Table of contents

The idea of using soft tissue mechanical properties to diagnose disease occurred to ancient Greek physicians more than 2000 years ago. Hippocrates and colleagues reportedly invented manual palpation as a means for detecting occult breast tumours before the advanced phase of this disease negated the effectiveness of surgical treatment. Simple palpation is still used today for early cancer detection of the prostate and breast. We now know that tissues stiffen as some tumours form and grow because of inflammation and desmoplasia, a dense cellular reaction specific to malignant breast lesions with highly cross-linked collagenous fibres. The development of elasticity imaging is driven, in part, by the need to improve the detection and differentiation of early malignant disease. However, elasticity imaging can also provide important new information in other clinical examinations, including visualization of myocardial dynamics to assess tissue viability following ischaemia and skeletal muscle force generation. Methods and applications of these topics are addressed in the following twenty papers.

The approaches to elasticity imaging vary widely but always involve the application of medical imaging technologies - often ultrasound and magnetic resonance because of their high sensitivity to small tissue movements - to track natural and applied deformations. We see from the papers in this special issue that elasticity is a term that applies to a broad range of parametric imaging for describing spatial and temporal variations in tissue viscoelasticity.

Static methods apply ultrasound or magnetic resonance signals in procedures that are best described as palpation by remote sensing. They are considered static because the data acquisition time (1/frame rate) is much faster than the tissue deformation rate. The same signal processing concepts involved in measuring velocity vectors in applications from radar tracking to blood flow imaging are used to estimate local displacement fields from echo signals recorded while straining body surfaces or vessel lumen mechanically or by radiation force. From displacement estimates, images of strain (elastograms), viscosity or stimulated acoustic emission are formed. The parameter selected for display in an image depends on the diagnostic task and the measurement geometry. Several papers in this issue discuss control of tissue movement, signal processing for parameter estimation and their combined effects on errors and image quality.

Dynamic methods are for imaging tissues strained at rates equal to or greater than the acquisition frame rate. Some methods estimate the distribution of shear moduli from images of low-frequency acoustic shear waves propagating in the body. These methods, referred to as sonoelasticity and magnetic resonance elastography, have been used to detect lesions and assess force generation in skeletal muscle. Also, planar tagged MR imaging is an exciting approach to the evaluation of cardiac dynamics that visualizes strain and strain rate during the cardiac cycle. Methods and applications of dynamic elasticity imaging are also presented.

Clearly, most of the approaches described in this issue are targeted toward clinical medicine. Each has strengths and weakness that vary with applications. However, many of these same ideas may be scaled down in size to study cell mechanics and mechano-transduction (two exciting new areas of basic research at the frontier of molecular biology), functional genomics and systems engineering. Perhaps the most promising aspect of these investigations is the interdisciplinary nature, which, in the true spirit of biomedical engineering, teaches us the value of research teams with expertize in physiology, biomechanics, signals and systems, radiation physics and medicine. We look forward to the progress these new methods will bring to clinical and basic biomedical research, and what they will teach us about complex biological systems and disease processes.

The advent of real-time ultrasound in the 1970s, together with a growing interest in tissue characterization, led to a number of investigators using the nature of tissue motion to distinguish healthy from diseased tissue. Our group at the (then) Ultrasonics Institute demonstrated the use of phase methods for detecting very small tissue motions, using natural stimuli. The method could also be applied in the lag (autocorrelation) domain to directly measure the amount of deformation to high accuracy. This method was also applied to measuring the amount of dilatation of blood vessels using both conventional and intravascular ultrasound. A basic limitation of these techniques was the poor spatial resolution, and quasistatic methods soon replaced this method of measuring tissue deformation. However, a new way of assessing the health of tissues had been established.

Two real-time strain imaging concepts and systems are presented. Both systems are based on a conventional ultrasound scanner that is connected to a PC with an A/D converter card for real-time data acquisition of rf data. Differential strain between successively acquired rf frames are estimated using phase root seeking. The first concept uses a special real-time implementation of manual elastography. In the second concept, denoted `vibrography', the static compression is replaced by low-frequency axial vibration of the probe, still operating in quasistatic acquisition mode. The properties of both concepts are discussed with regard to noise and motion artefacts, and it is shown, using simulations and phantom experiments, that both imaging concepts yield the same kind of strain images. Vibrography has the advantage that no manual compression has to be applied, total compression can be very low and some motion artefacts are better suppressed.

