Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue

Abstract

Purpose: To investigate the sensitivity of diffusion-MR signal to microstructural change in muscle tissue associated with pathology, and recommend optimal acquisition parameters. Methods: We employ Monte-Carlo simulation of diffusing spins in hierarchical tissue to generate synthetic diffusion-weighted signal curves over a wide range of scan parameters. Curves are analyzed using entropy—a measure of curve complexity. Entropy change between a baseline and various microstructural scenarios is investigated. We find acquisitions that optimize entropy difference in each scenario. Results: Permeability changes have a large effect on the diffusion-weighted signal curve. Muscle fiber atrophy is also important, although differentiating between mechanisms is challenging. Several acquisitions over a range of diffusion times is optimal for imaging microstructural change in muscle tissue. Sensitivity to permeability is optimized for high gradient strengths, but sensitivity to other scenarios is optimal at other values. Conclusions: The diffusion-attenuated signal is sensitive to the microstructural changes, but the changes are subtle. Taking full advantage of the changes to the overall curve requires a set of acquisitions over a range of diffusion times. Permeability causes the largest changes, but even the very subtle changes associated with fiber radius distribution change the curves more than noise alone. Magn Reson Med 78:1187–1198, 2017. © 2016 International Society for Magnetic Resonance in Medicine.