Ultrasonic mechanical relaxation imaging and the material science of breast cancer

Insana, Michael F.; Liu, Jie; Sridhar, Mallika; Pellot‐Barakat, Claire

doi:10.1109/ultsym.2005.1602957

Cited by 5 publications

(7 citation statements)

References 6 publications

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“…This appearance is rather typical of a malignant lesion. However the T 1 retardance time image displays longer T 1 values in the lesion area, which is consistent with normal collagen from a benign lesion [14]. Pathology showed the lesion is a benign fibroademoma.…”

Section: B Patient Resultssupporting

confidence: 60%

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2J-4 In-Vivo Imaging of Breast Tissue Viscoelasticity

Sridhar¹,

Tsou²,

Insana³

2006

2006 IEEE Ultrasonics Symposium

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Viscoelastic imaging techniques are being developed to measure mechanical features of breast tissues using standard ramp-and-hold stimuli for creep measurements. This paper discusses a 3-person volunteer study to detail experimental methods used to measure breast viscoelasticity. It also summarizes our recent clinical data with 25 breast mass patients.We use a linear array transducer mounted to a surface force sensor to apply a ramp-and-hold force to the breast surface while recording RF frames at 2 fps. In particular we determine (a) the linear range of breast tissue deformation, (b) our ability to apply and hold a constant force for up to 200 s with and without force feedback, and (c) characteristics of viscoelastic creep in breast tissue, all using a new scanning technique that allows for normal breathing with minimal artifacts.Linear responses were observed for breast up to 4% strain. Below 5N of applied force, the creep response displayed classical arrheodictic behavior of polymer solids, settling to a constant strain after 100 s. We model the creep response as the sum of many exponentials that can be parameterized by a loworder Voigt model to obtain the retardation times, T1=3.2±0.8 s and T2=42.0±28 s for normal breast tissue. The magnitude of creep is equivalent to the initial elastic response and hence is not significantly affected by small systematic errors in the stimulus. Newer scan techniques therefore extend acquisition times an order of magnitude to increase the model order and the information content.

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Section: B Patient Resultssupporting

confidence: 60%

“…We have shown previously [13] that this method can describe the spatial distribution of tissue-mimicking hydro-polymers like gelatin. We also showed in [14] with one illustrative clinical example the potential of viscoelastic imaging to reflect disease specific changes in the extracellular matrix.…”

Section: Introductionmentioning

confidence: 89%

2J-4 In-Vivo Imaging of Breast Tissue Viscoelasticity

Sridhar¹,

Tsou²,

Insana³

2006

2006 IEEE Ultrasonics Symposium

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“…G(s) and K(s) are shear and bulk moduli, respectively; they are analogous to the compliances J(s) and B(s) measured in creep. If the sample boundaries are confined in the manner described in Method B below, then there is only one nonzero strain tensor (19) Equation (19) relates the measurable compressive longitudinal wave modulus M̃ for the confined sample to fundamental relaxation moduli K̃ and G̃ in the Laplace domain [23].…”

Section: Uniaxial Compressive Strain: Stress Relaxation and Relaxatiomentioning

confidence: 99%

“…However, cancers can also appear softer than the background tissue [17] because the magnitude, spatial homogeneity, and temporal variation of the strain response depend on the physiology [18] and tumor microenvironment [6] of a specific patient. In addition, images of viscoelastic features show both lower [19] and higher [2,3] respondance times for malignant masses as compared to benign masses. Although electron microscopy data show changes in the connective tissue ultrastructure [20] that suggest lower viscosity, not enough is known about the viscoelastic behavior of breast tissues in vivo to determine if the diversity of findings are due to patient or experimental variabilities.…”

Section: Introductionmentioning

confidence: 99%

Elasticity Imaging of Polymeric Media

Sridhar

Liu

Insana

2006

Journal of Biomechanical Engineering

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Viscoelastic properties of soft tissues and hydropolymers depend on the strength of molecular bonding forces connecting the polymer matrix and surrounding fluids. The basis for diagnostic imaging is that disease processes alter molecular-scale bonding in ways that vary the measurable stiffness and viscosity of the tissues. This paper reviews linear viscoelastic theory as applied to gelatin hydrogels for the purpose of formulating approaches to molecular-scale interpretation of elasticity imaging in soft biological tissues. Comparing measurements acquired under different geometries, we investigate the limitations of viscoelastic parameters acquired under various imaging conditions. Quasistatic (step-and-hold and low-frequency harmonic) stimuli applied to gels during creep and stress relaxation experiments in confined and unconfined geometries reveal continuous, bimodal distributions of respondance times. Within the linear range of responses, gelatin will behave more like a solid or fluid depending on the stimulus magnitude. Gelatin can be described statistically from a few parameters of low-order rheological models that form the basis of viscoelastic imaging. Unbiased estimates of imaging parameters are obtained only if creep data are acquired for greater than twice the highest retardance time constant and any steady-state viscous response has been eliminated. Elastic strain and retardance time images are found to provide the best combination of contrast and signal strength in gelatin. Retardance times indicate average behavior of fast (1-10 s) fluid flows and slow (50-400 s) matrix restructuring in response to the mechanical stimulus. Insofar as gelatin mimics other polymers, such as soft biological tissues, elasticity imaging can provide unique insights into complex structural and biochemical features of connectives tissues affected by disease.

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“…If we consider only the axial displacement and a one-dimensional (1D) model, the reciprocal of the quasi-static axial strain can be interpreted as the local elasticity. The viscosity or the relaxation time can be estimated by using a model that predicts the displacement or strain as a function of frequency (Insana et al 2005, Turgay et al 2006, Eskandari et al 2008, Sridhar et al 2007. The moduli reconstructed using 1D models suffer from artifacts, because the effect of the boundary conditions on strain is not decoupled from the effect of material properties.…”

Section: Introductionmentioning

confidence: 99%

Viscoelastic characterization of soft tissue from dynamic finite element models

et al. 2008

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An iterative solution to the inverse problem of elasticity and viscosity is proposed in this paper. A new dynamic finite element model that is consistent with known rheological models has been derived to account for the viscoelastic changes in soft tissue. The model assumes known lumped masses at the nodes, and comprises two vectors of elasticity and viscosity parameters that depend on the material elasticity and viscosity distribution, respectively. Using this deformation model and the observed dynamic data for harmonic excitation, the inverse problem is solved to reconstruct the viscosity and elasticity in the medium by using a Gauss-Newton-based approach. As in other inverse problems, previous knowledge of the parameters on the boundaries of the medium is necessary to assure uniqueness and convergence and to obtain an accurate map of the viscoelastic properties. The sensitivity of the solutions to noise, model and boundary conditions has been studied through numerical simulations. Experimental results are also presented. The viscosity and elasticity of a gelatin-based phantom with inclusion of known properties have been reconstructed and have been shown to be close to the values obtained using standard rheometry.

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Ultrasonic mechanical relaxation imaging and the material science of breast cancer

Cited by 5 publications

References 6 publications

2J-4 In-Vivo Imaging of Breast Tissue Viscoelasticity

2J-4 In-Vivo Imaging of Breast Tissue Viscoelasticity

Elasticity Imaging of Polymeric Media

Viscoelastic characterization of soft tissue from dynamic finite element models

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