Litcius/Paper detail

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

Sarbesh Pandeya, Janice A. Nagy, Daniela Riveros, Carson Semple, Rebecca S. Taylor, Marie Mortreux, Benjamin Sanchez, Kush Kapur, Seward B. Rutkove

2021Muscle & Nerve38 citationsDOIOpen Access PDF

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: 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.

Topics & Concepts

Ex vivoElectrical impedance myographyDuchenne muscular dystrophyConnective tissueBiomedical engineeringMyocytemdx mouseIn vivoChemistryAnatomyPathologyMedicineBiologyInternal medicineVasodilationBiotechnologyDystrophinBody Composition Measurement TechniquesMuscle Physiology and DisordersNutrition and Health in Aging