Statistical analysis of pharmacokinetic models in dynamic contrast-enhanced magnetic resonance imaging.
This paper assesses the estimation of kinetic parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Asymptotic results from likelihood-based nonlinear regression are compared with results derived from the posterior distribution using Bayesian estimation, along with the output from an established software package (MRIW). By using the estimated error from kinetic parameters, it is possible to produce more accurate clinical statistics, such as tumor size, for patients with breast tumors. Further analysis has also shown that Bayesian methods are more accurate and do not suffer from convergence problems, but at a higher computational cost.
Schmid
Volker J
VJ
Institute for Biomedical Engineering, Suite 5, Sherfield Building, Imperial College, South Kensington, London SW7 2AZ, United Kingdom. v.schmid@imperial.ac.uk
Whitcher
Brandon J
BJ
Yang
Guang-Zhong
GZ
Taylor
N Jane
NJ
Padhani
Anwar R
AR