Application of High-Frequency Oscillations on Scalp EEG in Infant Spasm: A Prospective Controlled Study
Lisi Yan1,2,3,4,5, Lin Li1,2,3,4,5, Jin Chen1,2,3,4,5
1Department of Neurology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Insights
High-frequency oscillations (HFOs) detected by scalp electroencephalography (EEG) can distinguish between physiological and pathological states in infantile spasms (IS). Analyzing HFO energy predicts treatment effectiveness for epilepsy.
Area of Science:
- Neuroscience
- Clinical Neurology
- Biomedical Engineering
Background:
- Infantile spasms (IS) are a severe epilepsy syndrome.
- High-frequency oscillations (HFOs) are abnormal brain activity patterns.
- Scalp electroencephalography (EEG) is a non-invasive tool for detecting brain activity.
Purpose of the Study:
- To quantitatively analyze HFOs using scalp EEG in children with IS.
- To investigate the diagnostic and prognostic value of HFO energy in IS.
- To explore the relationship between HFOs and epilepsy treatment efficacy.
Main Methods:
- Sixty children with IS and sixty healthy controls were enrolled.
- Time-frequency analysis quantified gamma (γ), ripple, and fast ripple (FR) oscillation energy.
- HFO energy was compared between IS and control groups, and across different sleep-wake states and treatment outcomes.
Main Results:
- HFOs (γ, ripple, FR) were prominent in temporal and frontal lobes.
- IS patients showed higher γ band HFO energy during sleep compared to controls.
- Higher HFO energy in IS patients correlated with poorer treatment response.
Conclusions:
- Scalp EEG can reliably record HFOs in IS patients.
- HFO energy, particularly γ oscillations, is a more accurate indicator of pathological activity than frequency alone.
- HFO energy analysis serves as a potential biomarker for predicting epilepsy treatment effectiveness.
Objective:
We quantitatively analyzed high-frequency oscillations (HFOs) using scalp electroencephalography (EEG) in patients with infantile spasms (IS).
Methods:
We enrolled 60 children with IS hospitalized from January 2019 to August 2020. Sixty healthy age-matched children comprised the control group. Time-frequency analysis was used to quantify γ, ripple, and fast ripple (FR) oscillation energy changes.
Results:
γ, ripple, and FR oscillations dominated in the temporal and frontal lobes. The average HFO energy of the sleep stage is lower than that of the wake stage in the same frequency bands in both the normal control (NC) and IS groups (P < 0.05). The average HFO energy of the IS group was significantly higher than that of the NC group in γ band during sleep stage (P < 0.01). The average HFO energy of S and Post-S stage were higher than that of sleep stage in γ band (P < 0.05). In the ripple band, the average HFO energy of Pre-S, S, and Post-S stage was higher than that of sleep stage (P < 0.05). Before treatment, there was no significant difference in BASED score between the effective and ineffective groups. The interaction of curative efficacy × frequency and the interaction of curative efficacy × state are statistically significant. The average HFO energy of the effective group was lower than that of the ineffective group in the sleep stage (P < 0.05). For the 16 children deemed "effective" in the IS group, the average HFO energy of three frequency bands was not significantly different before compared with after treatment.
Significance:
Scalp EEG can record HFOs. The energy of HFOs can distinguish physiological HFOs from pathological ones more accurately than frequency. On scalp EEG, γ oscillations can better detect susceptibility to epilepsy than ripple and FR oscillations. HFOs can trigger spasms. The analysis of average HFO energy can be used as a predictor of the effectiveness of epilepsy treatment.
