| Literature DB >> 19454785 |
Jonathan Vappou1, Caroline Maleke, Elisa E Konofagou.
Abstract
Quantifying the mechanical properties of soft tissues remains a challenging objective in the field of elasticity imaging. In this work, we propose an ultrasound-based method for quantitatively estimating viscoelastic properties, using the amplitude-modulated harmonic motion imaging (HMI) technique. In HMI, an oscillating acoustic radiation force is generated inside the medium by using focused ultrasound and the resulting displacements are measured using an imaging transducer. The proposed approach is a two-step method that uses both the properties of the propagating shear wave and the phase shift between the applied stress and the measured strain in order to infer to the shear storage (G') and shear loss modulus (G''), which refer to the underlying tissue elasticity and viscosity, respectively. The proposed method was first evaluated on numerical phantoms generated by finite-element simulations, where a very good agreement was found between the input and the measured values of G' and G''. Experiments were then performed on three soft tissue-mimicking gel phantoms. HMI measurements were compared to rotational rheometry (dynamic mechanical analysis), and very good agreement was found at the only overlapping frequency (10 Hz) in the estimate of the shear storage modulus G' (14% relative error, averaged p-value of 0.34), whereas poorer agreement was found in G'' (55% relative error, averaged p-value of 0.0007), most likely due to the significantly lower values of G'' of the gel phantoms, posing thus a greater challenge in the sensitivity of the method. Nevertheless, this work proposes an original model-independent ultrasound-based elasticity imaging method that allows for direct, quantitative estimation of tissue viscoelastic properties, together with a validation against mechanical testing.Mesh:
Year: 2009 PMID: 19454785 DOI: 10.1088/0031-9155/54/11/020
Source DB: PubMed Journal: Phys Med Biol ISSN: 0031-9155 Impact factor: 3.609