| Title: | Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation |
| Journal: | Magnetic Resonance Imaging |
| Published: | 9 Jan 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/36632946/ |
| DOI: | https://doi.org/10.1016/j.mri.2023.01.002 |
Publication 10944
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Abstract
Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.</p>
9 Authors
- Alexandre Triay Bagur
- Darryl McClymont
- Chloe Hutton
- Andrea Borghetto
- Michael L Gyngell
- Paul Aljabar
- Matthew D Robson
- Michael Brady
- Daniel P Bulte
1 Application
| Application ID | Title |
|---|---|
| 9914 | Determining the Outcomes of People with Liver Disease |
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