Reconstruction of epilepsy-characteristic sources by means of a simultaneous evaluation of EEG- and MEG- data using calibrated realistic head models
Human Cognitive and Systems Neuroscience
Medical Physics, Biomedical Technology
Final Report Abstract
Our project had the main goal to contribute to presurgical epilepsy diagnosis by means of developing, validating and evaluating new methodologies for the reconstruction of epilepsycharacteristic sources from combined Electroencephalography- (EEG-) and Magnetoencephalography- (MEG-) data in a group of patients with refractory focal epilepsy due to focal cortical dysplasia (FCD) of type IIb. The recruitment of patients was done in collaboration with the Epilepsy Centers Münster-Osnabrück and Bochum. Data acquisition, also somatosensory and auditory evoked potentials and fields (SEP/SEF, AEP/AEF) of a group of healthy subjects for evaluation of the new methodologies, was carried out at the Institute for Biomagnetism and Biosignalanalysis (IBB) at the University Hospital Münster. To solve the forward problems of EEG and MEG accurately, we developed a new discontinuous Galerkin- (DG-) finite element method (FEM) approach and showed that it can alleviate so-called “skull leakage” effects. We also developed better FEM source models as well as unfitted DG (UDG-) FEM, which does not require the generation of volumetric meshes but relies on an implicit description of the tissue layers via level-sets. An automatic pipeline was developed to calibrate head models with respect to skull conductivity enabling a combined source analysis of EEG and MEG. In a group study on healthy subjects, we found a considerable inter-subject variability for (calibrated) skull conductivity and skull thickness with a statistically significant correlation between them and a significant negative correlation of skull conductivity with age. The new forward methods were implemented into the free and open-source C++ software DUNEuro, which was also integrated into the large neuroscientific open source toolboxes BrainStorm and FieldTrip, so that together with the open DUNEuro test data, the new methods and data are available to the broad open source neuroscience community. For the inverse problems of EEG and MEG source analysis, we developed new beamforming, conditionally Gaussian Hierarchical Bayesian modeling (CG-HBM) and Kalman-filtering methodologies and showed that these new methods can localize deeper sources, even in the presence of stronger more lateral sources. Additionally, we also investigated sub-average dipole scan centroid and spread sphere inverse approaches to estimate the extent of the irritative zone, with EEG contributing more to the radial and MEG to the tangential source aspects. We validated the new methods using computer simulations, evaluated by applications in group level analyses of SEP/SEF and AEP/AEF data and of FCD epilepsy data. In a large retrospective group study in 1000 patients we showed that MEG provides non-redundant information, which significantly contributes to patient selection, focus localization and ultimately long-term seizure freedom after epilepsy surgery and that specifically in extra-temporal lobe epilepsy and non-lesional cases, MEG provides excellent accuracy. We also showed that (i) combined EMEG source analysis can perform better than EEG or MEG alone, especially at lower SNRs, (ii) activity might be propagated at spike-peak, source analysis should thus be carried out at spike onset or at least half of the raising flank of the spike, (iii) the converging evidence from combined EMEG source analysis at the spike onset, seizure semiology, and structural/zoomed MRI gives converging evidence for the identification of the epileptogenic zone. Our EEG/MEG localizations were not always only found within the resection volumes. Since it is unclear what would have happened if the surgery had been performed in a different way, the resection volume should not be the only validation criterion for new methodology. Our epilepsy investigations in combination with our unique bioelectromagnetism methods and software developments enabled the successful ERA PerMed project PerEpi. So we will continue to measure and analyze EMEG and MRI epilepsy data, now in a larger European consortium.
Publications
- (2017), A Discontinuous Galerkin Method for the EEG Forward Problem, SIAM J. on Scientific Computing, 39 (1), B138–B164
Engwer, C., Vorwerk, J., Ludewig, J., Wolters, C.H.
(See online at https://doi.org/10.1137/15M1048392) - (2017), The effect of head model simplification on beamformer source localization, Frontiers in Neuroscience: Brain Imaging Methods, 11:625
Neugebauer, F., Möddel, G., Rampp, S., Burger, M. and Wolters, C.H.
(See online at https://doi.org/10.3389/fnins.2017.00625) - (2017), Zoomed MRI guided by combined EEG/MEG source analysis: A multimodal approach for optimizing presurgical epilepsy work-up and its application in a multi-focal epilepsy patient case study, Brain Topography, 30(4):417-433
Aydin, Ü., Rampp, S., Wollbrink, A., Kugel, H., Cho, J.-H., Knösche, T.R.,Grova, C., Wellmer, J. Wolters, C.H.
