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Detection of focal epileptiform events in the EEG by spatio-temporal dipole clustering

Peter Van Hese UGent, Bart Vanrumste, Hans Hallez UGent, Grant Carroll, Kristl Vonck UGent, Richard Jones, Philip Bones, Yves D'Asseler UGent and Ignace Lemahieu UGent (2008) Clinical Neurophysiology. 119(8). p.1756-1770
abstract
Objective: Methods for the detection of epileptiform events can be broadly divided into two main categories: temporal detection methods that exploit the EEG's temporal characteristics, and spatial detection methods that base detection on the results of an implicit or explicit source analysis. We describe how the framework of a spatial detection method was extended to improve its performance by including temporal information. This results in a method that provides (i) automated localization of an epileptogenic focus and (ii) detection of focal epileptiform events in an EEG recording. For the detection, only one threshold value needs to be set. Methods: The method comprises five consecutive steps: (1) dipole source analysis in a moving window, (2) automatic selection of focal brain activity, (3) dipole clustering to arrive at the identification of the epileptiform cluster, (4) derivation of a spatio-temporal template of the epileptiform activity, and (5) template matching. Routine EEG recordings from eight paediatric patients with focal epilepsy were labelled independently by two experts. The method was evaluated in terms of (i) ability to identify the epileptic focus, (ii) validity of the derived template, and (iii) detection performance. The clustering performance was evaluated using a leave-one-out cross validation. Detection performance was evaluated using Precision-Recall curves and compared to the performance of two temporal (mimetic and wavelet based) and one spatial (dipole analysis based) detection methods. Results: The method succeeded in identifying the epileptogenic focus in seven of the eight recordings. For these recordings, the mean distance between the epileptic focus estimated by the method and the region indicated by the labelling of the experts was 8 mm. Except for two EEG recordings where the dipole clustering step failed, the derived template corresponded to the epileptiform, activity marked by the experts. Over the eight EEGs, the method showed a mean sensitivity and selectivity of 92 and 77%, respectively. Conclusions: The method allows automated localization of the epileptogenic focus and shows good agreement with the region indicated by the labelling of the experts. If the dipole clustering step is successful, the method allows a detection of the focal epileptiform events, and gave a detection performance comparable or better to that of the other methods. Significance: The identification and quantification of epileptiform events is of considerable importance in the diagnosis of epilepsy. Our method allows the automatic identification of the epileptic focus, which is of value in epilepsy surgery. The method can also be used as an offline exploration tool for focal EEG activity, displaying the dipole clusters and corresponding time series. (c) 2008 International Federation of Clinical Neurophysiology.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
focal epileptiform activity, focal epilepsy, paediatric patients, detection of epileptiform events, dipole clustering
journal title
Clinical Neurophysiology
Clin. Neurophysiol.
volume
119
issue
8
pages
1756 - 1770
publisher
Elsevier Ireland Ltd
place of publication
Shannon CO Clare Ireland
Web of Science type
Article
Web of Science id
000258023300009
JCR category
CLINICAL NEUROLOGY
JCR impact factor
2.972 (2008)
JCR rank
47/156 (2008)
JCR quartile
2 (2008)
ISSN
1388-2457
DOI
10.1016/j.clinph.2008.04.009
language
English
UGent publication?
yes
classification
A1
id
609895
handle
http://hdl.handle.net/1854/LU-609895
date created
2009-05-07 15:06:23
date last changed
2013-04-05 09:45:57
@article{609895,
  abstract     = {Objective: Methods for the detection of epileptiform events can be broadly divided into two main categories: temporal detection methods that exploit the EEG's temporal characteristics, and spatial detection methods that base detection on the results of an implicit or explicit source analysis. We describe how the framework of a spatial detection method was extended to improve its performance by including temporal information. This results in a method that provides (i) automated localization of an epileptogenic focus and (ii) detection of focal epileptiform events in an EEG recording. For the detection, only one threshold value needs to be set.

