Among the available tools for the early diagnosis of breast cancer, the elastographic technique based on ultrasounds has many advantages such as the noninvasive measure, the absence of ionizing effects, the high tolerability by patients, and the wide diffusion of the ecographic machines. However this diagnostic procedure is strongly affected by many subjective factors and is considered not reliable enough even to reduce the number of biopsies used to identify the nature of lesions. Therefore in the literature experimental and numerical simulations on physical and virtual phantoms are presented to test and validate procedures and algorithms and to interpret elastosonographic results. In this work, first a description of the elastographic technique and a review of the principal finite element (FE) models are provided and second diagnostic indexes employed to assess the nature of a lump mass are presented. As advances in FE simulations of elastosonography, axisymmetric phantom, and anthropomorphic models are described, which, with respect to the literature, include some features of breast mechanics. In particular deterministic analyses were used to compare the various details of virtual elastograms and also to investigate diagnostic indexes with respect to the regions where strains were considered. In order to improve the reliability of the elastosonographic procedure, univariate and multivariate sensitivity analyses, based on a probabilistic FE approach, were also performed to identify the parameters that mostly influence the deformation contrast between healthy and cancerous tissues. Moreover, synthetic indicators of the strain field, such as the strain contrast coefficient, were evaluated in different regions of interest in order to identify the most suitable for lesion type assessment. The deterministic analyses show that the malignant lesion is characterized by a uniform strain inside the inclusion due to the firmly bonding condition, while in the benign inclusion (loosely bonded) a strain gradient is observed independently from the elastic modulus contrast. The multivariate analyses reveal that the strain contrast depends linearly on the relative stiffness between the lesion and the healthy tissue and not linearly on the interface friction coefficient. The anthropomorphic model shows other interesting features, such as the layer or curvature effects, which introduce difficulties in selecting a reference region for strain assessment. The results show that a simple axisymmetric model with linear elastic material properties can be suitable to simulate the elastosonographic procedure although the breast curvature and layer distinction play a significant role in the strain assessment.

References

References
1.
Thitaikumar
,
A.
,
Mobbs
,
L.
,
Kraemer-Chant
,
C.
,
Garra
,
B.
, and
Ophir
,
J.
, 2008, “
Breast Tumor Classification Using Axial Shear Strain Elastography: a Feasibility Study
,”
Phys. Med. Biol.
,
53
, pp.
4809
4823
.
2.
Di Maggio
,
C.
, 2004, “
State of the Art of Current Modalities for the Diagnosis of Breast Lesions
,”
Eur. J. Nucl. Med. Mol. Imaging
,
31
(
1
), pp.
S56
S69
.
3.
Gordon
,
P.
, and
Goldenberg
,
S.
, 1995, “
Malignant Breast Masses Detected Only by Ultrasound: A Retrospective Review
,”
Cancer
,
76
(
4
), pp.
626
630
.
4.
Ophir
,
J.
,
Céspedes
,
I.
,
Ponnekanti
,
H.
,
Yazdi
,
Y.
, and
Li
,
X.
, 1991, “
Elastography: A Quantitative Method for Imaging the Elasticity of Biological Tissues
,”
Ultrason. Imaging
,
13
(
2
), pp.
111
134
.
5.
Ophir
,
J.
,
Alam
,
S. K.
,
Garra
,
B.
,
Kallel
,
F.
,
Konofagou
,
E.
,
Krouskop
,
T.
, and
Varghese
,
T.
, 1999, “
Elastography: Ultrasonic Estimation and Imaging of Elastic Properties of Tissues
,”
Proc. Inst. Mech. Eng., Part H: J. Eng. Med.
,
213
, pp.
203
233
.
6.
Patil
,
A. V.
,
Garson
,
C. D.
, and
Hossack
,
J. A.
, 2007, “
3D Prostate Elastography: Algorithm, Simulations and Experiments
,”
Phys. Med. Biol.
,
52
, pp.
3643
3663
.
7.
McCormack
,
D.
,
Al-Shaer
,
M.
,
Goldschmidt
,
B.
,
Dale
,
P.
,
Henry
,
C.
,
Papageorgio
,
C.
,
Bhattacharyya
,
K.
, and
Viator
,
J.
, 2009, “
Photoacoustic Detection of Melanoma Micrometastasis in Sentinel Lymph Nodes
,”
ASME J. Biomech. Eng.
