paper.)
tors. It then determines a regular grid of around 4000 solution points in the grey matter of this spherical MRI and computes the lead field matrix using the known analytical solution for a spherical head model with three shells of different conductivities as defined by Ary et al. (1981). Possible differences in the conductivities due to the large lesions were thus not considered in the model. The two same electrode positions (128/256) were used for all subjects as derived from the mean of positions measured in 20 healthy subjects with a three dimensional digitizer and projected to a best fitting sphere. The co-registration between the spherical MRI and the spherical electrode positions was achieved by marking the landmarks (Nasion, Inion), pre-auricular points and Cz on the individual 3D MRI and matching them with the corresponding electrode positions. 2.5. Defining the accuracy of ESI focus localization The average map of the spikes was analysed and the time point of 50% rising phase (50% global field power peak) was subjected to the source localization procedure. It has been demonstrated that the ESI of the rising phase of the average spike represents most reliable the actual source of the epileptic activity (Scherg et al., 1999; Lantz et al., 2003; Lau et al., 2008). In all patients who were seizure free after surgery, the focus localization was stated to be correct when it fell within the resected area. For seven of the 12 operated patients a post-OP MRI was available. In six patients the quality of the post-OP MRI was sufficient to superimpose the MRI, the resected area and the ESI identified focus (Fig. 2). One patient’s (#5) post-OP MRI was of bad quality due to movement artefacts and not unequivocally usable for comparison with the pre-OP MRI. We renounced on a post-operative MRI in patients who underwent a hemispherotomy (#2, 10, 11) and/or were seizure-free and too young to undergo a post-op MRI procedure without sedation (#9). For the non-operated patient #14, we coregistered the spike triggered fMRI with the spike ESI results.
3. Results In average 27 spikes were selected in each subject. The mean signal to noise ratio was 3.4. The exact values for each patient are given in Table 1. Fig. 1 displays the anatomical MRI of all patients, with the level of the slice chosen to show best the extension of the individual patient’s lesion. Fig. 3 shows the slices with the maximal ESI activity. For those patients in whom the postoperative MRI was available we demonstrate a superimposed display of the resected area (red) and the ESI result (blue) as 3D volumes (Fig. 2). The identified maximum source of the epileptic activity fell within the epileptogenic zone in all but 2 of the 13 operated patients. In patients #2, 10 and 11 a hemispherotomy was carried out. Given that in all cases the focus lied in the affected hemisphere, the correctness of the solution is assumed. Since these patients are usually not candidates for intracranial EEG monitoring or extensive preoperative corticography, no further verification was obtained. However, in all 3 patients, PET results suggested predominantly frontal dysfunctions and thus corroborate the ESI findings in these patients (Figs. 2 and 3). In the remaining 9 operated patients with outcome class I (#1, 4, 5, 6, 7, 8, 9, 12, 13), in all except one patient (#5) the source of the focus was found in the resection brain area. In patient #5, the work-up indicated a right mesial frontal focus, whereas ESI located the principal focus in the right insula-temporal cortex (Fig. 3). Resection of the right frontal tissue resulted in seizure freedom; however, post-operatively the patient suffered from several complications (bleeding, hydrocephalus). In patient #3 seizures persisted, albeit with reduced frequency, despite resection of most of the presumed epileptogenic zone. However, ESI suggests an incomplete resection, because the focus was only partially removed, i.e. situated more anterior, overlying the somato-motor cortex.
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Fig. 2. Resection zone and superimposed ESI results of all patients. The resected areas are displayed in red within the post-OP MRI in patients #1, 2, 3, 7, 12 and 13 and manually indicated and approximated within the pre-OP MRI according to surgery reports for patients #4, 5, 6, 8, 9, 10 and 11. The ESI result is displayed in blue. For patient #3 we added a 3D display of the subdural grid position (electrodes as blue circles) in which the electrodes of seizure onset are highlighted in yellow. Patient #14 is the one non-operated case in which we show the focus localization according to spike triggered fMRI (green) and the high resolution EEG recording (in blue).
