Elastography measures tissue strain, which can be interpreted under certain simplifying assumptions to be representative of the underlying stiffness distribution. This is useful in cancer diagnosis where tumors tend to have a different stiffness to healthy tissue and has also shown potential to provide indication of the degree of bonding at tumor–tissue boundaries, which is clinically useful because of its dependence on tumor pathology. We consider the changes in axial strain for the case of a symmetrical model undergoing uniaxial compression, studied by characterizing changes in tumor contrast transfer efficiency (CTE), inclusion to background strain contrast and strain contrast generated by slip motion, as a function of Young’s modulus contrast and applied strain. We present results from a finite element simulation and an evaluation of these results using tissue-mimicking phantoms. The simulation results show that a discontinuity in displacement data at the tumor boundary, caused by the surrounding tissue slipping past the tumor, creates a halo of “pseudostrain” across the tumor boundary. Mobile tumors also appear stiffer on elastograms than adhered tumors, to the extent that tumors that have the same Young’s modulus as the background may in fact be visible as low-strain regions, or those that are softer than the background may appear to be stiffer than the background. Tumor mobility also causes characteristic strain heterogeneity within the tumor, which exhibits low strain close to the slippery boundary and increasing strain toward the center of the tumor. These results were reproduced in phantom experiments. In addition, phantom experiments demonstrated that when fluid lubrication is present at the boundary, these effects become applied strain-dependent as well as modulus-dependent, in a systematic and characteristic manner. The knowledge generated by this study is expected to aid interpretation of clinical strain elastograms by helping to avoid misinterpretation as well as provide additional diagnostic criteria stated in the paper and stimulate further research into the application of elastography to tumor mobility assessment.
We previously developed a 2D locally regularized strain estimation technique that was already validated with ex vivo
tissues. In this study, our technique is assessed with in vivo data, by examining breast abnormalities in clinical
conditions. Method reliability is analyzed as well as tissue strain fields according to the benign or malignant character of
the lesion. Ultrasound RF data were acquired in two centers on ten lesions, five being classified as fibroadenomas, the
other five being classified as malignant tumors, mainly ductal carcinomas from grades I to III. The estimation procedure
we developed involves maximizing a similarity criterion (the normalized correlation coefficient or NCC) between pre- and
post-compression images, the deformation effects being considered. The probability of correct strain estimation is
higher if this coefficient is closer to 1. Results demonstrated the ability of our technique to provide good-quality strain
images with clinical data. For all lesions, movies of tissue strain during compression were obtained, with strains that can
reach 15%. The NCC averaged over each movie was computed, leading for the ten cases to a mean value of 0.93, a
minimum value of 0.87 and a maximum value of 0.98. These high NCC values confirm the reliability of the strain
estimation. Moreover, lesions were clearly identified for the ten cases investigated. Finally, we have observed with
malignant lesions that compared to ultrasound data, strain images can put in relief a more important lesion size, and can
help in evaluating the lesion invasive character.
Ultrasound elastography tracks tissue displacements under small levels of compression to obtain images of strain, a
mechanical property useful in the detection and characterization of pathology. Due to the nature of ultrasound
beamforming, only tissue displacements in the direction of beam propagation, referred to as 'axial', are measured to high
quality, although an ability to measure other components of tissue displacement is desired to more fully characterize the
mechanical behavior of tissue. Previous studies have used multiple one-dimensional (1D) angled axial displacements
tracked from steered ultrasound beams to reconstruct improved quality trans-axial displacements within the scan plane
('lateral'). We show that two-dimensional (2D) displacement tracking is not possible with unmodified electronically-steered
ultrasound data, and present a method of reshaping frames of steered ultrasound data to retain axial-lateral
orthogonality, which permits 2D displacement tracking. Simulated and experimental ultrasound data are used to compare
changes in image quality of lateral displacements reconstructed using 1D and 2D tracked steered axial and steered lateral
data. Reconstructed lateral displacement image quality generally improves with the use of 2D displacement tracking at
each steering angle, relative to axial tracking alone, particularly at high levels of compression. Due to the influence of
tracking noise, unsteered lateral displacements exhibit greater accuracy than axial-based reconstructions at high levels of
applied strain.
This work presents a new approach to lateral strain estimation in the field of tissue elasticity imaging with ultrasound. A particular beamforming is used to produce a point spread function (PSF) with lateral oscillations. Lateral RF signals can then be considered as the juxtaposition of RF samples coming from the same depth. This enables to estimate the lateral strain with a scaling factor estimator applied to the lateral signals. The approach is validated in simulation on a medium stretched only in the lateral direction. The estimation is unbiased for lateral strain values from 0.5 to 7 % with standard deviation less than 0.5 %.
Conference Committee Involvement (6)
Ultrasonic Imaging and Tomography
16 February 2020 | Houston, Texas, United States
Ultrasonic Imaging and Tomography
17 February 2019 | San Diego, California, United States
Ultrasonic Imaging and Tomography
14 February 2018 | Houston, Texas, United States
Ultrasonic Imaging and Tomography
15 February 2017 | Orlando, Florida, United States
Ultrasonic Imaging and Tomography
28 February 2016 | San Diego, California, United States
Ultrasonic Imaging and Tomography
22 February 2015 | Orlando, Florida, United States
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.