Xuesong Luo1, Shaoping Wang1, Benjamin Sanchez2. 1. Department of Automation Science and Electric Engineering, Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beihang University, Beijing 100083, China. 2. 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.
Abstract
Objective: 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. Methods: 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. Results: 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%. Conclusions: We propose a bio-physics driven analytical framework describing needle EIM measurements in a nonhomogeneous bidomain tissue model. Clinical impact: 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.
Objective: 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. Methods: 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. Results: 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%. Conclusions: We propose a bio-physics driven analytical framework describing needle EIM measurements in a nonhomogeneous bidomain tissue model. Clinical impact: 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.
Authors: Johanna Hamel; Phil Lee; Melanie D Glenn; Tekalign Burka; In-Young Choi; Seth D Friedman; Dennis W W Shaw; Ayla McCalley; Laura Herbelin; Mazen M Dimachkie; Richard Lemmers; Silvère M van der Maarel; Richard J Barohn; Rabi Tawil; Jeffrey M Statland Journal: Muscle Nerve Date: 2020-01-22 Impact factor: 3.217