Seward B Rutkove1, Adam Pacheck1, Benjamin Sanchez1. 1. Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, DA-0730A, 330 Brookline Avenue, Boston, Masachusetts, 02215-5491, USA.
Abstract
INTRODUCTION: Surface-based electrical impedance myography (EIM) is sensitive to muscle condition in neuromuscular disorders. However, the specific contribution of muscle to the obtained EIM values is unknown. METHODS: We combined theory and the finite element method to calculate the electrical current distribution in a 3-dimensional model using different electrode array designs and subcutaneous fat thicknesses (SFTs). Through a sensitivity analysis, we decoupled the contribution of muscle from other surrounding tissues in the measured surface impedance values. RESULTS: The contribution of muscle to surface EIM values varied greatly depending on the electrode array size and the SFT. For example, the contribution of muscle with 6-mm SFT was 8% for a small array compared with 32% for a large array. CONCLUSIONS: The approach presented can be employed to inform the design of robust EIM electrode configurations that maximize the contribution of muscle across the disease and injury spectrum. Muscle Nerve 56: 887-895, 2017.
INTRODUCTION: Surface-based electrical impedance myography (EIM) is sensitive to muscle condition in neuromuscular disorders. However, the specific contribution of muscle to the obtained EIM values is unknown. METHODS: We combined theory and the finite element method to calculate the electrical current distribution in a 3-dimensional model using different electrode array designs and subcutaneous fat thicknesses (SFTs). Through a sensitivity analysis, we decoupled the contribution of muscle from other surrounding tissues in the measured surface impedance values. RESULTS: The contribution of muscle to surface EIM values varied greatly depending on the electrode array size and the SFT. For example, the contribution of muscle with 6-mm SFT was 8% for a small array compared with 32% for a large array. CONCLUSIONS: The approach presented can be employed to inform the design of robust EIM electrode configurations that maximize the contribution of muscle across the disease and injury spectrum. Muscle Nerve 56: 887-895, 2017.
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