Viscoelasticity imaging using ultrasound: parameters and error analysis.
TL;DR: The focus of this paper is on imaging parameter estimation from ultrasonic echo data, and how jitter from hand-held force applicators used for clinical applications propagate through the imaging chain to generate image noise.
Abstract: Techniques are being developed to image viscoelastic features of soft tissues from time-varying strain. A compress-hold-release stress stimulus commonly used in creep-recovery measurements is applied to samples to form images of elastic strain and strain retardance times. While the intended application is diagnostic breast imaging, results in gelatin hydrogels are presented to demonstrate the techniques. The spatiotemporal behaviour of gelatin is described by linear viscoelastic theory formulated for polymeric solids. Measured creep responses of polymers are frequently modelled as sums of exponentials whose time constants describe the delay or retardation of the full strain response. We found the spectrum of retardation times τ to be continuous and bimodal, where the amplitude at each τ represents the relative number of molecular bonds with a given strength and conformation. Such spectra indicate that the molecular weight of the polymer fibres between bonding points is large. Imaging parameters are found by summarizing these complex spectral distributions at each location in the medium with a second-order Voigt rheological model. This simplification reduces the dimensionality of the data for selecting imaging parameters while preserving essential information on how the creeping deformation describes fluid flow and collagen matrix restructuring in the medium. The focus of this paper is on imaging parameter estimation from ultrasonic echo data, and how jitter from hand-held force applicators used for clinical applications propagate through the imaging chain to generate image noise.
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TL;DR: Current approaches to elastography in three areas are reviewed--quasi-static, harmonic and transient--and inversion schemes for each elastographic imaging approach are described, with a focus on first-order approximation methods for linear elastic methods and isotropic materials and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior.
Abstract: Elastography is emerging as an imaging modality that can distinguish normal versus diseased tissues via their biomechanical properties. This paper reviews current approaches to elastography in three areas—quasi-static, harmonic and transient—and describes inversion schemes for each elastographic imaging approach. Approaches include first-order approximation methods; direct and iterative inversion schemes for linear elastic; isotropic materials and advanced reconstruction methods for recovering parameters that characterize complex mechanical behavior. The paper's objective is to document efforts to develop elastography within the framework of solving an inverse problem, so that elastography may provide reliable estimates of shear modulus and other mechanical parameters. We discuss issues that must be addressed if model-based elastography is to become the prevailing approach to quasi-static, harmonic and transient elastography: (1) developing practical techniques to transform the ill-posed problem with a well-posed one; (2) devising better forward models to capture the complex mechanical behavior of soft tissues and (3) developing better test procedures to evaluate the performance of modulus elastograms.
295 citations
Cites background or methods from "Viscoelasticity imaging using ultra..."
...Sridhar et al (2007a) used a three-parameter Kelvin–Vogit rheological model to predict the strain response at each pixel within the time-varying strain elastogram....
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...Sridhar et al (2007a, 2007b) developed an elastographic imaging approach for characterizing viscoelastic materials....
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TL;DR: By anatomically mapping the regional variation stiffness with micron resolution, it may be possible to provide new insight into the complex by which engineered and natural tissues develop complex structures.
Abstract: Biomechanical elastic properties are among the many variables used to characterize in vivo and in vitro tissues. Since these properties depend largely on the micro- and macroscopic structural organization tissue, it is crucial to understand the mechanical properties and the alterations that occur tissues respond to external forces or to disease processes. Using a novel technique called coherence elastography (OCE), we mapped the spatially distributed mechanical displacements strains in a representative model of a developing, engineered tissue as cells began to proliferate attach within a three-dimensional collagen matrix. OCE was also performed in the complex tissue of the Xenopus laevis (African frog) tadpole. Displacements were quantified a cross-correlation algorithm on pre- and postcompression images, which were acquired using coherence tomography (OCT). The images of the engineered tissue were acquired over a 10-development period to observe the relative strain differences in various regions. OCE was able differentiate changes in strain over time, which corresponded with cell proliferation and matrix as confirmed with histological observations. By anatomically mapping the regional variation stiffness with micron resolution, it may be possible to provide new insight into the complex by which engineered and natural tissues develop complex structures.
130 citations
TL;DR: 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 is proposed.
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.
125 citations
Cites background or methods from "Viscoelasticity imaging using ultra..."
...…viscoelasticity instead of pure elasticity (Catheline et al 2004, Chen et al 2004, Sinkus et al 2005, Salameh et al 2007, Sridhar and Insana 2007, Sridhar et al 2007, Huwart et al 2007, Sack et al 2008, Vappou et al 2008, Deffieux et al 2009), allowing therefore to measure viscoelastic…...
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...…measure the parameters of viscoelastic rheological models (e.g., Kelvin–Voigt) using the velocity of the shear wave at different frequencies (Catheline et al 2004, Chen et al 2004, Deffieux et al 2009) or using the creep response of the tested material (Sridhar and Insana 2007, Sridhar et al 2007)....
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TL;DR: Characterization of nonpalpable breast lesions is improved by the addition of viscoelastic strain imaging parameters, and the differentiation of malignant and benign BI-RADS 4 or 5 tumors is especially evident with the use of the retardation time estimates, T(1).
103 citations
Cites background or result from "Viscoelasticity imaging using ultra..."
...Very similar results were found in VE phantom studies where hydropolymer density was locally increased (19)....
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...first-order discrete Kelvin-Voigt rheologic model (9,19) is Figure 1....
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...dropolymer phantoms (19) over much longer acquisition...
