Predicting myofiber cross-sectional area and triglyceride content with electrical impedance myography: A study in db/db mice.

BACKGROUND

Electrical impedance myography (EIM) provides insight into muscle composition and structure. We sought to evaluate its use in a mouse obesity model characterized by myofiber atrophy.

METHODS

We applied a prediction algorithm, ie, the least absolute shrinkage and selection operator (LASSO), to surface, needle array, and ex vivo EIM data from db/db and wild-type mice and assessed myofiber cross-sectional area (CSA) histologically and triglyceride (TG) content biochemically.

RESULTS

EIM data from all three modalities provided acceptable predictions of myofiber CSA with average root mean square error (RMSE) of 15% in CSA (ie, ±209 μm for a mean CSA of 1439 μm ) and TG content with RMSE of 30% in TG content (ie, ±7.3 nmol TG/mg muscle for a mean TG content of 25.4 nmol TG/mg muscle).

CONCLUSIONS

EIM combined with a predictive algorithm provides reasonable estimates of myofiber CSA and TG content without the need for biopsy.