Suppr超能文献

脑内高频振荡的记录:简单的视觉评估与自动检测。

Intracerebrally recorded high frequency oscillations: simple visual assessment versus automated detection.

机构信息

Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Faculty of Medicine, Masaryk University, Brno, Czech Republic.

出版信息

Clin Neurophysiol. 2013 Oct;124(10):1935-42. doi: 10.1016/j.clinph.2013.03.032. Epub 2013 May 21.

Abstract

OBJECTIVE

We compared the possible contribution (in the detection of seizure onset zone - SOZ) of simple visual assessment of intracerebrally recorded high-frequency oscillations (HFO) with standard automated detection.

METHODS

We analyzed stereo-EEG (SEEG) recordings from 20 patients with medically intractable partial seizures (10 temporal/10 extratemporal). Independently using simple visual assessment and automated detection of HFO, we identified the depth electrode contacts with maximum occurrences of ripples (R) and fast ripples (FR). The SOZ was determined by independent visual identification in standard SEEG recordings, and the congruence of results from visual versus automated HFO detection was compared.

RESULTS

Automated detection of HFO correctly identified the SOZ in 14 (R)/10 (FR) out of 20 subjects; a simple visual assessment of SEEG recordings in the appropriate frequency ranges correctly identified the SOZ in 13 (R)/9 (FR) subjects.

CONCLUSIONS

Simple visual assessment of SEEG traces and standard automated detection of HFO seem to contribute comparably to the identification of the SOZ in patients with focal epilepsies. When using macroelectrodes in neocortical extratemporal epilepsies, the SOZ might be better determined by the ripple range.

SIGNIFICANCE

Standard automated detection of HFO enables the evaluation of HFO characteristics in whole data. This detection allows general purpose and objective evaluation, without any bias from the neurophysiologist's experiences and practice.

摘要

目的

我们比较了简单的颅内高频振荡(HFO)视觉评估与标准自动检测在检测致痫区(SOZ)方面的可能贡献。

方法

我们分析了 20 例药物难治性部分性癫痫患者的立体脑电图(SEEG)记录(10 例颞叶/10 例颞外)。我们分别使用简单的视觉评估和 HFO 的自动检测,确定了具有最大棘波(R)和快棘波(FR)发生的深部电极接触点。SOZ 通过标准 SEEG 记录中的独立视觉识别确定,并比较了视觉与自动 HFO 检测结果的一致性。

结果

HFO 的自动检测正确识别了 20 例患者中的 14 例(R)/10 例(FR)的 SOZ;适当频率范围内的 SEEG 记录的简单视觉评估正确识别了 13 例(R)/9 例(FR)患者的 SOZ。

结论

SEEG 轨迹的简单视觉评估和 HFO 的标准自动检测似乎对确定局灶性癫痫患者的 SOZ 具有相当的贡献。当在新皮质外颞叶癫痫中使用微电极时,SOZ 可能通过棘波范围更好地确定。

意义

HFO 的标准自动检测能够评估整个数据中的 HFO 特征。这种检测允许进行通用和客观的评估,而不受神经生理学家经验和实践的任何偏见。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验