Journal of Magnetic Resonance Imaging · 2016 · 56 citations · 41 references
MedicineRadiologyBiomedical ImagingDiagnostic ImagingDiagnostic RadiologyHepatobiliary ImagingIron MetabolismLiver ImagingMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMetabolic Liver DiseaseChemical Shift ImagingFat Quantification ImagingHepatic Iron AccumulationHepatic Iron Overload AssessmentIron Overload SyndromesMagnetic Resonance Imaging Iron QuantificationMagnetic Resonance Spectroscopic ImagingSteatosis Quantification
PURPOSE: * = 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: resulted in slope = 0.95 [0.79-1.12] (95% limits of agreement) at 1.5T and slope = 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. LEVEL OF EVIDENCE: 1 J. Magn. Reson. Imaging 2017;45:428-439.
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Lidia S. Szczepaniak, Pamela Nurenberg, David Léonard et al. · American Journal of Physiology-Endocrinology and Metabolism · 2004 · 1.6K citations