Purpose:To prospectively compare an investigational version of a complex-based chemical shift-based fat fraction magnetic resonance (MR) imaging method with MR spectroscopy for the quantifi cation of hepatic steatosis. Materials and Methods:This study was approved by the institutional review board and was HIPAA compliant. Written informed consent was obtained before all studies. Fifty-fi ve patients (31 women, 24 men; age range, 24-71 years) were prospectively imaged at 1.5 T with quantitative MR imaging and single-voxel MR spectroscopy, each within a single breath hold. The effects of T2* correction, spectral modeling of fat, and magnitude fi tting for eddy current correction on fat quantifi cation with MR imaging were investigated by reconstructing fat fraction images from the same source data with different combinations of error correction. Single-voxel T2-corrected MR spectroscopy was used to measure fat fraction and served as the reference standard. All MR spectroscopy data were postprocessed at a separate institution by an MR physicist who was blinded to MR imaging results. Fat fractions measured with MR imaging and MR spectroscopy were compared statistically to determine the correlation ( r 2 ), and the slope and intercept as measures of agreement between MR imaging and MR spectroscopy fat fraction measurements, to determine whether MR imaging can help quantify fat, and examine the importance of T2* correction, spectral modeling of fat, and eddy current correction. Two-sided t tests (signifi cance level, P = .05) were used to determine whether estimated slopes and intercepts were signifi cantly different from 1.0 and 0.0 , respectively. Sensitivity and specifi city for the classifi cation of clinically signifi cant steatosis were evaluated. Results:Overall, there was excellent correlation between MR imaging and MR spectroscopy for all reconstruction combinations. However, agreement was only achieved when T2* correction, spectral modeling of fat, and magnitude fi tting for eddy current correction were used ( r 2 = 0.99; slope 6 standard deviation = 1.00 6 0.01, P = .77; intercept 6 standard deviation = 0.2% 6 0.1, P = .19 ). Conclusion:T1-independent chemical shift-based water-fat separation MR imaging methods can accurately quantify fat over the entire liver, by using MR spectroscopy as the reference standard, when T2* correction, spectral modeling of fat, and eddy current correction methods are used.q RSNA, 2011

Purpose To determine the precision and accuracy of hepatic fat-fraction measured with a chemical shift-based MRI fat-water separation method, using single-voxel MR spectroscopy (MRS) as a reference standard. Materials and Methods In 42 patients, two repeated measurements were made using a T1-independent, T2∗-corrected chemical shift-based fat-water separation method with multi-peak spectral modeling of fat, and T2-corrected single voxel MR spectroscopy. Precision was assessed through calculation of Bland-Altman plots and concordance correlation intervals. Accuracy was assessed through linear regression between MRI and MRS. Sensitivity and specificity of MRI fat-fractions for diagnosis of steatosis using MRS as a reference standard were also calculated. Results Statistical analysis demonstrated excellent precision of MRI and MRS fat-fractions, indicated by 95% confidence intervals (units of absolute percent) of [−2.66%,2.64%] for single MRI ROI measurements, [−0.81%,0.80%] for averaged MRI ROI, and [−2.70%,2.87%] for single-voxel MRS. Linear regression between MRI and MRS indicated that the MRI method is highly accurate. Sensitivity and specificity for detection of steatosis using averaged MRI ROI were 100% and 94%, respectively. The relationship between hepatic fat-fraction and body mass index was examined. Conclusion Fat-fraction measured with T1-independent T2∗-corrected MRI and multi-peak spectral modeling of fat is a highly precise and accurate method of quantifying hepatic steatosis.

Purpose: To develop a chemical-shift-based imaging method for fat quantification that accounts for the complex spectrum of fat, and to compare this method with MR spectroscopy (MRS). Quantitative noninvasive biomarkers of hepatic steatosis are urgently needed for the diagnosis and management of nonalcoholic fatty liver disease (NAFLD). Materials and Methods:Hepatic steatosis was measured with "fat-fraction" images in 31 patients using a multiecho chemical-shift-based water-fat separation method at 1.5T. Fat-fraction images were reconstructed using a conventional signal model that considers fat as a single peak at -210 Hz relative to water ("single peak" reconstruction). Fat-fraction images were also reconstructed from the same source images using two methods that account for the complex spectrum of fat; precalibrated and self-calibrated "multipeak" reconstruction. Single-voxel MRS that was coregistered with imaging was performed for comparison.Results: Imaging and MRS demonstrated excellent correlation with single peak reconstruction (r 2 ϭ 0.91), precalibrated multipeak reconstruction (r 2 ϭ 0.94), and self-calibrated multipeak reconstruction (r 2 ϭ 0.91). However, precalibrated multipeak reconstruction demonstrated the best agreement with MRS, with a slope statistically equivalent to 1 (0.96 Ϯ 0.04; P ϭ 0.4), compared to self-calibrated multipeak reconstruction (0.83 Ϯ 0.05, P ϭ 0.001) and single-peak reconstruction (0.67 Ϯ 0.04, P Ͻ 0.001). Conclusion:Accurate spectral modeling is necessary for accurate quantification of hepatic steatosis with MRI.

Multipoint water–fat separation techniques rely on different water–fat phase shifts generated at multiple echo times to decompose water and fat. Therefore, these methods require complex source images and allow unambiguous separation of water and fat signals. However, complex-based water–fat separation methods are sensitive to phase errors in the source images, which may lead to clinically important errors. An alternative approach to quantify fat is through “magnitude-based” methods that acquire multiecho magnitude images. Magnitude-based methods are insensitive to phase errors, but cannot estimate fat-fraction greater than 50%. In this work, we introduce a water–fat separation approach that combines the strengths of both complex and magnitude reconstruction algorithms. A magnitude-based reconstruction is applied after complex-based water–fat separation to removes the effect of phase errors. The results from the two reconstructions are then combined. We demonstrate that using this hybrid method, 0–100% fat-fraction can be estimated with improved accuracy at low fat-fractions.

Purpose To validate a T1-independent, T2*-corrected fat quantification technique that uses accurate spectral modeling of fat using a homogeneous fat-water-SPIO phantom over physiologically expected ranges of fat percentage and T2* decay in the presence of iron overload. Materials and Methods A homogeneous gel phantom consisting of vials with known fat-fractions and iron concentrations is described. Fat-fraction imaging was performed using a multi-echo chemical shift-based fat-water separation method (IDEAL), and various reconstructions were performed to determine the impact of T2* correction and accurate spectral modeling. Conventional two-point Dixon (in-phase/out-of-phase) imaging and MR spectroscopy were performed for comparison with known fat-fractions. Results The best agreement with known fat-fractions over the full range of iron concentrations was found when T2* correction and accurate spectral modeling were used. Conventional two-point Dixon imaging grossly underestimated fat-fraction for all T2* values, but particularly at higher iron concentrations. Conclusion This work demonstrates the necessity of T2* correction and accurate spectral modeling of fat in order to accurately quantify fat using MRI.