当前位置: X-MOL 学术Clin. Neurophysiol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Amplitude of high frequency oscillations as a biomarker of the seizure onset zone
Clinical Neurophysiology ( IF 3.7 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.clinph.2020.07.021
Krit Charupanit 1 , Indranil Sen-Gupta 2 , Jack J Lin 3 , Beth A Lopour 1
Affiliation  

OBJECTIVE Studies of high frequency oscillations (HFOs) in epilepsy have primarily tested the HFO rate as a biomarker of the seizure onset zone (SOZ), but the rate varies over time and is not robust for all individual subjects. As an alternative, we tested the performance of HFO amplitude as a potential SOZ biomarker using two automated detection algorithms. METHOD HFOs were detected in intracranial electroencephalogram (iEEG) from 11 patients using a machine learning algorithm and a standard amplitude-based algorithm. For each detector, SOZ and non-SOZ channels were classified using the rate and amplitude of high frequency events, and performance was compared using receiver operating characteristic curves. RESULTS The amplitude of detected events was significantly higher in SOZ. Across subjects, amplitude more accurately classified SOZ/non-SOZ than rate (higher values of area under the ROC curve and sensitivity, and lower false positive rates). Moreover, amplitude was more consistent across segments of data, indicated by lower coefficient of variation. CONCLUSION As an SOZ biomarker, HFO amplitude offers advantages over HFO rate: it exhibits higher classification accuracy, more consistency over time, and robustness to parameter changes. SIGNIFICANCE This biomarker has the potential to increase the generalizability of HFOs and facilitate clinical implementation as a tool for SOZ localization.

中文翻译:

高频振荡幅度作为癫痫发作区的生物标志物

目标 癫痫中高频振荡 (HFO) 的研究主要测试了 HFO 率作为癫痫发作区 (SOZ) 的生物标志物,但该率随时间变化,并且并非对所有个体受试者都是稳健的。作为替代方案,我们使用两种自动检测算法测试了 HFO 振幅作为潜在 SOZ 生物标志物的性能。方法 使用机器学习算法和基于振幅的标准算法,在 11 名患者的颅内脑电图 (iEEG) 中检测到 HFO。对于每个检测器,使用高频事件的速率和幅度对 SOZ 和非 SOZ 通道进行分类,并使用接收器操作特性曲线比较性能。结果 SOZ 中检测到的事件的幅度显着更高。跨学科,幅度比速率更准确地分类 SOZ/非 SOZ(ROC 曲线下的面积值和灵敏度更高,假阳性率更低)。此外,幅度在数据段之间更加一致,这由较低的变异系数表明。结论 作为 SOZ 生物标志物,HFO 振幅比 HFO 率具有优势:它表现出更高的分类准确度、随着时间的推移更具一致性以及对参数变化的鲁棒性。意义 这种生物标志物有可能提高 HFO 的普遍性,并促进作为 SOZ 定位工具的临床实施。HFO 幅度比 HFO 速率具有优势:它表现出更高的分类准确度、随着时间的推移更具一致性以及对参数变化的鲁棒性。意义 这种生物标志物有可能提高 HFO 的普遍性,并促进作为 SOZ 定位工具的临床实施。HFO 幅度比 HFO 速率具有优势:它表现出更高的分类准确度、随着时间的推移更具一致性以及对参数变化的鲁棒性。意义 这种生物标志物有可能提高 HFO 的普遍性,并促进作为 SOZ 定位工具的临床实施。
更新日期:2020-11-01
down
wechat
bug