OSCILLATE: A low-rank approach for accelerated magnetic resonance elastography
Grace McIlvain
Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
Search for more papers by this authorAlexander M. Cerjanic
Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
University of Illinois College of Medicine, Urbana, Illinois, USA
Search for more papers by this authorAnthony G. Christodoulou
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
Search for more papers by this authorMatthew D. J. McGarry
Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
Search for more papers by this authorCorresponding Author
Curtis L. Johnson
Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
Correspondence
Curtis L. Johnson, PhD, Department of Biomedical Engineering, University of Delaware, 150 Academy St, Newark, DE 19716, USA.
Email: [email protected]
Search for more papers by this authorGrace McIlvain
Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
Search for more papers by this authorAlexander M. Cerjanic
Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
University of Illinois College of Medicine, Urbana, Illinois, USA
Search for more papers by this authorAnthony G. Christodoulou
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
Search for more papers by this authorMatthew D. J. McGarry
Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA
Search for more papers by this authorCorresponding Author
Curtis L. Johnson
Department of Biomedical Engineering, University of Delaware, Newark, Delaware, USA
Correspondence
Curtis L. Johnson, PhD, Department of Biomedical Engineering, University of Delaware, 150 Academy St, Newark, DE 19716, USA.
Email: [email protected]
Search for more papers by this authorFunding information: Delaware INBRE, Grant/Award Number: P20-GM103446; University of Delaware Research Foundation, National Institutes of Health, Grant/Award Numbers: F31-HD103361; R01-AG058853; R01-EB027577; U01-NS112120
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Abstract
Purpose
MR elastography (MRE) is a technique to characterize brain mechanical properties in vivo. Due to the need to capture tissue deformation in multiple directions over time, MRE is an inherently long acquisition, which limits achievable resolution and use in challenging populations. The purpose of this work is to develop a method for accelerating MRE acquisition by using low-rank image reconstruction to exploit inherent spatiotemporal correlations in MRE data.
Theory and Methods
The proposed MRE sampling and reconstruction method, OSCILLATE (Observing Spatiotemporal Correlations for Imaging with Low-rank Leveraged Acceleration in Turbo Elastography), involves alternating which k-space points are sampled between each repetition by a reduction factor, ROSC. Using a predetermined temporal basis from a low-resolution navigator in a joint low-rank image reconstruction, all images can be accurately reconstructed from a reduced amount of k-space data.
Results
Decomposition of MRE displacement data demonstrated that, on average, 96.1% of all energy from an MRE dataset is captured at rank L = 12 (reduced from a full rank of 24). Retrospectively undersampling data with ROSC = 2 and reconstructing at low-rank (L = 12) yields highly accurate stiffness maps with voxel-wise error of 5.8% ± 0.7%. Prospectively undersampled data at ROSC = 2 were successfully reconstructed without loss of material property map fidelity, with average global stiffness error of 1.0% ± 0.7% compared to fully sampled data.
Conclusions
OSCILLATE produces whole-brain MRE data at 2 mm isotropic resolution in 1 min 48 s.
Supporting Information
| Filename | Description |
|---|---|
| mrm29308-sup-0001-Supinfo.pdfPDF document, 1 MB | Figure S1. Magnitude and phase components of each of the 24 bases in a single slice of a representative subject Figure S2. Retrospective OSCILLATE reconstruction of fully-sampled (ROSC = 1) k-space data at (A) full rank (L = 24) and reduced rank (L = 12) with temporal basis determined from (B) the reference image series, image, and (C) the navigator images. navigator. NRMSE below each image are in reference to the baseline reference image. NRMSEs between brain images represent the error between respective stiffness maps and are calculated across all 5 subjects. NRMSE between images reconstructed with the two different temporal bases is small at 3.5% |
Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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