(See online at https://doi.org/10.1007/s10548-017-0568-9) - (2018), Coregistrating magnetic source and magnetic resonance imaging for epilepsy surgery in focal cortical dysplasia, NeuroImage: Clinical, 19:487-496, 2018
Kasper, B.S., Rössler, Hamer, Dörfler, Blümcke, Coras, Roesch, Mennecke, Wellmer, Sommer, Lorber, Lang, Graf, Stefan, Schwab, Buchfelder, Rampp S.
(See online at https://doi.org/10.1016/j.nicl.2018.04.034) - (2018), The Discontinuous Galerkin Finite Element Method for Solving the MEG and the combined MEG/EEG Forward Problem, Frontiers in Neuroscience: Brain Imaging Methods, 12:30
Piastra, M.C., Nüßing, A., Vorwerk, J., Bornfleth, H., Oostenveld, R., Engwer, C., Wolters, C.H.
(See online at https://doi.org/10.3389/fnins.2018.00030) - (2019), Individualized Targeting and Optimization of Multi-channel Transcranial Direct Current Stimulation in Drug-Resistant Epilepsy, IEEE BIBE, pp. 871-876
Antonakakis, M., Rampp, S., Kellinghaus, C., Wolters, C.H., Möddel, G.
(See online at https://doi.org/10.1109/BIBE.2019.00162) - (2019), Influence of head tissue conductivity uncertainties on EEG dipole reconstruction, Frontiers in Neuroscience : Section Neural Technology, 13:531 (2019)
Vorwerk, J., Aydin, Ü., Wolters, C.H., Butson, C.R.
(See online at https://doi.org/10.3389/fnins.2019.00531) - (2019), The effect of stimulation type, head modeling and combined EEG and MEG on the source reconstruction of the somatosensory P20/N20 component, Human Brain Mapping, 40(17):5011-5028
Antonakakis, M., Schrader, S., Wollbrink, A., Oostenveld, R., Rampp, S.,Haueisen, J., Wolters, C.H.
(See online at https://doi.org/10.1002/hbm.24754) - A realistic, accurate and fast source modeling approach for the EEG forward problem, NeuroImage, 184:56-67
Miinalainen, T., Rezaei, A., Us, D., Nüßing, A., Engwer, C., Wolters, C.H., Pursiainen, S.
(See online at https://doi.org/10.1016/j.neuroimage.2018.08.054) - Magnetoencephalography for epileptic focus localization in a series of 1000 cases. Brain. Oct 1;142(10):3059-3071
Rampp S, Stefan H, Wu X, Kaltenhäuser M, Maess B, Schmitt FC, Wolters CH, Hamer H, Kasper BS, Schwab S, Doerfler A, Blümcke I, Rössler K, Buchfelder M.
(See online at https://doi.org/10.1093/brain/awz231) - (2020), A novel method for calibrating head models to account for variability in conductivity and its evaluation in a sphere model, Phys Med Biol, 65(24), 245043
Schrader, S., Antonakakis, M., Rampp, S., Engwer, C., Wolters, C.H.
(See online at https://doi.org/10.1088/1361-6560/abc5aa) - (2020), Inter-Subject Variability of Skull Conductivity and Thickness in Calibrated Realistic Head Models, NeuroImage, 223:117353
Antonakakis, M., Schrader, S., Aydin, Ü., Khan, A., Gross, J., Zervakis, M.,Rampp, S., Wolters, C.H.
(See online at https://doi.org/10.1016/j.neuroimage.2020.117353) - (2020), Parametrizing the Conditionally Gaussian Prior Model for Source Localization with Reference to the P20/N20 Component of Median Nerve SEP/SEF, Brain Sciences, 10(12), 934
Rezaei, A., Antonakakis, M., Piastra, M.C., Wolters, C.H., Pursiainen, S.
(See online at https://doi.org/10.3390/brainsci10120934) - (2021), A Comprehensive Study on EEG and MEG Sensitivity to Cortical and Sub-cortical Sources, Human Brain Mapping, 42:978-992
Piastra, M.C., Nüßing, A., Vorwerk, J., Clerc, M., Engwer, C., Wolters, C.H.
(See online at https://doi.org/10.1002/hbm.25272) - (2021), DUNEuro - A software toolbox for forward modeling in bioelectromagnetism, PLoS ONE, 16(6):e0252431
Schrader, S., Westhoff, A., Piastra, M.C., Miinalainen, T., Pursiainen, S.,Vorwerk, J., Brinck, H., Wolters, C.H., Engwer, C.
(See online at https://doi.org/10.1371/journal.pone.0252431)
