Twin Peak Method for Estimating Tissue Viscoelasticity Using Shear Wave Elastography

Tissue viscoelasticity is becoming an increasingly useful biomarker beyond elasticity and can theoretically be estimated using shear wave elastography by inverting the propagation and attenuation characteristics of shear waves. Estimating viscosity is often more difficult than elasticity because attenuation, the main effect of viscosity, leads to poor signal-to-noise ratio of the shear wave motion. In the present work, we provide an alternative to existing methods of viscoelasticity estimation, based on peaks in the frequency-wavenumber (f-k) domain, which are considered more robust against noise compared with other features in the f-k domain. Specifically, the method minimizes the difference between simulated and measured versions of two sets of peaks (twin peaks) in the f-k domain, obtained first by traversing through each frequency and then by traversing through each wavenumber. The slopes and deviation of the twin peaks are sensitive to elasticity and viscosity, respectively, leading to the effectiveness of the proposed inversion algorithm for characterizing mechanical properties. This expected effectiveness is confirmed through in silico verification, followed by ex vivo validation and in vivo application, indicating that the proposed approach can be used effectively in accurately estimating viscoelasticity, thus potentially contributing to the development of enhanced biomarkers.