Effect of multipeak spectral modeling of fat for liver iron and fat quantification: correlation of biopsy with MR imaging results

Radiology. 2012 Oct;265(1):133-42. doi: 10.1148/radiol.12112520. Epub 2012 Aug 24.


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±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 (rS=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.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Area Under Curve
  • Biopsy
  • Fatty Liver / metabolism
  • Fatty Liver / pathology*
  • Female
  • Humans
  • Image Interpretation, Computer-Assisted
  • Imaging, Three-Dimensional
  • Iron / metabolism
  • Linear Models
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Prospective Studies
  • ROC Curve
  • Sensitivity and Specificity
  • Statistics, Nonparametric


  • Iron