Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy

Distributed inverse solutions aim to realistically reconstruct the origin of interictal epileptic discharges (IEDs) from noninvasively recorded electroencephalography (EEG) and magnetoencephalography (MEG) signals. Our aim was to compare the performance of different distributed inverse solutions in localizing IEDs: coherent maximum entropy on the mean (cMEM), hierarchical Bayesian implementations of independent identically distributed sources (IID, minimum norm prior) and spatially coherent sources (COH, spatial smoothness prior). Source maxima (i.e., the vertex with the maximum source amplitude) of IEDs in 14 EEG and 19 MEG studies from 15 patients with focal epilepsy were analyzed. We visually compared their concordance with intracranial EEG (iEEG) based on 17 cortical regions of interest and their spatial dispersion around source maxima. Magnetic source imaging (MSI) maxima from cMEM were most often confirmed by iEEG (cMEM: 14/19, COH: 9/19, IID: 8/19 studies). COH electric source imaging (ESI) maxima co-localized best with iEEG (cMEM: 8/14, COH: 11/14, IID: 10/14 studies). In addition, cMEM was less spatially spread than COH and IID for ESI and MSI (p < 0.001 Bonferroni-corrected post hoc t test). Highest positive predictive values for cortical regions with IEDs in iEEG could be obtained with cMEM for MSI and with COH for ESI. Additional realistic EEG/MEG simulations confirmed our findings. Accurate spatially extended sources, as found in cMEM (ESI and MSI) and COH (ESI) are desirable for source imaging of IEDs because this might influence surgical decision. Our simulations suggest that COH and IID overestimate the spatial extent of the generators compared to cMEM.

[1]  Christophe Grova,et al.  Wavelet-Based Localization of Oscillatory Sources From Magnetoencephalography Data , 2014, IEEE Transactions on Biomedical Engineering.

[2]  Douglas Cheyne,et al.  EEG source imaging of anterior temporal lobe spikes: Validity and reliability , 2014, Clinical Neurophysiology.

[3]  C. Michel,et al.  Electric source imaging of interictal activity accurately localises the seizure onset zone , 2013, Journal of Neurology, Neurosurgery & Psychiatry.

[4]  J. Ebersole,et al.  Intracranial EEG Substrates of Scalp EEG Interictal Spikes , 2005, Epilepsia.

[5]  Hiroshi Shibasaki,et al.  Simultaneous Recording of Epileptiform Discharges by MEG and Subdural Electrodes in Temporal Lobe Epilepsy , 1997, NeuroImage.

[6]  Laurent Albera,et al.  Localization of extended brain sources from EEG/MEG: The ExSo-MUSIC approach , 2011, NeuroImage.

[7]  M. Scherg,et al.  EEG and MEG Source Analysis of Single and Averaged Interictal Spikes Reveals Intrinsic Epileptogenicity in Focal Cortical Dysplasia , 2004, Epilepsia.

[8]  B. He,et al.  Effect of EEG electrode number on epileptic source localization in pediatric patients , 2015, Clinical Neurophysiology.

[9]  Fetsje Bijma,et al.  In vivo measurement of the brain and skull resistivities using an EIT-based method and realistic models for the head , 2003, IEEE Transactions on Biomedical Engineering.

[10]  Cécile Amblard,et al.  Biomagnetic source detection by maximum entropy and graphical models , 2004, IEEE Transactions on Biomedical Engineering.

[11]  Christophe Grova,et al.  MEG Source Localization of Spatially Extended Generators of Epileptic Activity: Comparing Entropic and Hierarchical Bayesian Approaches , 2013, PloS one.

[12]  Bin He,et al.  Dynamic imaging of seizure activity in pediatric epilepsy patients , 2012, Clinical Neurophysiology.

[13]  L. Vaina,et al.  Mapping the signal‐to‐noise‐ratios of cortical sources in magnetoencephalography and electroencephalography , 2009, Human brain mapping.

[14]  Jean Gotman,et al.  Spatial correlation of hemodynamic changes related to interictal epileptic discharges with electric and magnetic source imaging , 2014, Human brain mapping.

[15]  F Wendling,et al.  EEG extended source localization: Tensor-based vs. conventional methods , 2014, NeuroImage.

[16]  Théodore Papadopoulo,et al.  OpenMEEG: opensource software for quasistatic bioelectromagnetics , 2010, Biomedical engineering online.

[17]  Al Bartolucci,et al.  Functional imaging: II. Prediction of epilepsy surgery outcome , 2008, Annals of neurology.

[18]  Jean Gotman,et al.  Size of cortical generators of epileptic interictal events and visibility on scalp EEG , 2014, NeuroImage.

[19]  Isabelle Bloch,et al.  From 3D magnetic resonance images to structural representations of the cortex topography using topology preserving deformations , 1995, Journal of Mathematical Imaging and Vision.

[20]  J. Gotman,et al.  Dipole Modeling of Epileptic Spikes Can Be Accurate or Misleading , 2005, Epilepsia.

[21]  H. Hallez,et al.  Influence of skull conductivity perturbations on EEG dipole source analysis. , 2010, Medical physics.

