The aim of this study was to develop a Monte-Carlo model that can be used for the optimization of positron emission tomography (PET) procedures and image quality metrics. This model was developed using the Monte Carlo package of Geant4 application for tomographic emission (GATE) and the software for tomographic image reconstruction (STIR) with cluster computing to obtain reconstructed images. The PET scanner used in this study was the General Electric Discovery-ST (US). The GATE model was validated by comparing results obtained in accordance with the National Electrical Manufacturers Association NEMA-NU-2-2001 protocol [Mawlawi et al (2004) and Bettinardi et al (2004)]. All images were reconstructed with the commonly used 2D filtered back projection and the 3D reprojection algorithms. We found that the simulated spatial resolution in terms of full width at half maximum (FWHM) agreed within less than 3.29% in 2D and less than 2.51% in 3D with published data of others, respectively. The 2D values for the sensitivity, scatter fraction and count-rate were found to agree within less than 0.46%, 4.59% and 7.86%, respectively with these published values. Accordingly, our study showed that the corresponding 3D values were found to agree to less than 1.62%, 2.85% and 9.13%, respectively with Mawlawi et al (2004) published values. Sensitivity, which was also estimated without the presence of attenuation material by simulating an ideal source, showed differences between the extrapolated and the ideal source values (with and without attenuation) ranging in 2D from 0.04% to 0.82% (radial location R=0cm) and 0.52% to 0.67% in 3D mode (radial locations R=10cm). The simulated noise equivalent count rate was found to be 94.31kcps in 2D and 66.9kcps in 3D at 70 and 15kBq/mL respectively, compared to 94.08kcps in 2D and 70.88kcps in 3D at 54.6kBq/mL and 14kBq/mL respectively, from the published by others values. The simulated image quality was found in excellent agreement with these published values. In conclusion, our study showed that our Monte Carlo model can be used to assess, optimize, simplify and reduce the simulation time for the quality control procedure of PET scanners. By using this model, sensitivity can be obtained in a more simplified procedure. Reconstructed images by STIR can be also used to obtain radiopharmaceutical distribution of images and direct dose maps, quite useful to nuclear medicine practitioners.