scholarly journals Variation of scalp EEG high frequency oscillation rate with sleep stage and time spent in sleep in patients with pediatric epilepsy

Author(s):  
Dorottya Cserpan ◽  
Richard Rosch ◽  
Santo Pietro Lo Biundo ◽  
Johannes Sarnthein ◽  
Georgia Ramantani
2021 ◽  
Author(s):  
Dorottya Cserpan ◽  
Richard Rosch ◽  
Santo Pietro Lo Biundo ◽  
Johannes Sarnthein ◽  
Georgia Ramantani

High frequency oscillations (HFO) in scalp EEG are a new and promising epilepsy biomarker. HFO analysis is typically restricted to random and relatively brief sleep segments. However, considerable fluctuations of HFO rates have been observed over the recording nights, particularly in relation to sleep stages and cycles. Here, we identify the timing within the sleep period and the minimal data interval length that allow for sensitive and reproducible detection of scalp HFO. We selected 16 seizure-free whole-night scalp EEG recordings of children and adolescents with focal lesional epilepsy (median age 7.6 y, range 2.2-17.4 y). We used an automated and clinically validated HFO detector to determine HFO rates (80-250 Hz) in bipolar channels. To identify significant variability over different NREM sleep stages and over time spent in sleep, we modelled HFO rate as a Poisson process. We analysed the test-retest reliability to evaluate the reproducibility of HFO detection across recording intervals. Scalp HFO rates were higher in N3 than in N2 sleep and highest in the first sleep cycle, decreasing with time spent in sleep. In N3 sleep, the median reliability of HFO detection increased from 67% to 79% to 100% for 5-, 10-, and 15-min data intervals, improving significantly (p=0.004) from 5 to 10 min but not from 10 to 15 min. In this analysis of whole-night scalp EEG, we identified the first N3 sleep stage as the most sensitive time window for HFO rate detection. N3 data intervals of 10 min duration are required and sufficient for reliable measurements of HFO rates. Our study provides a robust and reliable framework for implementing scalp HFO as an EEG biomarker in pediatric epilepsy.


2016 ◽  
Vol 10 ◽  
pp. 318-325 ◽  
Author(s):  
Sergey Burnos ◽  
Tommaso Fedele ◽  
Olivier Schmid ◽  
Niklaus Krayenbühl ◽  
Johannes Sarnthein

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Dorottya Cserpan ◽  
Ece Boran ◽  
Santo Pietro Lo Biundo ◽  
Richard Rosch ◽  
Johannes Sarnthein ◽  
...  

Abstract High-frequency oscillations in scalp EEG are promising non-invasive biomarkers of epileptogenicity. However, it is unclear how high-frequency oscillations are impacted by age in the paediatric population. We prospectively recorded whole-night scalp EEG in 30 children and adolescents with focal or generalized epilepsy. We used an automated and clinically validated high-frequency oscillation detector to determine ripple rates (80–250 Hz) in bipolar channels. Children < 7 years had higher high-frequency oscillation rates (P = 0.021) when compared with older children. The median test−retest reliability of high-frequency oscillation rates reached 100% (iqr 50) for a data interval duration of 10 min. Scalp high-frequency oscillation frequency decreased with age (r = −0.558, P = 0.002), whereas scalp high-frequency oscillation duration and amplitude were unaffected. The signal-to-noise ratio improved with age (r = 0.37, P = 0.048), and the background ripple band activity decreased with age (r = −0.463, P = 0.011). We characterize the relationship of scalp high-frequency oscillation features and age in paediatric patients. EEG intervals of ≥10 min duration are required for reliable measurements of high-frequency oscillation rates. This study is a further step towards establishing scalp high-frequency oscillations as a valid epileptogenicity biomarker in this vulnerable age group.


2020 ◽  
Vol 37 (2) ◽  
pp. 191-194
Author(s):  
Tomohiko Murai ◽  
Takefumi Hitomi ◽  
Masao Matsuhashi ◽  
Riki Matsumoto ◽  
Yuki Kawamura ◽  
...  

PEDIATRICS ◽  
2001 ◽  
Vol 108 (1) ◽  
pp. 212-214
Author(s):  
J. P. Shenai; ◽  
P. Rimensberger; ◽  
U. Thome ◽  
F. Pohlandt; ◽  
P. Rimensberger

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Mohammad Habibullah ◽  
Nadarajah Mithulananthan ◽  
Krischonme Bhumkittipich ◽  
Mohammad Amin

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