Parametric reconstruction of kinetic PET data with plasma function estimation

It is often necessary to analyze the time response of a tracer. A common way of analyzing the tracer time response is to use a compartment model and estimate the model parameters. The model parameters are generally physiologically meaningful and called “kinetic parameters”. In this paper, we simultaneously estimate both the kinetic parameters at each voxel and the model-based plasma input function directly from the sinogram data. Although the plasma model parameters are not our primary interest, they are required for accurate reconstruction of kinetic parameters. The plasma model parameters are initialized with an image domain method to avoid local minima, and multiresolution optimization is used to perform the required reconstruction. Good initial guesses for the plasma parameters are required for the algorithm to converge to the correct answer. Therefore, we devised a preprocessing step involving clustering of the emission images by temporal characteristics to find a reasonable plasma curve that was consistent with the kinetics of the multiple tissue types. We compare the root mean squared error (RMSE) of the kinetic parameter estimates with the measured (true) plasma input function and with the estimated plasma input function. Tests using a realistic rat head phantom and a real plasma input function show that we can simultaneously estimate the kinetic parameters of the two-tissue compartment model and plasma input function. The RMSE of the kinetic parameters increased for some parameters and remained the same or decreased for other parameters.