title: Shear modulus reconstruction in dynamic elastography: time harmonic case.
abstract: This paper presents a direct inversion approach for reconstructing the elastic shear modulus in soft tissue from dynamic measurements of the interior displacement field during time harmonic excitation. The tissue is assumed to obey the equations of nearly incompressible, linear, isotropic elasto-dynamics in harmonic motion. A finite element discretization of the governing equations is used as a basis, and a procedure is outlined to eliminate the need for boundary conditions in the inverse problem. The hydrostatic stress (pressure) is also reconstructed in the process, and the effect of neglecting this term in the governing equations, which is common practice, is considered. The approach does not require iterations and can be performed on sub-regions of the domain resulting in a computationally efficient method. A sensitivity study is performed to investigate the detectability of abnormal regions of different size and shear modulus contrast from the background. The algorithm is tested on simulated data on a two-dimensional domain, where the data are generated on a very fine mesh to get a near exact solution, then downsampled to a coarser mesh that is similar to the spatial discretization of actual data, and noise is added. Results showing the effect of the hydrostatic stress term and noise are presented. A reconstruction using MR measured experimental data involving a tissue-mimicking phantom is also shown to demonstrate the algorithm.
authors.affiliation: Department of Mechanical, Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, New York 12180, USA. parke@rpi.edu
authors.forename: Eunyoung
authors.initials: E
authors.lastname: Park
authors.forename: Antoinette M
authors.initials: AM
authors.lastname: Maniatty
mesh_terms: D000465:Algorithms; D003952:Diagnostic Imaging / Q000295:instrumentation / Q000379:methods; D004548:Elasticity; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging; D015233:Models, Statistical; D019047:Phantoms, Imaging; D011312:Pressure; D012680:Sensitivity and Specificity; D013997:Time Factors