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

Abstract

Purpose 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. Materials and Methods From a group of 97 patients, 32 patients with hepatic fat fraction greater than 5%, as measured by MRS, were identified. In these patients, chemical shift encoded fat-water imaging was performed, covering the entire liver in a single breath-hold. Fat fraction was measured from the imaging data by post-processing using 6 different models: single- and dual-R2* correction, each performed with complex fitting, magnitude fitting and mixed magnitude/complex fitting to compare the effects of phase error correction. Fat fraction measurements were compared to co-registered spectroscopy measurements using linear regression. Results Linear regression demonstrated higher agreement with MRS using single-R2* correction compared with dual-R2* correction. Among single-R2* models, all 3 fittings methods performed similarly well (slope = 1.0 ± 0.06, r2=0.89–0.91). Conclusion Single-R2* modeling is more accurate than dual-R2* modeling for hepatic fat quantification in patients, even in those with high hepatic fat concentrations.

Comparison of brown and white adipose tissues in infants and children with chemical‐shift‐encoded water‐fat MRI

“…The multi-echo water-fat algorithms can jointly estimate FF and T 2 * on a voxel-wise basis, with the latter metric being considered a factor that needs to be accounted for in order to facilitate accurate computation of the former. Both FF and T 2 * metrics have been used in assessing hepatic fat and iron-overload (28)(29)(30). In the infants, the mDIXON sequence was the only research pulse sequence performed in addition to our institution's standard neural MRI protocols.…”

Measurement of liver fat fraction and iron with MRI and MR spectroscopy techniques

“…Robust signal modeling is also important with MR methods: the presence of lipid and iron (and other metabolites) in an imaging voxel presents a multi-component R2 or R2* relaxation process, which may vary depending on the concentration of each component. Current multi-peak imaging methods assume a single R2* component in order to provide adequate SNR properties, and results show excellent linear correlation with a lipid fraction reference in the absence of iron (28). However, some reports show a departure from linearity when iron is present with lipid (47).…”

“…A thorough analysis of the GRE signal model, in terms of compartmental T2*-dependence, has been investigated previously, with many additional assumptions (26,27). While lipid fraction estimation bias is reduced by including water and lipid T2* terms, it has been found that noise performance suffers significantly, counteracting the improved accuracy that is afforded by the multiple T2* terms (27)(28)(29). The noise performance is particularly important for low lipid fraction levels, which could be of diagnostic importance.…”

“…Most modern lipid-sensitive MR applications incorporate some degree of R2 or R2* correction using multiecho acquisitions. It has been shown that lipid fraction measurements using either MRI or MR spectroscopy without R2/R2* correction result in significant error (26,28,29,36). The effectiveness of these compensation methods often depends on the degree of iron concentration; severe iron overload can prevent adequate TE sampling and entirely obscure lipid quantification.…”

Accelerating MR Imaging Liver Steatosis Measurement Using Combined Compressed Sensing and Parallel Imaging: A Quantitative Evaluation

“…The data were modeled with one R2* component, as in most clinical studies (7)(8)(9)(10)(11). Dual R2* models have been investigated (35,36) but have been shown to have worse noise performance and may be unstable in pixels where one species is not present. It was not possible to produce data with conventional parallel imaging alone at comparable accelerations without structured artifacts within the regions of interest; therefore, quantitative analysis was not performed.…”