A novel method for the optimization of positron emission tomography scanners imaging performance.

Abstract

The aim of the present study was to propose a comprehensive method for positron emission tomography (PET) scanners image quality assessment, by simulation of a thin layer chromatography (TLC) flood source with a previously validated Monte Carlo model. We used the GATE Monte Carlo package (GEANT4 application for tomographic emission) and the reconstructed images were obtained using the software for tomographic image reconstruction (STIR), with cluster computing. The PET scanner used in this simulation study was the General Electric Discovery-ST (USA). The plane source that was used for the image quality assessment was a TLC plate, consisting of an aluminum (Al) foil, coated with a thin layer of silica and immersed in fluorodeoxyglucose (18F-FDG) bath solution (1 MBq). The influence of different scintillating crystals on PET scanner's image quality, in terms of the modulation transfer function (MTF), the normalized noise power spectrum (NNPS) and the detective quantum efficiency (DQE), were also investigated. Modulation transfer function was estimated from transverse slices of the plane source, whereas the NNPS from the corresponding coronal slices. Images were reconstructed by the commonly used 2D filtered back projection (FBP2D), the Kinahan and Rogers FPB3DRP and the maximum likelihood estimation (MLE)-OSMAPOSL algorithms. Images obtained using the OSMAPOSL algorithm were assessed by using 15 subsets and 3 iterations. The PET scanner configuration, equipped with LuAP crystals, exhibited the optimum MTF values in both 2D and 3D FBP image reconstruction, whereas the corresponding configuration with BGO crystals exhibited the optimum MTF values after the iterative algorithm. The scanner equipped with the BGO crystals was also found to exhibit overall the lowest noise levels and the highest DQE values after algorithms. These finding indicate that the GE Discovery ST PET scanner exhibits the optimum image quality parameters, in terms of MTF, NNPS and DQE, with BGO scintillating crystals. Our new method showed that the imaging performance of PET scanners can be fully characterized and further improved by investigation of the imaging chain components through Monte Carlo methods. To this aim, a TLC based plane source was used during the simulation, in order to assess the impact of the scintillating crystal material on PET image quality, with the application of a previously validated Monte Carlo model. The aforementioned plane source can be also useful for the further development of PET and SPET scanners through GATE simulations, for clinical applications.