Magnetic resonance elastography

Magnetic resonance elastography (MRE) is a non-invasive medical imaging technique that measures the stiffness of soft tissues by generating shear waves in tissue, imaging their propagation using MRI, and processing the images to generate a stiffness map (elastogram).[1] It is one of the most commonly used elastography techniques.[2]

Magnetic resonance elastography
Magnetic resonance elastography of the brain. A T1 weighted anatomical image is shown in the top-left, and the corresponding T2 weighted image from the MRE data is shown in the bottom-left. The wave image used to make the elastogram is shown in the top-right, and the resulting elastogram is in the bottom-right.
Purposemeasures the mechanical properties of soft tissues

MRE was first described by Muthupillai et al. in 1995.[3] Because diseased tissues are often stiffer than the surrounding normal tissue, MRE has been applied to visualize a variety of disease processes which affect tissue stiffness in the liver, breast, brain, heart, and skeletal muscle.[1][4] For example, breast tumors are much harder than healthy fibroglandular tissue.[5] MRE is similar to palpation; however, whereas palpation is a qualitative technique performed by physicians, MRE is a quantitative technique performed with a radiologist.[1]

Mechanics of Soft Tissue

MRE quantitatively determines the stiffness of biological tissues by measuring its mechanical response to an external stress.[4] Specifically, MRE calculates the shear modulus of a tissue from its shear-wave displacement measurements.[3] The elastic modulus quantifies the stiffness of a material, or how well it resists elastic deformation as a force is applied. For elastic materials, strain is directly proportional to stress within an elastic region. The elastic modulus is seen as the proportionality constant between stress and strain within this region. Unlike purely elastic materials, biological tissues are viscoelastic, meaning that it has characteristics of both elastic solids and viscous liquids. Their mechanical responses depend on the magnitude of the applied stress as well as the strain rate. The stress-strain curve for a viscoelastic material exhibits hysteresis. The area of the hysteresis loop represents the amount of energy lost as heat when a viscoelastic material undergoes an applied stress and is distorted. For these materials, the elastic modulus is complex and can be separated into two components: a storage modulus and a loss modulus. The storage modulus expresses the contribution from elastic solid behavior while the loss modulus expresses the contribution from viscous liquid behavior. Conversely, elastic materials exhibit a pure solid response. When a force is applied, these materials elastically store and release energy, which does not result in energy loss in the form of heat.[6]

Yet, MRE and other elastography imaging techniques typically utilize a mechanical parameter estimation that assumes biological tissues to be linearly elastic and isotropic for simplicity purposes.[1] The effective shear modulus can be expressed with the following equation:

where is the elastic modulus of the material and is the Poisson’s ratio.

The Poisson’s ratio for soft tissues is approximated to equal 0.5, resulting in the ratio between the elastic modulus and shear modulus to equal 3.[7] This relationship can be used to estimate the stiffness of biological tissues based on the calculated shear modulus from shear-wave propagation measurements. A driver system produces and transmits acoustic waves set at a specific frequency (50–500 Hz) to the tissue sample. At these frequencies, the velocity of shear waves can be about 1–10 m/s.[8][9] The effective shear modulus can be calculated from the shear wave velocity with the following:[10]

where is the tissue density and is the shear wave velocity.

Recent studies have been focused on incorporating mechanical parameter estimations into post-processing inverse algorithms that account for the complex viscoelastic behavior of soft tissues. Creating new parameters could potentially increase the specificity of MRE measurements and diagnostic testing.[11][12]

Applications

Liver

Liver fibrosis is a common result of many chronic liver diseases; progressive fibrosis can lead to cirrhosis. MRE of the liver provides quantitative maps of tissue stiffness over large regions of the liver. This non-invasive technique is able to detect increased stiffness of the liver parenchyma, which is a direct consequence of liver fibrosis. It helps to stage liver fibrosis or diagnose mild fibrosis with reasonable accuracy.[13][14][12][15]

Brain

MRE of the brain was first presented in the early 2000s.[16][17] Elastogram measures have been correlated with memory tasks,[18] fitness measures,[19] and progression of various neurodegenerative conditions. For example, regional and global decreases in brain viscoelasticity have been observed in Alzheimer’s disease[20][21] and multiple sclerosis.[22][23] It has been found that as the brain ages, it loses its viscoelastic integrity due to degeneration of neurons and oligodendrocytes.[24][25] A recent study looked into both the isotropic and anisotropic stiffness in brain and found a correlation between the two and with age, particularly in gray matter.[26]

MRE may also have applications for understanding the adolescent brain. Recently, it was found that adolescents have regional differences in brain viscoelasticity relative to adults.[27][28]

MRE has also been applied to functional neuroimaging. Whereas functional magnetic resonance imaging (fMRI) infers brain activity by detecting relatively slow changes in blood flow, functional MRE is capable of detecting neuromechanical changes in the brain related to neuronal activity occurring on the 100-millisecond scale.[29]

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See also

References
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