In this work, we propose a novel 4D reconstruction method for PET which is based on spatiotemporal total variation (ST-TV). The ST-TV method takes advantage of image redundancies in 4D and was efficiently implemented using the split Bregman formulation, which has been shown to be optimal for decreasing noise while maintaining image quality. To evaluate the proposed approach we simulated data for a dynamic numerical phantom with different number of counts to mimic high and low Signal-to-Noise Ratio (SNR) scenarios.

Triple coincidences in PET can be used to enable the simultaneous imaging and separation of  radiotracers labeled with standard positron emitters (such as 13N) and positron-gamma emitters (such as 76 Br). We have previously shown that multiplexed PET can be achieved without any kinetic modelling or hardware modification, and therefore it can be used in most current PET scanners. The goal of this study was to demonstrate that this methodology can be applied to solve important clinical needs, such as the quantitative measurement of the liquid absorption in the airways, a new biomarker for the treatment response of Cystic Fibrosis (CF) patients.