RESUMO
In our previous studies, we demonstrated that the Compton PET module, a layer structure PET detector with side readout, can provide high performance in terms of spatial/energy/timing resolution, as well as high gamma ray detection efficiency. In this study, we investigate how to translate the high performance of the detector module into good quality reconstructed tomographic images. This study is performed using GATE simulation, as well as with physical experiments. Similar detector geometry is used in the simulation and experiment: two identical 4-layer detector modules are placed with face to face distance of 56 mm. In the simulation study, each layer consists of a 1-mm-pitch pixelated crystal array. In the experimental study, each layer is a monolithic crystal, which is virtually binned into 1 mm2 cells to group single events according to the gamma ray interaction locations. A customized Derenzo phantom was placed between the two detector modules. By rotating the phantom using a motorized rotary stage, data along lines of response (LORs) at different angles were collected for reconstructing the tomographic image. The same reconstruction algorithm was used for both simulation and experimental studies. The results demonstrate that the simulation study could resolve 0.8 mm rods while the experimental study was able to resolve 1.0 mm rods.
RESUMO
PURPOSE: X-PET is a commercial small animal PET scanner incorporating several innovative designs to achieve improved performance. It is employed as a PET subsystem in the FLEX Triumph preclinical PET/CT scanner, the first commercial small animal PET/CT scanner worldwide. The authors report on a novel Monte Carlo (MC) model designed for the evaluation of performance parameters of the X-PET METHODS: The Geant4 Application for Tomographic Emission (GATE) MC code was used as a simulation tool. The authors implemented more accurate modeling of the geometry of detector blocks and associated electronic chains, including dead-time and time-independent parameters, compared to previously presented MC models of the X-PET scanner. Validation of the MC model involved comparison between simulated and measured performance parameters of the X-PET, including spatial resolution, sensitivity, and noise equivalent count rate (NECR). Thereafter, various simulations were performed to assess scanner performance parameters according to NEMA NU 4-2008 standards with the aim to present a reliable Monte Carlo platform for small animal PET scanner design optimization. RESULTS: The average differences between simulated and measured results were 11.2%, 33.3%, and 9.1% for spatial resolution, sensitivity, and NECR, respectively. The average system absolute sensitivity was 2.7%. Furthermore, the peak true count rate, peak NECR, and scatter fraction were 2050 kcps, 1520 kcps, and 4.7%, respectively, for a mouse phantom and 1017 kcps, 469 kcps, and 18.2%, respectively, for a rat phantom. Spatial resolution was also measured in ten different positions at two axial locations. The radial, tangential, and axial FWHM ranged from 1.31 to 1.96 mm, 1.17 to 2.11 mm, and 1.77 to 2.44 mm, respectively, as the radial position varied from 0 to 25 mm at the centre of the axial field-of-view. CONCLUSIONS: The developed MC simulation platform provides a reliable tool for performance evaluation of small animal PET scanners and has the potential to be used in other applications such as detector design optimization, correction of image degrading factors such as randoms, scatter, intercrystal scatter, parallax error, and partial volume effect.