Flouri, D, Lesnic, D orcid.org/0000-0003-3025-2770, Chrysochou, C et al. (6 more authors) (2021) Motion correction of free-breathing magnetic resonance renography using model-driven registration. Magnetic Resonance Materials in Physics, Biology and Medicine, 34 (6). pp. 805-822. ISSN 0968-5243
Abstract
Introduction
Model-driven registration (MDR) is a general approach to remove patient motion in quantitative imaging. In this study, we investigate whether MDR can effectively correct the motion in free-breathing MR renography (MRR).
Materials and methods
MDR was generalised to linear tracer-kinetic models and implemented using 2D or 3D free-form deformations (FFD) with multi-resolution and gradient descent optimization. MDR was evaluated using a kidney-mimicking digital reference object (DRO) and free-breathing patient data acquired at high temporal resolution in multi-slice 2D (5 patients) and 3D acquisitions (8 patients). Registration accuracy was assessed using comparison to ground truth DRO, calculating the Hausdorff distance (HD) between ground truth masks with segmentations and visual evaluation of dynamic images, signal-time courses and parametric maps (all data).
Results
DRO data showed that the bias and precision of parameter maps after MDR are indistinguishable from motion-free data. MDR led to reduction in HD (HDunregistered = 9.98 ± 9.76, HDregistered = 1.63 ± 0.49). Visual inspection showed that MDR effectively removed motion effects in the dynamic data, leading to a clear improvement in anatomical delineation on parametric maps and a reduction in motion-induced oscillations on signal-time courses.
Discussion
MDR provides effective motion correction of MRR in synthetic and patient data. Future work is needed to compare the performance against other more established methods.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Crown 2021. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | Model-driven registration; Motion correction; Image registration; Free-form deformation; Quantitative imaging; Magnetic resonance renography; Dynamic contrast-enhanced MRI |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Applied Mathematics (Leeds) 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 Kidney Research UK Account Ref: UNI008 RP55/2012 |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Jun 2021 11:20 |
Last Modified: | 05 Mar 2023 22:37 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/s10334-021-00936-x |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:175045 |