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TL;DR: Comparing in vivo breast measurements with those in gelatin hydrogels, preliminary ideas regarding the mechanisms for viscoelastic contrast are emerging.
Abstract: In vivo measurements of the viscoelasticproperties of breast tissue are described. Ultrasonic echo frames were recorded from volunteers at 5 fps while applying a uniaxial compressive force ( 1 – 20 N ) within a 1 s ramp time and holding the force constant for up to 200 s . A time series of strain images was formed from the echo data, spatially averaged viscouscreep curves were computed, and viscoelastic strain parameters were estimated by fitting creep curves to a second-order Voigt model. The useful strain bandwidth from this quasi-static ramp stimulus was 10 − 2 ⩽ ω ⩽ 10 0 rad ∕ s ( 0.0016 – 0.16 Hz ) . The stress-strain curves for normal glandular tissues are linear when the surface force applied is between 2 and 5 N . In this range, the creep response was characteristic of biphasic viscoelastic polymers, settling to a constant strain (arrheodictic) after 100 s . The average model-based retardance time constants for the viscoelastic response were 3.2 ± 0.8 and 42.0 ± 28 s . Also, the viscoelastic strain amplitude was approximately equal to that of the elastic strain. Above 5 N of applied force, however, the response of glandular tissue became increasingly nonlinear and rheodictic, i.e., tissuecreep never reached a plateau. Contrasting in vivo breast measurements with those in gelatin hydrogels, preliminary ideas regarding the mechanisms for viscoelasticcontrast are emerging.
68 citations
References
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TL;DR: In this paper, Monte Carlo techniques are used to fit dependent and independent variables least squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Abstract: Uncertainties in measurements probability distributions error analysis estimates of means and errors Monte Carlo techniques dependent and independent variables least-squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood. Appendices: numerical methods matrices graphs and tables histograms and graphs computer routines in Pascal.
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01 Jan 1961
TL;DR: In this article, the authors describe the nature of Viscoelastic behavior of polymeric systems and approximate relations among the linear Viscoels and approximate interrelations among the Viscelastic Functions.
Abstract: The Nature of Viscoelastic Behavior. Illustrations of Viscoelastic Behavior of Polymeric Systems. Exact Interrelations among the Viscoelastic Functions. Approximate Interrelations among the Linear Viscoelastic Functions. Experimental Methods for Viscoelastic Liquids. Experimental Methods for Soft Viscoelastic Solids and Liquids of High Viscosity. Experimental Methods for Hard Viscoelastic Solids. Experimental Methods for Bulk Measurements. Dilute Solutions: Molecular Theory and Comparisons with Experiments. Molecular Theory for Undiluted Amorphous Polymers and Concentrated Solutions Networks and Entanglements. Dependence of Viscoelastic Behavior on Temperature and Pressure. The Transition Zone from Rubberlike to Glasslike Behavior. The Plateau and Terminal Zones in Uncross-Linked Polymers. Cross-Linked Polymers and Composite Systems. The Glassy State. Crystalline Polymers. Concentrated Solutions, Plasticized Polymers, and Gels. Viscoelastic Behavior in Bulk (Volume) Deformation. Applications to Practical Problems. Appendices. Author & Subject Indexes.
12,676 citations
TL;DR: Numerical methods matrices graphs and tables histograms and graphs computer routines in Pascal and Monte Carlo techniques dependent and independent variables least-squares fit to a polynomial least-square fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood.
Abstract: Uncertainties in measurements probability distributions error analysis estimates of means and errors Monte Carlo techniques dependent and independent variables least-squares fit to a polynomial least-squares fit to an arbitrary function fitting composite peaks direct application of the maximum likelihood. Appendices: numerical methods matrices graphs and tables histograms and graphs computer routines in Pascal.
10,546 citations
Book•
01 Jul 1981TL;DR: This chapter discusses the mechanics of Erythrocytes, Leukocytes, and Other Cells, and their role in Bone and Cartilage, and the properties of Bioviscoelastic Fluids, which are a by-product of these cells.
Abstract: Prefaces. 1. Introduction: A sketch of the History and Scope of the Field. 2. The Meaning of the Constitutive Equation. 3. The Flow Properties of Blood. 4. Mechanics of Erythrocytes, Leukocytes, and Other Cells. 5. Interaction of Red Blood Cells with Vessel Wall, and Wall Shear with Endothelium. 6 Bioviscoelastic Fluids. Bioviscoelastic Solids. 8. Mechanical Properties and Active Remodeling of Blood Vessels. 9. Skeletal Muscle. 10. Heart Muscle. 11. Smooth Muscles. 12. Bone and Cartilage. Indices
6,027 citations
TL;DR: In this article, the authors present a sketch of the history and scope of the field of bio-physiology and discuss the meaning of the Constitutive Equation and the flow properties of blood.
Abstract: Prefaces. 1. Introduction: A sketch of the History and Scope of the Field. 2. The Meaning of the Constitutive Equation. 3. The Flow Properties of Blood. 4. Mechanics of Erythrocytes, Leukocytes, and Other Cells. 5. Interaction of Red Blood Cells with Vessel Wall, and Wall Shear with Endothelium. 6 Bioviscoelastic Fluids. Bioviscoelastic Solids. 8. Mechanical Properties and Active Remodeling of Blood Vessels. 9. Skeletal Muscle. 10. Heart Muscle. 11. Smooth Muscles. 12. Bone and Cartilage. Indices
3,670 citations