[22]  Gareth R. Barnes,et al.  Practical constraints on estimation of source extent with MEG beamformers , 2011, NeuroImage.

[23]  M. Hämäläinen Magnetoencephalography: A tool for functional brain imaging , 2005, Brain Topography.

[24]  Karl J. Friston,et al.  Multiple sparse priors for the M/EEG inverse problem , 2008, NeuroImage.

[25]  Lei Ding,et al.  Sparse MEG Source Imaging For Reconstructing Dynamic Sources of Interictal Spikes in Partial Epilepsy , 2013, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[26]  Lei Ding,et al.  Reconstructing spatially extended brain sources via enforcing multiple transform sparseness , 2014, NeuroImage.

[27]  A. Genow,et al.  Epilepsy surgery, resection volume and MSI localization in lesional frontal lobe epilepsy , 2004, NeuroImage.

[28]  J. Gotman,et al.  Scalp EEG is not a Blur: It Can See High Frequency Oscillations Although Their Generators are Small , 2013, Brain Topography.

[29]  Wolters Carsten Sensitivity of beamformer source analysis to deficiencies in forward modeling , 2010 .

[30]  Jérémie Mattout,et al.  Data-driven parceling and entropic inference in MEG , 2006, NeuroImage.

[31]  Douglas Cheyne,et al.  Reliability of MEG source imaging of anterior temporal spikes: Analysis of an intracranially characterized spike focus , 2014, Clinical Neurophysiology.

[32]  Bin He,et al.  Dynamic imaging of ictal oscillations using non-invasive high-resolution EEG , 2011, NeuroImage.

[33]  W W Sutherling,et al.  Influence of magnetic source imaging for planning intracranial EEG in epilepsy , 2008, Neurology.

[34]  Claudio Pollo,et al.  Electroencephalographic source imaging: a prospective study of 152 operated epileptic patients , 2011, Brain : a journal of neurology.

[35]  D. Lehmann,et al.  Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain. , 1994, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[36]  Richard M. Leahy,et al.  Brainstorm: A User-Friendly Application for MEG/EEG Analysis , 2011, Comput. Intell. Neurosci..

[37]  François Mauguière,et al.  The value of magnetoencephalography for seizure-onset zone localization in magnetic resonance imaging-negative partial epilepsy , 2013, Brain : a journal of neurology.

[38]  Frans S.S. Leijten,et al.  Inverse modeling in magnetic source imaging: Comparison of MUSIC, SAM(g2), and sLORETA to interictal intracranial EEG , 2013, Human brain mapping.

[39]  Jérémie Mattout,et al.  Multivariate source prelocalization (MSP): Use of functionally informed basis functions for better conditioning the MEG inverse problem , 2005, NeuroImage.

[40]  Georgia Ramantani,et al.  Electrical source imaging in cortical malformation–related epilepsy: A prospective EEG‐SEEG concordance study , 2014, Epilepsia.

[41]  H. Lüders,et al.  Detection of Epileptiform Activity by Human Interpreters: Blinded Comparison between Electroencephalography and Magnetoencephalography , 2005, Epilepsia.

[42]  J Gotman,et al.  Interictal Scalp Fast Oscillations as a Marker of the Seizure Onset Zone , 2012, Neurology.

[43]  Richard M. Leahy,et al.  Electromagnetic brain mapping , 2001, IEEE Signal Process. Mag..

[44]  Adam N Mamelak,et al.  Magnetoencephalography-directed surgery in patients with neocortical epilepsy. , 2002, Journal of neurosurgery.

[45]  Evelien Carrette,et al.  Clinical added value of magnetic source imaging in the presurgical evaluation of refractory focal epilepsy , 2012, Journal of Neurology, Neurosurgery & Psychiatry.

[46]  Hiroshi Masuda,et al.  Epileptic Spikes: Magnetoencephalography versus Simultaneous Electrocorticography , 2002, Epilepsia.

[47]  Jean Gotman,et al.  Extent of cortical generators visible on the scalp: Effect of a subdural grid , 2014, NeuroImage.

[48]  R. Ilmoniemi,et al.  Interpreting magnetic fields of the brain: minimum norm estimates , 2006, Medical and Biological Engineering and Computing.

[49]  Jean Gotman,et al.  Evaluation of EEG localization methods using realistic simulations of interictal spikes , 2006, NeuroImage.

[50]  M. S. Hämäläinen,et al.  Quantification of the benefit from integrating MEG and EEG data in minimum ℓ2-norm estimation , 2008, NeuroImage.

[51]  Karl J. Friston,et al.  Classical and Bayesian Inference in Neuroimaging: Theory , 2002, NeuroImage.

[52]  Florian Willomitzer,et al.  Consequences of EEG electrode position error on ultimate beamformer source reconstruction performance , 2014, Front. Neurosci..

[53]  Bin He,et al.  Interictal spike analysis of high-density EEG in patients with partial epilepsy , 2011, Clinical Neurophysiology.

[54]  Christoph M. Michel,et al.  Epileptic source localization with high density EEG: how many electrodes are needed? , 2003, Clinical Neurophysiology.