Imaging Tumor Microenvironment with Ultrasound

Sridhar, Mallika; Insana, Michael F.

doi:10.1007/11505730_43

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…However preliminary results have shown that T 1 in normal breast tissue is on the order of 3 s and T 2 is of order 60 s (Sridhar et al 2006a), and the viscoelastic amplitudes ε 1 and ε 2 are several times greater than for gelatin. Together these findings help explain why we have been able to obtain T 1 images in breast patient studies with 20 s acquisitions but not T 2 (Sridhar and Insana 2005).…”

Section: Acquisition Time and Contrastmentioning

confidence: 55%

“…The polysaccharide gel plays a major role in determining the viscoelastic properties of the stroma and is responsible for material properties (Fung 1993, Gordenne et al 1985, Stoeckelhuber et al 2002. Gelatin does not have a polysaccharide gel, and yet its mechanical properties can be adjusted to approximate those of soft tissues by adding chemical cross-linkers (Madsen et al 2005) or by adjusting pH to vary the ionic concentration (Sridhar and Insana 2005). In addition, gelatin properties are much more sensitive to thermal and mechanical histories (Ward andCourts 1977, Hoffman 1991) than living stroma because the aggregate structure of denatured collagen molecules in gelatin is less stable than the triple helical structure of collagen in stromal ECM.…”

Section: Introductionmentioning

confidence: 99%

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Viscoelasticity imaging using ultrasound: parameters and error analysis

Sridhar¹,

Liu²,

Insana³

2007

Phys. Med. Biol.

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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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Section: Acquisition Time and Contrastmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Viscoelasticity imaging using ultrasound: parameters and error analysis

Sridhar¹,

Liu²,

Insana³

2007

Phys. Med. Biol.

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“…10 However, this method is prone to error in noisy conditions. In the works of Sridhar et al, [14][15][16] the authors used a traditional curve peeling/stripping method first, and then fine-tuned the obtained estimates using a nonlinear Gauss-Newton fitting technique blended with the LM method. In another work, 17 they estimated the strain TC and steady-state values searching poles and zeros in the Laplace domain.…”

Section: Introductionmentioning

confidence: 99%

A Spline Interpolation–based Data Reconstruction Technique for Estimation of Strain Time Constant in Ultrasound Poroelastography

Islam

Righetti

2020

Ultrason Imaging

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Ultrasound poroelastography is a cost-effective non-invasive imaging technique, which is able to reconstruct several mechanical parameters of cancer and normal tissue such as Young's modulus, Poisson's ratio, interstitial permeability and vascular permeability. To estimate the permeabilities, estimation of the strain time constant (TC) is required, which is a challenging task because of non-linearity of the exponential strain curve and noise present in the experimental data. Moreover, noise in many strain frames becomes very high because of motion artifacts from the sonographer, animal/patient and/or the environment. Therefore, using these frames in computation of strain TC can lead to inaccurate estimates of the mechanical parameters. In this letter, we introduce a cubic spline based interpolation method, which uses only the good frames (frame of high SNR) to reconstruct the information of the bad frames (frames of low SNR) and estimate the strain TC. We prove with finite element simulation that the proposed reconstruction method can improve the estimation accuracy of the strain TC by 46% in comparison to the estimates from noisy data, and 37% in comparison to the estimates from Kalman filtered data at an SNR of 30 dB. Based on the high accuracy of the proposed method in estimating strain TC from poroelastography data, the proposed method can be preferred technique by the clinicians and researchers interested in non-invasive imaging of tissue mechanical parameters.

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“…Lesion areas are brighter, indicating that mechanisms take longer due to the increased collagen density when compared to softer background areas. ϵ 0 , T 1 , and T 2 are the three parameters currently used for viscoelastic imaging [46]. The measurements of Fig.…”

Section: Image Contrastmentioning

confidence: 99%

“…Method A is often used to acquire time sequences of axial strain images ϵ 11 (x,t) by flush mounting a linear array transducer into the compression plate [46], as shown in Fig. 5(a).…”

Section: Viscoelastic Measurement Techniquesmentioning

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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Imaging Tumor Microenvironment with Ultrasound

Cited by 5 publications

References 19 publications

Viscoelasticity imaging using ultrasound: parameters and error analysis

Viscoelasticity imaging using ultrasound: parameters and error analysis

A Spline Interpolation–based Data Reconstruction Technique for Estimation of Strain Time Constant in Ultrasound Poroelastography

Elasticity Imaging of Polymeric Media

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