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Seizure Onset Zone Localization from Ictal High-Density EEG in Refractory Focal Epilepsy

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Abstract

Epilepsy surgery is the most efficient treatment option for patients with refractory epilepsy. Before surgery, it is of utmost importance to accurately delineate the seizure onset zone (SOZ). Non-invasive EEG is the most used neuroimaging technique to diagnose epilepsy, but it is hard to localize the SOZ from EEG due to its low spatial resolution and because epilepsy is a network disease, with several brain regions becoming active during a seizure. In this work, we propose and validate an approach based on EEG source imaging (ESI) combined with functional connectivity analysis to overcome these problems. We considered both simulations and real data of patients. Ictal epochs of 204-channel EEG and subsets down to 32 channels were analyzed. ESI was done using realistic head models and LORETA was used as inverse technique. The connectivity pattern between the reconstructed sources was calculated, and the source with the highest number of outgoing connections was selected as SOZ. We compared this algorithm with a more straightforward approach, i.e. selecting the source with the highest power after ESI as the SOZ. We found that functional connectivity analysis estimated the SOZ consistently closer to the simulated EZ/RZ than localization based on maximal power. Performance, however, decreased when 128 electrodes or less were used, especially in the realistic data. The results show the added value of functional connectivity analysis for SOZ localization, when the EEG is obtained with a high-density setup. Next to this, the method can potentially be used as objective tool in clinical settings.

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Acknowledgements

The research was funded by a Ph.D. grant of the Institute for the Promotion of Innovation through Science and Technology in Flanders (IWT). We acknowledge the support of the Swiss National Science Foundation, Grant No. 33CM30-140332 (G. Birot, M. Seeck), 141165 (S. Vulliémoz) and the Foundation Gertrude von Meissner (S. Vulliémoz). This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant No. 660230 (P. van Mierlo).

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Authors and Affiliations

  1. MEDISIP, Department of Electronics and Information Systems, Ghent University, De Pintelaan 185, Building B Entrance 36, 9000, Ghent, Belgium

    Willeke Staljanssens, Gregor Strobbe, Roel Van Holen, Stefaan Vandenberghe & Pieter van Mierlo

  2. iMinds Medical IT, Ghent, Belgium

    Willeke Staljanssens, Gregor Strobbe, Roel Van Holen, Stefaan Vandenberghe & Pieter van Mierlo

  3. Functional Brain Mapping Laboratory, Department of Fundamental Neurosciences, University of Geneva, Campus Biotech, Geneva, Switzerland

    Gwénaël Birot, Markus Gschwind, Serge Vulliémoz & Pieter van Mierlo

  4. EEG and Epilepsy Unit, Neurology Department, University Hospitals and Faculty of Medicine of Geneva, Geneva, Switzerland

    Markus Gschwind, Margitta Seeck & Serge Vulliémoz

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  1. Willeke Staljanssens
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  2. Gregor Strobbe
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  3. Roel Van Holen
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  4. Gwénaël Birot
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  5. Markus Gschwind
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  6. Margitta Seeck
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  7. Stefaan Vandenberghe
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  8. Serge Vulliémoz
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  9. Pieter van Mierlo
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Correspondence to Willeke Staljanssens.

Appendix: Model Orders

Appendix: Model Orders

See Table 3.

Table 3 Overview of the used model order found with the Aikake Information Criterion for every patient and every setup
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Staljanssens, W., Strobbe, G., Holen, R.V. et al. Seizure Onset Zone Localization from Ictal High-Density EEG in Refractory Focal Epilepsy. Brain Topogr 30, 257–271 (2017). https://doi.org/10.1007/s10548-016-0537-8

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  • DOI: https://doi.org/10.1007/s10548-016-0537-8

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