Shear elasticity and shear viscosity imaging in soft tissue
"In this thesis, a new approach is introduced that provides estimates of shear elasticity and shear viscosity using timedomain measurements of shear waves in viscoelastic media. Simulations of shear wave particle displacements induced by an acoustic radiation force are accelerated significantly by a GPU. The acoustic radiation force is first calculated using the fast near field method (FNM) and the angular spectrum approach (ASA). The shear waves induced by the acoustic radiation force are then simulated in elastic and viscoelastic media using Green's functions. A parallel algorithm is developed to perform these calculations on a GPU, where the shear wave particle displacements at different observation points are calculated in parallel. The resulting speed increase enables rapid evaluation of shear waves at discrete points, in 2D planes, and for push beams with different spatial samplings and for different values of the fnumber (f/#). The results of these simulations show that push beams with smaller f/# require a higher spatial sampling rate. The significant amount of acceleration achieved by this approach suggests that shear wave simulations with the Green's function approach are ideally suited for highperformance GPUs. Shear wave elasticity imaging determines the mechanical parameters of soft tissue by analyzing measured shear waves induced by an acoustic radiation force. To estimate the shear elasticity value, the widely used timeofflight (TOF) method calculates the correlation between shear wave particle velocities at adjacent lateral observation points. Although this method provides accurate estimates of the shear elasticity in purely elastic media, our experience suggests that the TOF method consistently overestimates the shear elasticity values in viscoelastic media because the combined effects of diffraction, attenuation, and dispersion are not considered. To address this problem, we have developed an approach that directly accounts for all of these effects when estimating the shear elasticity. This new approach simulates shear wave particle velocities using a Green's functionbased approach for the Voigt model, where the shear elasticity and viscosity values are estimated using an optimizationbased approach that compares measured shear wave particle velocities with simulated shear wave particle velocities in the timedomain. The results are evaluated on a pointbypoint basis to generate images. There is good agreement between the simulated and measured shear wave particle velocities, where the new approach yields much better images of the shear elasticity and shear viscosity than the TOF method. The new estimation approach is accelerated with an approximate viscoelastic Green's function model that is evaluated with shear wave data obtained from in vivo human livers. Instead of calculating shear waves with combinations of different shear elasticities and shear viscosities, shear waves are calculated with different shear elasticities on the GPU and then convolved with a viscous loss model, which accelerates the calculation dramatically. The shear elasticity and shear viscosity values are then estimated using an optimizationbased approach by minimizing the difference between measured and simulated shear wave particle velocities. Shear elasticity and shear viscosity images are generated at every spatial point in a twodimensional (2D) fieldofview (FOV). The new approach is applied to measured shear wave data obtained from in vivo human livers, and the results show that this new approach successfully generates shear elasticity and shear viscosity images from this data. The results also indicate that the shear elasticity values estimated with this approach are significantly smaller than the values estimated with the conventional TOF method and that the new approach demonstrates more consistent values for these estimates compared with the TOF method. This experience suggests that the new method is an effective approach for estimating the shear elasticity and the shear viscosity in liver and in other soft tissue."Pages iiiii.
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Electronic Theses & Dissertations
 Copyright Status
 AttributionNonCommercialShareAlike 4.0 International
 Material Type

Theses
 Authors

Yang, Yiqun
 Thesis Advisors

McGough, Robert J.
 Committee Members

Baek, Seungik
Feeny, Brian F.
Udpa, Lalita
 Date
 2018
 Subjects

ViscoelasticityMathematical models
Shear wavesMathematical models
Acoustic radiation force impulse imaging
Shear waves
Simulation methods
 Program of Study

Electrical Engineering  Doctor of Philosophy
 Degree Level

Doctoral
 Language

English
 Pages
 xviii, 137 pages
 ISBN

9780355673715
0355673711
 Permalink
 https://doi.org/doi:10.25335/4hmmq104