Suitability of poroelastic and viscoelastic mechanical models for high and low frequency MR elastography

Authors

  • McGarry M. D. J.,

    1. Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755
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  • Johnson C. L.,

    1. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
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  • Sutton B. P.,

    1. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801 and Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
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  • Georgiadis J. G.,

    1. Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801; Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801; and Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801
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  • Van Houten E. E. W.,

    1. Department of Mechanical Engineering, University de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada
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  • Pattison A. J.,

    1. Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755
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  • Weaver J. B.,

    1. Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755 and Department of Radiology, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire 03755
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  • Paulsen K. D.

    1. Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755 and Norris Cotton Cancer Center, Dartmouth-Hitchcock Medical Center, Lebanon, New Hampshire 03755
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Abstract

Purpose:

Descriptions of the structure of brain tissue as a porous cellular matrix support application of a poroelastic (PE) mechanical model which includes both solid and fluid phases. However, the majority of brain magnetic resonance elastography (MRE) studies use a single phase viscoelastic (VE) model to describe brain tissue behavior, in part due to availability of relatively simple direct inversion strategies for mechanical property estimation. A notable exception is low frequency intrinsic actuation MRE, where PE mechanical properties are imaged with a nonlinear inversion algorithm.

Methods:

This paper investigates the effect of model choice at each end of the spectrum of in vivo human brain actuation frequencies. Repeat MRE examinations of the brains of healthy volunteers were used to compare image quality and repeatability for each inversion model for both 50 Hz externally produced motion and ≈1 Hz intrinsic motions. Additionally, realistic simulated MRE data were generated with both VE and PE finite element solvers to investigate the effect of inappropriate model choice for ideal VE and PE materials.

Results:

In vivo, MRE data revealed that VE inversions appear more representative of anatomical structure and quantitatively repeatable for 50 Hz induced motions, whereas PE inversion produces better results at 1 Hz. Reasonable VE approximations of PE materials can be derived by equating the equivalent wave velocities for the two models, provided that the timescale of fluid equilibration is not similar to the period of actuation. An approximation of the equilibration time for human brain reveals that this condition is violated at 1 Hz but not at 50 Hz. Additionally, simulation experiments when using the “wrong” model for the inversion demonstrated reasonable shear modulus reconstructions at 50 Hz, whereas cross-model inversions at 1 Hz were poor quality. Attenuation parameters were sensitive to changes in the forward model at both frequencies, however, no spatial information was recovered because the mechanisms of VE and PE attenuation are different.

Conclusions:

VE inversions are simpler with fewer unknown properties and may be sufficient to capture the mechanical behavior of PE brain tissue at higher actuation frequencies. However, accurate modeling of the fluid phase is required to produce useful mechanical property images at the lower frequencies of intrinsic brain motions.

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