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Electrical source imaging and connectivity analysis to localize the seizure-onset zone based on high-density ictal scalp EEG recordings

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Abstract
Functional connectivity analysis of ictal intracranial EEG (icEEG) recordings can help with seizure-onset zone (SOZ) localization in patients with focal epilepsy1. However, it would be of high clinical value to be able to localize the SOZ based on non-invasive ictal EEG recordings to better target or avoid icEEG and improve surgical outcome. In this work, we propose an approach to localize the SOZ based on non-invasive ictal high- density EEG (hd-EEG) recordings. We considered retrospective ictal hd-EEG recordings of two patients who were rendered seizure free after surgery. Furthermore, we simulated 1000 ictal hd-EEG epochs of 10s with an underlying network consisting of 3 randomly placed epileptic patches in the brain. EEG source imaging (ESI) was performed in CARTOOL using an individual head model (LSMAC) to calculate the forward model2. We considered dipoles uniformly distributed in the brain with a spacing of 5mm. LORETA3 was used as inverse solution method. Center dipoles of clusters with high activation were determined as dipoles for which there was no higher power in their neighborhood. The time-varying connectivity pattern between the time series of these dipoles was calculated using the integrated, full-frequency, and spectrum-weighted Adaptive Directed Transfer Function4. This was done in the frequency band containing the seizure information, 3-30Hz. The outdegree of each selected dipole was determined as the sum over time of all outgoing connections. Around the dipole with the highest outdegree, we determined a region of dipoles that had a power that was at least 90% of the power of the center dipole. This region was then considered as the SOZ. We were able to successfully localize the driver in the resected zone for both patients. For the simulation data, the results can be quantified: in 71% of the simulations, the localization error remained below 25mm. If the selection of the dipole would be solely based on the highest power, the error would be more than 82mm. ESI in combination with connectivity analysis can successfully localize the SOZ in non- invasive ictal hd-EEG recordings and outperforms localization based on power. This could have important clinical relevance for the presurgical evaluation in focal epilepsy. References: 1. van Mierlo, P et al. (2014) Prog Neurobiol. 121:19-35. 2. Brunet, D. et al. (2011) Comput. Intell. Neurosci. 2. 3. Pascal-Marqui, R.D., et al. (1994) Int. J. Psychophysiol. 18(1):49-65. 4. van Mierlo, P. et al. (2013) Epilepsia 54.8:1409-1418.
Keywords
EEG source imaging, connectivity, epilepsy, seizure-onset zone localization

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Chicago
Staljanssens, Willeke, Gregor Strobbe, Roel Van Holen, Gwenael Birot, Christophe Michel, Margitta Seeck, Serge Vulliémoz, and Pieter van Mierlo. 2015. “Electrical Source Imaging and Connectivity Analysis to Localize the Seizure-onset Zone Based on High-density Ictal Scalp EEG Recordings.” In International Conference on Basic and Clinical Multimodal Imaging, Abstracts.
APA
Staljanssens, W., Strobbe, G., Van Holen, R., Birot, G., Michel, C., Seeck, M., Vulliémoz, S., et al. (2015). Electrical source imaging and connectivity analysis to localize the seizure-onset zone based on high-density ictal scalp EEG recordings. International Conference on Basic and Clinical Multimodal Imaging, Abstracts. Presented at the International Conference on Basic and Clinical Multimodal Imaging.
Vancouver
1.
Staljanssens W, Strobbe G, Van Holen R, Birot G, Michel C, Seeck M, et al. Electrical source imaging and connectivity analysis to localize the seizure-onset zone based on high-density ictal scalp EEG recordings. International Conference on Basic and Clinical Multimodal Imaging, Abstracts. 2015.
MLA
Staljanssens, Willeke, Gregor Strobbe, Roel Van Holen, et al. “Electrical Source Imaging and Connectivity Analysis to Localize the Seizure-onset Zone Based on High-density Ictal Scalp EEG Recordings.” International Conference on Basic and Clinical Multimodal Imaging, Abstracts. 2015. Print.
@inproceedings{6937854,
  abstract     = {Functional connectivity analysis of ictal intracranial EEG (icEEG) recordings can help with seizure-onset zone (SOZ) localization in patients with focal epilepsy1. However, it would be of high clinical value to be able to localize the SOZ based on non-invasive ictal EEG recordings to better target or avoid icEEG and improve surgical outcome. In this work, we propose an approach to localize the SOZ based on non-invasive ictal high- density EEG (hd-EEG) recordings.
We considered retrospective ictal hd-EEG recordings of two patients who were rendered seizure free after surgery. Furthermore, we simulated 1000 ictal hd-EEG epochs of 10s with an underlying network consisting of 3 randomly placed epileptic patches in the brain. EEG source imaging (ESI) was performed in CARTOOL using an individual head model (LSMAC) to calculate the forward model2. We considered dipoles uniformly distributed in the brain with a spacing of 5mm. LORETA3 was used as inverse solution method. Center dipoles of clusters with high activation were determined as dipoles for which there was no higher power in their neighborhood. The time-varying connectivity pattern between the time series of these dipoles was calculated using the integrated, full-frequency, and spectrum-weighted Adaptive Directed Transfer Function4. This was done in the frequency band containing the seizure information, 3-30Hz. The outdegree of each selected dipole was determined as the sum over time of all outgoing connections. Around the dipole with the highest outdegree, we determined a region of dipoles that had a power that was at least 90\% of the power of the center dipole. This region was then considered as the SOZ.
We were able to successfully localize the driver in the resected zone for both patients. For the simulation data, the results can be quantified: in 71\% of the simulations, the localization error remained below 25mm. If the selection of the dipole would be solely based on the highest power, the error would be more than 82mm.
ESI in combination with connectivity analysis can successfully localize the SOZ in non- invasive ictal hd-EEG recordings and outperforms localization based on power. This could have important clinical relevance for the presurgical evaluation in focal epilepsy.
References:
1. van Mierlo, P et al. (2014) Prog Neurobiol. 121:19-35.
2. Brunet, D. et al. (2011) Comput. Intell. Neurosci. 2.
3. Pascal-Marqui, R.D., et al. (1994) Int. J. Psychophysiol. 18(1):49-65. 4. van Mierlo, P. et al. (2013) Epilepsia 54.8:1409-1418.},
  author       = {Staljanssens, Willeke and Strobbe, Gregor and Van Holen, Roel and Birot, Gwenael and Michel, Christophe and Seeck, Margitta and Vulli{\'e}moz, Serge and van Mierlo, Pieter},
  booktitle    = {International Conference on Basic and Clinical Multimodal Imaging, Abstracts},
  language     = {eng},
  location     = {Utrecht, The Netherlands},
  title        = {Electrical source imaging and connectivity analysis to localize the seizure-onset zone based on high-density ictal scalp EEG recordings},
  year         = {2015},
}