Intracerebrally recorded high frequency oscillations: Simple visual assessment versus automated detection

0397630 - ÚPT 2014 RIV IE eng J - Journal Article
Pail, M. - Halámek, Josef - Daniel, P. - Kuba, R. - Tyrlíková, I. - Chrastina, J. - Jurák, Pavel - Rektor, I. - Brázdil, M.
Intracerebrally recorded high frequency oscillations: Simple visual assessment versus automated detection.
Clinical Neurophysiology. Roč. 124, č. 10 (2013), s. 1935-1942. ISSN 1388-2457. E-ISSN 1872-8952
R&D Projects: GA ČR GAP103/11/0933; GA MŠMT ED0017/01/01
Institutional support: RVO:68081731
Keywords : High frequency oscillations * Spikes * Ripples * Temporal lobe epilepsy * Extratemporal lobe epilepsy * Seizure onset zone * Epileptogenic zone
Subject RIV: FH - Neurology
Impact factor: 2.979, year: 2013

Objective: We compared the possible contribution (in the detection of seizure onset zone -SOZ) of simple visual assessment of intracerebrally recorded high-frequency oscillations (HFO) with standard automated detection. Methods: We analyzed stereo-EEG (SEEG) recordings from 20 patients with medically intractable partial seizures (10 temporal/10 extratemporal). Independently using simple visual assessment and automated detection of HFO, we identified the depth electrode contacts with maximum occurrences of ripples (R) and fast ripples (FR). The SOZ was determined by independent visual identification in standard SEEG recordings, and the congruence of results from visual versus automated HFO detection was compared. Results: Automated detection of HFO correctly identified the SOZ in 14 (R)/10 (FR) out of 20 subjects; a simple visual assessment of SEEG recordings in the appropriate frequency ranges correctly identified the SOZ in 13 (R)/9 (FR) subjects. Conclusions: Simple visual assessment of SEEG traces and standard automated detection of HFO seem to contribute comparably to the identification of the SOZ in patients with focal epilepsies. When using macroelectrodes in neocortical extratemporal epilepsies, the SOZ might be better determined by the ripple range. Significance: Standard automated detection of HFO enables the evaluation of HFO characteristics in whole data. This detection allows general purpose and objective evaluation, without any bias from the neurophysiologist's experiences and practice. (C) 2013 Published by Elsevier Ireland Ltd. on behalf of International Federation of Clinical Neurophysiology.
Permanent Link: http://hdl.handle.net/11104/0225244