,
131
(
7
), p.
074519
.
8.
Greenleaf
,
J. F.
,
Fatemi
,
M.
, and
Insana
,
M.
, 2003, “
Selected Methods for Imaging Elastic Properties of Biological Tissues
,”
Annu. Rev. Biomed. Eng.
,
5
, pp.
57
78
.
9.
Thitaikumar
,
A.
, and
Ophir
,
J.
, 2007, “
Effect of Lesion Boundary Conditions on Axial Strain Elastograms: A Parametric Study
,”
Ultrasound Med. Biol.
,
33
(
9
), pp.
1463
1467
.
10.
Thitaikumar
,
A.
,
Krouskop
,
T.
,
Garra
,
B.
, and
Ophir
,
J.
, 2007, “
Visualization of Bonding at an Inclusion Boundary Using Axial Shear Strain Elastography: A Feasibility Study
,”
Phys. Med. Biol.
,
52
, pp.
2615
2633
.
11.
Krouskop
,
T. A.
,
Younes
,
P. S.
,
Srinivasan
,
S.
,
Wheeler
,
T.
, and
Ophir
,
J.
, 2003, “
Differences in the Compressive Stress-Strain Response of Infiltrating Ductal Carcinomas With and Without Lobular Features–Implications for Mammography and Elastography
,”
Ultrason. Imaging
,
25
(
3
), pp.
162
170
.
12.
Bilgen
,
M.
, and
Insana
,
M.
, 1998, “
Elastostatics of a Spherical Inclusion in Homogeneous Biological Media
,”
Phys. Med. Biol.
,
43
, pp.
1
20
.
13.
Hall
,
T. J.
,
Zhu
,
Y.
, and
Spalding
,
C.
, 2003, “
In Vivo Real-Time Freehand Palpation Imaging
,”
Ultrasound Med. Biol.
,
29
, pp.
427
435
.
14.
Bercoff
,
J.
,
Chaffai
,
S.
,
Tanter
,
M.
,
Sandrin
,
L.
,
Catheline
,
S.
,
Fink
,
M.
,
Gennisson
,
J.
, and
Meunier
,
M.
, 2003, “
In Vivo Breast Tumor Detection Using Transient Elastography
,”
Ultrasound Med. Biol.
,
29
, pp.
1387
1396
.
15.
Chandra
,
M.
,
Sehgal
,
S.
,
Weinstein
,
P.
,
Arger
,
E.
, and
Conant
,
J.
, 2006, “
A Review of Breast Ultrasound
,”
J. Mammary Gland Biol. Neoplasia.
,
11
(
2
), pp.
113
123
.
16.
O’Donnell
,
M.
,
Skovoroda
,
A.
, and
Shapo
,
B.
, 1991, “
Measurement of Arterial Wall Motion Using Fourier Based Speckle Tracking Algorithms
,”
Proceedings of the IEEE Ultrasonics Symposium
, pp.
1101
1104
.
17.
Bertrand
,
M. M.
,
Meunier
,
M.
,
Doucet
,
M.
, and
Ferland
,
G.
, 1989, “
Ultrasonic Biomechanical Strain Gauge based on Speckle Tracking
,”
IEEE Ultrasonics Symposium
, pp.
859
864
.
18.
Varghese
,
T.
,
Konofagou
,
E.
,
Ophir
,
J.
,
Alam
,
S.
, and
Bilgen
,
M.
, 2000, “
Direct Strain Estimation in Elastography Using Spectral Cross-Correlation
,”
Ultrasound Med. Biol.
,
26
, pp.
1525
1537
.
19.
Bilgen
,
M.
, and
Insana
,
M.
, 1996, “
Deformation Models and Correlation Analysis in Elastography
,”
J. Acoust. Soc. Am.
,
99
, pp.
3212
24
.
20.
Chaturvedi
,
P.
,
Insana
,
M.
, and
Hall
,
T.
, 1998, “
2-D Companding for Noise Reduction in Strain Imaging
,”
IEEE Trans. Ultrason. Ferroelectr. Freq. Control
,
45
, pp.
179
191
.
21.
Varghese
,
T.
, 2009, “
Quasi-Static Ultrasound Elastography
,”
Ultrasound Clin.
,
4
(
3
), pp.
323
338
.
22.
