Bogusz, F, Pieciak, T, Afzali, M et al. (1 more author) (2022) Diffusion-relaxation scattered MR signal representation in a multi-parametric sequence. Magnetic Resonance Imaging, 91. pp. 52-61. ISSN 0730-725X
Abstract
This work focuses on obtaining a magnetic resonance imaging (MRI) signal representation that accounts for a longitudinal T1 and transverse T2⋆ relaxations while at the same time integrating directional diffusion in the context of scattered multi-parametric acquisitions, where only a few diffusion gradient directions and b-values are available for each pair of echo and inversion times. The method is based on the three-dimensional simple harmonic oscillator-based reconstruction and estimation (SHORE) representation of the diffusion signal, which enables the estimation of the orientation distribution function and the retrieval of various quantitative indices such as the generalized fractional anisotropy or the return-to-the-origin probability while simultaneously resolving for T1 and T2⋆ relaxation times. Our technique, the Relax-SHORE, has been tested on both in silico and in vivo diffusion-relaxation scattered MR data. The results show that Relax-SHORE is accurate in the context of scattered acquisitions while guaranteeing flexibility in the diffusion signal representation from multi-parametric sequences.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 Elsevier Inc. All rights reserved. This is an author produced version of an article, published in Magnetic Resonance Imaging. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Diffusion MRI; Diffusion-relaxation; Multi-parametric sequence; Brain; Microstructure |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Cardiovascular and Metabolic Medicine (LICAMM) > Biomedical Imaging Science Dept (Leeds) |
Funding Information: | Funder Grant number Wellcome Trust 219536/Z/19/Z |
Depositing User: | Symplectic Publications |
Date Deposited: | 06 Jun 2022 13:02 |
Last Modified: | 11 May 2023 00:13 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.mri.2022.05.007 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:187629 |
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