Direct Estimation of Regional Kinetic Rate Constant Distributions from PET Sinograms and Correction of Statistical Estimation Error Distributions

We present a novel method to estimate the variation of kinetic model parameters directly from sinogram time series data. We determine the kinetic parameters independently for each voxel of the target through maximum likelihood estimation. The maximum likelihood estimates in the region of interest are collected into histograms. The histograms contain estimation error, which obeys maximum likelihood theory. We determine the error distribution through repeated estimation with a simulated homogeneous target. With simulated sinogram time series data we evaluate the method's performance with the 2K-model and the 3K-model. The results show that after error correction both the mean and the deviation can be obtained with good accuracy from the histograms.