北京生物医学工程

基于发作间期颅内脑电高频振荡的癫痫病灶定位

Epileptogenic zone localization based on intracranial interictal high frequency oscillations

作者：郑霄张丹石岩芳周文静洪波

单位：                      清华大学医学院生物医学工程系(北京100084)        

关键词：颅内脑电；高频振荡；非参数模型；致痫灶

分类号：

出版年·卷·期（页码）：2014·33·3（253-257）

摘要：

目的通过癫痫发作间期高频颅内脑电信号的记录和分析，实现一种基于概率模型的癫痫病灶定位自动
算法。方法以一段时间内颅内脑电高频能量的整体波动性水平为指标，建立大数据概率模型以判断某电极
是否覆盖致痫灶。结果本文分析了来自12例癫痫患者948个颅内电极的癫痫发作间期颅内脑电数据，与医生
人工定位结果作对比，平均敏感性80.4%±17.3%，特异性87.7%±17.2%；模型的稳定性和性能随着数据量增
加而提高。结论本文所提出高频能量波动性算法基于概率模型，不依赖个体化参数、自动化程度高、性能
好，有良好的临床应用前景。

Objective To propose and implement an automatic method based on a probability
model using intracranially recorded high-frequency brain activity for the identification of
epileptogenic zone.Methods Big data probability model was constructed based on the
characteristics of the epileptogenic activities described by the degree of overall high-
frequency power fluctuation in order to identify whether a channel was located in
epileptogenic zone or not.Results By using the probability model with 948-electrode data from
12 patients, and compared with the results marked by neurologists, 80.4% ±17.3% sensitivity
and 87.7% ±17.2% specificity were achieved.Conclusions Based on probability model, the
proposed method does not rely on individual parameters, and possesses high degree of
automation, good performance and a bright perspective in clinical diagnosis.

参考文献：

服务与反馈：

【文章下载】【加入收藏】

提示：您还未登录，请登录！点此登录