Faouzi Kallel

Elastography: Ultrasonic estimation and imaging of the elastic properties of tissues

Abstract 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 Poissons 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.

A Least-Squares Strain Estimator for Elastography

A least-squares strain estimator (LSQSE) for elastography is proposed. It is shown that with such an estimator, the signal-to-noise ratio in an elastogram (SNRe ) is significantly improved. This improvement is illustrated theoretically using a modified strain filter and experimentally using a homogeneous gel phantom. It is demonstrated that the LSQSE results in an increase of the elastographic sensitivity (smallest strain that could be detected), thereby increasing the strain dynamic range. Using simulated data, it is shown that a tradeoff exists between the improvement in SNRe and the reduction of strain contrast and spatial resolution.

Tissue elasticity reconstruction using linear perturbation method

A new method to reconstruct the elastic modulus of soft tissue subjected to an external static compression is presented. In this approach the Newton-Raphson method is used to vary a finite element (FE) model of the elasticity equations to fit, in a least squared sense, a set of axial tissue displacement fields estimated using a correlation technique applied to ultrasound signals. The ill-conditioning of the Hessian matrix is eliminated using the Tikhonov regularization technique. This regularization provides a compromise between fidelity to the observed data and a priori information of the solution. Using an echographic image formation model, it is shown that the method converges within a few iterations (8-10) and that strain images artifacts which are common in elastography are significantly reduced after the resolution of the inverse problem.

ELASTOGRAPHIC CHARACTERIZATION OF HIFU-INDUCED LESIONS IN CANINE LIVERS

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 -2.5 dB and -3.5 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 -2.5, -3 and -3.5 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 mm2 and 110 mm2. 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 (r2 = 0.93, p value < 0.0004, n = 16). This statistically significant high correlation demonstrates that elastography has the potential to become a reliable and accurate modality for HIFU therapy monitoring.

Elastography : Imaging the Elastic Properties of Soft Tissues with Ultrasound

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, Youngs moduli or Poissons 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.

The feasibility of elastographic visualization of HIFU-induced thermal lesions in soft tissues

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 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.

Fundamental limitations on the contrast-transfer efficiency in elastography: An analytic study

Elastography is a new ultrasonic imaging technique introduced to produce images of the Youngs modulus distribution of compliant tissue. This Youngs modulus distribution is derived from the ultrasonically estimated longitudinal internal strains induced by an external compression of the tissue. The displayed two-dimensional images are called elastograms. Recently, contrast-transfer efficiency, defined as the ratio of elasticity contrast as measured from elastogram to the true contrast, was used to illustrate by simulation the fundamental limitation of elastography in displaying the elastic modulus contrast of soft inclusion in a hard background and vice versa. In this paper, using a classical analytic solution of the elasticity equations derived for an infinite medium subjected to a uniaxial compression, we confirm such earlier simulations results. For this purpose we derive an analytic expression predicting the observed contrast in elastograms.

Tradeoffs in elastographic imaging.

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.

ELASTOGRAPHIC IMAGING OF LOW-CONTRAST ELASTIC MODULUS DISTRIBUTIONS IN TISSUE

Elastography is a new ultrasonic imaging technique that produces images of the strain distribution in compliant tissues. This strain distribution is derived from ultrasonically estimated longitudinal internal motion induced by an external compression of the tissue. The displayed two-dimensional (2-D) images are called elastograms. In this paper, it is demonstrated that, when signal-to-noise ratio-enhancing techniques are used, elastography is capable of imaging low-contrast elastic modulus tissue structures with high contrast-to-noise ratios. This is demonstrated using both computer simulations and data obtained from 3 days postmortem ovine kidneys in vitro. The elastograms of such organs suggest that the modulus slowly decays from the renal cortex (RC) to the interior of the renal sinus (RS). Such modulus variation is corroborated by independent measurements of the Youngs moduli. It is found that the RC is approximately twice as hard as the interior of the RS. We invoke our previous results on elastographic contrast-transfer efficiency to demonstrate that, at low contrast, the elastogram may be interpreted as a quantitative image of the relative Youngs modulus distribution.

Elastography: A systems approach

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.