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Axial-shear strain elastography was described recently as a method to visualize the state of bonding at an inclusion boundary. Although total shear strain elastography was initially proposed for this purpose, it did not evolve beyond the initial reported finite element model (FEM) and simulation studies. One of the major reasons for this was the practical limitation in estimating the tissue motion perpendicular (lateral) to the ultrasound (US) beam as accurately as the motion along the US beam (axial). Nevertheless, there has been a sustained effort in developing methods to improve the lateral motion tracking accuracy and thereby obtain better quality total shear strain elastogram (TSSE). We hypothesize that in some cases, even if good quality TSSE becomes possible, it may still be advantageous to utilize only the axial-shear strain (one of the components of the total shear strain) elastogram (ASSE). Specifically, we show through FEM and corroborating tissue-mimicking gelatin phantom experiments that the unique “ fill-in ” discriminant feature that was introduced recently for asymmetric breast lesion classification is depicted only in the ASSE and not in the TSSE. Note that the presence or conspicuous absence of this feature in ASSE was shown to characterize asymmetric inclusions' boundaries as either loosely-bonded or firmly-bonded to the surrounding, respectively. This might be an important observation because the literature suggests that benign breast lesions tend to be loosely-bonded, while malignant tumors are usually firmly-bonded. The results from the current study demonstrate that the use of shear strain lesion “ fill-in ” as a discriminant feature in the differentiation between asymmetric malignant and benign breast lesions is only possible when using the ASSEs and not the TSSEs.

The specific purpose of this review is to describe the progress of our work on elastography at the University of Texas Medical School-Houston in the past decade (2000-2010), and to relate it to our earlier work on this topic in the pre- ceding decade (1991-2000). This review is neither intended to cover all specific aspects of this fast growing field, nor to be an exhaustive review of the literature. Such information is available separately and in several literary reviews. The early work in our Laboratory was started (1) with the fundamental theoretical and experimental development of elas- tography and ended with demonstration of the feasibility of producing elastograms in a clinical setting (2). During the fol- lowing decade our work has branched out into three main directions. These were (1) a continued effort to demonstrate the ability of elastography to depict the elastic properties of tissues and to develop improved algorithms for attaining quality strain estimations; (2) the development and practical in vivo demonstration of Poisson's ratio elastography (poroelastogra- phy) for the study of poroelastic materials such as lymphedematous tissues; and (3) the development of axial-shear strain elastography (ASSE) for imaging the mechanical boundary conditions at tissue interfaces, and to demonstrate the utility of this modality in the differentiation between benign and malignant breast lesions in vivo. These three areas are the main topics that are covered in this review.

The purpose of this work was to investigate the potential of the normalized axial-shear strain area (NASSA) feature, derived from axial-shear strain elastograms (ASSE), for breast lesion classification of fibroadenoma and cancer. This study consisted of previously acquired in vivo digital radiofrequency data of breast lesions. A total of 33 biopsy-proven malignant tumors and 30 fibroadenoma cases were included in the study, which involved three observers blinded to the original BIRADS-ultrasound scores. The observers outlined the lesions on the sonograms. The ASSEs were segmented and color-overlaid on the sonograms, and the NASSA feature from the ASSE was computed semi-automatically. Receiver operating characteristic (ROC) curves were then generated and the area under the curve (AUC) was calculated for each observer performance. A logistic regression classifier was built to compare the improvement in the AUC when using BIRADS scores plus NASSA values as opposed to BIRADS scores alone. BIRADS score ROC had an AUC of 0.89 (95% CI = 0.81 to 0.97). In comparison, the average of the AUC for all the three observers using ASSE feature alone was 0.84. However, the AUC increased to 0.94 (average of 3 observers) when BIRADS score and ASSE feature were combined. The results demonstrate that the NASSA feature derived from ASSE has the potential to improve BIRADS breast lesion classification of fibroadenoma and malignant tumors.

Recently, we reported on the axial-shear strain fill-in of the interior of loosely bonded stiff elliptical inclu- sions in a soft backgroundat non-normal orientations, and the lack of fill-in in firmly bonded inclusions at any orien- tation. In this paper, we report on the experimental validation of the simulation studies using tissue-mimicking gelatin-based phantoms. We also show a few confirmatory examples of the existence of these phenomena in benign vs. malignant breast lesions in vivo. Phantom experiments showed that axial-shear strain zones caused by firmly bonded elliptical inclusions occurred only outside of the inclusion, as predicted by the simulation. By contrast, the axial-shear strain zones filled in the interior of loosely bonded elliptical inclusions at non-normal orientations. The axial-shear strain elastograms obtained from the in vivo cases appeared to be in general agreement with our experimental results. The results reported in this paper may have important clinical implications. Specifically, axial-shear strain fill-in inside an inclusion may be auniquesignature of stiff, loosely bonded, ellipsoidal or elongated inclusions at non-normal orientations. Thus, it may be useful as a marker of benignity of benign breast lesions (e.g., fibroadenomas) that are generally stiff, elongated and loosely bonded to the host tissues. (E-mail: Jonathan.Ophir@ uth.tmc.edu) 2010 World Federation for Ultrasound in Medicine & Biology.

