Effect of flip angle on the accuracy and repeatability of hepatic proton density fat fraction estimation by complex data-based, T1-independent, T2*-corrected, spectrum-modeled MRI.

PURPOSE: To evaluate the effect of flip angle (FA) on accuracy and within-examination repeatability of hepatic proton-density fat fraction (PDFF) estimation with complex data-based magnetic resonance imaging (MRI). MATERIALS AND METHODS: PDFF was estimated at 3T in 30 subjects using two sets of five MRI sequences with FA from 1° to 5° in each set. One set used 7 msec repetition time and acquired 6 echoes (TR7/E6); the other used 14 msec and acquired 12 echoes (TR14/E12). For each FA in both sets the accuracy of MRI-PDFF was assessed relative to MR spectroscopy (MRS)-PDFF using four regression parameters (slope, intercept, average bias, R(2) ). Each subject had four random sequences repeated; within-examination repeatability of MRI-PDFF for each FA was assessed with intraclass correlation coefficient (ICC). Pairwise comparisons were made using bootstrap-based tests. RESULTS: Most FAs provided high MRI-PDFF estimation accuracy (intercept range -1.25 to 0.84, slope 0.89-1.06, average bias 0.24-1.65, R(2) 0.85-0.97). Most comparisons of regression parameters between FAs were not significant. Informally, in the TR7/E6 set, FAs of 2° and 3° provided the highest accuracy, while FAs of 1° and 5° provided the lowest. In the TR14/E12 set, accuracy parameters did not differ consistently between FAs. FAs in both sets provided high within-examination repeatability (ICC range 0.981-0.998). CONCLUSION: MRI-PDFF was repeatable and, for most FAs, accurate in both sequence sets. In the TR7/E6 sequence set, FAs of 2° and 3° informally provided the highest accuracy. In the TR14/E12 sequence set, all FAs provided similar accuracy.

Cross-sectional investigation of correlation between hepatic steatosis and IVIM perfusion on MR imaging.

The purpose of this study was to investigate the relationship between liver fat fraction (FF) and diffusion parameters derived from the intravoxel incoherent motion (IVIM) model. Thirty-six subjects with suspected nonalcoholic fatty liver disease underwent diffusion-weighted magnetic resonance imaging with 10 b-values and spoiled gradient recalled echo imaging with six echoes for fat quantification. Correlations were measured between FF, transverse relaxivity (R2), diffusivity (D) and perfusion fraction (f). The primary finding was that no significant correlation was obtained for D vs. FF or f vs. FF. Significant correlations were obtained for D vs. R2 (r=-0.490, P=.002) and f vs. D (r=-0.458, P=.005). The conclusion is that hepatic steatosis does not affect measurement of perfusion or diffusion and therefore is unlikely to confound the use of apparent diffusivity to evaluate hepatic fibrosis.

Cardiac motion in diffusion-weighted MRI of the liver: artifact and a method of correction.

PURPOSE: To characterize cardiac motion artifacts in the liver and assess the use of a postprocessing method to mitigate these artifacts in repeat measurements. MATERIALS AND METHODS: Three subjects underwent breathhold diffusion-weighted (DW) scans consisting of 25 repetitions for three b-values (0, 500, 1000 sec/mm(2)). Statistical maps computed from these repetitions were used to assess the distribution and behavior of cardiac motion artifacts in the liver. An objective postprocessing method to reduce the artifacts was compared with radiologist-defined gold standards. RESULTS: Signal dropout is pronounced in areas proximal to the heart, such as the left lobe, but also present in the right lobe and in distal liver segments. The dropout worsens with b-value and leads to overestimation of the diffusivity. By reference to a radiologist-defined gold standard, a postprocessing correction method is shown to reduce cardiac motion artifact. CONCLUSION: Cardiac motion leads to significant artifacts in liver DW imaging; we propose a postprocessing method that may be used to mitigate the artifact and is advantageous to standard signal averaging in acquisitions with multiple repetitions.