Methods: The method comprises five consecutive steps: (1) dipole source analysis in a moving window, (2) automatic selection of focal brain activity, (3) dipole clustering to arrive at the identification of the epileptiform cluster, (4) derivation of a spatio-temporal template of the epileptiform activity, and (5) template matching. Routine EEG recordings from eight paediatric patients with focal epilepsy were labelled independently by two experts. The method was evaluated in terms of (i) ability to identify the epileptic focus, (ii) validity of the derived template, and (iii) detection performance. The clustering performance was evaluated using a leave-one-out cross validation. Detection performance was evaluated using Precision-Recall curves and compared to the performance of two temporal (mimetic and wavelet based) and one spatial (dipole analysis based) detection methods.

Results: The method succeeded in identifying the epileptogenic focus in seven of the eight recordings. For these recordings, the mean distance between the epileptic focus estimated by the method and the region indicated by the labelling of the experts was 8 mm. Except for two EEG recordings where the dipole clustering step failed, the derived template corresponded to the epileptiform, activity marked by the experts. Over the eight EEGs, the method showed a mean sensitivity and selectivity of 92 and 77\%, respectively.

Conclusions: The method allows automated localization of the epileptogenic focus and shows good agreement with the region indicated by the labelling of the experts. If the dipole clustering step is successful, the method allows a detection of the focal epileptiform events, and gave a detection performance comparable or better to that of the other methods.

Significance: The identification and quantification of epileptiform events is of considerable importance in the diagnosis of epilepsy. Our method allows the automatic identification of the epileptic focus, which is of value in epilepsy surgery. The method can also be used as an offline exploration tool for focal EEG activity, displaying the dipole clusters and corresponding time series. (c) 2008 International Federation of Clinical Neurophysiology.},
  author       = {Van Hese, Peter and Vanrumste, Bart and Hallez, Hans and Carroll, Grant and Vonck, Kristl and Jones, Richard and Bones, Philip and D'Asseler, Yves and Lemahieu, Ignace},
  issn         = {1388-2457},
  journal      = {Clinical Neurophysiology},
  keyword      = {focal epileptiform activity,focal epilepsy,paediatric patients,detection of epileptiform events,dipole clustering},
  language     = {eng},
  number       = {8},
  pages        = {1756--1770},
  publisher    = {Elsevier Ireland Ltd},
  title        = {Detection of focal epileptiform events in the EEG by spatio-temporal dipole clustering},
  url          = {http://dx.doi.org/10.1016/j.clinph.2008.04.009},
  volume       = {119},
  year         = {2008},
}

Chicago
Van Hese, Peter, Bart Vanrumste, Hans Hallez, Grant Carroll, Kristl Vonck, Richard Jones, Philip Bones, Yves D’Asseler, and Ignace Lemahieu. 2008. “Detection of Focal Epileptiform Events in the EEG by Spatio-temporal Dipole Clustering.” Clinical Neurophysiology 119 (8): 1756–1770.
APA
Van Hese, P., Vanrumste, B., Hallez, H., Carroll, G., Vonck, K., Jones, R., Bones, P., et al. (2008). Detection of focal epileptiform events in the EEG by spatio-temporal dipole clustering. Clinical Neurophysiology, 119(8), 1756–1770.
Vancouver
1.
Van Hese P, Vanrumste B, Hallez H, Carroll G, Vonck K, Jones R, et al. Detection of focal epileptiform events in the EEG by spatio-temporal dipole clustering. Clinical Neurophysiology. Shannon CO Clare Ireland: Elsevier Ireland Ltd; 2008;119(8):1756–70.
MLA
Van Hese, Peter, Bart Vanrumste, Hans Hallez, et al. “Detection of Focal Epileptiform Events in the EEG by Spatio-temporal Dipole Clustering.” Clinical Neurophysiology 119.8 (2008): 1756–1770. Print.