Quantifying dynamic contrast‐enhanced MRI of the knee in children with juvenile rheumatoid arthritis using an arterial input function (AIF) extracted from popliteal artery enhancement, and the effect of the choice of the AIF on the kinetic parameters
Open Access
- 8 August 2005
- journal article
- research article
- Published by Wiley in Magnetic Resonance in Medicine
- Vol. 54 (3) , 560-568
- https://doi.org/10.1002/mrm.20597
Abstract
Quantification of dynamic contrast-enhanced (DCE) MRI based on pharmacokinetic modeling requires specification of the arterial input function (AIF). A full representation of the plasma concentration data, including the initial rise and decay parts, considering the delay and dispersion of the bolus contrast is important. This work deals with modeling of DCE-MRI data from the knees of children with a history of juvenile rheumatoid arthritis (JRA) by using an AIF extracted from the signal enhancement data from the nearby popliteal artery. Three models for the AIFs were considered: a triexponential (AIF1), a gamma-variate plus a biexponential (AIF2), and a biexponential (AIF3). The pharmacokinetic parameters obtained from the model were Ktrans′, kep, and V. The results from AIF1 and AIF2 showed no statistically significant difference. However, some statistically significant differences were seen with AIF3, particularly for parameters Ktrans′ and V in the synovium (SNVM). These results suggest the importance of obtaining an appropriate AIF representation in pharmacokinetic modeling of JRA. Specifically, the initial rising part of the AIF should be incorporated for optimal pharmacokinetic modeling results. The pharmacokinetic parameters (mean ± SD) derived from AIF1, using the average plasma concentration data, were as follows: SNVM Ktrans′(min−1) = 0.52 ± 0.34, kep(min−1) = 0.71 ± 0.39, and V = 0.33 ± 0.16, and for the distal femoral physis (DFP) Ktrans′(min−1) = 1.83 ± 1.78, kep(min−1) = 2.65 ± 1.80, and V = 0.46 ± 0.31. The pharmacokinetic parameters in the SNVM may be useful for investigating activity and therapeutic efficacy in studies of JRA. Longitudinal studies are necessary to find or demonstrate the parameter that is more sensitive to disease activity. Magn Reson Med, 2005.Keywords
This publication has 21 references indexed in Scilit:
- Quantification of dynamic contrast-enhanced MR imaging of the knee in children with juvenile rheumatoid arthritis based on pharmacokinetic modelingMagnetic Resonance Imaging, 2004
- Parametric imaging of tumor perfusion using flow‐ and permeability‐limited tracersJournal of Magnetic Resonance Imaging, 2002
- Correlation of Microvascular Permeability Derived from Dynamic Contrast-Enhanced MR Imaging with Histologic Grade and Tumor Labeling IndexAcademic Radiology, 2001
- Capillary transfer constant of Gd‐DTPA in the myocardium at rest and during vasodilation assessed by MRIMagnetic Resonance in Medicine, 1998
- Modeling tracer kinetics in dynamic Gd‐DTPA MR imagingJournal of Magnetic Resonance Imaging, 1997
- Myocardial perfusion modeling using MRIMagnetic Resonance in Medicine, 1996
- Quantitative Analysis of Dynamic Gd‐DTPA Enhancement in Breast Tumors Using a Permeability ModelMagnetic Resonance in Medicine, 1995
- Dynamic studies of gadolinium uptake in brain tumors using inversion‐recovery echo‐planar imagingMagnetic Resonance in Medicine, 1992
- Pharmacokinetic Parameters in CNS Gd-DTPA Enhanced MR ImagingJournal of Computer Assisted Tomography, 1991
- Quantitation of blood‐brain barrier defect by magnetic resonance imaging and gadolinium‐DTPA in patients with multiple sclerosis and brain tumorsMagnetic Resonance in Medicine, 1990