Recently, the feasibility of visualizing the characteristics of bonding at an inclusion-background boundary using axial-shear strain elastography was demonstrated. In this paper, we report a feasibility study on the utility of the axial-shear strain elastograms in the classification of in vivo breast tumor as being benign or malignant. The study was performed using data sets obtained from 15 benign and 15 malignant cases that were biopsy proven. A total of three independent observers were trained, and their services were utilized for the study. A total of 9 cases were used as training set and the remaining cases were used as testing set. The feature from the axial-shear strain elastogram, namely, the area of the axial-shear region, was extracted by the observers. The observers also outlined the tumor area on the corresponding sonogram, which was used to normalize the area of the axial-shear strain region. There are several observations that can be drawn from the results. First, the result indicates that the observers consistently ( approximately 82% of the cases) noticed the characteristic pattern of the axial-shear strain distribution data as predicted in the previous simulation studies, i.e. alternating regions of positive and negative axial-shear strain values around the tumor-background interface. Second, the analysis of the result suggests that in approximately 57% of the cases in which the observers did not visualize tumor in the sonogram, the elastograms helped them to locate the tumor. Finally, the analysis of the result suggests that for the discriminant feature value of 0.46, the number of unnecessary biopsies could be reduced by 56.3% without compromising on sensitivity and on negative predictive value (NPV). Based on the results in this study, feature values greater than 0.75 appear to be indicative of malignancy, while values less than 0.46 to be indicative of benignity. Feature values between 0.46 and 0.75 may result in an overlap between benign and malignant cases.

In this paper, we have investigated the feasibility of imaging the mechanical behavior of poroelastic materials using axial strain elastography. Cylindrical samples obtained from poroelastic materials having different elastic and permeability properties were subjected to a constant compression force (a classical creep experiment), during which poroelastographic data were acquired. For comparison, we also tested a few gelatin phantoms and non-homogeneous poroelastic phantoms constructed by combining different poroelastic materials. From the acquired data, we generated time-dependent sequences of axial strain elastograms and effective Poisson's ratio elastograms, which were then used for generating axial strain and effective Poisson's ratio time-constant elastograms. Thereafter, the various poroelastographic images were analyzed to evaluate the presence of statistically significant differences among the two types of poroelastic samples and for image quality analysis. The results of this study demonstrate that it is technically feasible to use axial strain elastography to distinguish among homogeneous poroelastic materials characterized by different elastic and permeability properties. They also show that the use of axial strain elastography instead of effective Poisson's ratio elastography results in objectively higher quality poroelastograms of the temporal behavior of the poroelastic materials under loading. However, the use of effective Poisson's ratio elastography may in any case be required to verify that the temporal changes occurring in the axial strains of the homogeneous poroelastic samples are also accompanied by temporal changes of the effective Poisson's ratios and are therefore due to poroelastic behavior.

Ultrasound elastography produces strain images of compliant tissues under quasi-static compression. In axial-shear strain elastography, the local axial-shear strain resulting from application of quasi-static axial compression to an inhomogeneous material is imaged. The overall hypothesis of this work is that the pattern of axial-shear strain distribution around the inclusion/background interface is completely determined by the bonding at the interface after normalization for inclusion size and applied strain levels, and that it is feasible to extract certain features from the axial-shear strain elastograms to quantify this pattern. The mechanical model used in this study consisted of a single stiff circular inclusion embedded in a homogeneous softer background. First, we performed a parametric study using finite-element analysis (FEA) (no ultrasound involved) to identify possible features that quantify the pattern of axial-shear strain distribution around an inclusion/background interface. Next, the ability to extract these features from axial-shear strain elastograms, estimated from simulated pre- and post-compression noisy RF data, was investigated. Further, the feasibility of extracting these features from in vivo breast data of benign and malignant tumors was also investigated. It is shown using the FEA study that the pattern of axial-shear strain distribution is determined by the degree of bonding at the inclusion/background interface. The results suggest the feasibility of using normalized features that capture the region of positive and negative axial-shear strain area to quantify the pattern of the axial-shear strain distribution. The simulation results showed that it was feasible to extract the features, as identified in the FEA study, from axial-shear strain elastograms. However, an effort must be made to obtain axial-shear strain elastograms with the highest signal-to-noise ratio (SNR(asse)) possible, without compromising the resolution. The in vivo results demonstrated the feasibility of producing and extracting features from the axial-shear strain elastograms from breast data. Furthermore, the in vivo axial-shear strain elastograms suggest an additional feature not identified in the simulations that may potentially be used for distinguishing benign from malignant tumors-the proximity of the axial-shear strain regions to the inclusion/background interface identified in the sonogram.

Management of fluid overload in patients with end-stage renal disease represents a unique challenge to clinical practice because of the lack of accurate and objective measurement methods. Currently, peripheral edema is subjectively assessed by palpation of the patient's extremities, ostensibly a qualitative indication of tissue viscoelastic properties. New robust quantitative estimates of tissue fluid content would allow clinicians to better guide treatment, minimizing reactive treatment decision making. Ultrasound viscoelastography (UVE) can be used to estimate strain in viscoelastic tissue, deriving material properties that can help guide treatment. We are developing and testing a simple, low-cost UVE system using a single-element imaging transducer that is simpler and less computationally demanding than array-based systems. This benchtop validation study tested the feasibility of using the UVE system by measuring the mechanical properties of a tissue-mimicking material under large strains. We generated depth-dependent creep curves and viscoelastic parameter maps of time constants and elastic moduli for the Kelvin model of viscoelasticity. During testing, the UVE system performed well, with mean UVE-measured strain matching standard mechanical testing with maximum absolute errors ≤4%. Motion tracking revealed high correlation and signal-to-noise ratios, indicating that the system is reliable.

Conventional spectral elastographic techniques estimate strain using cross-correlation methods. Despite promising results, decorrelation effects compromise the accuracy of these techniques and, subsequently, the tissue strain estimates. Since tissue compression in the time-domain corresponds to upscaling in the frequency-domain, decorrelation effects become more pronounced as tissue strains increase and are a fundamental concern in spectral cross-correlation elastography. In this paper, a two-stage hybrid spectral elastographic technique is introduced. For the first stage, an approximated spectral scaling factor (i.e. initial strain estimate) is employed to compensate for bandwidth broadening (due to tissue compression) between pre- and post-compression power spectra pairs. The second stage then estimates any residual strain information using spectral cross-correlation methods due to improper scaling factor selection in the first stage. This novel hybrid spectral elastographic technique was compared to both conventional spectral and adaptive temporal elastographic methods in simulation and experimentation. In addition to demonstrating enhancement in performance over the conventional spectral elastographic technique, the hybrid spectral-based method introduced in this paper is shown to outperform the adaptive temporal-based elastographic approach.