Patient #14 was not operated given that seizures disappeared with improved drug treatment and because there was a major neurosurgical risk associated to an intervention. He underwent EEGtriggered fMRI, PET and SPECT imaging. All 3 modalities were concordant with respect to the focus localization as determined by ESI, i.e. in the inferior and posterior aspect of a highly dysplastic insula. It can reasonably be assumed that the source solution is correct despite absence of a post-operative MRI. 4. Discussion Our results suggest that ESI based on high density EEG is able to identify the epileptogenic focus with excellent accuracy in most patients despite volume relevant brain lesions that most likely
changed conductivity properties within the skull. In 12 of 14 patients (85%) ESI was correct, a yield that is comparable to similar studies in patients without significant brain malformations (Michel et al., 2004a; Sperli et al., 2006). In the 2 cases with incorrect localization, the accuracy – or inaccuracy – of ESI is difficult to determine: the remaining seizures after incomplete resection of the focus in patient #3, as determined by ESI, may speak in favour for the superiority of ESI over the intracranial data. In contrast to the other patients, a large portion of the active area as identified with ESI was outside the lesion in the surrounding tissue. However, due to its vicinity to vital sensory-motor cortex and because of the intracranial EEG, which suggested more posterior and caudal onset (yellow circles in Fig. 2), the resection zone was not extended. In this patient, ESI also proposed an addi-
Fig. 3. Anatomical pre-OP MRI with ESI maximum. In each patients MRI the maximum of the estimated source of the average interictal spike (LAURA) is indicated in red. Note that the level of maximal source activity does not necessarily correspond to the level of maximal extent of the lesion shown in Fig. 1.
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tional independent source in the temporal lobe remote from the resected area. Careful inspection of the temporal dynamics indicated that this temporal source dominated at the beginning of the spike and that the parietal source was activated later during the rising phase of the spike. This observation suggests the onset of the epileptogenic activity in the temporal lobe followed by fast propagation to the parietal lobe. However, the intracranial recordings with electrodes covering both brain regions (Fig. 2) did not speak in favour of such a sequential activation, albeit not all regions of the lateral aspect of the temporal lobe were covered. This case also raises the question of the correspondence of ictal and interical activity and the detection of fast propagation. A recent study with simultaneous intracranial and scalp EEG indicated that source analysis of scalp spikes at their initial rising phase, as done in this study, might provide more focal localizing information than the analysis of seizure origin or spike peaks because of fast propagation of the epileptic activity (Ray et al., 2007). In patient #5, ESI localized incorrectly to the insula temporal cortex, because resection of right mesial frontal cortical tissue led to seizure freedom. However, the post-operative complications, in particular bleeding into the right frontal cavity, might also have lesioned the insula-temporal cortex and that this additional lesion has led to seizure freedom. Our study evaluated the influence of conductivity changes due to large lesions in the real case, if these changes are not specifically considered in the source localization procedure. We used standard conductivity values for the three compartments of the head (brain, CSF, skull) without taking into account the possible changes induced by the lesions. However, we restricted the source space to the remaining grey matter of the individual brain of the patient, excluding potential sources within the lesion. We also took advantage of recent hard- and software developments by using high-resolution EEG recordings (128–256 channels) and distributed inverse solutions that do not a priori assume a limited amount of sources. Our results indicate that the influence of conductivity variations due to large brain lesions is negligible with respect to the capability of high-resolution ESI to accurately localize epileptic foci. From a theoretical point of view, EEG-based source imaging should be of limited use in large brain lesions, because the EEG is affected by the changes in conductivity properties induced by such lesions. Simulation studies partly supported this assumption: Vatta and colleagues (Vatta et al., 2002) evaluated 64 different simulated pathology situations and showed highest errors in dipole estimations for liquid filled lesions, whereas solid, calcified lesions show negligible sensitivity to uncertainties