Automated long‐term EEG analysis to localize the epileptogenic zone. Issue 3 (30th June 2017)
- Record Type:
- Journal Article
- Title:
- Automated long‐term EEG analysis to localize the epileptogenic zone. Issue 3 (30th June 2017)
- Main Title:
- Automated long‐term EEG analysis to localize the epileptogenic zone
- Authors:
- van Mierlo, Pieter
Strobbe, Gregor
Keereman, Vincent
Birot, Gwénael
Gadeyne, Stefanie
Gschwind, Markus
Carrette, Evelien
Meurs, Alfred
Van Roost, Dirk
Vonck, Kristl
Seeck, Margitta
Vulliémoz, Serge
Boon, Paul - Abstract:
- Summary: Objective: We investigated the performance of automatic spike detection and subsequent electroencephalogram (EEG) source imaging to localize the epileptogenic zone (EZ) from long‐term EEG recorded during video‐EEG monitoring. Methods: In 32 patients, spikes were automatically detected in the EEG and clustered according to their morphology. The two spike clusters with most single events in each patient were averaged and localized in the brain at the half‐rising time and peak of the spike using EEG source imaging. On the basis of the distance from the sources to the resection and the known patient outcome after surgery, the performance of the automated EEG analysis to localize the EZ was quantified. Results: In 28 out of the 32 patients, the automatically detected spike clusters corresponded with the reported interictal findings. The median distance to the resection in patients with Engel class I outcome was 6.5 and 15 mm for spike cluster 1 and 27 and 26 mm for cluster 2, at the peak and the half‐rising time of the spike, respectively. Spike occurrence (cluster 1 vs. cluster 2) and spike timing (peak vs. half‐rising) significantly influenced the distance to the resection (p < 0.05). For patients with Engel class II, III, and IV outcomes, the median distance increased to 36 and 36 mm for cluster 1. Localizing spike cluster 1 at the peak resulted in a sensitivity of 70% and specificity of 100%, positive prediction value (PPV) of 100%, and negative predictive valueSummary: Objective: We investigated the performance of automatic spike detection and subsequent electroencephalogram (EEG) source imaging to localize the epileptogenic zone (EZ) from long‐term EEG recorded during video‐EEG monitoring. Methods: In 32 patients, spikes were automatically detected in the EEG and clustered according to their morphology. The two spike clusters with most single events in each patient were averaged and localized in the brain at the half‐rising time and peak of the spike using EEG source imaging. On the basis of the distance from the sources to the resection and the known patient outcome after surgery, the performance of the automated EEG analysis to localize the EZ was quantified. Results: In 28 out of the 32 patients, the automatically detected spike clusters corresponded with the reported interictal findings. The median distance to the resection in patients with Engel class I outcome was 6.5 and 15 mm for spike cluster 1 and 27 and 26 mm for cluster 2, at the peak and the half‐rising time of the spike, respectively. Spike occurrence (cluster 1 vs. cluster 2) and spike timing (peak vs. half‐rising) significantly influenced the distance to the resection (p < 0.05). For patients with Engel class II, III, and IV outcomes, the median distance increased to 36 and 36 mm for cluster 1. Localizing spike cluster 1 at the peak resulted in a sensitivity of 70% and specificity of 100%, positive prediction value (PPV) of 100%, and negative predictive value (NPV) of 53%. Including the results of spike cluster 2 led to an increased sensitivity of 79% NPV of 55% and diagnostic OR of 11.4, while the specificity dropped to 75% and the PPV to 90%. Significance: We showed that automated analysis of long‐term EEG recordings results in a high sensitivity and specificity to localize the epileptogenic focus. … (more)
- Is Part Of:
- Epilepsia open. Volume 2:Issue 3(2017)
- Journal:
- Epilepsia open
- Issue:
- Volume 2:Issue 3(2017)
- Issue Display:
- Volume 2, Issue 3 (2017)
- Year:
- 2017
- Volume:
- 2
- Issue:
- 3
- Issue Sort Value:
- 2017-0002-0003-0000
- Page Start:
- 322
- Page End:
- 333
- Publication Date:
- 2017-06-30
- Subjects:
- Automated spike detection -- Automated spike localization -- EEG source imaging -- Patient‐specific head model
Epilepsy -- Periodicals
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616.853005 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)2470-9239/issues ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/epi4.12066 ↗
- Languages:
- English
- ISSNs:
- 2470-9239
- Deposit Type:
- Legaldeposit
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- Available online (eLD content is only available in our Reading Rooms) ↗
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