Poroelastography has been recently introduced as a new elastographic technique that may be used to describe the spatial and temporal behavior of poroelastic materials. The experimental methodology proposed thus far for phantoms and tissues in vitro requires the acquisition of a precompression rf frame, the application of a unit step strain compression to the sample and the acquisition of subsequent post-compression frames from the material. Elastograms and poroelastograms are generated by cross-correlating the sequentially-acquired postcompression frames with the reference precompression frame. The application of poroelastography to tissues in vivo must address the echo decorrelation problems that are encountered due to uncontrolled tissue motion, which may become significant shortly after the acquisition of the precompression frame. In this paper, we investigate the feasibility of performing poroelastography experiments using an alternative experimental scheme. In the proposed experimental methodology, the reference precompression frame is continuously moved while the time interval between the frames that are correlated is kept short. This allows long data acquisition times with simultaneous minimization of the decorrelation due to undesired tissue motion in vivo. We validated this new method using both a step and a ramp compression functions. We performed poroelastographic simulations and experiments in phantoms and in tissues in vivo. The results were compared to those obtained using the traditional acquisition methodology. This study shows that the two methods yield similar results in vitro and suggests that the new method may be more robust to decorrelation noise in applications in vivo.

In this paper, we develop a theoretical expression for the signal-to-noise ratio (SNR) of shear strain elastograms. The previously-developed ideas for the axial strain filter (ASF) and lateral strain filter (LSF) are extended to define the concept of the shear strain filter (SSF). Some of our theoretical results are verified using simulations and phantom experiments. The results indicate that the signal-to-noise ratio of shear-strain elastograms ( SNRsse) improves with increasing shear strain and with improvements in system parameters such as the sonographic signal-to-noise ratio ( SNRs) beamwidth, center frequency and fractional bandwidth. The results also indicate that the amount of axial strain present along with the shear strain is an important parameter that determines the upper bound on SNRsse. The SNRsse will be higher in the absence of additional deformation due to axial strain.

Elastography based on strain imaging currently endures mechanical artefacts and limited contrast transfer efficiency. Solving the inverse elasticity problem (IEP) should obviate these difficulties; however, this approach to elastography is often fraught with problems because of the ill-posed nature of the IEP. The aim of the present study was to determine how the quality of modulus elastograms computed by solving the IEP compared with those produced using standard strain imaging methodology. Strain-based modulus elastograms (i.e., modulus elastograms computed by simply inverting strain elastograms based on the assumption of stress uniformity) and model-based modulus elastograms (i.e., modulus elastograms computed by solving the IEP) were computed from a common cohort of simulated and gelatin-based phantoms that contained inclusions of varying size and modulus contrast. The ensuing elastograms were evaluated by employing the contrast-to-noise ratio (CNRe) and the contrast transfer efficiency (CTEe) performance metrics. The results demonstrated that, at a fixed spatial resolution, the CNRe of strain-based modulus elastograms was statistically equivalent to those computed by solving the IEP. At low modulus contrast, the CTEe of both elastographic imaging approaches was comparable; however, at high modulus, the CTEe of model-based modulus elastograms was superior. (E-mail: marvin.m.doyley@dartmouth.edu) © 2005 World Federation for Ultrasound in Medicine & Biology.

An experimental study of the spatial resolution in elastography was conducted. Models that involved two cylindrical inclusions arranged as a wedge were used to characterize the axial and lateral resolution of the axial strain elastograms. A study of the dependence of the spatial resolution on several factors such as the algorithmic parameters, the applied strain and the modulus contrast was performed. The axial resolution was found to show a linear dependence with respect to the algorithmic parameters, namely the window length and the window shift used for strain estimation. The lateral resolution showed a weak dependence on the algorithmic parameters. A weak dependence of the spatial resolution on factors such as the modulus contrast and the applied strain was found. The trade-offs between the spatial resolution and the elastographic contrast-to-noise ratio (CNRe) were then analyzed. A nonlinear trade-off between the CNRe and the axial and lateral resolution was shown for conventional strain estimation techniques, with the CNRe improving at a more than linear rate with respect to a linear degradation in the resolution. This study provided an experimental framework for charac- terizing the spatial resolution in elastography and facilitating a comparison of the CNRe with spatial resolution. © 2004 World Federation for Ultrasound in Medicine & Biology.

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.

Conventional elastography involves quasistatic mechanical compression (external or internal) of the tissue under ultrasonic insonification to obtain radiofrequency (RF) A-lines before and after compression. Cross-correlation of the pre- and postcompression A-lines results in displacement images with axial gradients that produce the strain images (strain elastograms). Though the strain elastograms show structural similarities to the modulus images, they are not related in a simple way to the modulus images because the strains depend on both modulus and geometry of the materials being deformed. Therefore, a quantification of the similarities between the strain and modulus images may enhance the interpretation confidence of strain elastograms in depicting tissue structure. To demonstrate similarities between modulus images and strain elastograms, a feasibility study of using nanoindentation to obtain modulus images of thin slices of tissue and tissue-mimicking phantoms (agar-gelatin mixtures) was performed first, with encouraging results. This was followed by a comparison of modulus images and strain elastograms obtained from the same sample slices. The experimental results indicated that, under certain experimental conditions, it is feasible to perform quantitative comparisons between strain images (using elastography) and modulus images. A good visual, as well as quantitative, correspondence between structures in the modulus and strain images could be obtained at a 3-mm scale.

