Analytical Estimation of Out-of-plane Strain in Ultrasound Elastography to Improve Axial and Lateral Displacement Fields*

Many types of cancers are associated with changes in tissue mechanical properties. This has led to the development of elastography as a clinically viable method where tissue mechanical properties are mapped and visualized for cancer detection and staging. In quasi-static ultrasound elastography, a mechanical stimulation is applied to the tissue using ultrasound probe. Using ultrasound radiofrequency (RF) data acquired before and after the stimulation, the tissue displacement field can be estimated. Elasticity image reconstruction algorithms use this displacement data to generate images of the tissue elasticity properties. The accuracy of the generated elasticity images depends highly on the accuracy of the tissue displacement estimation. Tissue incompressibility can be used as a constraint to improve the estimation of axial and, more importantly, the lateral displacements in 2D ultrasound elastography. Especially in clinical applications, this requires accurate estimation of the out-of-plane strain. Here, we propose a method for providing an accurate estimate of the out-of-plane strain which is incorporated in the incompressibility equation to improve the axial and lateral displacements estimation before elastography image reconstruction. The method was validated using in silico and tissue mimicking phantom studies, leading to significant improvement in the estimated displacement.

[1]  Hassan Rivaz,et al.  Global Time-Delay Estimation in Ultrasound Elastography , 2017, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[2]  J Ophir,et al.  Precision estimation and imaging of normal and shear components of the 3D strain tensor in elastography. , 2000, Physics in medicine and biology.

[3]  A. Oberai,et al.  The Coupled Adjoint-State Equation in forward and inverse linear elasticity: Incompressible plane stress , 2019 .

[4]  K. R. Raghavan,et al.  Lateral displacement estimation using tissue incompressibility , 1996, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[5]  Hassan Rivaz,et al.  Global Ultrasound Elastography in Spatial and Temporal Domains , 2019, IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control.

[6]  Hassan Rivaz,et al.  Breast Ultrasound Elastography Using Full Inversion-Based Elastic Modulus Reconstruction , 2017, IEEE Transactions on Computational Imaging.

[7]  J. Jensen,et al.  A new method for estimation of velocity vectors , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[8]  Abbas Samani,et al.  An iterative hyperelastic parameters reconstruction for breast cancer assessment , 2008, SPIE Medical Imaging.

[9]  Gregory D. Hager,et al.  Real-Time Regularized Ultrasound Elastography , 2011, IEEE Transactions on Medical Imaging.

[10]  M.E. Aderson,et al.  Multi-dimensional velocity estimation with ultrasound using spatial quadrature , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[11]  D. Ennis,et al.  Analytical method to measure three-dimensional strain patterns in the left ventricle from single slice displacement data , 2010, Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance.

[12]  Abbas Samani,et al.  A method to measure the hyperelastic parameters of ex vivo breast tissue samples. , 2004, Physics in medicine and biology.