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Estimation of Field Inhomogeneity Map Following Magnitude-Based Ambiguity-Resolved Water-Fat Separation

2022-06-17 · Alexandre Triay Bagur, Darryl McClymont, Chloe Hutton, Andrea Borghetto, Michael L Gyngell, Paul Aljabar, Matthew D Robson, Michael Brady, Daniel P Bulte

PURPOSE: To extend magnitude-based PDFF (Proton Density Fat Fraction) and $R_2^*$ mapping with resolved water-fat ambiguity to calculate field inhomogeneity (field map) using the phase images. THEORY: The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and $R_2^*$ from magnitude fitting may be updated using the estimated field maps. METHODS: 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. RESULTS: 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 Biobank (PDFF bias = -0.03 %, LoA (limits of agreement) [-0.1,0.1] %; Field map bias = 0.06 Hz, LoA = [-0.2,0.3] Hz). Robust field mapping was observed at 3 T, for inhomogeneities over 300 Hz including rapid variation across edges. CONCLUSION: Field mapping following magnitude-based water-fat separation with resolved water-fat ambiguity was demonstrated in-vivo and showed potential at high field.

📄 PDF Abstract BibTeX arXiv:2206.08796

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