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Ultrasound viscoelasticity assessment using an adaptive torsional shear wave propagation method
Author(s) -
Ouared Abderrahmane,
Kazemirad Siavash,
Montag Emmanuel,
Cloutier Guy
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4942813
Subject(s) - viscoelasticity , shear modulus , elastography , robustness (evolution) , finite element method , elasticity (physics) , isotropy , inverse problem , shear waves , rheology , acoustics , materials science , shear (geology) , mathematics , mathematical analysis , ultrasound , physics , optics , structural engineering , composite material , engineering , biochemistry , chemistry , gene
Purpose: Different approaches have been used in dynamic elastography to assess mechanical properties of biological tissues. Most techniques are based on a simple inversion based on the measurement of the shear wave speed to assess elasticity, whereas some recent strategies use more elaborated analytical or finite element method (FEM) models. In this study, a new method is proposed for the quantification of both shear storage and loss moduli of confined lesions, in the context of breast imaging, using adaptive torsional shear waves (ATSWs) generated remotely with radiation pressure. Methods: A FEM model was developed to solve the inverse wave propagation problem and obtain viscoelastic properties of interrogated media. The inverse problem was formulated and solved in the frequency domain and its robustness to noise and geometric constraints was evaluated. The proposed model was validated in vitro with two independent rheology methods on several homogeneous and heterogeneous breast tissue‐mimicking phantoms over a broad range of frequencies (up to 400 Hz). Results: Viscoelastic properties matched benchmark rheology methods with discrepancies of 8%–38% for the shear modulus G ′ and 9%–67% for the loss modulus G ″. The robustness study indicated good estimations of storage and loss moduli (maximum mean errors of 19% on G ′ and 32% on G ″) for signal‐to‐noise ratios between 19.5 and 8.5 dB. Larger errors were noticed in the case of biases in lesion dimension and position. Conclusions: The ATSW method revealed that it is possible to estimate the viscoelasticity of biological tissues with torsional shear waves when small biases in lesion geometry exist.