Literature DB >> 15313323

A quantitative comparison of modulus images obtained using nanoindentation with strain elastograms.

S Srinivasan1, T Krouskop, J Ophir.   

Abstract

Tissue stiffness is generally known to be associated with pathologic changes. Ultrasound (US) elastography, on the other hand, is capable of imaging tissue strain, which may or may not be well-correlated with tissue stiffness. Hence, a quantitative comparison between the elastographic tissue strain images and the corresponding tissue modulus images needed to be performed to evaluate the usefulness of elastography in imaging tissue stiffnesss properties. Simulations were performed to demonstrate and quantify the similarities between modulus images and strain elastograms. This was followed by comparing nanoindenter-based modulus images with strain elastograms of thin slices of tissue-mimicking phantoms. Finally, some beef slices, canine prostates, ovine kidneys and breast cancers grown in mice were used to demonstrate the qualitative correspondence between modulus images and strain elastograms. The simulations and the experiments indicated that it is feasible to perform quantitative comparisons between strain images (using elastography) and modulus images on certain tissue structures and geometries. A good quantitative correspondence (correlation values of greater than 0.8) between structures in the modulus and strain images could be obtained at scales equal to or larger than 20 Qlambda (where Q is the quality factor defined as the ratio of the center frequency over the band width and lambda is the wavelength of the US system) modulus contrasts larger than 5, applied strains between 0.5% and 3% and window lengths for computing strain elastograms between 3 Qlambda and 5 Qlambda. The gelatin-phantom experiments showed lower values of correlation (values around 0.5) than with theory and simulations. The decrease in correlation was attributed to the presence of measurement noise in both strain elastography and modulus imaging, an increase of dimensionality of the problem (from 2-D to 3-D), local anisotropy, heterogeneity and nonstationarity. Experiments on real tissue slices showed further decrease in the correlation to around 0.3, possibly due to additional confounding factors such as time-dependent mechanical properties and geometrical distortions in the tissue during imaging. The work presented in this paper demonstrates that there is an intrinsic relationship between strain elastograms and the actual distribution of soft tissue elastic moduli, and bodes well for continued work in the area of elastography.

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Year:  2004        PMID: 15313323     DOI: 10.1016/j.ultrasmedbio.2004.05.005

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  7 in total

1.  Quantifying local stiffness variations in radiofrequency ablations with dynamic indentation.

Authors:  Ryan J DeWall; Tomy Varghese; Christopher L Brace
Journal:  IEEE Trans Biomed Eng       Date:  2011-12-08       Impact factor: 4.538

2.  Soft tissue elastometer.

Authors:  V Egorov; S Tsyuryupa; S Kanilo; M Kogit; A Sarvazyan
Journal:  Med Eng Phys       Date:  2007-03-23       Impact factor: 2.242

3.  Measurement of the dynamic shear modulus of mouse brain tissue in vivo by magnetic resonance elastography.

Authors:  Stefan M Atay; Christopher D Kroenke; Arash Sabet; Philip V Bayly
Journal:  J Biomech Eng       Date:  2008-04       Impact factor: 2.097

Review 4.  Magnetic resonance elastography: a general overview of its current and future applications in brain imaging.

Authors:  Antonio Di Ieva; Fabio Grizzi; Elisa Rognone; Zion Tsz Ho Tse; Tassanai Parittotokkaporn; Ferdinando Rodriguez Y Baena; Manfred Tschabitscher; Christian Matula; Siegfrid Trattnig; Riccardo Rodriguez Y Baena
Journal:  Neurosurg Rev       Date:  2010-02-27       Impact factor: 3.042

5.  Modeling Ramp-hold Indentation Measurements based on Kelvin-Voigt Fractional Derivative Model.

Authors:  HongMei Zhang; QingZhe Zhang; LiTao Ruan; JunBo Duan; MingXi Wan; Michael F Insana; HongMei Zhang; QingZhe Zhang; LiTao Ruan; JunBo Duan; MingXi Wan; Michael F Insana
Journal:  Meas Sci Technol       Date:  2018-02-15       Impact factor: 2.046

6.  In-vitro Strain and Modulus Measurements in Porcine Cervical Lymph Nodes.

Authors:  Queeny Wing-Han Yuen; Yong-Ping Zheng; Yan-Ping Huang; Jun-Feng He; James Chung-Wai Cheung; Michael Ying
Journal:  Open Biomed Eng J       Date:  2011-03-30

7.  A Novel Nonlinear Parameter Estimation Method of Soft Tissues.

Authors:  Qianqian Tong; Zhiyong Yuan; Mianlun Zheng; Xiangyun Liao; Weixu Zhu; Guian Zhang
Journal:  Genomics Proteomics Bioinformatics       Date:  2017-12-13       Impact factor: 7.691

  7 in total

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