title: Towards optimal imaging with PET: an in silico feasibility study.
abstract: The efficacy of Positron Emission Tomography (PET) imaging relies fundamentally on the ability of the system to accurately identify true coincidence events. With existing systems, this is currently accomplished with an energy acceptance criterion followed by correction techniques to remove suspected false coincidence events. These corrections generally result in signal and contrast loss and thus limit the PET system's ability to achieve optimum image quality. A key property of annihilation radiation is that the photons are polarised with respect to each other. This polarisation correlation offers a potentially powerful discriminator, independent of energy, to accurately identify true events. In this proof of concept study, we investigate how photon polarisation information can be exploited in PET imaging by developing a method to discriminate true coincidences using the polarisation correlation of annihilation pairs. We implement this method using a Geant4 PET simulation of a GE Advance/Discovery LS system and demonstrate the potential advantages of the polarisation coincidence selection method over a standard energy criterion method. Current PET ring detectors are not capable of exploiting the polarisation correlation of the photon pairs. Compton PET systems, however are promising candidates for this application. We demonstrate the feasibility of a two-component Compton camera system in identifying true coincidences with Monte Carlo simulations. Our study demonstrates the potential of improving signal gain using polarisation, particularly for high photon emission rates. We also demonstrate the ability of the Compton camera at exploiting this polarisation correlation in PET.
authors.affiliation: School of Physics, University of Sydney, NSW, Australia.
authors.forename: A L
authors.initials: AL
authors.lastname: McNamara
authors.forename: M
authors.initials: M
authors.lastname: Toghyani
authors.forename: J E
authors.initials: JE
authors.lastname: Gillam
authors.forename: K
authors.initials: K
authors.lastname: Wu
authors.forename: Z
authors.initials: Z
authors.lastname: Kuncic
mesh_terms: D003198:Computer Simulation; D005240:Feasibility Studies; D007090:Image Interpretation, Computer-Assisted / Q000592:standards*; D015233:Models, Statistical; D009010:Monte Carlo Method; D017785:Photons; D049268:Positron-Emission Tomography / Q000295:instrumentation* / Q000379:methods*