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.

Figure of image quality and information capacity in digital mammography.

OBJECTIVES: In this work, a simple technique to assess the image quality characteristics of the postprocessed image is developed and an easy to use figure of image quality (FIQ) is introduced. This FIQ characterizes images in terms of resolution and noise. In addition information capacity, defined within the context of Shannon's information theory, was used as an overall image quality index. MATERIALS AND METHODS: A digital mammographic image was postprocessed with three digital filters. Resolution and noise were calculated via the Modulation Transfer Function (MTF), the coefficient of variation, and the figure of image quality. In addition, frequency dependent parameters such as the noise power spectrum (NPS) and noise equivalent quanta (NEQ) were estimated and used to assess information capacity. RESULTS: FIQs for the "raw image" data and the image processed with the "sharpen edges" filter were found 907.3 and 1906.1, correspondingly. The information capacity values were 60.86 × 10(3) and 78.96 × 10(3) bits/mm(2). CONCLUSION: It was found that, after the application of the postprocessing techniques (even commercial nondedicated software) on the raw digital mammograms, MTF, NPS, and NEQ are improved for medium to high spatial frequencies leading to resolving smaller structures in the final image.