Ultrasound shear wave phase velocity imaging using black-box system identification (BSI): a data-driven approach.

Shear wave elasticity imaging (SWEI) is an established approach for diagnosing lesions in human tissue. However, the shear wavelengths used by traditional SWEI are usually not short enough, leading to inferior accuracy in small-target (<10 mm) reconstruction. To exploit short shear wavelengths (high-frequency content), this study introduces a new phase velocity (PV) estimation technique as an alternative to the conventional group velocity (GV) modality.We propose using a black-box model instead of a fully physics-based model to describe the transition process of two arbitrary shear wave signals. With this representation, local PV can be obtained via black-box system identification (BSI). For validation, two PV estimation scenarios were established: (numerical) dispersion measurements in viscoelastic media, and (real) imaging targets in a CIRS elasticity phantom. BSI was compared with a state-of-the-art PV imaging method that uses local wavenumber estimation (LWE).BSI showed excellent accuracy in the dispersion estimation for all three viscoelastic media in the simulations. In the phantom study, the two PV methods exhibited good agreement in the frequency dependence of target quantification, and could both generate a higher target reconstruction accuracy than GV. LWE images were strongly affected by noise-induced faulty estimates, whereas BSI showed no notable artifacts.This study demonstrates the advantage of the PV modality over the GV modality as the former can achieve better target visualization by increasing imaging frequency. It also implies the feasibility of data-driven modeling for soft tissue characterization.