Estimating myofiber cross‐sectional area and connective tissue deposition with electrical impedance myography: A study in D2‐mdx mice

Abstract

Introduction: Surface electrical impedance myography (sEIM) has the potential for providing information on muscle composition and structure noninvasively. We sought to evaluate its use to predict myofiber size and connective tissue deposition in the D2-mdx model of Duchenne muscular dystrophy (DMD).Methods: We applied a prediction algorithm, the least absolute shrinkage and selection operator, to select specific EIM measurements obtained with surface and ex vivo EIM data from D2-mdx and wild-type (WT) mice (analyzed together or separately). We assessed myofiber cross-sectional area histologically and hydroxyproline (HP), a surrogate measure for connective tissue content, biochemically.Results: Using WT and D2-mdx impedance values together in the algorithm, sEIM gave average root-mean-square errors (RMSEs) of 26.6% for CSA and 45.8% for HP, which translate into mean errors of ±363 μm 2 for a mean CSA of 1365 μm 2 and of ±1.44 μg HP/mg muscle for a mean HP content of 3.15 μg HP/mg muscle. Stronger predictions were obtained by analyzing sEIM data from D2-mdx animals alone (RMSEs of 15.3% for CSA and 34.1% for HP content). Predictions made using ex vivo EIM data from D2-mdx animals alone were nearly equivalent to those obtained with sEIM data (RMSE of 16.59% for CSA), and slightly more accurate for HP (RMSE of 26.7%).Discussion: Surface EIM combined with a predictive algorithm can provide estimates of muscle pathology comparable to values obtained using ex vivo EIM, and can be used as a surrogate measure of disease severity and progression and response to therapy.

Relationships between in vivo surface and ex vivo electrical impedance myography measurements in three different neuromuscular disorder mouse models

“…Experimental animals undergo regular weekly health and behavioral assessments (including body mass, motor score, mobility and gait, ability to feed, paw grip endurance, paw grip strength), and electrophysiological studies (electrical impedance myography). For the analyses completed here, impedance data acquired as part of three earlier studies [26][27][28] were utilized. The sample sizes for each group were thus those used in each of the earlier studies.…”

“…We have previously shown that surface and ex vivo EIM data both correlate to histological features of muscle in a variety of conditions [26,27,[33][34][35], so have not repeated that effort here. Rather, our goal was simply to establish what our expectations should be in processing surface impedance data in relation to ex vivo values and to consider the possibility that the surface frequencies of interest more strongly relate to lower frequency ex vivo values, at least in the D2-mdx and ALS animals.…”

Using machine learning algorithms to enhance the diagnostic performance of electrical impedance myography

“…Recently, we have used individual multifrequency impedance values in a least absolute selection and shrinkage operator (LASSO) analysis to predict histological features of the muscle, including myofiber size, fatty infiltration of muscle, and connective tissue deposition in wild‐type (WT) mice and three genetic disease models: SOD1 amyotrophic lateral sclerosis (ALS), 13 D2‐mdx (a mouse model of Duchenne muscular dystrophy), 14 and the db/db mouse (a model of type two diabetes that produces major fatty deposition and myofiber atrophy) 15 . Each of these animal models was studied separately; thus, the histological prediction models were specific to those individual disorders.…”

Altered electrical properties in skeletal muscle of mice with glycogen storage disease type II

“…More recently, we have focused on obtaining similar information such as myofiber CSA by using an in vivo non-invasive surface impedance approach coupled with statistical analysis to establish a relationship between impedance values and muscle fibers of varying size, including those from immature animals 10 , and in a murine neuromuscular disease model associated with prominent muscle atrophy 11 . We have also assessed changes in the extracellular space by the analysis of impedance data in several murine models including: inflammatory infiltrates in carrageenan-induced inflammation 12 ; increased fat deposition in the db/db obese diabetic mouse 13 ; and increased fibrosis in the D2-mdx model of Duchenne Muscular Dystrophy (DMD) 14 .…”