Acoustic radiation force has been proposed as a method of interrogating the mechanical properties of tissue. One simple approach applies a series of focused ultrasonic pulses to generate an acoustic radiation force, then processes the echoes returned from these pulses to estimate the radiation-force-induced displacement as a function of time. This process can be repeated at a number of locations to acquire data for image formation. In previous work we have formed images of tissue stiffness by depicting the maximum displacement induced at each tissue location after a finite period of insonification. While these maximum displacement images are able to differentiate materials of disparate mechanical properties, they exploit only a fraction of the information available. In this paper we show that the time-displacement curves acquired from tissue mimicking phantoms exhibit a viscoelastic response which is accurately described by the Voigt model. We describe how the viscous and elastic parameters of this model may be determined from experimental data. Finally, we show phantom images that depict not only the maximum local displacement, but also the viscous and elastic model parameters. These images offer complementary information about the target.

Over the past few years there has been an increasing interest in using the radiation force of ultrasound for evaluating, characterizing and imaging biological tissues. Of particular interest are those methods that measure the dynamic properties of tissue at low frequencies. In this paper we present dynamic radiation force methods for probing tissue as a new field, discuss the inter- relationship of several methods within this field and compare their features. The techniques in this field can be categorized into three groups: transient methods, shear-wave measurement methods and a recently developed method called vibro-acoustography. The last method is the focus of this paper. After briefly describing the key concepts of the first two methods, we will present a detailed description of vibro-acoustography. Finally, we will compare the capabilities and limitations of these methods.

Intravascular ultrasound elastography is a method for measuring the local elastic properties using intravascular ultrasound (IVUS). The elastic properties of the different tissues within the atherosclerotic plaque are measured through the strain. Knowledge of these elastic properties is useful for guiding interventional procedures (balloon dilatation, ablation) and detection of the vulnerable plaque. In the last decade, several groups have applied elastography intravascularly with various levels of success. In this paper, the approaches of the different research groups will be discussed. The focus will be on our approach to the application of intravascular elastography.

Elastograms were acquired in vitro and in vivo using the relative local displacements between IVUS images acquired at two levels of intravascular pressure with a 30 MHz mechanical or a 20 MHz array echo catheter. These displacements were estimated from the time shift between gated radiofrequency echo signals using cross-correlation algorithms with interpolation around the peak.

Experiments on gel-based phantoms mimicking atherosclerotic vessels demonstrated the capability of elastography to identify soft and hard tissues independently of the echogenicity contrast. In vitro experiments on human arteries have demonstrated the potential of intravascular elastography to identify different plaque types based on their mechanical properties. These plaques could not be identified using the IVUS image alone. In vivo experiments revealed that reproducible elastograms could be obtained near end-diastole. Partial validation using the echogram was performed.

Intravascular elastography provides information that is frequently unavailable or inconclusive from the IVUS image and which may therefore assist in the diagnosis and treatment of atherosclerotic disease.

Sonoelastography is an ultrasound imaging technique where low-amplitude, low-frequency shear waves (less than 0.1 mm displacement and less than 1 kHz frequency) are propagated through internal organs, while real-time Doppler techniques are used to image the resulting vibration pattern. When a discrete hard inhomogeneity, such as a tumour, is present within a region of soft tissue, a decrease in the vibration amplitude will occur at its location. This forms the basis for tumour detection using sonoelastography. For three-dimensional (3D) imaging the acquisition of sequential tomographic slices using this technique, combined with image segmentation, enables the reconstruction, quantification and visualization of tumour volumes. Sonoelastography and magnetic resonance images (MRI) of a tissue phantom containing a hard isoechoic inclusion are compared to evaluate the accuracy of this method. The tumour delineation from sonoelastography was found to have good agreement with the tumour from MRI except for a bleeding at one of its ends. Although sonoelastography is still in an experimental phase, the principles behind this imaging modality are explained and some practical aspects of acquiring sonoelastography images are described. Results from a 3D sonoelastography reconstruction of a tissue mimicking phantom and an ex vivo whole prostate specimen are presented.

