Quantifying myofiber integrity using diffusion MRI and random permeable barrier modeling in skeletal muscle growth and Duchenne muscular dystrophy model in mice.

Publication Type Academic Article
Authors Winters K, Reynaud O, Novikov D, Fieremans E, Kim S
Journal Magn Reson Med
Volume 80
Issue 5
Pagination 2094-2108
Date Published 03/25/2018
ISSN 1522-2594
Keywords Diffusion Magnetic Resonance Imaging, Image Interpretation, Computer-Assisted, Muscle, Skeletal, Muscular Dystrophy, Duchenne
Abstract PURPOSE: To measure the microstructural changes during skeletal muscle growth and progressive pathologies using the random permeable model with diffusion MRI, and compare findings to conventional imaging modalities such as three-point Dixon and T2 imaging. METHODS: In vivo and ex vivo DTI experiments with multiple diffusion times (20-700 ms) were completed on wild-type (n = 22) and muscle-dystrophic mdx mice (n = 8) at various developmental time points. The DTI data were analyzed with the random permeable model framework that provides estimates of the unrestricted diffusion coefficient (D0 ), membrane surface-to-volume ratio (S/V), and membrane permeability (κ). In addition, the MRI experiments included conventional measures, such as tissue fat fractions and T2 relaxation. RESULTS: During normal muscle growth between week 4 and week 13, the in vivo S/V, fractional anisotropy, and fat fraction correlated positively with age (ρ = 0.638, 0.664, and 0.686, respectively), whereas T2 correlated negatively (ρ = -0.847). In mdx mice, all DTI random permeable model parameters and fat fraction had significant positive correlation with age, whereas fractional anisotropy and T2 did not have significant correlation with age. Histological measurements of the perimeter-to-area ratio served as a proxy for the model-derived S/V in the cylindrical myofiber geometry, and had a significant correlation with the ex vivo S/V (r = 0.71) as well as the in vivo S/V (r = 0.56). CONCLUSION: The present study demonstrates that DTI at multiple diffusion times with the random permeable model analysis allows for noninvasively quantifying muscle fiber microstructural changes during both normal muscle growth and disease progression. Future studies can apply our technique to evaluate current and potential treatments to muscle myopathies.
DOI 10.1002/mrm.27188
PubMed ID 29577406
PubMed Central ID PMC6107391
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