Quantitative EEG Fingerprints of Landau-Kleffner Syndrome
Prasannakumar Gajera1, Akshaya Rathin Sivaji1, Jun Park2
1Epilepsy Center, University Hospitals, Cleveland Medical Center, Case Western Reserve University, 2UH Rainbow Babies & Children's Hospital, Case Western Reserve University
Objective:
NA
Background:

Landau–Kleffner Syndrome (LKS) is an epileptic encephalopathy characterized by acquired language regression and verbal auditory agnosia, commonly associated with electrical status epilepticus in sleep (ESES) during non-REM sleep. Persistent generalized spike-and-waves during sleep are believed to cause functional inhibition of temporal cortical regions responsible for auditory and language processing. Through an illustrative case of a child with LKS, we aim to demonstrate a recognizable pattern of ESES on quantitative EEG to complement EEG interpretation. 

Design/Methods:
NA
Results:

Case:

 A 5-year-old right-handed boy with normal prior development presented with sudden language regression, reduced comprehension, and poorly intelligible speech (~25% understandable), though hearing remained normal. Awake EEG demonstrated isolated generalized epileptiform discharges, while sleep EEG revealed >90% high-amplitude generalized spike-and-wave activity consistent with ESES. His brain MRI was unremarkable. Based on clinical and EEG findings, LKS was diagnosed. Clobazam was initiated and titrated over six months, with serial EEG monitoring showing >99% resolution of ESES over a year. His speech improved substantially, with near-fluent language and mild articulation errors at one-year follow-up. QEEG during ESES consistently exhibited frequency-specific alterations, including surges in seizure detection and seizure probability index. Rhythmicity spectrogram showed synchronous increases in rhythmic power across delta, theta, alpha, and beta frequency bands. Fast Fourier Transform (FFT) spectrogram showed a predominately low-frequency broadband, which reflected the slow-wave components of raw EEG data, especially pronounced during non-REM sleep. Notably, the predominance of spike-and-wave complexes in sleep also translated to visible absence of sleep state changes on qEEG compared to a normal sleep qEEG sample.

Conclusions:

Quantitative EEG showed an instantly recognizable pattern correlating with ESES pattern on scalp EEG. Quantitative EEG can serve as an effective adjunctive tool when interpreted alongside a scalp EEG in LKS.

10.1212/WNL.0000000000217254
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