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

Nonalcoholic Fatty Liver disease (NAFLD) is the most common cause of chronic liver disease in Western societies with an increasing prevalence that parallels current epidemics of obesity and diabetes (1,2). NAFLD is considered by many to be the hepatic manifestation of the metabolic syndrome, a constellation of diseases including adult-onset diabetes (type II), hyperlipidemia, and obesity (3,4). Individuals with NAFLD can progress to a more aggressive form of NAFLD known as nonalcoholic steatohepatitis (NASH), which is characterized by inflammation, ballooning degeneration and fibrosis, in addition to steatosis (5,6). Many patients with steatohepatitis progress to end-stage fibrosis (cirrhosis), which predisposes patients to hepatocellular carcinoma (HCC) and liver failure (7,8). Intracellular accumulation of triglycerides and fatty acids (steatosis) is the earliest and hallmark histological feature of NAFLD. Definitive diagnosis of NAFLD and grading of steatosis requires biopsy, which is regarded as the clinical gold standard test and is the current standard of care. Biopsy, however, is limited by cost, high sampling variability (9), and other significant risks that limit its utility for repeated evaluation of liver disease. For these reasons, a noninvasive, cost-effective, and quantitative alternative to biopsy is needed for accurate quantification of hepatic steatosis. MRI is highly sensitive to the presence of fat due to differences in chemical shift between water and fat. MR spectroscopy (MRS) is considered by many to be the noninvasive reference standard for quantification of hepatic fat content (10,11). MRS has both higher sensitivity and specificity for hepatic fat quantification compared with ultrasound and computed tomography (12), indicating that an MR-based technique would be advantageous for hepatic fat quantification. However, like biopsy, MRS is prone to sampling error due to the heterogeneity of steatosis because typically only a single voxel is used to assess the entire liver. Alternatively, chemical shift based water–fat separation methods have demonstrated accurate quantification of hepatic steatosis by several groups (11,13–17). Several confounding factors have been identified that corrupt the ability of MRI to accurately quantify fat using fat–water separation techniques (18). These factors must be addressed before the measured fat-fraction accurately reflects the underlying concentration of triglycerides. Specific confounding factors include T1 bias (13, 19–21), noise bias (19), the complex NMR spectrum of fat (13,14,22), T2∗ decay (13,23), and phase errors caused by eddy currents (24). To perform the correction for eddy currents, a complex image-based fat-water separation including spectral modeling and T2∗ correction is performed first. Then, a second fit to a magnitude signal model is performed, using the complex estimates of water, fat and T2∗ as the starting conditions. This provides estimates of water and fat that are free from the effects of phase shifts from eddy currents. After correction for all confounding factors, the measured fat-fraction is equivalent to the proton density fat-fraction (PDFF). PDFF is an inherent property of the tissue, and is platform and protocol independent, making it a potentially useful biomarker of liver fat content. A recently described complex chemical shift-based fat-water separation method, based on IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation) has been described for fat quantification in the liver (14,19,22,23,25). Using a low flip angle to minimize T1 bias (19), magnitude discrimination to minimize noise bias (19), T2∗ correction (22,23), multi-peak fat spectral modeling (14,22) including six spectral peaks of fat, and eddy current correction (24), accurate quantification has been validated in phantom experiments (26), animal experiments (17) and more recently in in vivo studies (25), over a wide range of fat-fractions (17,26). These studies collectively provide validation on the accuracy of this method. However, rigorous validation of a biomarker also requires an understanding of the precision (repeatability) of a method to assess longitudinal changes in the biomarker. Therefore the primary purpose of this work is to determine the precision of clinical MRI hepatic fat quantification when correction for all known confounding factors has been performed. A secondary purpose is to reproduce accuracy measurements reported in previous validation studies (25), using MRS as the reference standard for hepatic fat-fraction.