To test the feasibility of applying ultrasonic elastography on small animal oncology models, experiments were performed in vitro and in situ on murine mammary lesions induced exogenously by tumor cell line 66.3. In vitro studies involved three 1-week-old excised tumors embedded in a phantom block with ultrasonic properties similar to those of soft biologic tissues. In situ studies involved five mice whose bodies were embedded in pure gelatin blocks. The data were acquired from the blocks with a clinical scanner modified to have an automated compressor assembly and processed to construct the elastograms at various imaging planes within each block. The results were analyzed both qualitatively and quantitatively to assess the merits of the elastographic imaging and its limitations for in vivo serial studies of tumors in small animal oncology models.

Mechanics of articular cartilage can be represented using poroelastic theories where fluid and solid displacements are viscously coupled to create a time-dependent spatially heterogeneous behavior. In recent models of this tissue, finite element methods have been used to predict tissue deformation as a function of time for adult articular cartilage bearing a characteristic depth-dependent structure and composition. However, current experimental methods are limited in providing verification of these predictions. The current study presents an apparatus for imaging the radial displacement profile of cartilage in unconfined compression using an ultrasound technique called elastography. We acquired ultrasound A-scans across the lateral diameter of full-thickness cartilage disks containing a thin layer of underlying bone, during axial compression. Elastography was then applied to correlate temporally sequential A-scans to estimate the solid radial displacement profile in articular cartilage while it undergoes compression and stress-relaxation. Both time-dependent and depth-dependent solid radial displacement profiles were obtained with a precision better than 0.2 μm. The results generally agree with predictions of poroelastic models, demonstrating lateral expansion with an effective Poisson's ratio just after completion of the compression phase of the mechanical tests reaching values from 0.18 to 0.4 (depending on compression speed), followed by contraction to lower values. A more restricted movement was observed at both the articular surface and near to the subchondral bone than at regions midway between these two locations.

A ten-month study is presented of materials for use in heterogeneous elastography phantoms. The materials consist of gelatin with or without a suspension of microscopic safflower oil droplets. The highest volume percent of oil in the materials is 50%. Thimerosal acts as a preservative. The greater the safflower oil concentration, the lower the Young's modulus. Elastographic data for heterogeneous phantoms, in which the only variable is safflower oil concentration, demonstrate stability of inclusion geometry and elastic strain contrast. Young's modulus ratios (elastic contrasts) producible in a heterogeneous phantom are as high as 2.7. The phantoms are particularly useful for ultrasound elastography. They can also be employed in MR elastography, although the highest achievable ratio of longitudinal to transverse relaxation times is considerably less than is the case for soft tissues.

Elastography is a method that can ultimately generate several new kinds of images, called elastograms. As such, all the properties of elastograms are different from the familiar properties of sonograms. While sonograms convey information related to the local acoustic backscatter energy from tissue components, elastograms relate to its local strains, Young's moduli or Poisson's ratios. In general, these elasticity parameters are not directly correlated with sonographic parameters, i.e. elastography conveys new information about internal tissue structure and behavior under load that is not otherwise obtainable. In this paper we summarize our work in the field of elastography over the past decade. We present some relevant background material from the field of biomechanics. We then discuss the basic principles and limitations that are involved in the production of elastograms of biological tissues. Results from biological tissues in vitro and in vivo are shown to demonstrate this point. We conclude with some observations regarding the potential of elastography for medical diagnosis.

Conventional techniques in elastography estimate strain as the gradient of the displacement estimates obtained through crosscorrelation of pre- and postcompression rf A-lines. In these techniques, the displacements are estimated over overlapping windows and the strains are estimated as the gradient of the displacement estimates over adjacent windows. The large amount of noise at high window overlaps may result in poor quality elastograms, thus restricting the applicability of conventional strain estimation techniques to low window overlaps, which, in turn, results in a small number of pixels in the image. To overcome this restriction, we propose a multistep strain estimation technique. It computes the first elastogram using nonoverlapped windows. In the next step, the data windows are shifted by a small distance (small fraction of window size) and another elastogram is produced. This is repeated until the cumulative shift equals/exceeds the window size and all the elastograms are staggered to produce the final elastogram. Simulations and experiments were performed using this technique to demonstrate significant improvement in the elastographic signal-to-noise ratio ( SNRe) and the contrast-to-noise ratio ( CNRe) at high window overlaps over conventional strain estimation techniques, without noticeable loss of spatial resolution. This technique might be suitable for reducing the algorithmic noise in the elastograms at high window overlaps.

Early detection of cardiovascular diseases has been a very active research area in the medical imaging field. Assessment of the local and global mechanical functions is one of the major goals of accurate diagnosis. In this study, we investigated the feasibility of elastography for estimation and imaging of the local cardiac muscle displacement and strain in a human heart in vivo. In its noninvasive applications, elastography has been typically used to determine local tissue strain through the use of externally applied compression. For our study, we utilized the cardiac muscle motion during a cardiac cycle as the mechanical stimulus, and acquired successive radiofrequency (RF) data frames of the septal and posterior walls over a few cardiac cycles in parasternal and apical views, respectively. High-quality ciné-loop elastograms were obtained due to high frame rates and the resulting low decorrelation noise. Furthermore, the strain contrast was higher in the parasternal case, when only the posterior wall was imaged, and strain estimation was more robust in the apical view. High repeatability of the results was observed through elastographic measurements over several cardiac cycles. Finally, an M-mode version of elastography was used to follow part of the interventricular septum or the posterior wall over the course of two cardiac cycles. Not only do these preliminary results show that elastography is feasible in cardiac applications in vivo, but also that it can provide new information regarding cardiac motion and mechanical function. Future prospects include assessment of the role of elastography in detection of ischemia and infarction.

