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Updated: Jun 5, 2025

Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography
Published on: May 10, 2022
Mechanically anisotropic phantoms for magnetic resonance elastography
Kevin N Eckstein1, Daniel Yoon1, Margrethe Ruding1
1Mechanical Engineering and Materials Science, Washington University, St. Louis, Missouri, USA.
Purpose:
Imaging phantoms with known anisotropic mechanical properties are needed to evaluate magnetic resonance elastography (MRE) methods to estimate anisotropic parameters. The aims of this study were to fabricate mechanically anisotropic MRE phantoms, characterize their mechanical behavior by direct testing, then assess the accuracy of MRE estimates of anisotropic properties using a transversely isotropic nonlinear inversion (TI-NLI) algorithm.
Methods:
Directionally scaled and unscaled lattices were designed to exhibit anisotropic or isotropic mechanical properties. Lattices were three-dimensionally printed in poly(ethelyne glycol) diacrylate using a commercial digital light processing printer, then infilled with gelatin to form a composite material. Benchtop testing determined two shear stiffnesses, and , governing loading parallel and perpendicular to the symmetry axis, and two analogous Young's moduli and . From these measures, shear anisotropy = and tensile anisotropy = were calculated. Three phantoms were driven by a central actuator and imaged with MRE at frequencies from 300 to 500 Hz. From MRE data, the TI-NLI algorithm estimated maps of , , and .
Results:
In benchtop tests, geometrically scaled lattice composites exhibited the following anisotropic properties: = 6.1 ± 0.7 kPa, = 0.83 ± 0.13, = 0.78 ± 0.09} (mean ± standard deviation). MRE of scaled lattice composites revealed elliptical wavefields; TI-NLI analysis identified the following median property ranges: = 11-19 kPa, = 0.6-1.0, = 0.8-1.6}.
Conclusion:
Anisotropic MRE phantoms are created by embedding anisotropic three-dimensionally printed lattices into a softer matrix. The TI-NLI algorithm accurately estimates spatial contrast in anisotropic properties.

