Skip to main content
SpringerLink
Log in

MEG Source Imaging Algorithm for Finding Deeper Epileptogenic Zone

  • Conference paper
  • First Online:
Advanced Computational Methods in Life System Modeling and Simulation (ICSEE 2017, LSMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 761))

  • 1979 Accesses

Abstract

In recent years, magnetoencephalography (MEG) has played a prominent role on neocortical epilepsy preoperative evaluation. However, its clinical utility with locating deeper sources may be more challenging such as the mesial temporal structures. We proposed a new source imaging algorithm for finding the epileptogenic zone in mesial temporal lobe epilepsy (mTLE). Since the localization results using the Elekta MEG method are very sensitive to some MEG noises, the source modeling was modified by spatial filtering in wavelet domain and cortex constraint. Two surgical patients randomly selected with medically refractory mTLE, which were diagnosed based on a comprehensive preoperative evaluation, had been studied in this manuscript. The localization results using proposed method on individual MRI showed that the deeper regions had been exactly found in the mesial temporal lobe. Yet, the results using the Elekta Neuromag Software only appeared in the lateral temporal lobe. Thus, the proposed algorithm maybe become an effective method in detecting deeper epileptogenic zone.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Nissen, I.A., Stam, C.J., Citroen, J., Reijneveldb, J.C., Hillebranda, A.: Preoperative evaluation using magnetoencephalography: experience in 382 epilepsy patients. Epilepsy Res. 124, 23–33 (2016)

    Article  Google Scholar 

  2. Barnes, G.R., Hillebrand, A.: Statistical flattening of MEG beamformer images. Hum. Brain Mapp. 18, 1–12 (2003)

    Article  Google Scholar 

  3. Zumer, J.M., Attias, H.T., Sekihara, K., Nagarajan, S.S.: A probabilistic algorithm integrating source localization and noise suppression for MEG and EEG data. Neuroimage 37, 102–115 (2007)

    Article  Google Scholar 

  4. Wu, J.Y., et al.: Magnetic source imaging localizes epileptogenic zone in children with tuberous sclerosis complex. Neurology 66, 1270–1272 (2006)

    Article  Google Scholar 

  5. Nissen, I.A., et al.: Identifying the epileptogenic zone in interictal resting-state MEG source-space networks. Epilepsia 58, 137–148 (2017)

    Article  Google Scholar 

  6. Hillebrand, A., Singh, K.D., Holliday, I.E., Furlong, P.L., Barnes, G.R.: A new approach to neuroimaging with magnetoencephalography. Hum. Brain Mapp. 25, 199–211 (2005)

    Article  Google Scholar 

  7. Engel, J.: Introduction to temporal lobe epilepsy. Epilepsy Res. 26, 141–150 (1996)

    Article  Google Scholar 

  8. Engel, J.: Mesial temporal lobe epilepsy: what have we learned? Neuroscientist 7, 340–352 (2001)

    Article  Google Scholar 

  9. Engel, J.: Recent advances in surgical treatment of temporal lobe epilepsy. Acta Neurol. Scand. 86(S140), 71–80 (1992)

    Article  Google Scholar 

  10. Sutherling, W.W., et al.: Influence of magnetic source imaging for planning intracranial EEG in epilepsy. Neurology 71, 990–996 (2008)

    Article  Google Scholar 

  11. Murakami, H., et al.: Correlating magnetoencephalography to stereo-electroencephalography in patients undergoing epilepsy surgery. Brain 139, 2935–2947 (2016)

    Article  Google Scholar 

  12. Bast, T., et al.: EEG and MEG source analysis of single and averaged interictal spikes reveals intrinsic epileptogenicity in focal cortical dysplasia. Epilepsia 45, 621–631 (2004)

    Article  Google Scholar 

  13. Wennberg, R., Cheyne, D.: Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus. Clin. Neurophysiol. 125, 903–918 (2014)

    Article  Google Scholar 

  14. Leijten, F.S.S., et al.: High-resolution source imaging in mesiotemporal lobe epilepsy: a comparison between MEG and simultaneous EEG. J. Clin. Neurophysiol. 20, 227–238 (2003)

    Article  Google Scholar 

  15. Shigeto, H., et al.: Feasibility and limitations of magnetoencephalographic detection of epileptic discharges: simultaneous recording of magnetic fields and electrocorticography. Neurol. Res. 24, 531–536 (2002)

