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Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography
Published on: May 10, 2022
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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.
Magnetic Resonance in Medicine
|December 4, 2024
Summary
Researchers developed anisotropic magnetic resonance elastography (MRE) phantoms using 3D-printed lattices. The transversely isotropic nonlinear inversion (TI-NLI) algorithm accurately estimated anisotropic mechanical properties within these novel MRE phantoms.
Area of Science:
- Biomedical Engineering
- Medical Imaging
- Materials Science
Background:
- Magnetic Resonance Elastography (MRE) requires phantoms with known anisotropic mechanical properties for accurate parameter estimation.
- Developing such phantoms is crucial for validating and improving MRE techniques for anisotropic tissues.
Purpose of the Study:
- To fabricate mechanically anisotropic MRE phantoms.
- To characterize their mechanical behavior through direct testing.
- To assess the accuracy of MRE estimates of anisotropic properties using a transversely isotropic nonlinear inversion (TI-NLI) algorithm.
Main Methods:
- Anisotropic and isotropic lattices were 3D-printed and infilled with gelatin to create composite MRE phantoms.
- Benchtop testing determined shear stiffnesses and Young's moduli to calculate anisotropy ratios.
- MRE imaging was performed on scaled lattice composites, and TI-NLI algorithm estimated anisotropic property maps.
Main Results:
- Benchtop tests confirmed anisotropic properties in scaled lattice composites ( = 6.1 ± 0.7 kPa, = 0.83 ± 0.13, = 0.78 ± 0.09).
- MRE imaging revealed elliptical wavefields, and TI-NLI analysis provided median property ranges ( = 11-19 kPa, = 0.6-1.0, = 0.8-1.6).
Conclusions:
- Mechanically anisotropic MRE phantoms were successfully created by embedding 3D-printed anisotropic lattices within a soft matrix.
- The TI-NLI algorithm demonstrated accuracy in estimating spatial contrast of anisotropic mechanical properties.

