Murphy Paige M, von Paternos Adam J, Santaniello Sabato
Annu Int Conf IEEE Eng Med Biol Soc. 2017 Jul;2017:1054-1057. doi: 10.1109/EMBC.2017.8037008.
High frequency oscillations (HFOs) are potential biomarkers of epileptic areas. In patients with drug-resistant epilepsy, HFO rates tend to be higher in the seizure onset zone (SOZ) than in other brain regions and the resection of HFO-generating areas positively correlates with seizure-free surgery outcome. Nonetheless, the development of robust unsupervised HFO-based tools for SOZ localization remains challenging. Current approaches predict the SOZ by processing small samples of intracranial EEG (iEEG) data and applying patient-specific thresholds on the HFO rate. The HFO rate, though, varies largely over time with the patient's conditions (e.g., sleep versus wakefulness) and across patients. We propose a novel localization method for SOZ that uses a time-varying, HFO-based index to estimate the epileptic susceptibility of the iEEG channels. The method is insensitive to the average HFO rate across channels (which is both patient- and condition-specific), tracks the channel susceptibility over time, and predicts the SOZ based on the temporal evolution of the HFO rate. Tested on a preliminary dataset of continuous multi-day multichannel interictal iEEG recordings from two epileptic patients (117±97.6 h/per patient, mean ± S.D.), the reported SOZ prediction had an average 0.70±0.18 accuracy and 0.67±0.07 area under the ROC curve (mean ± S.D.) across patients.
高频振荡（HFOs）是癫痫区域的潜在生物标志物。在耐药性癫痫患者中，癫痫发作起始区（SOZ）的HFO发生率往往高于其他脑区，切除产生HFO的区域与无癫痫发作的手术结果呈正相关。尽管如此，开发强大的基于HFO的无监督SOZ定位工具仍然具有挑战性。目前的方法是通过处理颅内脑电图（iEEG）数据的小样本并对HFO发生率应用患者特定阈值来预测SOZ。然而，HFO发生率会随着患者的病情（例如，睡眠与清醒）以及不同患者而在很大程度上随时间变化。我们提出了一种新的SOZ定位方法，该方法使用基于HFO的时变指数来估计iEEG通道的癫痫易感性。该方法对通道间的平均HFO发生率不敏感（这是特定于患者和病情的），随时间跟踪通道易感性，并根据HFO发生率的时间演变来预测SOZ。在来自两名癫痫患者的连续多日多通道发作间期iEEG记录的初步数据集上进行测试（每位患者117±97.6小时，平均值±标准差），报告的SOZ预测在患者中的平均准确率为0.70±0.18，ROC曲线下面积为0.67±0.07（平均值±标准差）。
