Yan Lisi, Li Lin, Chen Jin, Wang Li, Jiang Li, Hu Yue
Department of Neurology, Children's Hospital of Chongqing Medical University, Chongqing, China.
Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China.
Front Hum Neurosci. 2021 Jun 10;15:682011. doi: 10.3389/fnhum.2021.682011. eCollection 2021.
We quantitatively analyzed high-frequency oscillations (HFOs) using scalp electroencephalography (EEG) in patients with infantile spasms (IS).
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.
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 ( < 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 ( < 0.01). The average HFO energy of S and Post-S stage were higher than that of sleep stage in γ band ( < 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 ( < 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 ( < 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.
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.
我们使用头皮脑电图（EEG）对婴儿痉挛症（IS）患者的高频振荡（HFOs）进行了定量分析。
我们纳入了2019年1月至2020年8月期间住院的60例IS患儿。60名年龄匹配的健康儿童组成对照组。采用时频分析来量化γ、涟漪和快涟漪（FR）振荡能量变化。
γ、涟漪和FR振荡在颞叶和额叶占主导。正常对照组（NC）和IS组在相同频段睡眠期的平均HFO能量均低于清醒期（P<0.05）。IS组在睡眠期γ频段的平均HFO能量显著高于NC组（P<0.01）。γ频段S期和S期后阶段的平均HFO能量高于睡眠期（P<0.05）。在涟漪频段，S期前、S期和S期后的平均HFO能量高于睡眠期（P<0.05）。治疗前，有效组和无效组的基于基线的评分无显著差异。疗效×频率的交互作用和疗效×状态的交互作用具有统计学意义。有效组在睡眠期的平均HFO能量低于无效组（P<0.05）。对于IS组中被认为“有效”的16名儿童，三个频段的平均HFO能量在治疗前后无显著差异。
头皮EEG可记录HFOs。HFOs的能量比频率能更准确地区分生理性HFOs和病理性HFOs。在头皮EEG上，γ振荡比涟漪和FR振荡能更好地检测癫痫易感性。HFOs可引发痉挛。平均HFO能量分析可作为癫痫治疗效果的预测指标。
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