The effects of high intensity focused ultrasound (HIFU)-induced continuously varying thermal gradients on sound ray propagation were modeled theoretically. This modeling was based on Fermat's variational principle of least time for rays propagating in a continuously varying thermal gradient described by a radially symmetric heat equation. Such thermal lenses dynamically affect HIFU beam focusing, and simultaneously create ultrasonic geometric and intensity distortions and artifacts in monitoring devices. Techniques which are based upon ultrasonic cross-correlation methods, such as elastography and two-dimensional temperature estimation, also suffer distortion effects and generate artifacts.

The limits and trade-offs of the axial resolution in elastography were investigated using a controlled simulation study. The axial resolution in elastography was estimated as the distance between the full widths at half-maximum of the strain profiles of two equally stiff lesions embedded in a softer homogeneous background. The results show that the upper bound of the axial resolution in elastography is controlled by the physical wave parameters of the ultrasound (US) system used to acquire the data (transducer center frequency and band- width). However, an inappropriate choice of the parameters used to process the US data (cross-correlation window length and shift between consecutive windows) may compromise the best resolution attainable. The measured elastographic axial resolution was found to be on the order of the ultrasonic wavelength. (E-mail: Jonathan.Ophir@uth.tmc.edu) © 2002 World Federation for Ultrasound in Medicine & Biology.

This paper presents the tradeoffs in elastographic imaging. Elastography is viewed as a new imaging modality and presented in terms of three fundamental concepts that constitute the basis for the elastographic imaging process. These are the tissue elastic deformation process, the statistical analysis of strain estimation and the image characterization. The first concept involves the use of the contrast transfer efficiency ( CTE) that describes the mapping of a distribution of local tissue elastic moduli into a distribution of local longitudinal tissue strains. The second concept defines the elastographic system and the relationship between ultrasonic and signal processing parameters. This process is described in terms of a stochastic framework (the strain filter) that provides upper and practical performance bounds and their dependence on the various system parameters. Finally, the output image, the elastogram, is characterized by its image parameters, such as signal-to-noise ratio, contrast-to-noise ratio, dynamic range and resolution. Finite-element simulations are used to generate examples of elastograms that are confirmed by the theoretical prediction tools.

In sonography, phase aberration plays a role in the corruption of sonograms. Phase aberration does not have a significant impact on elastography, if statistically similar phase errors are present in both the pre- and postcompression signals. However, if the phase errors are present in only one of the pre- or postcompression signal pairs, the precision of the strain estimation process will be reduced. In some cases, increased phase errors may occur only in the postcompression signal due to changes in the tissue structure with the applied compression. Phase-aberration effects increase with applied strain and may be viewed as an image quality derating factor, much like frequency-dependent attenuation or undesired lateral tissue motion. In this paper, we present a theoretical and simulation study of the effects of phase aberration on the elastographic strain-estimation process, using the strain filter approach.

Spectral estimation of tissue strain has been performed previously by using the centroid shift of the power spectrum or by estimating the variation in the mean scatterer spacing in the spectral domain. The centroid shift method illustrates the robustness of the direct, incoherent strain estimator. In this paper, we present a strain estimator that uses spectral cross-correlation of the pre- and postcompression power spectrum. The centroid shift estimator estimates strain from the mean center frequency shift, while the spectral cross-correlation estimates the shift over the entire spectrum. Spectral cross-correlation is shown to be more sensitive to small shifts in the power spectrum and, thus, provides better estimation for smaller strains when compared to the spectral centroid shift. Spectral cross-correlation shares all the advantages gained using the spectral centroid shift, in addition to providing accurate and precise strain estimation for small strains. The variance and noise properties of the spectral strain estimators quantified by their respective strain filters are also presented.

The Cramér-Rao Lower Bounds (CRLB) are derived for the displacement and strain estimation in directions orthogonal to the ultrasonic beam axis, using a previously-described recorrelation method of axial, lateral and elevational motion estimation. We also compare it to the lateral tracking method that involves the sole use of the axial signal in the transverse direction. Our theoretical results, verified with simulations and phantom experiments, show that elastography is capable of measuring axial and transverse strain at up to 10% axially applied compression. Finally, we predict the performance of the estimation of the Poisson's ratio using decoupled axial and lateral estimates that result from the recorrelation method.

The practice of elastography is generally limited to small applied compressions (typically 1%), under the assumption of a linear stress-strain relationship in biological tissue. However, the recent reports of larger applied compressions and precompression levels to increase the strain contrast violate the above assumption. The nonlinear stress-strain relationships in different breast tissue types significantly alter the contrast in elastography, especially for large applied compression. The moduli of normal fibrous and glandular breast tissue (along with cancerous lesions) are strain-dependent, with tissue stiffness increasing with applied compression. In this paper, we illustrate that the strain-dependence of the modulus has a significant impact on the elastographic contrast and on the contrast-to-noise ratio, and may even cause a reversal of the contrast in certain situations. This paper also emphasizes the effect of the precompression strain level on the strain contrast.

Elastography typically measures and images the normal strain component along the insonification/compression axis, i.e., in the axial direction. We have recently shown that, by using interpolation and cross-correlation methods of transversely displaced RF echo segments, it is possible to measure and image displacement and strain transversely to the beam with good precision. This enables the estimation and imaging of all three principal normal strain components. Generally, motion in a direction other than that in which strain is estimated may result in decorrelation noise, severely corrupting the estimates. Therefore, a correction method is applied to correct the displacement and strain estimates for decorrelating motion. In this paper, we show how corrected displacement estimates can also be used to estimate and image the shear strain components. This may allow us to identify regions of decorrelation noise in the normal strain measurement that are due to shear strain. Shear strain estimates provide supplementary information, which can characterize different tissue elements based on their mobility. In the case of breast lesions, low mobility is related to malignancy. Following an in vivo case, we show with 2D simulations how assessment of tumor mobility can be achieved with shear strain estimation.

