In vivo characterization of the liver fat ¹H MR spectrum.
ABSTRACT A theoretical triglyceride model was developed for in vivo human liver fat (1) H MRS characterization, using the number of double bonds (-CH=CH-), number of methylene-interrupted double bonds (-CH=CH-CH(2)-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. T(2)-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 CH(2) peaks at 2.1 and 1.3 ppm were linearly correlated (slope, 0.172; r = 0.991), as were the 0.9 ppm CH(3) and 1.3 ppm CH(2) peaks (slope, 0.125; r = 0.989). The 2.75 ppm CH(2) peak represented 0.6% of the total fat signal in high-liver-fat subjects. These values predict that 8.6% of 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.
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ABSTRACT: PURPOSE: To demonstrate an approach to water-fat separation with R2* correction using compressed sensing and parallel imaging. METHODS: Acquisition times for chemical shift based water-fat separation imaging are lengthy, and many applications rely on image acceleration techniques. In this study, we present an integrated compressed sensing, parallel imaging, R2* corrected water-fat separation technique for water-fat imaging of highly accelerated acquisitions. Reconstruction times are reduced using coil compression. RESULTS: The proposed technique is demonstrated using a customized IDEAL-SPGR pulse sequence to acquire retrospectively and prospectively undersampled datasets of the liver, calf, knee, and abdominal cavity. This technique is shown to offer comparable image quality relative to fully sampled reference images for a range of acceleration factors. At high acceleration factors, this technique is shown to offer improved image quality over parallel imaging. CONCLUSION: A technique is described that uses compressed sensing and parallel imaging to reconstruct R2*-corrected water and fat images from accelerated datasets. Acceleration factors as high as 7.0 are shown with excellent image quality. These high acceleration factors enable water-fat separation with higher resolution or greater anatomical coverage in breath-hold applications. Magn Reson Med, 2013. © 2013 Wiley Periodicals, Inc.Magnetic Resonance in Medicine 03/2013; · 2.96 Impact Factor
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ABSTRACT: Not only the fat content but also the composition of fatty acids (FAs) in stored triglycerides might be of interest in the research on nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. In this study, a novel reconstruction approach is proposed that uses theoretical knowledge of the chemical structure of FAs to simultaneously quantify the fat fraction (FF) and the FAs composition (chain length cl, number of double bonds ndb, and number of methylene-interrupted double bonds nmidb) from multiple gradient echo images. Twenty phantoms with various fat contents (FF = 9-100%) and FA compositions (cl = 12.1-17.9, ndb = 0.23-5.10, and nmidb = 0.04-2.39) were constructed and imaged in a 3-T Siemens scanner. In addition, spectra were acquired in each phantom. Slopes and "standard deviations from true values" were used to investigate the accuracy of the two methods. The imaging method holds well in a comparison to the previously suggested spectroscopy method and showed similar overall accuracy. The in vivo feasibility was demonstrated in the thigh adipose tissue of a healthy volunteer. In conclusion, our developed method is a promising tool for FF and FA composition quantification. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.Magnetic Resonance in Medicine 04/2012; · 2.96 Impact Factor