A theoretical triglyceride model was developed for in vivo human liver fat 1H MRS characterization, using the number of double bonds (–CH=CH–), number of methylene-interrupted double bonds (–CH=CH–CH2–CH=CH–) and average fatty acid chain length. Five 3 T, single-voxel, stimulated echo acquisition mode spectra (STEAM) were acquired consecutively at progressively longer TEs in a fat–water emulsion phantom and in 121 human subjects with known or suspected nonalcoholic fatty liver disease. T2-corrected peak areas were calculated. Phantom data were used to validate the model. Human data were used in the model to determine the complete liver fat spectrum. In the fat–water emulsion phantom, the spectrum predicted by the model (based on known fatty acid chain distribution) agreed closely with spectroscopic measurement. In human subjects, areas of CH2 peaks at 2.1 and 1.3 ppm were linearly correlated (slope, 0.172; r = 0.991), as were the 0.9 ppm CH3 and 1.3 ppm CH2 peaks (slope, 0.125; r = 0.989). The 2.75 ppm CH2 peak represented 0.6% of the total fat signal in high-liver-fat subjects. These values predict that 8.6% ofm the total fat signal overlies the water peak. The triglyceride model can characterize human liver fat spectra. This allows more accurate determination of liver fat fraction from MRI and MRS.

Hepatic steatosis is characterized by abnormal and excessive accumulation of lipids within hepatocytes. It is an important feature of diffuse liver disease, and the histological hallmark of nonalcoholic fatty liver disease (NAFLD). Other conditions associated with steatosis include alcoholic liver disease, viral hepatitis, human immunodeficiency virus (HIV) and genetic lipodystrophies, cystic fibrosis liver disease, and hepatotoxicity from various therapeutic agents. Liver biopsy, the current clinical gold standard for assessment of liver fat, is invasive and has sampling errors, and is not optimal for screening, monitoring, clinical decision‐making, or well suited for many types of research studies. Noninvasive methods that accurately and objectively quantify liver fat are needed. Ultrasound (US) and computed tomography (CT) can be used to assess liver fat but have limited accuracy as well as other limitations. Magnetic resonance (MR) techniques can decompose the liver signal into its fat and water signal components and therefore assess liver fat more directly than CT or US. Most MR techniques measure the signal fat‐fraction (the fraction of the liver MR signal attributable to liver fat), which may be confounded by numerous technical and biological factors and may not reliably reflect fat content. By addressing the factors that confound the signal fat‐fraction, advanced MR techniques measure the proton density fat‐fraction (the fraction of the liver proton density attributable to liver fat), which is a fundamental tissue property and a direct measure of liver fat content. These advanced techniques show promise for accurate fat quantification and are likely to be commercially available soon. J. Magn. Reson. Imaging 2011;. © 2011 Wiley‐Liss, Inc.

Gd-EOB-DTPA allows a comprehensive evaluation of the liver with the acquisition of both dynamic and hepatocyte phase images. This provides potential additional information, especially for the detection and characterization of small liver lesions. However, protocol optimization is necessary for improved image quality and workflow.

Hepatic steatosis is characterized by abnormal and excessive accumulation of lipids within hepatocytes. It is an important feature of diffuse liver disease, and the histological hallmark of non-alcoholic fatty liver disease (NAFLD). Other conditions associated with steatosis include alcoholic liver disease, viral hepatitis, HIV and genetic lipodystrophies, cystic fibrosis liver disease, and hepatotoxicity from various therapeutic agents. Liver biopsy, the current clinical gold standard for assessment of liver fat, is invasive and has sampling errors, and is not optimal for screening, monitoring, clinical decision making, or well-suited for many types of research studies. Non-invasive methods that accurately and objectively quantify liver fat are needed. Ultrasound (US) and computed tomography (CT) can be used to assess liver fat but have limited accuracy as well as other limitations. Magnetic resonance (MR) techniques can decompose the liver signal into its fat and water signal components and therefore assess liver fat more directly than CT or US. Most magnetic resonance (MR) techniques measure the signal fat-fraction (the fraction of the liver MR signal attributable to liver fat), which may be confounded by numerous technical and biological factors and may not reliably reflect fat content. By addressing the factors that confound the signal fat-fraction, advanced MR techniques measure the proton density fat-fraction (the fraction of the liver proton density attributable to liver fat), which is a fundamental tissue property and a direct measure of liver fat content. These advanced techniques show promise for accurate fat quantification and are likely to be commercially available soon.

