DCE-MRI of the liver: effect of linear and nonlinear conversions on hepatic perfusion quantification and reproducibility

J Magn Reson Imaging. 2014 Jul;40(1):90-8. doi: 10.1002/jmri.24341. Epub 2013 Nov 4.

Abstract

Purpose: To evaluate the effect of different methods to convert magnetic resonance (MR) signal intensity (SI) to gadolinium concentration ([Gd]) on estimation and reproducibility of model-free and modeled hepatic perfusion parameters measured with dynamic contrast-enhanced (DCE)-MRI.

Materials and methods: In this Institutional Review Board (IRB)-approved prospective study, 23 DCE-MRI examinations of the liver were performed on 17 patients. SI was converted to [Gd] using linearity vs. nonlinearity assumptions (using spoiled gradient recalled echo [SPGR] signal equations). The [Gd] vs. time curves were analyzed using model-free parameters and a dual-input single compartment model. Perfusion parameters obtained with the two conversion methods were compared using paired Wilcoxon test. Test-retest and interobserver reproducibility of perfusion parameters were assessed in six patients.

Results: There were significant differences between the two conversion methods for the following parameters: AUC60 (area under the curve at 60 s, P < 0.001), peak gadolinium concentration (Cpeak, P < 0.001), upslope (P < 0.001), Fp (portal flow, P = 0.04), total hepatic flow (Ft, P = 0.007), and MTT (mean transit time, P < 0.001). Our preliminary results showed acceptable to good reproducibility for all model-free parameters for both methods (mean coefficient of variation [CV] range, 11.87-23.7%), except for upslope (CV = 37%). Among modeled parameters, DV (distribution volume) had CV <22% with both methods, PV and MTT showed CV <21% and <29% using SPGR equations, respectively. Other modeled parameters had CV >30% with both methods.

Conclusion: Linearity assumption is acceptable for quantification of model-free hepatic perfusion parameters while the use of SPGR equations and T1 mapping may be recommended for the quantification of modeled hepatic perfusion parameters.

Keywords: fibrosis; liver; perfusion quantification.

Publication types

  • Comparative Study
  • Randomized Controlled Trial
  • Research Support, N.I.H., Extramural

MeSH terms

  • Aged
  • Algorithms*
  • Blood Flow Velocity
  • Contrast Media / pharmacokinetics
  • Female
  • Hepatitis C / pathology
  • Hepatitis C / physiopathology*
  • Humans
  • Image Interpretation, Computer-Assisted / methods*
  • Liver / pathology
  • Liver / physiopathology*
  • Liver Circulation
  • Magnetic Resonance Angiography / methods*
  • Male
  • Meglumine / analogs & derivatives*
  • Meglumine / pharmacokinetics
  • Metabolic Clearance Rate
  • Middle Aged
  • Models, Biological*
  • Models, Statistical
  • Nonlinear Dynamics
  • Observer Variation
  • Organometallic Compounds / pharmacokinetics*
  • Prospective Studies
  • Reproducibility of Results
  • Sensitivity and Specificity

Substances

  • Contrast Media
  • Organometallic Compounds
  • gadobenic acid
  • Meglumine