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

    loading  Checking for direct PDF access through Ovid

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. J. Magn. Reson. Imaging 2014;40:90–98 © 2013 Wiley Periodicals, Inc.

Related Topics

    loading  Loading Related Articles