Luo Xuesong, Wang Shaoping, Sanchez Benjamin
Department of Automation Science and Electric Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, China.
Sanchez Research Lab, Department of Electrical and Computer Engineering, Sorenson Molecular Biotechnology Building, 36 South Wasatch Drive, University of Utah, Salt Lake City, UT 84112, USA.
IEEE J Electromagn RF Microw Med Biol. 2022 Mar;6(1):103-110. doi: 10.1109/jerm.2021.3091515. Epub 2021 Jun 22.
Needle electrical impedance myography (EIM) is a recently developed technique for neuromuscular evaluation. Despite its preliminary successful clinical application, further understanding is needed to aid interpreting EIM outcomes in nonhomogeneous skeletal muscle measurements.
The framework presented models needle EIM measurements in a bidomain isotropic model. Finite element method (FEM) simulations verify the validity of our model predictions studying two cases: a spherical volume surrounded by tissue and a two-layered tissue.
Our models show that EIM is influenced by the vicinity of tissue with different electrical properties. The apparent resistance, reactance and phase relative errors between our theoretical predictions and FEM simulations in the spherical volume case study are ≤0.2%, ≤1.2% and ≤1.0%, respectively. For the two-layered tissue model case study, the relative errors are ≤2%.
We propose a bio-physics driven analytical framework describing needle EIM measurements in a nonhomogeneous bidomain tissue model.
Our theoretical predictions may lead to new ways for interpreting needle EIM data in neuromuscular diseases that cause compositional changes in muscle content, e.g. connective tissue deposition within the muscle. These changes will manifest themselves by changing the electric properties of the conductor media and will impact impedance values.
针电极电阻抗肌电图(EIM)是一种最近开发的用于神经肌肉评估的技术。尽管其在临床应用中初步取得成功,但仍需要进一步了解,以帮助解释在非均匀骨骼肌测量中的EIM结果。
所提出的框架在双域各向同性模型中对针电极EIM测量进行建模。有限元方法(FEM)模拟通过研究两种情况验证了我们模型预测的有效性:被组织包围的球形体积和双层组织。
我们的模型表明,EIM受具有不同电学性质的组织附近区域的影响。在球形体积案例研究中,我们的理论预测与FEM模拟之间的表观电阻、电抗和相位相对误差分别≤0.2%、≤1.2%和≤1.0%。对于双层组织模型案例研究,相对误差≤2%。
我们提出了一个由生物物理学驱动的分析框架,用于描述非均匀双域组织模型中的针电极EIM测量。
我们的理论预测可能会为解释神经肌肉疾病中的针电极EIM数据带来新方法,这些疾病会导致肌肉成分发生变化,例如肌肉内结缔组织沉积。这些变化将通过改变导体介质的电学性质表现出来,并会影响阻抗值。