A novel iterative approach is presented to estimate Young's modulus in homogeneous soft tissues using vibration sonoelastography. A low-frequency (below 100 Hz) external vibration is applied and three or more consecutive frames of B-scan image data are recorded. The internal vibrational motion of the soft tissue structures is calculated from 2D displacements between pairs of consecutive frames, which are estimated using a mesh-based speckle tracking method. An iterative forward finite element approach has been developed to reconstruct Young's modulus from the measured vibrational motion. This is accomplished by subdividing the 2D image domain into sample blocks in which Young's modulus is assumed to be constant. Because the finite element equations are internally consistent, boundary values other than displacement are not required. The sensitivity of the results to Poisson's ratio and the damping coefficient (viscosity) is investigated. The approach is verified using simulated displacement data and using data from tissue-mimicking phantoms.

An effective shear modulus reconstruction technique is described which uses ultrasonic strain measurements for diagnosis of superficial tissues, i.e. our previously developed ultrasonic strain measurement and shear modulus reconstruction methods are combined and enhanced. The technique realizes very low computational load, yet yields fairly high quantitativeness, high stability and spatial resolution, and large dynamic range. The suitability of the method is demonstrated on in vitro pork ribs and in vivo human breast tissues (fibroadenoma and scirrhous carcinoma).

This paper describes an inverse reconstruction technique based on a modified Newton Raphson iterative scheme and the finite element method, which has been developed for computing the spatial distribution of Young's modulus from within soft tissues. Computer simulations were conducted to determine the relative merits of reconstructing tissue elasticity using knowledge of (a) known displacement boundary conditions (DBC), and (b) known stress boundary conditions (SBC). The results demonstrated that computing Young's modulus using knowledge of SBC allows accurate quantification of Young's modulus. However, the quality of the images produced using this reconstruction approach was dependent on the Young's modulus distribution assumed at the start of the reconstruction procedure. Computing Young's modulus from known DBC provided relative estimates of tissue elasticity which, despite the disadvantage of not being able to accurately quantify Young's modulus, formed images that were generally superior in quality to those produced using the known SBC, and were not affected by the trial solution.

The results of preliminary experiments on phantoms demonstrated that this reconstruction technique is capable in practice of improving the fidelity of tissue elasticity images, reducing the artefacts otherwise present in strain images, and recovering Young's modulus images that possess excellent spatial and contrast resolution.

Multidimensional, high-resolution ultrasonic imaging of rapidly moving tissue is primarily limited by sparse sampling in the lateral dimension. In order to achieve acceptable spatial resolution and velocity quantization, interpolation of laterally sampled data is necessary. We present a novel method for estimating lateral subsample speckle motion and compare it with traditional interpolation methods. This method, called grid slopes, requires no a priori knowledge and can be applied to data with as few as two samples in the lateral dimension. Computer simulations were performed to compare grid slopes with two conventional interpolation schemes, parabolic fit and cubic spline. Results of computer simulations show that parabolic fit and cubic spline performed poorly at translations greater than 0.5 samples, and translations less than 0.5 samples were subject to an estimation bias. Grid slopes accurately estimated translations between 0 and 1 samples without estimation bias at high signal-to-noise ratios. Given that the grid slopes interpolation technique performs well at high signal-to-noise ratios, one pertinent clinical application might be tissue motion tracking.

In elastography we have previously developed a tracking and correction method that estimates the axial and lateral strain components along and perpendicular to the compressor/scanning axis following an externally applied compression. However, the resulting motion is a three-dimensional problem. Therefore, in order to fully describe this motion we need to consider a 3D model and estimate all three principal strain components, i.e. axial, lateral and elevational (out-of-plane), for a full 3D tensor description.

Since motion is coupled in all three dimensions, the three motion components have to be decoupled prior to their estimation. In this paper, we describe a method that estimates and corrects motion in three dimensions, which is an extension of the 2D motion tracking and correction method discussed before. In a similar way as in the 2D motion estimation, and by assuming that ultrasonic frames are available in more than one parallel elevational plane, we used methods of interpolation and cross-correlation between elevationally displaced RF echo segments to estimate the elevational displacement and strain. In addition, the axial, lateral and elevational displacements were used to estimate all three shear strain components that, together with the normal strain estimates, fully describe the full 3D normal strain tensor resulting from the uniform compression. Results of this method from three-dimensional finite-element simulations are shown.

For the purpose of quantifying the noise in acoustic elastography, a displacement covariance matrix is derived analytically for the cross-correlation based 3D motion estimator. Static deformation induced in tissue from an external mechanical source is represented by a second-order strain tensor. A generalized 3D model is introduced for the ultrasonic echo signals. The components of the covariance matrix are related to the variances of the displacement errors and the errors made in estimating the elements of the strain tensor. The results are combined to investigate the dependences of these errors on the experimental and signal-processing parameters as well as to determine the effects of one strain component on the estimation of the other. The expressions are evaluated for special cases of axial strain estimation in the presence of axial, axial-shear and lateral-shear type deformations in 2D. The signals are shown to decorrelate with any of these deformations, with strengths depending on the reorganization and interaction of tissue scatterers with the ultrasonic point spread function following the deformation. Conditions that favour the improvements in motion estimation performance are discussed, and advantages gained by signal companding and pulse compression are illustrated.

The well-documented effectiveness of palpation as a diagnostic technique for detecting cancer and other diseases has provided motivation for developing imaging techniques for non-invasively evaluating the mechanical properties of tissue. A recently described approach for elasticity imaging, using propagating acoustic shear waves and phase-contrast MRI, has been called magnetic resonance elastography (MRE). The purpose of this work was to conduct preliminary studies to define methods for using MRE as a tool for addressing the paucity of quantitative tissue mechanical property data in the literature. Fresh animal liver and kidney tissue specimens were evaluated with MRE at multiple shear wave frequencies. The influence of specimen temperature and orientation on measurements of stiffness was studied in skeletal muscle. The results demonstrated that all of the materials tested (liver, kidney, muscle and tissue-simulating gel) exhibit systematic dependence of shear stiffness on shear rate. These data are consistent with a viscoelastic model of tissue mechanical properties, allowing calculation of two independent tissue properties from multiple-frequency MRE data: shear modulus and shear viscosity. The shear stiffness of tissue can be substantially affected by specimen temperature. The results also demonstrated evidence of shear anisotropy in skeletal muscle but not liver tissue. The measured shear stiffness in skeletal muscle was found to depend on both the direction of propagation and polarization of the shear waves.

A quasistatic magnetic resonance elastography (MRE) method for the evaluation of breast cancer is proposed. Using a phase contrast, stimulated echo MRI approach, strain imaging in phantoms and volunteers is presented. First-order assessment of tissue biomechanical properties based on inverse strain mapping is outlined and demonstrated. The accuracy of inverse strain imaging is studied through simulations in a two-dimensional model and in an anthropomorphic, three-dimensional finite-element model of the breast. To improve the accuracy of modulus assessment by elastography, inverse methods are discussed as an extension to strain imaging, and simulations quantify MRE in terms of displacement signal/noise required for robust inversion. A direct inversion strategy providing information on tissue modulus and pressure distribution is described along with a novel iterative method utilizing a priori knowledge of tissue geometry. It is shown that through the judicious choice of information from previous contrast-enhanced MRI breast images, MRE data acquisition requirements can be significantly reduced while maintaining robust modulus reconstruction in the presence of strain noise. An experimental apparatus for clinical breast MRE and preliminary images of a normal volunteer are presented.

Through recent development of MR techniques, it is now possible to assess regional myocardial wall function in a non-invasive way. Using MR tagging, space is marked with planes which deform with the tissue, providing markers for tracking the local motion of the myocardium. Numerous methods to reconstruct the three-dimensional displacement field have been developed. The aim of this article is to provide a framework to quantitatively compare the performance of four methods the authors have developed. Five sets of experiments are described, and their results are reported. Instructions are also provided to perform similar tests on any method using the same data.

The experiments show that some characteristic properties of the methods, such as sensitivity to noise or spatial resolution, can be quantitatively classified. Cross-comparison of performances show what range values for these properties can be considered acceptable.