Ophir
,
J.
,
Céspedes
,
I.
,
Garra
,
B.
,
Ponnekanti
,
H.
,
Huang
,
Y.
, and
Maklad
,
N.
, 1996, “
Elastography: Ultrasonic Imaging of Tissue Strain and Elastic Modulus in Vivo
,”
Eur. J. Ultrasound
,
3
, pp.
49
70
.
23.
Chiorean
,
A.
,
Duma
,
M.
,
Dudea
,
S.
,
Iancu
,
A.
,
Roman
,
D. D. R.
, and
Sfrngeu
,
S.
, 2008, “
Real-Time Ultrasound Elastography of the Breast: State of the Art
,”
Med. Ultrason.
,
10
(
2
), pp.
73
82
.
24.
Stavros
,
A.
,
Thickman
,
D.
,
Rapp
,
C. L.
,
Dennis
,
M. A.
,
Parker
,
S. H.
, and
Sisney
,
G. A.
, 1995, “
Solid Breast Nodules: Use of Sonography to Distinguish Between Benign and Malignant Lesions
,”
Radiology
,
196
, pp.
123
134
.
25.
Muradali
,
D.
, and
Kulkarni
,
S.
, 2005, “
Sonography of the Breast: To Core or Not to Core?
,”
JACR
,
56
(
5
), pp.
276
288
.
26.
Azar
,
F.
,
Metaxas
,
D.
, and
Schnall
,
M.
, 2002, “
Methods for Modeling and Predicting Mechanical Deformations of the Breast Under External Perturbations
,”
Med. Image Anal.
,
6
(
1
), pp.
1
27
.
27.
Roose
,
L.
,
Maerteleire
,
W. D.
,
Mollemans
,
W.
,
Maes
,
F.
, and
Suetens
,
P.
, 2006, “
Simulation of Soft-Tissue Deformations for Breast Augmentation Planning
,” in
Biomedical Simulation
, edited by
Harders
et al.
,
Springer
,
Berlin
, pp.
197
205
.
28.
Rajagopal
,
V.
,
Nielsen
,
P.
, and
Nash
,
M.
, 2009, “
Modeling Breast Biomechanics for Multi-Modal Image Analysis—Successes and Challenges
,”
WIREs Syst. Biol. Med.
,
1
(
2
), pp.
151
282
.
29.
Patil
,
A. V.
,
Krouskop
,
T. A.
,
Ophir
,
J.
, and
Srinivasan
,
S.
, 2008, “
On the Differences Between Two-Dimensional and Three-Dimensional Simulations for Assessing Elastographic Image Quality: A Simulation Study
,”
Ultrasound Med. Biol.
,
34
(
7
), pp.
1129
1138
.
30.
Sosa-Cabrera
,
D.
,
Krissian
,
K.
,
Gonzalez-Fernandez
,
J.
,
Gomez-Deniz
,
L.
,
Rovaris
,
E.
,
Castano-Moraga
,
C.
, and
Ruiz-Alzola
J.
, 2009, “
Strain Tensor Elastography: 2D and 3D Visualizations
,”
Tensors in Image Processing and Computer Vision
,
Springer
,
London
, Part IV, pp.
381
403
.
31.
Samani
,
A.
,
Bishop
,
J.
,
Yaffe
,
M.
, and
Plewes
,
D.
, 2001, “
Biomechanical 3-D Finite Element Modelling of the Human Breast Using Mri Data
,”
IEEE Trans. Med. Imaging
,
20
(
4
), pp.
271
279
.
32.
Tanner
,
C.
,
Degenhard
,
A.
,
Schnabel
,
J. A.
,
Smith
,
A. C.
,
Hayes
,
C.
,
Sonoda
,
L. I.
,
Leach
,
M. O.
,
Hose
,
D. R.
,
Hill
,
D. L. G.
, and
Hawkes
,
D. J.
, 2001, “
A Method for the Comparison of Biomechanical Breast Models
,”
Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
.
33.
Rajagopal
,
V.
,
Chung
,
J.-H.
,
Bullivant
,
D.
,
Nielsen
,
P. M. F.
, and
Nash
,
M. P.
, 2007, “
Determining the Finite Elasticity Reference State from a Loaded Configuration
,”
Int. J. Numer. Methods Eng.
,
72
(
12
), pp.
1434
1451
.
34.