We have reported several artifacts in elastography (1991). These include mechanical artifacts, such as stress concentration, and signal processing artifacts, such as zebras, which are caused by bias errors incurred during the estimation of the peak of correlation functions using a curve-fitting method. We investigate the bias errors and show that bias errors in curve-fitting methods are substantially increased because of nonlinear operations on the echo signals that reduce other errors. We also show that, for typical sampling rates, the bias errors can be ignored in the absence of these nonlinear operations.

The elastographic visualization and evaluation of high-intensity focused ultrasound (HIFU)-induced lesions were investigated. The lesions were induced in vitro in freshly excised canine livers. The use of different treatment intensity levels and exposure times resulted in lesions of different sizes. Each lesion was clearly depicted by the corresponding elastogram as being an area harder than the background. The strain contrast of the lesion/background was found to be dependent on the level of energy deposition. A lesion/background strain contrast between 22.5 dB and 23.5 dB was found to completely define the entire zone of tissue damage. The area of tissue damage was automatically estimated from the elastograms by evaluating the number of pixels enclosed inside the isointensity contour lines corresponding to a strain contrast of 22.5, 23 and 23.5 dB. The area of the lesion was measured from a tissue photograph obtained at approximately the same plane where elastographic data were collected. The estimated lesion areas ranged between approximately 10 mm 2 and 110 mm 2 . A high correlation between the damaged areas as depicted by the elastograms and the corresponding areas as measured from the gross pathology photographs was found (r 2 5 0.93, p value < 0.0004, n 5 16). This statistically significant high correlation demonstrates that elastography has the potential to become a reliable and accurate modality for HIFU therapy monitoring. © 1999 World Federation for Ultrasound in Medicine & Biology.

The potential for visualizing high-intensity focused ultrasound (HIFU)-induced thermal lesions in biological soft tissues in vitro using elastography was investigated. Thermal lesions were created in rabbit paraspinal skeletal muscle in vivo. The rabbits were sacrificed 60 h following the treatment and lesioned tissues were excised. The tissues were cast in a block of clear gel and elastographic images of the lesions were acquired. Gross pathology of the tissue samples confirmed the characteristics of the lesions.

The basic principles of using sonographic techniques for imaging the elastic properties of tissues are described, with particular emphasis on elastography. After some preliminaries that describe some basic tissue stiffness measurements and some contrast transfer limitations of strain images are presented, four types of elastograms are described, which include axial strain, lateral strain, modulus and Poisson's ratio elastograms. The strain filter formalism and its utility in understanding the noise performance of the elastographic process is then given, as well as its use for various image improvements. After discussing some main classes of elastographic artefacts, the paper concludes with recent results of tissue elastography in vitro and in vivo.

In elastography, tissue under investigation is compressed, and the resulting strain is estimated from the gradient of displacement estimates. Therefore, it is important to accurately estimate the displacements (time-delay) for good quality elastograms. A principal source of error in time-delay estimation in elastography is the decorrelation of the echo signal due to tissue compression (decorrelation noise). Temporal stretching of the postcompression signals has been shown to reduce the decorrelation noise at small strains. In this article, we present a deconvolution filter that reduces the decorrelation even further when applied in conjunction with signal stretching. The performance of the proposed filter is evaluated using simulated data.

The range of strains that can be imaged by any practical elastographic imaging system is inherently limited, and a performance measure is valuable to evaluate these systems from the signal and noise properties of their output images. Such a measure was previously formulated for systems employing cross-correlation based time-delay estimators through the strain filter. While the strain filter predicts the signal-to-noise ratio (SNR/sub e/) for each tissue strain in the elastogram and provides valuable insights into the nature of image noise, it understated the effects of image resolution (axial resolution, as determined by the cross-correlation window length) on the noise. In this work, the strain filter is modified to study the strain noise at multiple resolutions. The effects of finite window length on signal decorrelation and on the variance of the strain estimator are investigated. Long-duration windows are preferred for improved sensitivity, dynamic range, and SNR/sub e/. However, in this limit the elastogram is degraded due to poor resolution. The results indicate that for nonzero strain, a window length exists at which the variance of strain estimator attains its minima, and consequently the elastographic sensitivity, dynamic range and SNR/sub e/ are strongly affected by the selected window length. Simulation results corroborate the theoretical results, illustrating the presence of a window length where the strain estimation variance is minimized for a given strain value. Multiresolution elastography, where the strain estimate with the highest SNR/sub e/ obtained by processing the pre- and post-compression waveforms at different window lengths is used to generate a composite elastogram and is proposed to improve elastograms. All the objective elastogram parameters (namely: SNR/sub e/, dynamic range, sensitivity and the average elastographic resolution-defined as the cross-correlation window length) are improved with multiresolution elastography when compared to the traditional method of utilizing a single window length to generate the elastogram. Experimental results using a phantom with a hard inclusion illustrates the improvement in elastogram obtained using multiresolution analysis.

To determine the appearance of various breast lesions on elastograms and to explore the potential of elastography in the diagnosis of breast lesions.A total of 46 breast lesions were examined with elastography. Patients underwent biopsy or aspiration of all lesions, revealing 15 fibroadenomas, 12 carcinomas, six fibrocystic nodules, and 13 other lesions. The elastogram was generated from radio-frequency data collected with use of a 5-MHz linear-array transducer. The elastogram and corresponding sonogram were evaluated by a single observer for lesion visualization, relative brightness, and margin definition and regularity. The sizes of the lesions at each imaging examination and at biopsy were recorded and compared.Softer tissues such as fat appear as bright areas on elastograms. Firm tissues, including parenchyma, cancers, and other masses, appear darker. The cancers were statistically significantly darker than fibroadenomas (P.005) and substantially larger on the elastogram than on the sonogram. Seventy-three percent of fibroadenomas and 56% of solid benign lesions could be distinguished from cancers by using lesion brightness and size difference. Some cancers that appeared as areas of shadowing on sonograms appeared as discrete masses on elastograms.Elastography has the potential to be useful in the evaluation of areas of shadowing on the sonogram. It also may be helpful in the distinction of benign from malignant masses.

