Experimental reverse time migration for imaging of elasticity changes

Recent studies have shown stiffness is an relevant tissue property to monitor during High Intensity Focused Ultrasound (HIFU) treatments. Tissue stiffness is temperature-dependant but also a major indicator of thermal necrosis. Shear Wave Imaging can be used to map stiffness changes in 2D, but current inverse problem limits the spatial resolution and contrast of elasticity maps. The aim of this study is to revisit the migration theory used in geophysics for elasticity imaging. Here, we demonstrate the feasibility of a new inverse problem of elastodynamics based on the experimental application of Reverse Time Migration (RTM) technique for the monitoring of elasticity changes. First, simulations have been performed using a 3D finite differences Virieux scheme of the viscoelastic wave equation (ACEL). The propagation of elastic plane waves is investigated first in a reference homogeneous non-viscous medium and secondly when adding a gaussian inclusion (3% to 60% shear wave speed contrast). Here, the Tarantola's adjoint method consists in time-reversing the difference of the two successively generated shear waves (before and after heating) in the medium. The inversion is done by time-correlating the forward and the adjoint solution. Second, experiments were performed using a tungsten wire (125 μm diameter) as a heating source in gelatin phantoms to decrease the local stiffness. The Supersonic Shear Imaging (SSI) technique gives access experimentally to the movie of 2D propagation of the wave before and while heating. Each wave was created by 3 pushing beams of lOOμs and their propagation was acquired at 10kHz using a commercial ultrasound scanner (Aixplorer, Supersonic Imagine) and a 8MHz probe. Acquisitions were performed every 40s during 20nιin of heating and data were processed offline. RTM was able to achieve inversion of shear wave propagation. We show that it can solve this optimization problem with a single-iteration in homogeneous media. This new method is more accurate than the time-of-flight (TOF) inversion algorithm. Spatial resolution is improved (factor 2). Simulations and experimental results show a very good recovery of the inclusion elasticity for different size and amplitude.