Author(s)

Xiangyu Xue ¹

Affiliation(s)

¹ School of Biomedical Sciences and Engineering, Beijing University of Aeronautics and Astronautics, Beijing, China

Corresponding Author

Xiangyu Xue

ABSTRACT

The key to successful epilepsy surgery is accurate localisation of the epileptogenic zone, yet conventional methods have a number of limitations. To overcome these limitations, we propose a new method: virtual intracranial electroencephalography (ViEEG) technique, which combines the advantages of magnetoencephalography (MEG) and intracranial electroencephalography (iEEG). By using the electromagnetic signals of epileptic patients in the interictal period, we successfully reconstructed the virtual intracranial EEG signals and predicted the location of the epileptogenic zone. The experimental results show that the virtual intracranial EEG signal can effectively predict the epileptogenic zone with high accuracy. This method not only reduces the difficulty of data acquisition and clinical workload, but also improves the success rate of surgery. Therefore, ViEEG technology is expected to become an important auxiliary tool in epilepsy surgery and provide more accurate treatment for patients.

KEYWORDS

Epilepsy, magnetic brain signals, virtual intracranial EEG, epileptogenic zone prediction

CITE THIS PAPER

Xiangyu Xue, Virtual Intracranial Electrical Signal Reconstruction and Epileptogenic Zone Prediction Study Based on VIEEG. MEDS Clinical Medicine (2024) Vol. 5: 30-38. DOI: http://dx.doi.org/10.23977/medsc.2024.050305.

REFERENCES

[1] Kristin M Gunnarsdottir, Jorge Gonzalez-Martinez, Simon Wing, Sridevi V Sarma. Sources and Sinks in Interictal iEEG Networks: An iEEG Marker of the Epileptogenic Zone[J]. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, 2021, Vol. 2021: 6558-6561.
[2] Cao M; Galvis D; Vogrin SJ; Woods WP; Vogrin S; Wang F; Woldman W; Terry JR; Peterson A; Plummer C; Cook MJ. Virtual intracranial EEG signals reconstructed from MEG with potential for epilepsy surgery. [J].Nature communications, 2022, Vol.13(1): 994.
[3] Matthew Pease, Jonathan Elmer, Ameneh Zare Shahabadi, Arka N Mallela, Juan F Ruiz-Rodriguez, Daniel Sexton, Niravkumar Barot, Jorge A Gonzalez-Martinez, Lori Shutter, David O Okonkwo, James F Castellano. Predicting post-traumatic epilepsy using admission electroencephalography after severe traumatic brain injury [J]. Epilepsia, 2023, Vol. 64(7): 1842-1852.
[4] Ting Wu, Guowei He. Independent component analysis of streamwise velocity fluctuations in turbulent channel flows [J].Theoretical & Applied Mechanics Letters, 2022, Vol. 12(4): 233-240.
[5] Luca Alessandro Silva; Giacomo Zanella. Robust leave-one-out cross-validation for high-dimensional Bayesian models [J]. Journal of the American Statistical Association, 2023: 1-27. 

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