Epilepsy Unit, Institute of Cure, Recovery, and Scientific Research (IRCCS) Foundation Carlo Besta Neurological Institute, Milan, Italy.
Claudio Munari Epilepsy Surgery Center, Niguarda Hospital, Milan, Italy.
Epilepsia. 2019 Jan;60(1):96-106. doi: 10.1111/epi.14610. Epub 2018 Nov 22.
Long-term recording with intracerebral electrodes is commonly utilized to identify brain areas responsible for seizure generation (epileptogenic zone) and to tailor therapeutic surgical resections in patients with focal drug-resistant epilepsy. This invasive diagnostic procedure generates a wealth of data that contribute to understanding human epilepsy. We analyze intracerebral signals to identify and classify focal ictal patterns.
We retrospectively analyzed stereo-electroencephalographic (EEG) data in a cohort of patients either cryptogenic (magnetic resonance imaging negative) or presenting with noncongruent anatomoelectroclinical data. A computer-assisted method based on EEG signal analysis in frequency and space domains was applied to 467 seizures recorded in 105 patients submitted to stereo-EEG presurgical monitoring.
Two main focal seizure patterns were identified. P-type seizures, typical of neocortex, were observed in 73 patients (69.5%), lasted 22 ± 13 seconds (mean +SD), and were characterized by a sharp-onset/sharp-offset transient superimposed on low-voltage fast activity (126 ± 19 Hz). L-type seizures were observed in 43 patients (40.9%) and consistently involved mesial temporal structures; they lasted longer (93 ± 48 second), started with 116 ± 21 Hz low-voltage fast activity superimposed on a slow potential shift, and terminated with large-amplitude, periodic bursting activity. In 23 patients (21.9%), the L-type seizure was preceded by a P seizure. Spasmlike and unclassifiable EEG seizures were observed in 11.4% of cases.
The proposed computer-assisted approach revealed signal information concealed to visual inspection that contributes to identifying two principal seizure patterns typical of the neocortex and of mesial temporal networks.
颅内电极的长期记录常用于识别致痫区（癫痫灶），并为药物难治性局灶性癫痫患者制定治疗性手术切除方案。这种有创性诊断程序产生了大量有助于了解人类癫痫的数据。我们分析颅内信号以识别和分类局灶性发作模式。
我们回顾性分析了一组隐源性（磁共振成像阴性）或表现出非一致解剖-电临床数据的患者的立体脑电图（EEG）数据。一种基于脑电图信号在频域和空域分析的计算机辅助方法应用于 105 名接受立体 EEG 术前监测的患者中记录的 467 次癫痫发作。
确定了两种主要的局灶性癫痫发作模式。P 型发作，典型的皮质起源，发生在 73 名患者（69.5%），持续 22±13 秒（平均值+标准差），特征为锐起/锐消的短暂尖波叠加在低电压快活动上（126±19 Hz）。L 型发作发生在 43 名患者（40.9%）中，始终涉及内侧颞叶结构；它们持续时间更长（93±48 秒），起始时为叠加在慢电位漂移上的 116±21 Hz 低电压快活动，终止时为大振幅、周期性爆发活动。在 23 名患者（21.9%）中，L 型发作之前是 P 型发作。痉挛样和无法分类的 EEG 癫痫发作在 11.4%的病例中观察到。
所提出的计算机辅助方法揭示了隐藏在视觉检查中的信号信息，有助于识别两种典型的皮质和内侧颞叶网络的主要发作模式。
