Analytic reconstruction methods for list-mode time-of-flight PET

The ability of time-of-flight (TOF) PET imaging to improve image statistics has been well recognized and so far in TOF-PET image reconstruction research the attention has been paid to minimizing the image variance while speeding up the computation time in iterative reconstruction algorithms. In this work, we identify and study another advantage of TOF-PET imaging: the ability to generate theoretically exact PET images (in the mean) from list-mode TOF-PET data in real time. In addition, we observe that this new imaging capability is also feasible with non-TOF PET systems provided that their TOF measurements are retained. This new imaging capability may be exploited to allow for in-time adjustments to imaging protocols/patient positions, to develop image-guided applications with PET, or enable real-time observation of the responses of biological systems to challenges/stimuli.