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Estimating myofiber cross‐sectional area and connective tissue deposition with electrical impedance myography: A study in D2 ‐ mdx mice
Author(s) -
Pandeya Sarbesh R.,
Nagy Janice A.,
Riveros Daniela,
Semple Carson,
Taylor Rebecca S.,
Mortreux Marie,
Sanchez Benjamin,
Kapur Kush,
Rutkove Seward B.
Publication year - 2021
Publication title -
muscle and nerve
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.025
H-Index - 145
eISSN - 1097-4598
pISSN - 0148-639X
DOI - 10.1002/mus.27240
Subject(s) - ex vivo , electrical impedance myography , duchenne muscular dystrophy , connective tissue , mdx mouse , myocyte , biomedical engineering , in vivo , chemistry , anatomy , pathology , medicine , biology , in vitro , biochemistry , vasodilation , microbiology and biotechnology , dystrophin
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.