Adaptive parametric kinetic modelling for improved full field of view fitting of PET data

Methods for adaptively fitting kinetic models to image data are explored. In conducting this fitting two goals are set: 1) that good fits are obtained for all image voxels; and 2) that where a primary biologically based model is appropriate, this model is used. The first goal is obtained through the inclusion of a more general secondary model. The second goal is achieved through the penalisation of estimates from this secondary model with the weighting of this penalisation optimised using generalised cross validation. The result is a modelling scheme where the secondary model is adaptively included for voxels that the primary model is unable to fit. The envisaged application is in 4D (space and time) reconstruction to prevent spatial propagation of errors from regions where a primary model is not appropriate. An evaluation of reconstructed clinical data using a dataset with challenging kinetics has been conducted. Application to the clinical dataset showed promising results with the modelling scheme able to fit kinetics associated with activity in the region of the injection site veins, the right ventricle, right atrium and the gall bladder. The method requires the careful selection of the secondary model and further work is needed to optimise this selection and evaluate the benefit for 4D reconstruction.