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Global sensitivity analysis of skeletal muscle dMRI metrics: Effects of microstructural and pulse parameters
Author(s) -
Naughton Noel M.,
Georgiadis John G.
Publication year - 2020
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.28014
Subject(s) - sensitivity (control systems) , diffusion mri , signal (programming language) , skeletal muscle , diffusion , biological system , noise (video) , materials science , biomedical engineering , nuclear magnetic resonance , mathematics , computer science , physics , artificial intelligence , anatomy , biology , magnetic resonance imaging , medicine , radiology , electronic engineering , engineering , image (mathematics) , programming language , thermodynamics
Purpose Estimating microstructural parameters of skeletal muscle from diffusion MRI (dMRI) signal requires understanding the relative importance of both microstructural and dMRI sequence parameters on the signal. This study seeks to determine the sensitivity of dMRI signal to variations in microstructural and dMRI sequence parameters, as well as assess the effect of noise on sensitivity. Methods Using a cylindrical myocyte model of skeletal muscle, numerical solutions of the Bloch‐Torrey equation were used to calculate global sensitivity indices of dMRI metrics (FA, RD, MD, λ 1 , λ 2 , λ 3 ) for wide ranges of microstructural and dMRI sequence parameters. The microstructural parameters were: myocyte diameter, volume fraction, membrane permeability, intra‐ and extracellular diffusion coefficients, and intra‐ and extracellular T 2 times. Two separate pulse sequences were examined, a PGSE and a generalized diffusion‐weighted sequence that accommodates a larger range of diffusion times. The effect of noise and signal averaging on the sensitivity of the dMRI metrics was examined by adding synthetic noise to the simulated signal. Results Among the examined parameters, the intracellular diffusion coefficient has the strongest effect, and myocyte diameter is more influential than permeability for FA and RD. The sensitivity indices do not vary significantly between the two pulse sequences. Also, noise strongly affects the sensitivity of the dMRI signal to microstructural variations. Conclusions With the identification of key microstructural features that affect dMRI measurements, the reported sensitivity results can help interpret dMRI measurements of skeletal muscle in terms of the underlying microstructure and further develop parsimonious dMRI models of skeletal muscle.