Effect of Multipeak Spectral Modeling of Fat for Liver Iron and Fat Quantification: Correlation of Biopsy with MR Imaging Results

Abstract

Purpose:To investigate the effect of the multipeak spectral modeling of fat on R2* values as measures of liver iron and on the quantification of liver fat fraction, with biopsy as the reference standard. Materials and Methods:Institutional review board approval and informed consent were obtained. Patients with liver disease (n = 95; 50 men, 45 women; mean age, 57.2 years 6 14.1 [standard deviation]) underwent a nontargeted liver biopsy, and 97 biopsy samples were reviewed for steatosis and iron grades. MR imaging at 1.5 T was performed 24-72 hours after biopsy by using a three-echo three-dimensional gradient-echo sequence for water and fat separation. Data were reconstructed off-line, correcting for T1 and T2* effects. Fat fraction and R2* maps (1/T2*) were reconstructed and differences in R2* and steatosis grades with and without multipeak modeling of fat were tested by using the Kruskal-Wallis test. Spearman rank correlation coefficient was used to assess fat fractions and steatosis grades. Linear regression analysis was performed to compare the fat fraction for both models. Results:Mean steatosis grade at biopsy ranged from 0% to 95%. Biopsy specimens in 26 of 97 patients (27%) showed liver iron (15 mild, six moderate, and five severe). In all 71 samples without iron, a strong increase in the apparent R2* was observed with increasing steatosis grade when single-peak modeling of fat was used (P = .001). When multipeak modeling was used, there were no differences in the apparent R2* as a function of steatosis grading (P = .645), and R2* values agreed closely with those reported in the literature. Good correlation between fat fraction and steatosis grade was observed (r S = 0.85) both without and with spectral modeling. Conclusion:In the presence of fat, multipeak spectral modeling of fat improves the agreement between R2* and liver iron. Single-peak modeling of fat leads to underestimation of liver fat.q RSNA, 2012Supplemental material: http://radiology.rsna.org/lookup /suppl

Combined Use of MR Fat Quantification and MR Elastography in Living Liver Donors: Can It Reduce the Need for Preoperative Liver Biopsy?

“…In addition, both examinations showed high accuracy in the detection of clinically significant hepatic steatosis (AUC, 0.93), as well as the presence of hepatic fibrosis (AUC, 0.85). Our study results show good agreement with previous studies, which also demonstrated excellent accuracy in the estimation of hepatic FF by using multiecho chemicalshift imaging with multipeak fat spectrum modeling or T2-corrected multiecho single-voxel 1 H MR spectroscopy (39,40), as well as significant correlation between LS values at MR elastography and the degree of hepatic fibrosis at pathologic examination (25,41). Considering that both methods are achieved within a breath hold and cover a larger area than percutaneous liver biopsy, as well as the high accuracy in the prediction of substantial hepatic steatosis, MR fat quantification and MR elastography may serve as a screening tool for the selection of donors without a risk of substantial hepatic steatosis and/or hepatic fibrosis.…”

Accuracy of MR Imaging–estimated Proton Density Fat Fraction for Classification of Dichotomized Histologic Steatosis Grades in Nonalcoholic Fatty Liver Disease

“…Kühn et al (52) reported an MR imaging PDFF threshold of 4.5% for diagnosis of grade 1 or higher steatosis. This threshold provided 84% sensitivity and 100% specificity.…”

“…Finally, iron grade was not available as part of our histologic analysis. Instead, we used R2* as a surrogate for iron to address its potential confounding effect on the relationship between steatosis and MR imaging PDFF (52).…”

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

“…However, it has been shown that the spectral characteristics of triglycerides between BAT and WAT are quite similar, with only subtle differences in chain length and degree of carbon unsaturation (40). Furthermore, several recent literature reports have shown that the estimated FF is minimally impacted by moderate differences in the fat spectral models assumed during water-fat decomposition and image reconstruction (41,42). The use of an appropriate multi-peak fat spectral model is nonetheless more accurate than the traditional single-peak water-methylene model.…”