Mechanically anisotropic phantoms for magnetic resonance elastography

Motivation: Imaging phantoms with known anisotropic mechanical properties are needed to evaluate magnetic resonance elastography (MRE) methods to estimate anisotropic parameters. Goal(s): Fabricate mechanically anisotropic phantoms, characterize their mechanical behavior by direct testing, then assess the accuracy of MRE estimates of anisotropic properties. Approach: Directionally scaled and unscaled lattices were designed to exhibit anisotropic or isotropic mechanical properties when embedded in a gelatin phantom. From MRE data, a transversely isotropic nonlinear inversion (TI-NLI) algorithm estimated maps of stiffness and mechanical anisotropy. Results: MRE of scaled lattice-composites revealed elliptical wavefields; TI-NLI analysis estimated anisotropic properties that agreed with benchtop testing results. Impact: The accurate detection of mechanical anisotropy within our phantom builds the credibility of anisotropic MRE techniques, which could have future clinical use to detect pathological changes to fibrous tissues like brain white matter.

Authors

Publication Details

Journal
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Published
2025-09-16
DOI
https://doi.org/10.58530/2025/0796
Primary Topic
Elasticity and Material Modeling
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mechanically anisotropic phantoms for magnetic resonance elastography

Ruth J. Okamoto, Margrethe Ruding, Ramin Balouchzadeh, Philip V. Bayly et al.
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Elasticity and Material Modeling
article

Mechanically anisotropic phantoms for magnetic resonance elastography

Ruth J. Okamoto, Margrethe Ruding, Ramin Balouchzadeh, Philip V. Bayly, Curtis L. Johnson, Matthew McGarry, Kevin N. Eckstein, Daniel Yoon, Aaliyah Thompson‐Mazzeo
article en

Abstract

Motivation: Imaging phantoms with known anisotropic mechanical properties are needed to evaluate magnetic resonance elastography (MRE) methods to estimate anisotropic parameters. Goal(s): Fabricate mechanically anisotropic phantoms, characterize their mechanical behavior by direct testing, then assess the accuracy of MRE estimates of anisotropic properties. Approach: Directionally scaled and unscaled lattices were designed to exhibit anisotropic or isotropic mechanical properties when embedded in a gelatin phantom. From MRE data, a transversely isotropic nonlinear inversion (TI-NLI) algorithm estimated maps of stiffness and mechanical anisotropy. Results: MRE of scaled lattice-composites revealed elliptical wavefields; TI-NLI analysis estimated anisotropic properties that agreed with benchtop testing results. Impact: The accurate detection of mechanical anisotropy within our phantom builds the credibility of anisotropic MRE techniques, which could have future clinical use to detect pathological changes to fibrous tissues like brain white matter.

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
Openalex Percentile: Top 76%
Elasticity and Material Modeling
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.