Estimation of Anisotropic Material Properties of Soft Tissue by MRI of Ultrasound-Induced Shear Waves

Abstract

This paper describes a new method for estimating anisotropic mechanical properties of fibrous soft tissue by imaging shear waves induced by focused ultrasound (FUS) and analyzing their direction-dependent speeds. Fibrous materials with a single, dominant fiber direction may exhibit anisotropy in both shear and tensile moduli, reflecting differences in the response of the material when loads are applied in different directions. The speeds of shear waves in such materials depend on the propagation and polarization directions of the waves relative to the dominant fiber direction. In this study, shear waves were induced in muscle tissue (chicken breast) ex vivo by harmonically oscillating the amplitude of an ultrasound beam focused in a cylindrical tissue sample. The orientation of the fiber direction relative to the excitation direction was varied by rotating the sample. Magnetic resonance elastography (MRE) was used to visualize and measure the full 3D displacement field due to the ultrasound-induced shear waves. The phase gradient (PG) of radially propagating “slow” and “fast” shear waves provided local estimates of their respective wave speeds and directions. The equations for the speeds of these waves in an incompressible, transversely isotropic (TI), linear elastic material were fitted to measurements to estimate the shear and tensile moduli of the material. The combination of focused ultrasound and MR imaging allows noninvasive, but comprehensive, characterization of anisotropic soft tissue.

Full Characterization of in vivo Muscle as an Elastic, Incompressible, Transversely Isotropic Material Using Ultrasonic Rotational 3D Shear Wave Elasticity Imaging

“…Three ITI material parameters have been measured in vivo by magnetic resonance elastography (MRE) [48], and in ex vivo animal tissue [49], [50]. Looking at the three muscles in the calf using MRE in vivo, Guo et al [48] found lower χ µ values (soleus 0.50, gastrocnemius 0.80, tibialis anterior 0.27) compared to χ µ = 2.11 herein for vastus lateralis, and also χ E values lower than herein (soleus 1.47, gastrocnemius 2.26, tibialis 2.00, compared to χ E = 4.67 for vastus lateralis).…”

“…Many studies to date have measured the directional dependence of shear wave propagation in muscle, reporting a wide range of speeds along and across the fiber axis [16], [24], [36]- [50]. These reports used an experimental setup similar to that shown in Fig.…”

Mapping Stiffness Landscape of Heterogeneous and Anisotropic Fibrous Tissue

“…As our method delineated, when the mechanical properties of axonal fibers and ECM are coupled with imaging data, it can offer new tools to boost the MRE capabilities to depict the anisotropic stiffness of brain 107 , and identify or evaluate brain disorders such as Alzheimer's 14,15,76 , Parkinson's 16 , and multiple sclerosis [108][109][110] . With the aim of achieving this, extensive recent efforts have focused on connecting MRE and DTI for predicting anisotropic mechanical properties of the brain tissue of the human or other species [111][112][113][114][115] . It has been shown that there are strong correlations between the mechanical properties assessed by MRE in the CC and CR and microstructural properties derived from DTI 107 .…”

A Deep Learning Framework for Predicting the Heterogeneous Stiffness Map of Brain White Matter Tissue

“…The displacement field acquired from MRE is inverted to estimate mechanical properties, such as stiffness and damping [36][37][38][39] . In recent years, there has been a shift towards incorporating anisotropy considerations in MRE, which previously predominantly used inversion models assuming mechanical isotropy [40][41][42] . Despite the promising advantages of MRE, there are ongoing efforts to improve the accuracy of entire process, encompassing imaging, wave generation, actuation frequency, acquisition strategy, physiological vibration analysis, inversion algorithms, and processing pipelines.…”