Robustness of fat quantification using chemical shift imaging.

The purpose of this study was to investigate the effect of parameter changes that can potentially lead to unreliable measurements in fat quantification. Chemical shift imaging was performed using spoiled gradient echo sequences with systematic variations in the following: two-dimensional/three-dimensional sequence, number of echoes, delta echo time, fractional echo factor, slice thickness, repetition time, flip angle, bandwidth, matrix size, flow compensation and field strength. Results indicated no significant (or significant but small) changes in fat fraction with parameter. The significant changes can be attributed to the known effects of T1 bias and two forms of noise bias.

In vivo characterization of the liver fat ¹H MR spectrum.

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.

Estimation of hepatic proton-density fat fraction by using MR imaging at 3.0 T.

PURPOSE: To compare the accuracy of several magnetic resonance (MR) imaging-based methods for hepatic proton-density fat fraction (FF) estimation at 3.0 T, with spectroscopy as the reference technique. MATERIALS AND METHODS: This prospective study was institutional review board approved and HIPAA compliant. Informed consent was obtained. One hundred sixty-three subjects (39 with known hepatic steatosis, 110 with steatosis risk factors, 14 without risk factors) underwent proton MR spectroscopy and non-T1-weighted gradient-echo MR imaging of the liver. At spectroscopy, the reference FF was determined from frequency-selective measurements of fat and water proton densities. At imaging, FF was calculated by using two-, three-, or six-echo methods, with single-frequency and multifrequency fat signal modeling. The three- and six-echo methods corrected for T2*; the two-echo methods did not. For each imaging method, the fat estimation accuracy was assessed by using linear regression between the imaging FF and spectroscopic FF. Binary classification accuracy of imaging was assessed at four reference spectroscopic thresholds (0.04, 0.06, 0.08, and 0.10 FF). RESULTS: Regression intercept of two-, three-, and six-echo methods were -0.0211, 0.0087, and -0.0062 (P <.001 for all three) without multifrequency modeling and -0.0237 (P <.001), 0.0022, and -0.0007 with multifrequency modeling, respectively. Regression slope of two-, three-, and six-echo methods were 0.8522, 0.8528, and 0.7544 (P <.001 for all three) without multifrequency modeling and 0.9994, 0.9775, and 0.9821 with multifrequency modeling, respectively. Significant deviation of intercept and slope from 0 and 1, respectively, indicated systematic error. Classification accuracy was 82.2%-90.1%, 93.9%-96.3%, and 83.4%-89.6% for two-, three-, and six-echo methods without multifrequency modeling and 88.3%-92.0%, 95.1%-96.3%, and 94.5%-96.3% with multifrequency modeling, respectively, depending on the FF threshold. T2*-corrected (three- and six-echo) multifrequency imaging methods had the overall highest FF estimation and classification accuracy. Among methods without multifrequency modeling, the T2-corrected three-echo method had the highest accuracy. CONCLUSION: Non-T1-weighted MR imaging with T2 correction and multifrequency modeling helps accurately estimate hepatic proton-density FF at 3.0 T.

Assessment of liver fat quantification in the presence of iron.

This study assesses the stability of magnetic resonance liver fat measurements against changes in T2* due to the presence of iron, which is a confound for accurate quantification. The liver T2* was experimentally shortened by intravenous infusion of a super paramagnetic iron oxide contrast agent. Low flip angle multiecho gradient echo sequences were performed before, during and after infusion. The liver fat fraction (FF) was calculated in co-localized regions-of-interest using T2* models that assumed no decay, monoexponential decay and biexponential decay. Results show that, when T2* was neglected, there was a strong underestimation of FF and with monoexponential decay there was a weak overestimation of FF. Curve-fitting using the biexponential decay was found to be problematic. The overestimation of FF may be due to remaining deficiencies in the model, although is unlikely to be important for clinical diagnosis of steatosis.