Complex shear modulus reconstruction using ultrasound shear-wave imaging

Many pathological processes in tissues are recognized by morphological changes that reflect alterations of the soft tissue mechanical properties. Ultrasound shear-wave imaging can provide quantitative information about soft tissue mechanical properties, specifically the complex shear modulus. Advancing this field has the potential to bridge molecular, cellular, and tissue biology and to influence medical diagnoses and patient treatment. This dissertation describes several quantitative developments in the field of ultrasound shear-wave imaging. The initial study is a time-domain method for quantitative reconstruction of the complex shear modulus, estimated from the tracked displacement of the embedded spherical scatterer. This study also established a methodology for independent experimental verification of estimated material properties using rheometer measurements. The second study presents a technique for shear-wave imaging using a vibrating needle source for shear wave excitation. An advantage of such an approach is extended bandwidth of the measurement and a well-defined shear wave propagation that can be advantageous in the complex shear modulus reconstruction. This method was used to explore viscoelastic mechanisms in liver tissue and to explore different modeling approaches. It was found that the shear dynamic viscosity provides more contrast in imaging thermal damage in porcine liver, as compared to the shear elastic modulus. The third study was to develop an FDTD 3D viscoelastic solver capable of accurate modeling of shear wave propagation in heterogeneous media. Numerical results are experimentally validated. Furthermore, this numerical framework is used to study complex modulus imaging, specifically a direct algebraic Helmholtz inversion. The practical limitations and complex shear modulus reconstruction artifacts were studied, where it was found that distortions can be minimized simply by imaging the magnitude of the complex shear modulus. The final study was a recursive Bayesian solution to complex shear modulus reconstruction. A result of this is a stochastic filtering approach that uses a priori information about spatio-temporal dynamics of wave propagation to provide low variance estimates of the complex shear modulus. The stochastic filtering approach is studied both in simulation and experiments. The benefit of such an approach is low variance online reconstruction of the complex shear modulus per imaging frequency