Rajagopal
,
V.
,
Nash
,
M.
,
Highnam
,
R.
, and
Nielsen
,
P.
, 2008, “
The Breast Biomechanics Reference State for Multi-Modal Image Analysis
,” in
Lecture Notes in Computer Science: International Workshop on Digital Mammography
, pp.
385
392
.
35.
Rajagopal
,
V.
,
Lee
,
A.
,
Chung
,
J.
,
Warren
,
R.
,
Highnam
,
R.
,
Nash
,
M.
, and
Nielsen
,
P.
, 2008, “
Creating Individual-Specific Biomechanical Models of the Breast for Medical Image Analysis
,”
Acad. Radiol.
,
15
, pp.
1425
1436
.
36.
Krouskop
,
T.
,
Wheeler
,
T.
,
Kallel
,
F.
,
Garra
,
B.
, and
Hall
,
T.
, 1998, “
Elastic Moduli of Breast and Prostate Tissues Under Compression
,”
Ultrason. Imaging
,
20
, pp.
260
274
.
37.
Wellman
,
P.
,
Howe
,
R.
,
Dalton
,
E.
, and
Kern
,
K.
, 1999, “
Breast Tissue Stiffness in Compression is Correlated to Histological Diagnosis
,” Technical Report, Harvard Biorobotics Lab.
38.
Samani
,
A.
, and
Plewes
,
D.
, 2007, “
An Inverse Problem Solution for Measuring the Elastic Modulus of Intact Ex Vivo Breast Tissues
,”
Phys. Med. Biol.
,
52
, pp.
1247
1260
.
39.
Williams
,
C. B.
, 1997, “
X-Photon-to-Information Conversion Efficiency in Digital Telemammography
,” Technical Report, Ohio State University.
40.
Han
,
L.
,
Noble
,
J. A.
, and
Burcher
,
M.
, 2003, “
A Novel Ultrasound Indentation System for Measuring Biomechanical Properties of in Vivo Soft Tissue
,”
Ultrasound Med. Biol.
,
29
(
6
), pp.
813
823
.
41.
Egorov
,
V.
, and
Sarvazyan
,
A.
, 2008, “
Mechanical Image of the Breast
,”
IEEE Trans. Med. Imaging
,
27
(
9
), pp.
1275
1287
.
42.
Samani
,
A.
,
Zubovits
,
J.
, and
Plewes
,
D.
, 2007, “
Elastic Moduli of Normal and Pathological Human Breast Tissues: An Inversion-Technique-Based Investigation of 169 Samples
,”
Phys. Med. Biol.
,
52
, pp.
1565
1576
.
43.
Samani
,
A.
, and
Plewes
,
D.
, 2004, “
A Method to Measure the Hyperelastic Parameters of ex Vivo Breast Tissue Samples
,”
Phys. Med. Biol.
,
49
, pp.
4395
4405
.
44.
Tanner
,
C.
,
Schanabel
,
J.
,
Hill
,
D.
, and
Hawkes
,
D.
, 2006, “
Factors Influencing the Accuracy of Biomechanical Breast Models
,”
Med. Phys.
,
33
(
6
), pp.
1758
1769
.
45.
del Palomar
,
A.
,
Calvo
,
B.
,
Herrero
,
J.
,
López
,
J.
, and
Doblaré
,
M.
, 2008, “
A Finite Element Model to Accurately Predict Real Deformations of the Breast
,”
Med. Eng. Phys.
,
30
(
9
), pp.
1089
1097
.
46.
Kallel
,
F.
, and
Ophir
,
M. B. J.
, 1996, “
Fundamental Limitations on the Contrast-Transfer Efficiency in Elastography: an Analytic Study
,”
Ultrasound Med. Biol.
,
22
(
4
), pp.
463
470
.
47.
Celi
,
S.
,
Di Puccio
,
F.
, and
Forte
,
P.
, 2005, “
Sensitivity of Angioplasty Effects to Vessel Material Properties by Probabilistic Analysis
,”
Proceedings of the II International Conference on Computational Bioengineering
, edited by
H.
Rodrigues
et al.
,
Lisbon
,
Portugal
, pp.
567
578
.
48.
Sheskin
,
D. J
., 1997,
Handbook of Parametric and Nonparametric Statistical Procedures
,
CRC
,
Boca Raton, Florida
.
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