in conductivity assignment. Localization errors were also tolerable (smaller than 0.5 cm) when source and lesions were far apart from each other. The authors propose correction procedures to identify and incorporate lesion-induced conductivity changes in the source localization estimation. Awada et al. (1998) examined errors in dipole source localization when wrong conductivity values for different brain tissues were assumed, and conclude that the localization error generally increases as the dipole moves away from the centre of the head toward the boundary. However, their simulations were restricted to two-dimensional, transaxial cross-sections of the head. The authors themselves state that the estimation errors are likely to be less extensive for 3D calculations. The simulation study by Haueisen and Ramon on the influence of tissue resistivity changes on the neuromagnetic field and the electric scalp potential (Haueisen et al., 1997) showed that both, EEG and MEG signal are affected by changes of the resistivity of the tissue that surrounds the source (grey matter), but that only the EEG signal is influenced by changes close to the electrodes as well. However, it is the magnitude (strength) of the magnetic field and the electric scalp potential that is affected rather than their topography. Our results corroborate this hypothesis and the results of Benar and Gotman (2002) that
indicate that the accuracy of source localization procedures is affected only to a negligible extent by brain tissue changes. Advances in computer power make it now possible to use boundary element head models (BEM) to precisely model the shape of the different isotropic homogeneous head compartments in the individual brain (Fuchs et al., 2002). We did not use such advanced headmodels in this study but relied on a simpler head model reconstruction based on spherical deformation of the individual grey matter. This fast SMAC method has successfully been used in different clinical and experimental studies (Michel et al., 2004a; Phillips et al., 2005; Sperli et al., 2006); for review see Michel et al. (2004b). The results presented here demonstrate that it leads to adequate localization of epileptic foci in the individual brain. Nevertheless, since the individual gray matter is needed for the source space constraints segmentation of the individual cortex in the SMAC method, the application of BEM models would be straightforward in cases where greater spatial resolution is required. A final point concerns the number of electrodes for adequate source imaging in epilepsy. In this study high resolution EEG was used in all patients (128–256 channels). In a previous study (Sperli et al., 2006)we showed that even with standard clinical EEG systems of around 30 electrodes, correct localization on a lobar level is achieved in over 90% of the cases, including some with large brain lesions. However, for sublobar precision, higher numbers of electrodes are needed, as shown in Sperli et al. (2006) as well as by Lantz et al. (2003). In this latter study data originally recorded from 123 electrodes were downsampled to 63 and 31 electrodes. It was shown that localization precision with respect to distance of the source maximum to the resected area increased in average from 6 to 22 mm when sampling with 123 and 31 electrodes, respectively. 5. Conclusions Our retrospective study shows excellent accuracy of electrical source localization in patients with large brain lesions, comparable to the accuracy obtained in non-lesional epilepsy patients and to other non-invasive localization methods (Lantz et al., 1999; Michel et al., 2004a; Zumsteg et al., 2006) (for review see Plummer et al. (2008)). Even though a prospective study with a larger number of patients would be necessary to doubtless verify our results, our finding is of important clinical relevance as it increases the confidence in source localization procedures and extends their application to surgical candidate patients with lesioned brains. Acknowledgments The data were analyzed with the Cartool software (http://brainmapping.unige.ch/Cartool.php) which is developed by Denis Brunet, from the Functional Brain Mapping Laboratory, Geneva, supported by the Center for Biomedical Imaging (CIBM), Geneva and Lausanne, Switzerland. The work was also supported by the Swiss National Science by the Grant No. 3200-113766 to M.S. and No. 3200-111783 to C.M. References Ary JP, Klein SA, Fender DH. Location of sources of evoked scalp potentials: corrections for skull and scalp thicknesses. IEEE Trans Biomed Eng 1981;28(6):447–52. Awada KA, Jackson DR, Baumann SB, Williams JT, Wilton DR, Fink PW, et al. Effect of conductivity uncertainties and modeling errors on EEG source localization using a 2-D model. IEEE Trans Biomed Eng 1998;45(9):1135–45.
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