Wang, Yuqi

Current clinically used ultrasound elastography is obtained when tissue undergoes small deformation (<2% strain). However, small deformation may not be large enough to characterize tissues that exhibit similar elasticity properties to normal tissue at small deformation but behave differently from normal tissue at large deformation (>10% strain). Therefore, tissue elasticity properties measured at large deformation may provide better diagnostic differentiation. Combining the quasi-static and shear wave ultrasound elastography methods, we propose a noninvasive method to estimate the nonlinear elasticity property of tissue. To test this method, cubic tissue-mimicking phantoms were constructed. We progressively compressed the phantom to produce a series of stepwise stress states. At every stress state, we conducted shear wave measurements in which two acoustic radiation force pushes generated shear waves, which were measured using ultrafast imaging in order to estimate the local shear modulus. For every compression step, we tracked incremental tissue displacements between two successive frames and then accumulated these displacements for all steps to obtain the cumulative displacements and strains. Using the shear modulus and cumulative strain images we calculated the stress map under an incompressibility assumption. Finally, we obtained the local stress-strain curve that reflected the nonlinear elasticity of the tested material.

Compression elastography allows the precise measurement of large deformations of soft tissue in vivo. From a measured large deformation, an inverse problem for both the linear and nonlinear elastic moduli distributions can be solved. As part of a larger clinical study to evaluate NEMs in breast cancer, we evaluate the repeatability of linear and nonlinear modulus maps from repeat measurements. Within the cohort of 31 subjects scanned to date, several had repeated scans. These repeated scans were processed to evaluate NEM repeatability. In vivo data were acquired by a custom, digitally controlled, uniaxial compression device with force feedback. RF-data were acquired using plane wave imaging, at a frame-rate of 200 Hz, with a ramp-and-hold compressive force of 8N, applied at 8 N/s. A two-dimensional (2D) block-matching algorithm was used to obtain sample-level displacement fields which were then tracked at subsample resolution using 2D cross correlation. Linear and nonlinear elasticity parameters in the Blatz model of tissue elasticity are estimated using iterative optimization. Repeatability between both modes and elastic modulus maps is measured and compared. Preliminary results indicate that when images are acquired in the same region of tissue, the modulus maps are consistent. [Work supported by NIH R01CA195527.]