Ferrari-Marinho Taissa, Perucca Piero, Dubeau Francois, Gotman Jean
Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
Epilepsy Res. 2016 Nov;127:200-206. doi: 10.1016/j.eplepsyres.2016.09.009. Epub 2016 Sep 6.
High-frequency oscillations (80-500Hz; HFOs) have been shown to be a specific biomarker of the seizure-onset zone. The relationship of HFOs with seizures having different intracranial electroencephalography (iEEG) morphological onsets, however, has shown significant relationships in experimental animals but has not been studied in humans. We investigated how interictal and ictal HFOs relate to different seizure-onset morphological patterns.
We analyzed the most representative seizure type of 37 patients with drug-resistant focal epilepsy who underwent iEEG for diagnostic evaluation. According to the morphology, 211 seizure-onset zone channels were classified in six patterns (low-voltage fast activity; sharp activity at ≤13Hz; low-frequency high-amplitude periodic spikes; burst of high-amplitude polyspikes; spike-and-wave activity; and delta brush). Interictal and ictal HFOs were compared between the six seizure-onset patterns.
Interictal ripple and fast ripple rates differed significantly across seizure-onset patterns (p<0.001). Significant differences were also found for ictal HFOs density across the different seizure-onset patterns (p<0.001). Sharp activity at ≤13Hz was associated with the lowest interictal HFO rate suggesting either that the mechanism that generates this type of EEG morphology do not generate HFOs or possibly that this pattern is more likely to be generated in a region of seizure spread. Regarding the difference in HFO density between pre-ictal baseline and seizure-onset section across the six patterns, burst of high-amplitude polyspikes and delta brushes had the highest densities of both ripples and fast ripples (p<0.001).
We demonstrated that distinct seizure-onset patterns correlate specific interictal and ictal HFO profiles confirming that seizures with different morphological patterns likely have different mechanisms of generation. This study emphazises that, in clinical practice, seizure-onset patterns should be distinguished and specified when analyzing HFOs, particularly if they are used in presurgical evaluation to better localize the seizure-onset zone.
高频振荡（80 - 500Hz；HFOs）已被证明是癫痫发作起始区的一种特异性生物标志物。然而，HFOs与具有不同颅内脑电图（iEEG）形态学发作起始的癫痫之间的关系，在实验动物中已显示出显著关联，但尚未在人类中进行研究。我们调查了发作间期和发作期的HFOs与不同癫痫发作起始形态学模式之间的关系。
我们分析了37例耐药性局灶性癫痫患者中最具代表性的癫痫发作类型，这些患者接受了iEEG以进行诊断评估。根据形态学，将211个癫痫发作起始区通道分为六种模式（低电压快活动；≤13Hz的棘波活动；低频高幅周期性尖波；高幅多棘波爆发；棘慢波活动；以及δ刷）。比较了六种癫痫发作起始模式之间的发作间期和发作期HFOs。
发作间期的涟漪和快涟漪发生率在不同癫痫发作起始模式之间存在显著差异（p<0.001）。在不同癫痫发作起始模式的发作期HFOs密度方面也发现了显著差异（p<0.001）。≤13Hz的棘波活动与最低的发作间期HFO发生率相关，这表明产生这种脑电图形态的机制要么不产生HFOs，要么可能是这种模式更有可能在癫痫扩散区域产生。关于六种模式在发作前基线和癫痫发作起始段之间的HFO密度差异，高幅多棘波爆发和δ刷的涟漪和快涟漪密度最高（p<0.001）。
我们证明了不同的癫痫发作起始模式与特定的发作间期和发作期HFO特征相关，证实了具有不同形态学模式的癫痫可能具有不同的产生机制。本研究强调，在临床实践中，在分析HFOs时应区分并明确癫痫发作起始模式，特别是当它们用于术前评估以更好地定位癫痫发作起始区时。
