Quantification of Liver Fat in the Presence of Iron Overload

Purpose: To evaluate the accuracy of R2* models (1/T-2* = R2*) for chemical shift-encoded magnetic resonance imaging (CSE-MRI)-based proton density fat-fraction (PDFF) quantification in patients with fatty liver and iron overload, using MR spectroscopy (MRS) as the reference standard. Materials and Methods: Two Monte Carlo simulations were implemented to compare the root-mean-squared-error (RMSE) performance of single-R2* and dual-R2* correction in a theoretical liver environment with high iron. Fatty liver was defined as hepatic PDFF >5.6% based on MRS; only subjects with fatty liver were considered for analyses involving fat. From a group of 40 patients with known/suspected iron overload, nine patients were identified at 1.5T, and 13 at 3.0T with fatty liver. MRS linewidth measurements were used to estimate R2* values for water and fat peaks. PDFF was measured from CSE-MRI data using single-R2* and dual-R2* correction with magnitude and complex fitting. Results: Spectroscopy-based R2* analysis demonstrated that the R2* of water and fat remain close in value, both increasing as iron overload increases: linear regression between R2*(W) and R2*(F) resulted in slope 5 0.95 [0.79-1.12] (95% limits of agreement) at 1.5T and slope 5 0.76 [0.49-1.03] at 3.0T. MRI-PDFF using dual-R2* correction had severe artifacts. MRI-PDFF using single-R2* correction had good agreement with MRS-PDFF: Bland-Altman analysis resulted in -0.7% (bias) +/- 2.9% (95% limits of agreement) for magnitude-fit and -1.3% +/- 4.3% for complex-fit at 1.5T, and -1.5% +/- 8.4% for magnitude-fit and -2.2% +/- 9.6% for complex-fit at 3.0T. Conclusion: Single-R2* modeling enables accurate PDFF quantification, even in patients with iron overload.