Monte Carlo Simulation to Study the Robustness of Empirical DCE-MRI Kinetic Parameters to Gaussian Noise

Ka-Loh Li¹, Alan Jackson¹, Gerard Thompson¹, Xiaoping Zhu¹

Using empirical descriptors to assess T1-weighted DCE-MRI data is easy to perform. However, the effects of MRI noise on the reliability of empirical kinetic parameters have not been systematically investigated. This study investigated the robustness of several empirical parameters to Gaussian noise under various pharmacokinetic and noisy conditions using Monte Carlo simulation. We found that area under the enhancement curves was most robust to Gaussian noise. Signal enhancement ratio is mostly sensitive to noise and pharmacokinetic conditions. The study improved our understanding of the noise effect on empirical kinetic parameters, leading to better interpretation of these parametric images.