Catherine D. G. Hines

Quantification of Hepatic Steatosis with T1-independent, T2*-corrected MR Imaging with Spectral Modeling of Fat: Blinded Comparison with MR Spectroscopy

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 quantification 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-five 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 fitting for eddy current correction on fat quantification 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 (significance level, P = .05) were used to determine whether estimated slopes and intercepts were significantly different from 1.0 and 0.0, respectively. Sensitivity and specificity for the classification of clinically significant 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 fitting for eddy current correction were used (r(2) = 0.99; slope ± standard deviation = 1.00 ± 0.01, P = .77; intercept ± standard deviation = 0.2% ± 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.

Quantification of hepatic steatosis with MRI: the effects of accurate fat spectral modeling.

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).

T1 independent, T2* corrected chemical shift based fat–water separation with multi‐peak fat spectral modeling is an accurate and precise measure of hepatic steatosis

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.

T1 independent, T2* corrected MRI with accurate spectral modeling for quantification of fat: Validation in a fat‐water‐SPIO phantom

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.

Combination of complex-based and magnitude-based multiecho water-fat separation for accurate quantification of fat-fraction

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. Magn Reson Med, 2011.

Repeatability of magnetic resonance elastography for quantification of hepatic stiffness.

To determine the sources of variability of MRE hepatic stiffness measurements using healthy volunteers and patients and to calculate the minimum change required for statistical significance. Hepatic stiffness measured with magnetic resonance elastography (MRE) has demonstrated tremendous potential as a noninvasive surrogate of hepatic fibrosis, although the underlying repeatability of MRE for longitudinal tracking of liver disease has not been documented.

Addressing Phase Errors in Fat-Water Imaging Using a Mixed Magnitude/Complex Fitting Method

Accurate, noninvasive measurements of liver fat content are needed for the early diagnosis and quantitative staging of nonalcoholic fatty liver disease. Chemical shift‐based fat quantification methods acquire images at multiple echo times using a multiecho spoiled gradient echo sequence, and provide fat fraction measurements through postprocessing. However, phase errors, such as those caused by eddy currents, can adversely affect fat quantification. These phase errors are typically most significant at the first echo of the echo train, and introduce bias in complex‐based fat quantification techniques. These errors can be overcome using a magnitude‐based technique (where the phase of all echoes is discarded), but at the cost of significantly degraded signal‐to‐noise ratio, particularly for certain choices of echo time combinations. In this work, we develop a reconstruction method that overcomes these phase errors without the signal‐to‐noise ratio penalty incurred by magnitude fitting. This method discards the phase of the first echo (which is often corrupted) while maintaining the phase of the remaining echoes (where phase is unaltered). We test the proposed method on 104 patient liver datasets (from 52 patients, each scanned twice), where the fat fraction measurements are compared to coregistered spectroscopy measurements. We demonstrate that mixed fitting is able to provide accurate fat fraction measurements with high signal‐to‐noise ratio and low bias over a wide choice of echo combinations. Magn Reson Med, 2012.

Independent estimation of T*2 for water and fat for improved accuracy of fat quantification

Noninvasive biomarkers of intracellular accumulation of fat within the liver (hepatic steatosis) are urgently needed for detection and quantitative grading of nonalcoholic fatty liver disease, the most common cause of chronic liver disease in the United States. Accurate quantification of fat with MRI is challenging due the presence of several confounding factors, including T*2 decay. The specific purpose of this work is to quantify the impact of T*2 decay and develop a multiexponential T*2 correction method for improved accuracy of fat quantification, relaxing assumptions made by previous T*2 correction methods. A modified Gauss‐Newton algorithm is used to estimate the T*2 for water and fat independently. Improved quantification of fat is demonstrated, with independent estimation of T*2 for water and fat using phantom experiments. The tradeoffs in algorithm stability and accuracy between multiexponential and single exponential techniques are discussed. Magn Reson Med 63:849–857, 2010.

Quantification of hepatic steatosis with 3-T MR imaging: validation in ob/ob mice.

PURPOSE To validate quantitative imaging techniques used to detect and measure steatosis with magnetic resonance (MR) imaging in an ob/ob mouse model of hepatic steatosis. MATERIALS AND METHODS The internal research animal and resource center approved this study. Twenty-eight male ob/ob mice in progressively increasing age groups underwent imaging and were subsequently sacrificed. Six ob/+ mice served as control animals. Fat fraction imaging was performed with a chemical shift-based water-fat separation method. The following three methods of conventional fat quantification were compared with imaging: lipid extraction and qualitative and quantitative histologic analysis. Fat fraction images were reconstructed with single- and multiple-peak spectral models of fat and with and without correction for T2* effects. Fat fraction measurements obtained with the different reconstruction methods were compared with the three methods of fat quantification, and linear regression analysis and two-sided and two-sample t tests were performed. RESULTS Lipid extraction and qualitative and quantitative histologic analysis were highly correlated with the results of fat fraction imaging (r(2) = 0.92, 0.87, 0.82, respectively). No significant differences were found between imaging measurements and lipid extraction (P = .06) or quantitative histologic (P = .07) measurements when multiple peaks of fat and T2* correction were included in image reconstruction. Reconstructions in which T2* correction, accurate spectral modeling, or both were excluded yielded lower agreement when compared with the results yielded by other techniques. Imaging measurements correlated particularly well with histologic grades in mice with low fat fractions (intercept, -1.0% +/-1.2 [standard deviation]). CONCLUSION MR imaging can be used to accurately quantify fat in vivo in an animal model of hepatic steatosis and may serve as a quantitative biomarker of hepatic steatosis.

Comparison of R2* correction methods for accurate fat quantification in fatty liver

To compare the performance of fat fraction quantification using single‐R2* and dual‐R2* correction methods in patients with fatty liver, using MR spectroscopy (MRS) as the reference standard.