Detective quantum efficiency (DQE) in PET scanners: A simulation study.

The aim of the present study is to introduce the detective quantum efficiency (DQE) for the image quality assessment of positron emission tomography (PET) scanners. For this purpose, a thin layer chromatography (TLC) plane source was simulated using a previously validated, scanner and source geometry, Monte Carlo (MC) model. The model was developed with the Geant4 application for tomographic emission (GATE) MC package and reconstructed images obtained with the software for tomographic image reconstruction (STIR), with cluster computing. The GE Discovery ST PET scanner was simulated by using a previously validated code. A plane source consisting of a TLC plate, was simulated by a layer of silica gel on aluminum (Al) foil substrate, immersed in 18F-FDG bath solution (1MBq). Image quality was assessed in terms of the modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) in order to obtain the detective quantum efficiency (DQE). MTF curves were estimated from transverse reconstructed images of the plane source, whereas the NNPS data were estimated from the corresponding coronal images. Images were reconstructed by the maximum likelihood estimation ordered subsets maximum a posteriori one step late (MLE)-OS-MAP-OSL algorithm, by using various subsets 1-21) and iterations 1-20). MTF values were found to increase up to the 12th iteration whereas remain almost constant thereafter. However, the range of the increase in the MTF is limited as the number of subsets increases. The noise levels were found to increase with the corresponding increase of both the number of iterations and subsets. The maximum NNPS value (0.517mm2) was observed for the 420 MLEM-equivalent iterations reconstructed image at 0cycles/mm. Finally DQE values were found to increase for spatial frequencies up to 0.038cycles/mm and to decrease thereafter with the corresponding increase in both number of iterations and subsets. The maximum DQE value (0.48 at 0.038cycles/mm) was obtained for the 8 MLEM-equivalent iterations image. The simulated PET evaluation method based on the TLC plane source can be useful in the quality control and in the further development of PET and SPECT scanners though GATE simulations.

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

OBJECTIVE: 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. METHODS AND MATERIALS: 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. RESULTS: 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. CONCLUSION: 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.

A new PET resolution measurement method through Monte-Carlo simulations.

OBJECTIVE: The aim of this study was to propose a novel method for image quality assessment in PET scanners through estimation of the modulation transfer function (MTF) of a plane source. The simulation was implemented using the previously validated Monte-Carlo model. A comparison of the proposed method with the more traditional technique, based on a line source, was also performed. MATERIALS AND METHODS: The Geant4 application for tomographic emission (GATE) Monte-Carlo package was used for model development, and reconstructed images were obtained using software for tomographic image reconstruction (STIR) with cluster computing. A novel plane source consisting of a radioactive ((18)F-fluorodeoxyglucose) thin-layer chromatography plate was simulated (total source activity: 44.4 MBq) to assess image quality through the MTF. All images were reconstructed with the three-dimensional filtered back projection (FBP3DRP) and ordered-subsets expectation maximization (OSEM) reprojection algorithms. RESULTS: The MTFs obtained using ordered-subsets expectation maximization show, in all cases, that higher frequencies are preserved compared with those obtained using the FBP3DRP. In addition, the plane source method is less prone to noise than the conventional line source method (SD=0.0031 and 0.0203, respectively). CONCLUSION: The thin-layer chromatography-based plane source presented requires materials commonly found in a clinical environment and could be used to assess image quality in nuclear medicine departments and to further develop PET and single-photon emission computed tomography scanners through Monte-Carlo simulations.

Towards the optimization of nuclear medicine procedures for better spatial resolution, sensitivity, scan image quality and quantitation measurements by using a new Monte Carlo model featuring PET imaging.

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.