Investigating the accuracy of FatNav-derived estimates of temporal B0 changes and their application to retrospective correction of high-resolution 3D GRE of the human brain at 7T

Gretsch, Frédéric, Marques, José P. and Gallichan, Daniel ORCID: https://orcid.org/0000-0002-0143-2855 2018. Investigating the accuracy of FatNav-derived estimates of temporal B0 changes and their application to retrospective correction of high-resolution 3D GRE of the human brain at 7T. Magnetic Resonance in Medicine 80 (2) , pp. 585-597. 10.1002/mrm.27063

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Abstract

Purpose: To investigate the precision of estimates of temporal variations of magnetic field achievable by doubleecho fat image navigators (FatNavs), and their potential application to retrospective correction of 3D GRE-based sequences. Methods: Both head motion and temporal changes of B0 were tracked using double-echo highly-accelerated 3D FatNavs as navigators – allowing estimation of the temporal changes in low spatial order field coefficients. The accuracy of the method was determined by direct comparison to controlled offsets in the linear imaging gradients. Double-echo FatNavs were also incorporated into a high-resolution 3D GRE sequence to retrospectively correct for both motion and temporal changes in B0 during natural and deep breathing. The additional scan time was 5 minutes (a 40% increase). Correction was also investigated using only the first echo of the FatNav to explore the trade-off in accuracy vs scan-time. Results: Excellent accuracy (0.27 Hz, 1.57-2.75 Hz/m) was achieved for tracking field changes and no significant bias could be observed. Artefacts in the 3D GRE images induced by temporal field changes, if present, were effectively reduced using either the field estimates from the double-echo or the first-echo-only from the FatNavs. Conclusion: FatNavs were shown to be an excellent candidate for accurate, fast and precise estimation of global field variations for the tested patterns of respiration. Future work will investigate ways to increase the temporal sampling to increase robustness to variations in breathing patterns.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Engineering Cardiff University Brain Research Imaging Centre (CUBRIC)
Publisher:	Wiley
ISSN:	0740-3194
Date of First Compliant Deposit:	24 January 2018
Date of Acceptance:	6 December 2017
Last Modified:	01 Dec 2024 08:15
URI:	https://orca.cardiff.ac.uk/id/eprint/108428

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