Application of Eshelby’s Solution to Elastography for Diagnosis of Breast Cancer

Application of Eshelby’s Solution to Elastography for Diagnosis of Breast Cancer

Chunfang Meng

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Bonghun Shin

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Darindra Gopaul

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Samantha Fienberg

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Hyock Ju Kwon

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Application of Eshelby’s Solution to Elastography for Diagnosis of Breast Cancer

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Application of Eshelby’s Solution to Elastography for Diagnosis of Breast Cancer Banner

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Abstract

Eshelby’s solution is the analytical method that can derive the elastic field within and around an ellipsoidal inclusion embedded in a matrix. Since breast tumor can be regarded as an elastic inclusion with different elastic properties from those of surrounding matrix when the deformation is small, we applied Eshelby’s solution to predict the stress and strain fields in the breast containing a suspicious lesion. The results were used to investigate the effectiveness of strain ratio (SR) from elastography in representing modulus ratio (MR) that may be the meaningful indicator of the malignancy of the lesion. This study showed that SR significantly underestimates MR and is varied with the shape and the modulus of the lesion. Based on the results from Eshelby’s solution and finite element analysis (FEA), we proposed a surface regression model as a polynomial function that can predict the MR of the lesion to the matrix. The model has been applied to gelatin-based phantoms and clinical ultrasound images of human breasts containing different types of lesions. The results suggest the potential of the proposed method to improve the diagnostic performance of breast cancer using elastography.

