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Magnetic Resonance Elastography Reconstruction for Anisotropic Tissues

Research output: Contribution to journalArticlepeer-review

Behzad Babaei, Daniel Fovargue, Robert A. Lloyd, Renee Miller, Lauriane Jugé, Max Kaplan, Ralph Sinkus, David Nordsletten, Lynne E Bilston

Original languageEnglish
Article number102212
JournalMedical Image Analysis
PublishedDec 2021

Bibliographical note

Funding Information: This research was supported by a Discovery grant from the Australian Research Council ( DP160100061 ). L.E.B. is supported by senior research fellowships from the National Health and Medical Research Council of Australia (APP1077934, APP1172988). D.N. would like to acknowledge funding from Engineering and Physical Sciences Research Council ( EP/N011554/1 and EP/R003866/1 ). Publisher Copyright: © 2021 The Author(s)

King's Authors


Elastography has become widely used clinically for characterising changes in soft tissue mechanics that are associated with altered tissue structure and composition. However, some soft tissues, such as muscle, are not isotropic as is assumed in clinical elastography implementations. This limits the ability of these methods to capture changes in anisotropic tissues associated with disease. The objective of this study was to develop and validate a novel elastography reconstruction technique suitable for estimating the linear viscoelastic mechanical properties of transversely isotropic soft tissues. We derived a divergence-free formulation of the governing equations for acoustic wave propagation through a linearly transversely isotropic viscoelastic material, and transformed this into a weak form. This was then implemented into a finite element framework, enabling the analysis of wave input data and tissue structural fibre orientations, in this case based on diffusion tensor imaging. To validate the material constants obtained with this method, numerous in silico phantom experiments were run which encompassed a range of variations in wave input directions, material properties, fibre structure and noise. The method was also tested on ex vivo muscle and in vivo human volunteer calf muscles, and compared with a previous curl-based inversion method. The new method robustly extracted the transversely isotropic shear moduli (G , G , G ) from the in silico phantom tests with minimal bias, including in the presence of experimentally realistic levels of noise in either fibre orientation or wave data. This new method performed better than the previous method in the presence of noise. Anisotropy estimates from the ex vivo muscle phantom agreed well with rheological tests. In vivo experiments on human calf muscles were able to detect increases in muscle shear moduli with passive muscle stretch. This new reconstruction method can be applied to quantify tissue mechanical properties of anisotropic soft tissues, such as muscle, in health and disease. [Abstract copyright: Copyright © 2021 The Author(s). Published by Elsevier B.V. All rights reserved.]

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