While ultrasound shear wave elastography originally focused on tissue stiffness under the assumption of elasticity, recent work has investigated the higher order, viscoelastic properties of the tissue. This article presents a method to use group shear wave speeds (gSWSs) at a series of derivative orders to characterize viscoelastic materials. This method uses a least squares fitting algorithm to match the experimental data to the calculated gSWS data, using an assumed material model and excitation geometry matched to the experimental imaging configuration. Building on a previous study that used particle displacement, velocity, and acceleration signals, this study extends the analysis to a continuous range of fractional derivative orders between 0 and 2. The method can be applied to any material model. Herein, material characterization was performed for three different two-parameter models and three different three-parameter models. This group speed-based method was applied to both shear wave simulations with ultrasonic tracking and experimental acquisitions in viscoelastic phantoms [similar to the Phase II Quantitative Imaging Biomarkers Alliance (QIBA) phantoms]. In both the cases, the group speed method produced more repeatable characterization overall than fitting the phase velocity results from the peak of the 2-D Fourier transform. Results suggest that the linear attenuation model is a better fit than the Voigt model for the viscoelastic QIBA phantoms.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029806PMC
http://dx.doi.org/10.1109/TUFFC.2019.2944126DOI Listing

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