    Article  Google Scholar 

  16. Wennberg, R., Valianteb, T., Cheynec, D.: EEG and MEG in mesial temporal lobe epilepsy: where do the spikes really come from? Clin. Neurophysiol. 122, 1295–1313 (2011)

    Article  Google Scholar 

  17. Enatsu, R., et al.: Usefulness of MEG magnetometer for spike detection in patients with mesial temporal epileptic focus. Neuroimage 41, 1206–1219 (2008)

    Article  Google Scholar 

  18. Bagić, A., Ebersole, J.S.: Does MEG/MSI dipole variability mean unreliability? Clin. Neurophysiol. 126, 209–211 (2015)

    Article  Google Scholar 

  19. Elekta Neuromag Oy: The MEG signal processor (graph) users guide and reference manual. http://www.martinos.org/meg/Neuromag-manuals.php. Accessed 13 June 2017

  20. Oishi, M., et al.: Single and multiple clusters of magnetoencephalographic dipoles in neocortical epilepsy: significance in characterizing the epileptogenic zone. Epilepsia 47, 355–364 (2006)

    Article  Google Scholar 

  21. Knake, S., et al.: The value of multichannel MEG and EEG in the presurgical evaluation of 70 epilepsy patients. Epilepsy Res. 69, 80–86 (2006)

    Article  Google Scholar 

  22. Medvedovsky, M., et al.: Sensitivity and specificity of seizure-onset zone estimation by ictal magnetoencephalography. Epilepsia 53, 1649–1657 (2012)

    Article  Google Scholar 

  23. Litvak, V., et al.: EEG and MEG data analysis in SPM8. Comput. Intell. Neurosci. 2011, 852961 (2011)

    Article  Google Scholar 

  24. Oostenveld, R., Fries, P., Maris, E., Schoffelen, J.M.: FieldTrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data. Comput. Intell. Neurosci. 2011, 156869 (2011)

    Article  Google Scholar 

  25. Besl, P.J., McKay, N.D.: A method for registration of 3D shapes. IEEE T Pattern Anal. 14, 239–254 (1992)

    Article  Google Scholar 

  26. Gross, J., Ioannides, A.A.: Linear transformations of data space in MEG. Phys. Med. Biol. 44, 2081–2097 (1999)

    Article  Google Scholar 

  27. Heers, M., et al.: Frequency domain beamforming of magnetoencephalographic beta band activity in epilepsy patients with focal cortical dysplasia. Epilepsy Res. 108, 1195–1203 (2014)

    Article  Google Scholar 

  28. Schaller, K., Cabrilo, I.: Anterior temporal lobectomy. Acta Neurochir. 158, 161–166 (2016)

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by National Key Research and Development program of the Ministry of Science and Technology (grant number 2016YFF0201002), the Natural Science Foundation of China (grant numbers 61301005 and 61572055), the Natural Science Project of National Statistical Bureau (2014LY088), the project of Brain Functional Disease and Neuromodulation of Beijing Key Laboratory, ‘Thousands of People Plan’ Workstation between Beihang University and Jiangsu Yuwell Medical Equipment & Supply Co. Ltd.

Author information

Authors and Affiliations

  1. School of Biological Science and Medical Engineering, Beihang University, Beijing, 100191, China

    Yegang Hu, Baoshan Yang, Guangrui Tang & Jicong Zhang

  2. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing, 100191, China

    Yegang Hu, Baoshan Yang, Guangrui Tang & Jicong Zhang

  3. Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China

    Yicong Lin & Yuping Wang

Authors
  1. Yegang Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yicong Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Baoshan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Guangrui Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yuping Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jicong Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jicong Zhang .

Editor information

Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Minrui Fei

  2. Shanghai University, Shanghai, China

    Shiwei Ma

  3. Shanghai University, Shanghai, China

    Xin Li

  4. Shanghai University, Shanghai, China

    Xin Sun

  5. Shanghai University, Shanghai, China

    Li Jia

  6. Shanghai University, Shanghai, China

    Zhou Su

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Nature Singapore Pte Ltd.

About this paper

Cite this paper

Hu, Y., Lin, Y., Yang, B., Tang, G., Wang, Y., Zhang, J. (2017). MEG Source Imaging Algorithm for Finding Deeper Epileptogenic Zone. In: Fei, M., Ma, S., Li, X., Sun, X., Jia, L., Su, Z. (eds) Advanced Computational Methods in Life System Modeling and Simulation. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 761. Springer, Singapore. https://doi.org/10.1007/978-981-10-6370-1_53

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-6370-1_53

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6369-5

  • Online ISBN: 978-981-10-6370-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation