Magnetic resonance elastography: Non-invasive mapping of tissue elasticity

Abstract

Magnetic resonance elastography (MRE) is a phase-contrast-based MRI imaging technique that can directly visualize and quantitatively measure propagating acoustic strain waves in tissue-like materials subjected to harmonic mechanical excitation. The data acquired allows the calculation of local quantitative values of shear modulus and the generation of images that depict tissue elasticity or stiffness. This is significant because palpation, a physical examination that assesses the stiffness of tissue, can be an effective method of detecting tumors, but is restricted to parts of the body that are accessible to the physician’s hand. MRE shows promise as a potential technique for ‘palpation by imaging’, with possible applications in tumor detection (particularly in breast, liver, kidney and prostate), characterization of disease, and assessment of rehabilitation (particularly in muscle). We describe MRE in the context of other recent techniques for imaging elasticity, discuss the processing algorithms for elasticity reconstruction and the issues and assumptions they involve, and present recent ex vivo and in vivo results.

Introduction

There is strong precedent in clinical medicine for the concept that tissue viscoelastic properties, assessed by palpation, are markedly affected by a variety of disease processes. Student physicians learn that the presence of a hard mass in the thyroid, breast or prostate is suspicious for malignancy. Indeed, many tumors of these structures are still first detected by touch. It is not uncommon for surgeons at the time of laparotomy to palpate tumors that were undetected in preoperative imaging by CT, MRI or ultrasound. None of these modalities provide the information about the elastic properties of tissue elicited by palpation. The elastic moduli of various human soft tissues are known to vary over a wide range (more than four orders of magnitude). In contrast, most of the physical properties depicted by conventional medical imaging modalities are distributed over a much smaller numerical range.

Over the last decade, the recognition of the potential diagnostic value of characterizing mechanical properties has led a number of investigators to seek methods for imaging tissue elasticity. In materials science, the classic approach for measuring the elastic modulus of a sample is to apply a known stress and to measure the resulting strain. Refinements of this method involve the use of multiple measurements with varying stress, and/or the application of dynamic rather than static stress. Most of the proposed methods for elasticity imaging follow a similar approach. A stress is applied to tissue and the resulting strain distribution is observed or measured using a conventional imaging technique such as ultrasonography. The mode of stress application can be static, quasi-static, or dynamic. A recent review of such work is given by Gao et al. (1996).

Magnetic resonance elastography (MRE) is a recently developed technique that can directly visualize and quantitatively measure propagating acoustic strain waves in tissue-like materials subjected to harmonic mechanical excitation (Muthupillai et al., 1995, Muthupillai et al., 1996a). Shear waves at frequencies in the 10–1000 Hz range are used as a probe because they are much less attenuated than at higher frequencies, their wavelength in tissue-like materials is in the useful range of millimeters to tens of millimeters, and because shear modulus varies widely in bodily tissues. A phase-contrast MRI technique is used to spatially map and measure the shear wave displacement patterns. From this data, local quantitative values of shear modulus can be calculated and images (elastograms) that depict tissue elasticity or stiffness can be generated. In this paper we briefly summarize other techniques for imaging elasticity and describe the principles of MRE. We then consider the equations of harmonic motion in soft tissue and describe various approaches for reconstructing elastograms from MRE data and the assumptions inherent in each. These algorithms are then tested on synthetic and physical phantom data sets of known stiffness and issues such as noise sensitivity and resolution are discussed. Finally, a summary of recent ex vivo and in vivo results is presented.