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利用多频生物阻抗监测检测神经内针放置:一种新方法。

Detection of intraneural needle-placement with multiple frequency bioimpedance monitoring: a novel method.

作者信息

Kalvøy Håvard, Sauter Axel R

机构信息

Department of Clinical and Biomedical Engineering, Oslo University Hospital Rikshospitalet, Oslo, Norway.

Division of Emergencies and Critical Care, Department of Anaesthesiology, Oslo University Hospital Rikshospitalet, Oslo, Norway.

出版信息

J Clin Monit Comput. 2016 Apr;30(2):185-92. doi: 10.1007/s10877-015-9698-3. Epub 2015 Apr 23.

Abstract

Electrical impedance measurements have been used to detect intraneural needle placement, but there is still a lack of precision with this method. The purpose of the study was to develop a method for the discrimination of nerve tissue from other tissue types based on multiple frequency impedance measurements. Impedance measurements with 25 different frequencies between 1.26 and 398 kHz were obtained in eight pigs while placing the tip of a stimulation needle within the sciatic nerve and in other tissues. Various impedance variables and measurement frequencies were tested for tissue discrimination. Best tissue discrimination was obtained by using three different impedance parameters with optimal measurement frequencies: Modulus (126 kHz), Phase angle (40 kHz) and the Delta of the phase angle (between 126 and 158 kHz). These variables were combined in a Compound variable C. The area under the curve in a receiver operating characteristic was consecutively increased for the Modulus (78 %), Phase angle (86 %), Delta of the phase angle (94 %), and the Compound variable C (97 %), indicating highest specificity and sensitivity for C. An algorithm based on C was implemented in a real-time feasibility test and used in an additional test animal to demonstrate our new method. Discrimination between nerve tissue and other tissue types was improved by combining several impedance variables at multiple measurement frequencies.

摘要

电阻抗测量已被用于检测神经内针的位置,但该方法仍缺乏精确性。本研究的目的是开发一种基于多频阻抗测量来区分神经组织与其他组织类型的方法。在八头猪身上,将刺激针的尖端置于坐骨神经和其他组织内,同时获得了1.26至398kHz之间25种不同频率的阻抗测量值。对各种阻抗变量和测量频率进行了组织区分测试。通过使用具有最佳测量频率的三个不同阻抗参数可实现最佳的组织区分:模量(126kHz)、相位角(40kHz)以及相位角之差(126至158kHz之间)。这些变量被组合成复合变量C。在接收器操作特性曲线下的面积,对于模量(78%)、相位角(86%)、相位角之差(94%)和复合变量C(97%)依次增加,表明C具有最高的特异性和敏感性。基于C的算法在实时可行性测试中得以实现,并用于另一头测试动物以验证我们的新方法。通过在多个测量频率下组合多个阻抗变量,神经组织与其他组织类型之间的区分得到了改善。

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