Quantitative analysis and EEG markers of KCNT1 epilepsy of infancy with migrating focal seizures

Summary

Objective

We aimed to characterize epilepsy of infancy with migrating focal seizures (EIMFS), a rare, severe early onset developmental epilepsy related to KCNT1 mutation, and to define specific electroencephalography (EEG) markers using EEG quantitative analysis. The ultimate goal would be to improve early diagnosis and to better understand seizure onset and propagation of EIMFS as compared to other early onset developmental epilepsy.

Methods

EEG of 7 EIMFS patients with KCNT1 mutations (115 seizures) and 17 patients with other early onset epilepsies (30 seizures) was included in this study. After detection of seizure onset and termination, spatiotemporal characteristics were quantified. Seizure propagation dynamics were analyzed using chronograms and phase coherence.

Results

In patients with EIMFS, seizures started and were localized predominantly in temporal and occipital areas, and evolved with a stable frequency (4‐10 Hz). Inter‐ and intrahemispheric migrations were present in 60% of EIMFS seizures with high intraindividual reproducibility of temporospatial dynamics. Interhemispheric migrating seizures spread in 71% from temporal or occipital channels to the homologous contralateral ones, whereas intrahemispheric seizures involved mainly frontotemporal, temporal, and occipital channels. Causality links were present between ictal activities detected under different channels during migrating seizures. Finally, time delay index (based on delays between the different ictal onsets) and phase correlation index (based on coherence of ictal activities) allowed discrimination of EIMFS and non‐EIMFS seizures with a specificity of 91.2% and a sensitivity of 84.4%.

Significance

We showed that the migrating pattern in EIMFS is not a random process, as suggested previously, and that it is a particular propagation pattern that follows the classical propagation pathways. It is notable that this study reveals specific EEG markers (time delay and phase correlation) accessible to visual evaluation, which will improve EIMFS diagnosis.

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