Viscoelasticity imaging using ultrasound: parameters and error analysis.

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 tau to be continuous and bimodal, where the amplitude at each tau 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.

[1]  T. Krouskop,et al.  Phantom materials for elastography , 1997, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[2]  T. Varghese,et al.  Tissue-mimicking agar/gelatin materials for use in heterogeneous elastography phantoms , 2005, Physics in medicine and biology.

[3]  S. Boppart,et al.  Optical coherence elastography of engineered and developing tissue. , 2006, Tissue engineering.

[4]  Michael F Insana,et al.  Elasticity imaging of polymeric media. , 2007, Journal of biomechanical engineering.

[5]  V. Normand,et al.  Dynamic study of gelatin gels by creep measurements , 1997 .

[6]  Helmut Ermert,et al.  An ultrasound research interface for a clinical system. , 2006, IEEE transactions on ultrasonics, ferroelectrics, and frequency control.

[7]  S Van Huffel,et al.  Improved Lanczos algorithms for blackbox MRS data quantitation. , 2002, Journal of magnetic resonance.

[8]  A. G. Ward The physical properties of gelatin solutions and gels , 1954 .

[9]  Y. Fung,et al.  Biomechanics: Mechanical Properties of Living Tissues , 1981 .

[10]  Mickael Tanter,et al.  Viscoelastic shear properties of in vivo breast lesions measured by MR elastography. , 2005, Magnetic resonance imaging.

[11]  M. Bilgen,et al.  Elastostatics of a spherical inclusion in homogeneous biological media. , 1998, Physics in medicine and biology.

[12]  P. R. Bevington,et al.  Data Reduction and Error Analysis for the Physical Sciences , 1969 .

[13]  A. Manduca,et al.  MR elastography of breast cancer: preliminary results. , 2002, AJR. American journal of roentgenology.

[14]  S. Huffel,et al.  MR spectroscopy quantitation: a review of time‐domain methods , 2001, NMR in biomedicine.

[15]  C. S. Spalding,et al.  In vivo real-time freehand palpation imaging. , 2003, Ultrasound in medicine & biology.

[16]  U. Welsch,et al.  Proteoglycan–collagen associations in the non-lactating human breast connective tissue during the menstrual cycle , 2002, Histochemistry and Cell Biology.

[17]  T. Krouskop,et al.  Elastic Moduli of Breast and Prostate Tissues under Compression , 1998, Ultrasonic imaging.

[18]  K. Parker,et al.  Sono-Elasticity: Medical Elasticity Images Derived from Ultrasound Signals in Mechanically Vibrated Targets , 1988 .

[19]  A. John Mallinckrodt,et al.  Data Reduction and Error Analysis for the Physical Sciences , 1993 .

[20]  G A Losa,et al.  Sulfated proteoglycans in the extracellular matrix of human breast tissues with infiltrating carcinoma , 1993, International journal of cancer.

[21]  Michael F. Insana,et al.  Viscoelastic Imaging of Breast Tumor Microenvironment With Ultrasound , 2004, Journal of Mammary Gland Biology and Neoplasia.

[22]  N. Tschoegl The Phenomenological Theory of Linear Viscoelastic Behavior , 1989 .

[23]  P. M. Gilsenan,et al.  Shear creep of gelatin gels from mammalian and piscine collagens. , 2001, International journal of biological macromolecules.

[24]  I Céspedes,et al.  Fundamental mechanical limitations on the visualization of elasticity contrast in elastography. , 1995, Ultrasound in medicine & biology.

[25]  Michael F. Insana,et al.  Ultrasonic Elasticity Imaging as a Tool for Breast Cancer Diagnosis and Research , 2006 .

[26]  W. M. Carey,et al.  Digital spectral analysis: with applications , 1986 .

[27]  William F. Walker,et al.  Significance of correlation in ultrasound signal processing , 2001, SPIE Medical Imaging.

[28]  P. Higgs,et al.  Creep measurements on gelatin gels. , 1990, International journal of biological macromolecules.

[29]  Helmut Schiessel,et al.  Hierarchical analogues to fractional relaxation equations , 1993 .

[30]  J. Ferry Viscoelastic properties of polymers , 1961 .

[31]  Gregg E. Trahey,et al.  Acoustic radiation force impulse imaging of in vivo breast masses , 2004 .

[32]  Jack H. Freed,et al.  Rapid singular value decomposition for time-domain analysis of magnetic resonance signals by use of the lanczos algorithm , 1989 .

[33]  G. Adam,et al.  Menstrual-Cycle Dependence of Breast Parenchyma Elasticity: Estimation With Magnetic Resonance Elastography of Breast Tissue During the Menstrual Cycle , 2003, Investigative radiology.

[34]  M. O’Donnell,et al.  Internal displacement and strain imaging using ultrasonic speckle tracking , 1994, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[35]  J. Greenleaf,et al.  Selected methods for imaging elastic properties of biological tissues. , 2003, Annual review of biomedical engineering.

[36]  Michael F. Insana,et al.  Imaging Tumor Microenvironment with Ultrasound , 2005, IPMI.

[37]  B. Garra,et al.  Elastography of breast lesions: initial clinical results. , 1997, Radiology.

[38]  Alan S. Stern,et al.  NMR Data Processing , 1996 .

[40]  P. Chaturvedi,et al.  Testing the limitations of 2-D companding for strain imaging using phantoms , 1998, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[41]  Armen P. Sarvazyan,et al.  Mechanical imaging: : A new technology for medical diagnostics , 1998, Int. J. Medical Informatics.

[42]  J. Greenleaf,et al.  Ultrasound-stimulated vibro-acoustic spectrography. , 1998, Science.

[43]  J. Ophir,et al.  Elastography: A Quantitative Method for Imaging the Elasticity of Biological Tissues , 1991, Ultrasonic imaging.

[44]  R. Bagley,et al.  A Theoretical Basis for the Application of Fractional Calculus to Viscoelasticity , 1983 .

[45]  A. J. Staverman,et al.  Higher approximation methods for the relaxation spectrum from static and dynamic measurements of visco-elastic materials , 1953 .