A comparison between detectors of high frequency oscillations
A comparison between detectors of high frequency oscillations
复制标题
DOI：
10.1016/j.clinph.2011.06.006
复制
发表时间：
2012-01-01
影响因子：
4.7
通讯作者：
Gotman, J.
中科院分区：
文献类型：
--
作者：
Zelmann, R.;Mari, F.;Gotman, J.
Objective: High frequency oscillations (HFOs) have been implicated in ictogenesis and epileptogenesis. The effect of contact size (in the clinical range: 1-10 mm(2)) on HFO detection has not been determined. This study assesses the feasibility of HFO detection in a rat epilepsy model using macrocontacts and clinical amplifiers, and the effect of contact size on HFO detection within the macrocontact range.Methods: Eight epileptic rats were implanted with intracerebral electrodes containing three adjacent contacts of different sizes (0.02, 0.05 and 0.09 mm(2)). HFOs were manually marked on 5 min interictal EEG segments. HFO rates and durations were compared between the different contacts.Results: 10,966 ripples and 1475 fast ripples were identified in the recordings from 30 contacts. There were no significant differences in spike or HFO rates between the different contact sizes, nor was there a significant difference in HFO duration.Conclusions: HFOs can be detected in a rat epilepsy model using macrocontacts. Within the studied range, size did not significantly influence HFO detection.Significance: Using comparative anatomy of rat and human limbic structures, these findings suggest that reducing the size of macrocontacts (compared to those commercially available) would not improve HFO detection rates. (C) 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.Objective: High frequency oscillations (HFOs) are a biomarker of epileptogenicity. Visual marking of HFOs is highly time-consuming and inevitably subjective, making automatic detection necessary. We compare four existing detectors on the same dataset.Methods: HFOs and baselines were identified by experienced reviewers in intracerebral EEGs from 20 patients. A new feature of our detector to deal with channels where baseline cannot be found is presented. The original and an optimal configuration are implemented. Receiver operator curves, false discovery rate, and channel ranking are used to evaluate performance.Results: All detectors improve performance with the optimal configuration. Our detector had higher sensitivity, lower false positives than the others, and similar false detections. The main difference in performance was in very active channels.Conclusions: Each detector was developed for different recordings and with different aims. Our detector performed better in this dataset, but was developed on data similar to the test data. Moreover, optimizing on a particular data type improves performance in any detector.Significance: Automatic HFO detection is crucial to propel their clinical use as biomarkers of epileptogenic tissue. Comparing detectors on a single dataset is important to analyze their performance and to emphasize the issues involved in validation. (C) 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
