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

• Published in: Muscle & nerve Vol. 63; no. 6; pp. 941 - 950
• Main Authors: Pandeya, Sarbesh R., Nagy, Janice A., Riveros, Daniela, Semple, Carson, Taylor, Rebecca S., Mortreux, Marie, Sanchez, Benjamin, Kapur, Kush, Rutkove, Seward B.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.06.2021; Wiley Subscription Services, Inc
• Subjects: Algorithms; Animals; Connective tissue; Connective Tissue - physiopathology; Connective tissues; Deposition; Duchenne's muscular dystrophy; Dystrophy; Electric Impedance; Electrical impedance; electrical impedance myography; Electromyography; Hydroxyproline; Impedance; LASSO prediction algorithm; Mice; Mice, Inbred mdx; Muscle Fibers, Skeletal - physiology; muscle hydroxyproline content; Muscle, Skeletal - physiopathology; Muscles; Muscular dystrophy; Muscular Dystrophy, Duchenne - physiopathology; myofiber atrophy; myofiber size; Predictions; Tissues; myofiber atrophy; myofiber size; muscle hydroxyproline content; LASSO prediction algorithm; electrical impedance myography; muscular dystrophy
• ISSN: 0148-639X; 1097-4598
• DOI: 10.1002/mus.27240

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 μm2 for a mean CSA of 1365 μm2 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.