References

48 Cites in Article

Reference Format

R Siegel,D Naishadham,A Jemal (2014). Cancer statistics, 2013.
L Levy,M Suissa,J Chiche,G Teman,B Martin (2007). BIRADS ultrasonography.
R A Smith,V Cokkinides,H Eyre (2006). American Cancer Society guidelines for the early detection of cancer.
J Ophir,S Alam,B Garra,F Kallel,E Konofagou,T Krouskop (2002). Elastography: imaging the elastic properties of soft tissues with ultrasound.
A Skovoroda,A Klishko,D Gusakyan,Y Mayevskii,V Yermilova,G A Oranskaya (1995). Quantitative analysis of the mechanical characterristics of pathologically changed soft biological tissues.
J Ophir,I Cespedes,B Garra,H Ponnekanti,Y Huang,N Maklad (1996). Elastography: Ultrasonic imaging of tissue strain and elastic modulus in vivo.
H Kwon,J Lee (2014). Low-cost quasi-real-time elastography using B-mode ultrasound images.
J Bercoff,M Tanter,M Fink (2004). Supersonic shear imaging: a new technique for soft tissue elasticity mapping.
M Fink,M Tanter (2010). Multiwave imaging and super resolution.
Mickael Tanter,Jeremy Bercoff,Alexandra Athanasiou,Thomas Deffieux,Jean-Luc Gennisson,Gabriel Montaldo,Marie Muller,Anne Tardivon,Mathias Fink (2008). Quantitative Assessment of Breast Lesion Viscoelasticity: Initial Clinical Results Using Supersonic Shear Imaging.
Ako Itoh,Ei Ueno,Eriko Tohno,Hiroshi Kamma,Hideto Takahashi,Tsuyoshi Shiina,Makoto Yamakawa,Takeshi Matsumura (2006). Breast Disease: Clinical Application of US Elastography for Diagnosis.
Anke Thomas,Friedrich Degenhardt,André Farrokh,Sebastian Wojcinski,Torsten Slowinski,Thomas Fischer (2010). Significant Differentiation of Focal Breast Lesions.
Hui Zhi,Xiao-Yun Xiao,Hai-Yun Yang,Bing Ou,Yan-Ling Wen,Bao-Ming Luo (2010). Ultrasonic Elastography in Breast Cancer Diagnosis.
F Kallel,M Bertrand,J Ophir (1996). Fundamental limitations on the contrast-transfer efficiency in elastography: An analytic study.
Simona Celi,Francesca Di Puccio,Paola Forte (2011). Advances in Finite Element Simulations of Elastosonography for Breast Lesion Detection.
T Krouskop,T Wheeler,F Kallel,B Garra (1998). Elastic moduli of breast and prostate tissues under compression.
A Sarvazyan,A Skovoroda,S Emelianov,J B Fowlkes,J G Pipe,R Adler,R Buxton,P Carson (1995). Biophysical Bases of Elasticity Imaging.
Abbas Samani,Judit Zubovits,Donald Plewes (2007). Elastic moduli of normal and pathological human breast tissues: an inversion-technique-based investigation of 169 samples.
K Raghavan,A Yagle (1994). Forward and inverse problems in elasticity imaging of soft tissues.
A Skovoroda,S Aglyamov (1995). Reconstruction of elastic properties of soft biological tissues exposed to low-frequencies disruption.
C Sumi,A Suzuki,K Nakayama (1995). Phantom experiment on estimation of shear modulus distribution in soft-tissue from ultrasonic measurement of displacement vector field.
C Sumi (2007). Spatially variant regularization for tissue strain measurement and shear modulus reconstruction.
Le Floc,',S Cloutier,G Finet,G Tracqui,P Pettigrew,R Ohayon,J (2010). Vascular imaging modulography: an experimental in vitro study.
Paul Barbone,Assad Oberai (2007). Elastic modulus imaging: some exact solutions of the compressible elastography inverse problem.
F Kallel,M Bertrand (1996). Tissue elasticity reconstruction using linear perturbation method.
Michael Richards,Paul Barbone,Assad Oberai (2009). Quantitative three-dimensional elasticity imaging from quasi-static deformation: a phantom study.
J Jiang,T Varghese,C L Brace,E Madsen,T J Hall,S Bharat (2009). Young's modulus reconstruction for radio-frequency ablation electrode-induced displacement fields: a feasibility study.
R Baldewsing,J Schaar,F Mastik,Cwj Oomens,Afw Van Der Steen (2005). Assessment of vulnerable plaque composition by matching the deformation of a parametric plaque model to measured plaque deformation.
Assad Oberai,Nachiket Gokhale,Gonzalo Feij o (2003). Solution of inverse problems in elasticity imaging using the adjoint method.
A Samani,J Bishop,D Plewes (2001). A constrained modulus reconstruction technique for breast cancer assessment.
Hari Ponnekanti,Jonathan Ophir,Yuun Huang,Ignacio Céspedes (1995). Fundamental mechanical limitations on the visualization of elasticity contrast in elastography.
Radj Baldewsing,Frits Mastik,Johannes Schaar,Patrick Serruys,Antonius Van Der Steen (2006). Young’s modulus reconstruction of vulnerable atherosclerotic plaque components using deformable curves.
Mehmet Bilgen,Michael Insana (1998). Elastostatics of a spherical inclusion in homogeneous biological media.
B Alberts,D Bray,J Lewis,M Raff,K Roberts,J Watson (1994). Molecular Biology of the Cell.
Ycb Fung (1967). Elasticity of soft tissues in simple elongation.
M Doyley (2012). Model-based elastography: a survey of approaches to the inverse elasticity problem.
John Eshelby (1957). The determination of the elastic field of an ellipsoidal inclusion, and related problems.
John Eshelby (1959). The elastic field outside an ellipsoidal inclusion.
J Ju,L Sun (1999). A Novel Formulation for the Exterior-Point Eshelby's Tensor of an Ellipsoidal Inclusion.
T Mura (1987). Micromechanics of Defects in Solids.
J Ju,L Sun (2001). Effective elastoplastic behavior of metal matrix composites containing randomly located aligned spheroidal inhomogeneities. Part I: micromechanics-based formulation.
Yougun Han,Dong-Woo Kim,Hyock-Ju Kwon (2012). Application of digital image cross-correlation and smoothing function to the diagnosis of breast cancer.
Yougun Han,Allan Rogalsky,Boxin Zhao,Hyock Kwon (2011). The application of digital image techniques to determine the large stress–strain behaviors of soft materials.
Theo Pavan,Ernest Madsen,Gary Frank,Jingfeng Jiang,Antonio Carneiro,Timothy Hall (2012). A nonlinear elasticity phantom containing spherical inclusions.
Grace Wahba (1990). Spline Models for Observational Data.
Ernest Madsen,James Zagzebski,Gary Frank (1982). An anthropomorphic ultrasound breast phantom containing intermediate-sized scatteres.
D Champion,R Hartley (2009). Statistics for Criminal Justice and Criminology.
R Mould (1998). Introductory Medical Statistics.

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No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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How to Cite This Article

Chunfang Meng. 2019. \u201cApplication of Eshelby’s Solution to Elastography for Diagnosis of Breast Cancer\u201d. Global Journal of Medical Research - D: Radiology, Diagnostic GJMR-D Volume 19 (GJMR Volume 19 Issue D1).

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GJMR Volume 19 Issue D1

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Crossref Journal DOI 10.17406/gjmra

Print ISSN 0975-5888

e-ISSN 2249-4618

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GJMR-D Classification NLMC Code: WB 200

Submission ReceivedDecember 10, 2018
Peer Review Double Blind
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Accepted January 1, 2019
Published January 15, 2019

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March 26, 2019

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Article Matrices

Total Score: 135

Country: Canada

Subject: Global Journal of Medical Research - D: Radiology, Diagnostic

Authors: Chunfang Meng, Bonghun Shin, Darindra Gopaul, Samantha Fienberg, Hyock Ju Kwon (PhD/Dr. count: 0)

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