Scatter correction techniques in 3D PET: A Monte Carlo evaluation

In this work, a Monte Carlo software package, PET-EGS, designed to simulate realistic PET clinical studies, was used to assess three different approac hes to scatter correction in 3D PET: analytical (gaussian fitting technique ), experimental (dual energy window technique) and probabilistic (Monte Car lo technique). Phantom and clinical studies were carried out by 3D PET and simulated by PE T-EGS. A clinical study (F-18- FDG brain study) was simulated assuming PET emission/transmission multiple-volume images as a voxelised source object d escribing the distribution of both the radioactivity and attenuation coeffi cients and accounting for out-of-field activity and media. The accuracy of PET-EGS in modelling the physical response of a 3D PET scan ner was assessed by statistical comparison between measured and total (scat ter + unscatter) simulated distributions (probability for the two distribut ions to be the same distribution: p > 0.95). The accuracy of the scatter mo dels, for each scatter correction technique, was evaluated on sinograms by statistical comparison between the estimated and the simulated scatter dist ributions (agreement < 1 sigma). The accuracy of scatter correction was eva luated on sinograms by comparison between scatter corrected and simulated u nscatter distributions, proving a comparable accuracy of all the considered scatter correction techniques for brainlike distributed sources.