Bamber and Bush (1995) used the correlation coefficient for freehand elasticity imaging. Varghese and Ophir (1996) found it to be a biased estimator of strain with a large variability. In this study, we systematically investigate the effect of changes in various system and processing parameters on the performance of the correlation coefficient strain estimator, and demonstrate, using simulated data, that noise and frequency-dependent attenuation can introduce variable bias in this estimator.

We present a review of elastography from a systems point of view. We show that elastography can be viewed as a cascade of two distinct processes. The first process involves the mapping of the distribution of local elastic moduli in the target into a distribution of local longitudinal strains. This process is governed by the theory of elasticity as applied to a particular experimental setup under some specific boundary conditions and some assumptions. Since this process involves errors due to the simplified mechanical model used, artifacts such as target hardening, stress concentrations, and limited contrast-transfer efficiency are usually encountered. These errors may be recursively minimized by solving the inverse problem, thus increasing the contrast-transfer efficiency such that a more accurate modulus image may be obtained. The second process involves the production of the strain image (elastogram) from ultrasonically estimated values of local strains. Here, the limitations of the ultrasound system [such as time-bandwidth product, center frequency, and sonographic signal-to-noise ratio (SNR)] as well as the signal-processing algorithms used to process the signals cause additional corruption of the data through the introduction of constraints in the attainable elastographic SNR, resolution, sensitivity, and strain dynamic range. This process is described in terms of a stochastic strain filter. These two system components are discussed in detail, and it is concluded that both must be optimized in a specific order to result in quality elastograms. © 1997 John Wiley & Sons, Inc. Int J Imaging Syst Technol, 8, 89–103, 1997

The accuracy and precision of the strain estimates in elastography depend on a myriad number of factors. A clear understanding of the various factors (noise sources) that plague strain estimation is essential to obtain quality elastograms. The nonstationary variation in the performance of the strain filter due to frequency-dependent attenuation and lateral and elevational signal decorrelation are analyzed in this and the companion paper for the cross-correlation-based strain estimator. In this paper, we focus on the role of frequency-dependent attenuation in the performance of the strain estimator. The reduction in the signal-to-noise ratio (SNRs) in the RF signal, and the center frequency and bandwidth downshift with frequency-dependent attenuation are incorporated into the strain filter formulation. Both linear and nonlinear frequency dependence of attenuation are theoretically analyzed. Monte-Carlo simulations are used to corroborate the theoretically predicted results. Experimental results illustrate the deterioration in the precision of the strain estimates with depth in a uniformly elastic phantom. Theoretical, simulation and experimental results indicate the importance of high SNRs values in the RF signals, because the strain estimation sensitivity, elastographic SNRe and dynamic range deteriorate rapidly with a decrease in the SNRs. In addition, a shift in the strain filter toward higher strains is observed at large depths in tissue due to the center frequency downshift.

We review the principles of elastography and some of its accomplishments to date in the area of breast imaging in vivo. We present a literature review of a variety of methods for the estimation of tissue elasticity that have been reported in the literature in the past 15 years, and of data on the elastic properties of soft tissues. This is followed by a description of elastography and its relationship to the theory of elasticity. The principles underlying the elastography imaging technique, and methods for time delay estimations and their tradeoffs are discussed. We then present results of computer simulations, phantom and tissue studies in vitro, and some breast imaging studies in vivo. After a discussion of the origin and appearance of some important elastographic artifacts, we conclude with some general observations and conclusions.

Elastography uses estimates of the time delay (obtained by cross-correlation) to compute strain estimates in tissue due to quasistatic compression. Because the time delay estimates do not generally occur at the sampling intervals, the location of the cross-correlation peak does not give and accurate estimate of the time delay. Sampling errors in the time-delay estimate are reduced using signal interpolation techniques to obtain subsample time-delay estimates. Distortions of the echo signals due to tissue compression introduce correlation artifacts in the elastogram. These artifacts are reduced by a combination of small compressions and temporal stretching of the postcompression signal. Random noise effects in the resulting elastograms are reduced by averaging several elastograms, obtained from successive small compressions (assuming that the errors are uncorrelated). Multicompression averaging with temporal stretching is shown to increase the signal-to-noise ratio in the elastogram by an order of magnitude, without sacrificing sensitivity, resolution or dynamic range. The strain filter concept is extended in this article to theoretically characterize the performance of multicompression averaging with temporal stretching.

Elastography is a technique for the estimation of tissue elasticity that is based on the estimation of strain. Tissue strain can be estimated by finite difference computations of echo time-delay. Echo time-delays are obtained by cross-correlation processing of pre- and post-compression echo signals. Errors in strain estimation can be expressed in terms of the errors in time delay estimation for given echo-signal characteristics. The smallest time delay estimation error is given by the Cramer-Rao Lower Bound (CRLB), which can be achieved when operating under the small error condition. Based on the CRLB, we obtain an expression for the lower bound for the strain estimation error (LBSE). The LBSE equation is derived under the assumption that the post-compression echo signal can be reconstructed to the original shape of the echo signal before compression. The theoretical bound given by the LBSE may or may not be achievable in practice, depending on the compliance with the requirements for echo signal reconstruction. In an example, the obtained LBSE shows that there is potential for significant reduction of the current level of noise in elastograms. >