This article presents a method for measuring three-dimensional mechanical displacement and strain fields using stimulated echo MRI. Additional gradient pulses encode internal displacements in response to an externally applied deformation. By limiting the mechanical transition to the stimulated echo mixing time, a more accurate static displacement measurement is obtained. A three-dimensional elasticity reconstruction within a region of interest having a uniform shear modulus along its boundary is performed by numerically solving discretized elasticity equilibrium equations. Data acquisition, strain measurements and reconstruction were performed using a silicone gel phantom containing an inclusion of known elastic properties. A comparison between two-dimensional and three-dimensional reconstructions from simulated and experimental displacement data shows higher accuracy from the three-dimensional reconstruction. The long-term objective of this work is to provide a method for remotely palpating and elastically quantitating manually inaccessible tissues.

MR elastography is a novel imaging technique for the visualization of elastic properties of tissue. It is expected that this method will have diagnostic value for the clarification of suspicious breast lesions. Low-frequency mechanical waves are coupled into the tissue and visualized via an MR sequence which is phase-locked to the mechanical excitation. Commonly, elasticity is assumed to be isotropic and reconstruction is performed in only two dimensions. The technique is extended to three dimensions such that the entire symmetric elasticity tensor is assessed. This is achieved by measuring different phases of the mechanical wave during one oscillatory cycle. Thereby it is possible to provide information about the anisotropy of the elasticity tensor. Finite-element simulations as well as phantom experiments are performed to demonstrate the feasibility of the method. Initial clinical results of a breast carcinoma are presented. The analysis of the eigenvalues of the elasticity tensor support the hypothesis that breast carcinoma might exhibit an anisotropic elasticity distribution. The surrounding benign tissue appears isotropic. Thereby new and additional diagnostic information is provided which might help in distinguishing between benign and malignant breast diseases.

Harmonic phase magnetic resonance imaging (HARP) is a new technique for measuring the motion of the left ventricle of the heart. HARP uses magnetic resonance tagging, Fourier filtering and special processing algorithms to calculate key indices of myocardial motion including Eulerian and Lagrangian strain. This paper presents several new methods for visualizing myocardial motion based on HARP. Quantities that are computed and visualized include motion grids, velocity fields, strain rates, pathlines, tracked Eulerian strain, and contraction angle. The computations are fast and fully automated and have the potential for clinical application.

In MRI tagging, magnetic tags - spatially encoded magnetic saturation planes - are created within tissues acting as temporary markers. Their deformation pattern provides useful qualitative and quantitative information about the functional properties of underlying tissue and allows non-invasive analysis of mechanical function. The measured displacement at a given tag point contains only unidirectional information; in order to track the full 3D motion, these data have to be combined with information from other orthogonal tag sets over all time frames. Here, we provide a method to describe the motion of the heart using a four-dimensional tensor product of B-splines. In vivo validation of this tracking algorithm is performed using different tagging sets on the same heart. Using the validation results, the appropriate control point density was determined for normal cardiac motion tracking. Since our motion fields are parametric and based on an image plane based Cartesian coordinate system, trajectories or other derived values (velocity, acceleration, strains...) can be calculated for any desired point within the volume spanned by the control points. This method does not rely on specific chamber geometry, so the motion of any tagged structure can be tracked. Examples of displacement and strain analysis for both ventricles are also presented.

A method for compliance estimation employing magnetic resonance pulse wave velocity measurement is presented. Time-resolved flow waves are recorded at several positions along the vessel using a phase contrast sequence, and pulse wave velocity is calculated from the delay of the wave onsets. Using retrospective cardiac gating in combination with an optically decoupled electrocardiogram acquisition, a high temporal resolution of 3 ms can be achieved. A phantom set-up for the simulation of pulsatile flow in a compliant vessel is described. In the phantom, relative errors of pulse wave velocity estimation were found to be about 15%, whereas in a volunteer, larger errors were found that might be caused by vessel branches. Results of pulse wave velocity estimation agree with direct aortic distension measurements which rely on a peripheral estimate of aortic pressure and are therefore less accurate. Studies in 12 volunteers show values of pulse wave velocity consistent with the literature; in particular the well-known increase in pulse wave velocity with age was observed. Preliminary results show that the method can be applied to aortic aneurysms.