Impact of fully 4D reconstruction on kinetic parameter estimates

The spatiotemporal noise reduction of fully 4D reconstruction, in comparison to 3D reconstruction, has the potential to offer improved kinetic parameter estimates. These estimates should be as close to the ground truth as possible to achieve accurate quantification of function. Conventionally, the bias, coefficient of variation and error of these estimates are calculated based on simulated datasets, the latter defining the ground truth. One caveat of these simulations lies in the complexity to correctly model data acquired with a real PET tomograph. Due to this complexity, it is seldom possible to accurately model a PET tomograph. This work presents a list-mode subsets methodology for the use of real PET data in assessing the impact of fully 4D reconstruction on kinetic parameter estimates in comparison to conventional 3D reconstruction methods. Using high-resolution PET data from the HRRT, we demonstrate reduction in mean absolute error in BP estimates using fully 4D reconstruction compared to 3D reconstruction.