Elastography is a new ultrasonic imaging technique that produces images (elastograms) of the elastic properties of complaint tissue. To determine the Young's modulus it is necessary to measure or estimate any five of seven relevant variables. In elastography, the measured quantity is the normal strain component in the direction of the applied load, and the three normal components of stress may be estimated using the modified Love's analytical models while assuming a value close to 0.5 (incompressible) for Poisson's ratio. The distribution of Young's moduli can thus be computed and displayed in the form of two-dimensional images called elastrograms. The analytical models used for the estimation of the three normal components of stress assume that the target is semi-infinite and homogeneous in composition. The objective of this article is to determine some of the errors associated with the assumption of homogeneity of the target. Experiments using computer simulations were performed to study the efficiency with which elastograms display the contrast in the Young's modulus of a lesion or target, with respect to its background under certain conditions. It was observed (using the definition of contrast-transfer efficiency of elastography as the ratio of the elasticity contrast as measured from an elastogram, to the true contrast) that elastograms were consistently efficient in quantitatively depicting the elasticity contrast of hard lesions; however, they showed suboptimal contrast-transfer efficiency in cases of soft lesions in a hard background. In general, elastograms are efficient in displaying the elasticity contrast of hard or soft lesions which have a low contrast level with respect to the surroundings, irrespective of their size and location.

Breast cancers that are found and confirmed because they are causing symptoms tend to be larger and are more likely to have already spread to the lymph nodes and beyond. Thus, early detection and confirmation are of paramount importance. The normalized axial-shear strain area (NASSA) feature from the axial-shear strain elastogram (ASSE) has been shown to be a feature that can identify the boundary-bonding conditions that are indicative of the presence of cancer. Recently, we investigated and reported on the potential of the NASSA feature for breast lesion classification into fibroadenomas and cancers. In this article, we investigate the size distribution of the lesions that were part of the previous study and analyze classification performance specifically on small lesions (10 mm diameter). A total of 33 biopsy-proven malignant tumors and 30 fibroadenomas were part of the study that involved three observers blinded to the Breast Imaging Reporting and Data System (BIRADS) ultrasound scores. The observers outlined the lesions on the sonograms and the lesion size (maximum circle-equivalent diameter in millimeters) was computed from this outline. The ASSE was automatically segmented and color-overlaid on the sonogram, and the NASSA feature from ASSE was computed semi-automatically. Receiver operating characteristic curves were then generated for the subset of cases involving small lesions. Box plots were produced for the two different lesion size groups, small and large, from a logistic regression classifier that was built previously. The results of our study show that approximately 38% and 22% of the fibroadenomas and cancers, respectively, were small. Furthermore, it was found that the NASSA feature resulted in a perfect classification of the small lesions, both in the training data and in the cross-validation. For lesions10 mm the difference in fibroadenoma and cancer mean scores was 0.73 ± 0.13 (p0.001), whereas lesions10 mm had a difference of 0.52 ± 0.24 (p0.001). The results also showed that the small lesions actually had better classification than the larger lesions (10 mm). These results suggest that the ASSE feature can work equally well, even on small lesions, to improve the standard ultrasound BIRADS-based breast lesion classification of fibroadenoma and malignant tumors.

Elastography, a technique that uses ultrasonic pulses to track the internal displacements of small tissue elements in response to an externally applied stress, has been applied to beef muscle. Beef longissimus (1 day post mortem ) and semimembranosus (5 days post mortem ) muscles were obtained from A maturity beef carcasses. Samples were vacuum-packaged and frozen to −20°C. For elastography measurements, muscles were equilibrated to a constant temperature (30° C ± 0·5) in a water tank. Custom transmitters and receivers were used in conjunction with a 2·25 MHz medical transducer. The transducer was driven by a 286 PC, and the radio-frequency echoes digitized at 50 MHz and 8 bits. The pre- and post- compression echo trains (A-lines) were subjected to cross-correlation analysis. Visual interpretation of beef elastograms demonstrate circular areas of relatively inelastic tissues and smaller, banding areas of elastic tissues in the cross-section of beef longissimus muscle. The dark inelastic areas from the elastograms may be related to myofibrilar areas from the same muscle sections; the light, elastic band areas from the elastograms may be related to perimysiaal connective tissue or intramuscular fat. Fatty septa and a calcified abscess could be easily identified on the elastogram. These preliminary results demonstrate that elastography may have potential as a non-intrusive method of visualizing tissue components of beef muscle.

In this paper, we report on a study that investigated the feasibility of reliably visualizing high-intensity focused ultrasound (HIFU) lesion boundaries using axial-shear strain elastograms (ASSE). The HIFU-induced lesion cases used in the present work were selected from data acquired in a previous study. The samples consisted of excised canine livers with thermal lesions produced by a magnetic resonance-compatible HIFU system (GE Medical System, Milwaukee, WI, USA) and were cast in a gelatin block for the elastographic experiment. Both single and multiple HIFU-lesion samples were investigated. For each of the single-lesion samples, the lesion boundaries were determined independently from the axial strain elastogram (ASE) and ASSE at various iso-intensity contour thresholds (from -2 dB to -6 dB), and the area of the enclosed lesion was computed. For samples with multiple lesions, the corresponding ASSE was analyzed for identifying any unique axial-shear strain zones of interest. We further performed finite element modeling (FEM) of simple two-inclusion cases to verify whether the in vitro ASSE obtained were reasonable. The results show that the estimation of the lesion area using ASSE is less sensitive to iso-intensity threshold selection, making this method more robust compared with the ASE-based method. For multiple lesion cases, it was shown that ASSE enables high-contrast visualization of a "thin" untreated region in between multiple fully-treated HIFU-lesions. This contrast visualization was also noticed in the FEM predictions. In summary, the results demonstrate that it is feasible to reliably visualize HIFU lesion boundaries using ASSE.