The Liver Imaging Reporting and Data System (LI-RADS) standardizes the interpretation, reporting, and data collection for imaging examinations in patients at risk for hepatocellular carcinoma (HCC). It assigns category codes reflecting relative probability of HCC to imaging-detected liver observations based on major and ancillary imaging features. LI-RADS also includes imaging features suggesting malignancy other than HCC. Supported and endorsed by the American College of Radiology (ACR), the system has been developed by a committee of radiologists, hepatologists, pathologists, surgeons, lexicon experts, and ACR staff, with input from the American Association for the Study of Liver Diseases and the Organ Procurement Transplantation Network/United Network for Organ Sharing. Development of LI-RADS has been based on literature review, expert opinion, rounds of testing and iteration, and feedback from users. This article summarizes and assesses the quality of evidence supporting each LI-RADS major feature for diagnosis of HCC, as well as of the LI-RADS imaging features suggesting malignancy other than HCC. Based on the evidence, recommendations are provided for or against their continued inclusion in LI-RADS.q RSNA, 2017 Online supplemental material is available for this article.An Tang REVIEW: LI-RADS Major Features for Hepatocellular Carcinoma DiagnosisTang et al selection of five major features was based on expert opinion, the literature review was performed to ensure that imaging-based diagnostic criteria were able to achieve near-100% specificity for the noninvasive diagnosis of HCC. This review focused on the evidence supporting the inclusion of imaging features and did not attempt to gather evidence on the composition of the LI-RADS diagnostic algorithm and probability of HCC for different combinations of criteria (other than the hallmark combination of APHE and washout appearance) in the LI-RADS diagnostic table.Each subgroup was charged with developing key research questions and then critically reviewing the literature to answer research questions thematically related to its assigned topic. Search StrategyThe PICO (patient population, intervention, comparison, and outcome) format frequently used in structured reviews does not lend itself well to studies of diagnostic performance. Rather than using PICO-style questions to guide the searches, therefore, the subgroups formulated free-form questions in advance with feedback from the other subgroups. A total of 10 questions were formulated under the framework and with the understanding that their answers would inform recommendations for removing or continuing to include the corresponding LI-RADS features. After the questions were formulated, each subgroup searched the PubMed develop a standardized Liver Imaging Reporting and Data System (LI-RADS) for interpretation, reporting, and data collection of imaging studies in patients at risk for developing HCC (1). The committee was composed mainly of diagnostic radiologists, but also hepatologists, surgeons, patho...

Purpose: To evaluate magnetic resonance imaging (MRI)-determined proton density fat fraction (PDFF) reproducibility across two MR scanner platforms and, using MR spectroscopy (MRS)-determined PDFF as reference standard, to confirm MRI-determined PDFF estimation accuracy. Materials and Methods:This prospective, cross-sectional, crossover, observational pilot study was approved by an Institutional Review Board. Twenty-one subjects gave written informed consent and underwent liver MRI and MRS at both 1.5T (Siemens Symphony scanner) and 3T (GE Signa Excite HD scanner). MRI-determined PDFF was estimated using an axial 2D spoiled gradient-recalled echo sequence with low flip-angle to minimize T1 bias and six echo-times to permit correction of T2* and fat-water signal interference effects. MRS-determined PDFF was estimated using a stimulated-echo acquisition mode sequence with long repetition time to minimize T1 bias and five echo times to permit T2 correction. Interscanner reproducibility of MRI determined PDFF was assessed by correlation analysis; accuracy was assessed separately at each field strength by linear regression analysis using MRS-determined PDFF as reference standard.Results: 1.5T and 3T MRI-determined PDFF estimates were highly correlated (r ¼ 0.992). MRI-determined PDFF estimates were accurate at both 1.5T (regression slope/ intercept ¼ 0.958/-0.48) and 3T (slope/intercept ¼ 1.020/ 0.925) against the MRS-determined PDFF reference.Conclusion: MRI-determined PDFF estimation is reproducible and, using MRS-determined PDFF as reference standard, accurate across two MR scanner platforms at 1.5T and 3T.

Gd-EOB-DTPA shows promise as a problem-solving tool in the cirrhotic liver because it provides additional information that may be helpful in lesion detection and characterization. Further research is needed to optimize Gd-EOB-DTPA imaging protocols in cirrhosis and develop diagnostic criteria for liver lesions in the cirrhotic liver.

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