• David B Berry, Benjamin Regner, Vitaly Galinsky, Samuel R Ward, and Lawrence R Frank.
• Department of Bioengineering, University of California San Diego, La Jolla, California, USA.
• Magn Reson Med. 2018 Jul 1; 80 (1): 317-329.

PurposeTo establish a series of relationships defining how muscle microstructure and diffusion tensor imaging (DTI) are related.MethodsThe relationship among key microstructural features of skeletal muscle (fiber size, fibrosis, edema, and permeability) and the diffusion tensor were systematically simulated over physiologically relevant dimensions individually, and in combination, using a numerical simulation application. Stepwise multiple regression was used to identify which microstructural features of muscle significantly predict the diffusion tensor using single-echo and multi-echo DTI pulse sequences. Simulations were also performed in models with histology-informed geometry to investigate the relationship between fiber size and the diffusion tensor in models with real muscle geometry.ResultsFiber size is the strongest predictor of λ2, λ3, mean diffusivity, and fractional anisotropy in skeletal muscle, accounting for approximately 40% of the variance in the diffusion model when calculated with single-echo DTI. This increased to approximately 70% when diffusion measures were calculated from the short T2 component of the multi-echo DTI sequence. This nonlinear relationship begins to plateau in fibers with greater than 60-μm diameter.ConclusionsAs the normal fiber size of a human muscle fiber is 40 to 60 μm, this suggests that DTI is a sensitive tool to monitor muscle atrophy, but may be limited in measurements of muscle with larger fibers. Magn Reson Med 80:317-329, 2018. © 2017 International Society for Magnetic Resonance in Medicine.© 2017 International Society for Magnetic Resonance in Medicine.

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