- Poster presentation
- Open Access
Blind estimation of pharmacokinetic parameters in cardiac DCE-MRI
© Fluckiger et al; licensee BioMed Central Ltd. 2010
- Published: 21 January 2010
- Myocardial Blood Flow
- Blood Pool
- Myocardial Tissue
- Perfusion Data
- Contrast Agent Concentration
Myocardial blood flow estimation in DCE-MRI requires measuring the time course of contrast agent concentration in both the blood pool and myocardial tissues. The differences in signal enhancement in these two regions can complicate the imaging process. This problem has been overcome by performing two studies (dual bolus) with differing contrast agent concentrations.
This work presents a novel application of the alternating minimization with model (AMM) method to cardiac perfusion data. We estimate the AIF directly from myocardial tissue curves, eliminating the need for perfusion data acquisition at two different concentration levels.
Dual bolus dynamic cardiac MR data was obtained with low (0.004 mmol/kg) and higher (0.02 mmol/kg) doses of Gd-BOPTA. The images were registered spatially and myocardial voxels were identified manually to obtain a set of tissue activity curves (TACs). The TACs were clustered into 12 curves and input to the AMM method to estimate a parameterized AIF. The estimated AIF was scaled such that the average value of the final three data points was equivalent to the measured high-dose AIF. The extended Tofts-Kety model was used to calculate kinetic parameters pixel-wise in the myocardium using both the directly measured AIF from the low-concentration scan and the AMM estimated AIF.
The AMM blind estimation technique has the potential for simplifying quantitative myocardial perfusion studies. More studies are needed to refine the method and determine its robustness.
This article is published under license to BioMed Central Ltd.