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Assessing quantitative EEG spectrograms to identify non‐epileptic events
Author(s) -
Goenka Ajay,
Boro Alexis,
Yozawitz Elissa
Publication year - 2017
Publication title -
epileptic disorders
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.673
H-Index - 53
eISSN - 1950-6945
pISSN - 1294-9361
DOI - 10.1684/epd.2017.0921
Subject(s) - spectrogram , electroencephalography , epilepsy , epileptic seizure , audiology , stereoelectroencephalography , psychology , medicine , neuroscience , ictal , artificial intelligence , computer science
Aims . To evaluate the sensitivity and specificity of quantitative EEG (QEEG) spectrograms in order to distinguish epileptic from non‐epileptic events. Methods . Seventeen patients with paroxysmal non‐epileptic events, captured during EEG monitoring, were retrospectively assessed using QEEG spectrograms. These patients were compared to a control group of 13 consecutive patients (ages 25‐60 years) with epileptic seizures of similar semiology. Assessment of raw EEG was employed as the gold standard against which epileptic and non‐epileptic events were validated. QEEG spectrograms, available using Persyst 12 EEG system integration software, were each assessed with respect to their usefulness to distinguish epileptic from non‐epileptic seizures. The given spectrogram was interpreted as indicating a seizure if, at the time of the clinically identified event, it showed a visually significant change from baseline. Results . Eighty‐two clinically identified paroxysmal events were analysed (46 non‐epileptic and 36 epileptic). The “seizure detector trend analysis” spectrogram correctly classified 33/46 (71%) non‐epileptic events (no seizure indicated during a clinically identified event) vs . 29/36 (81%) epileptic seizures (seizure indicated during a clinically identified event) ( p =0.013). Similarly, “rhythmicity spectrogram”, FFT spectrogram, “asymmetry relative spectrogram”, and integrated‐amplitude EEG spectrogram detected 28/46 (61%), 30/46 (65%), 22/46 (48%) and 27/46 (59%) non‐epileptic events vs . 27/36 (75%), 25/36 (69%), 25/36 (69%) and 27/36 (75%) epileptic events, respectively. Conclusions . High sensitivities and specificities for QEEG seizure detection analyses suggest that QEEG may have a role at the bedside to facilitate early differentiation between epileptic seizures and non‐epileptic events in order to avoid unnecessary administration of antiepileptic drugs and possible iatrogenic consequences.