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Purpose: The effects of regularizing priors on the maximum likelihood (ML) reconstruction of activity patterns in Positron Emission Tomography (PET) were assessed., Methods: Two edge-preserving priors (one originally proposed by Nuyts et al. and nowadays implemented and commercialized by General Electric Medical Systems as Q.Clear software, and a second one originally proposed by Rapisarda et al. and our group) were assessed and compared to a standard Ordered Subset (OS)-ML reconstruction, assumed as reference. The main difference between the two priors is that Nuyts prior (NY-p) penalizes relative voxel differences while Rapisarda prior (RP-p) absolute ones. Prior parameters were selected by imposing a reference noise texture inside uniform regions with activity comparable to that measured in 18 F-FluoroDeoxyGlucose (FDG) patient livers overall the field of view. Comparisons were then made: (a) on phantom data in terms of sphere recovery coefficients, ability to correctly reconstruct uniform irregularly shaped objects and heterogeneous patterns in patient backgrounds; (b) on patient data in terms of lesion detectability and image quality., Results: On phantoms, both priors succeeded in improving all the assessed features with respect to standard OS-ML reconstruction, mainly thanks to the better signal convergence and to the noise breakup control. On 10 mm spheres, an average recovery coefficient augment of 9% (NY-p) and 34% (RP-p) was obtained; homogeneity of uniform activity objects augmented of 4% (NY-p) and 11% (RP-p); accuracy in reconstructing heterogeneous lesions improved on average of 5% (NY-p) and 15% (RP-p). On patients, lesion detectability resulted improved (on 27 of 30 lesions), regardless of lesion anatomical districts and position in the scanner field of view. NY-p provides a spatial resolution and a noise texture more uniform in the field of view and an image quality similar to standard OS-ML. RP-p has instead a behavior more dependent on the local counting statistics that imposes a trade-off between spatial resolution uniformity and noise texture homogeneity., Conclusions: The assessed regularizing priors improve PET uptake pattern reconstruction accuracy. Therefore, they should be considered both for oncological lesion detection and uptake spatial distribution assessment. Pitfalls and open challenges are also discussed., (© 2017 American Association of Physicists in Medicine.)

Purpose: The aim of this work was the assessment of the physical performance of the new hybrid PET∕CT system: Discovery-690., Methods: The Discovery-690 combines a lutetium-yttrium-orthosilicate (LYSO) block detector designed PET tomograph with a 64-slice CT scanner. The system is further characterized by a dedicated powerful computing platform implementing fully 3D-PET iterative reconstruction algorithms. These algorithms can account for time of flight (TOF) information and∕or a 3D model of the PET point spread function (PSF). PET physical performance was measured following NEMA NU-2-2007 procedures. Furthermore, specific tests were used: (i) to measure the energy and timing resolution of the PET system and (ii) to evaluate image quality, by using phantoms representing different clinical conditions (e.g., brain and whole body). Data processing and reconstructions were performed as required by standard procedures. Further reconstructions were carried out to evaluate the performance of the new reconstruction algorithms. In particular, four algorithms were considered for the reconstruction of the PET data: (i) HD = standard configuration, without TOF and PSF, (ii) TOF = HD + TOF, (iii) PSF = HD + PSF, and (iv) TOFPSF = HD + TOF + PSF., Results: The transverse (axial) spatial resolution values were 4.70 (4.74) mm and 5.06 (5.55) mm at 1 cm and 10 cm off axis, respectively. Sensitivity (average between 0 and 10 cm) was 7.5 cps∕kBq. The noise equivalent count rate (NECR) peak was 139.1 kcps at 29.0 kBq∕ml. The scatter fraction at the NECR peak was 37%. The correction accuracy for the dead time losses and random event counts had a maximum absolute error below the NECR peak of 2.09%. The average energy and timing resolution were 12.4% and 544.3 ps, respectively. PET image quality was evaluated with the NEMA IEC Body phantom by using four reconstruction algorithms (HD, TOF, PSF, and TOFPSF), as previously described. The hot contrast (after 3 iterations and for a lesion∕background activity ratio of 4:1) for the spheres of 10, 13, 17, and 22 mm was (HD) 29.8, 45.4, 55.4, and 68.1%; (TOF) 39.9, 53.5, 62.7, and 72.2%; (PSF) 28.3, 47.3, 60.4, and 71.8%; (TOFPSF) 43.8, 62.9, 70.6, and 76.4%. The cold contrast for the spheres of 28 and 37 mm was (HD) 62.4 and 65.2%; (TOF) 77.1 and 81.4%; (PSF) 62.0 and 65.2%; (TOFPSF) 77.3 and 81.6%. Similar hot and cold contrast trends were found during the analyses of other phantoms representing different clinical conditions (brain and whole body). Nevertheless, the authors observed a predominant role of either TOF or PSF, depending on the specific characteristics and dimensions of the phantoms., Conclusions: Discovery-690 shows very good PET physical performance for all the standard NEMA NU-2-2007 measurements. Furthermore, the new reconstruction algorithms available for PET data (TOF and PSF) allow further improvements of the D-690 image quality performance both qualitatively and quantitatively.

Purpose: The aim of this study was to assess the performance measurements of the new PET/CT system Discovery-600 (D-600, GEMS, Milwaukee, WI)., Methods: Performance measures were obtained with the National Electrical Manufacturers Association (NEMA) NU 2-2007 procedures., Results: The transverse (axial) spatial resolution FWHMs were 4.9 (5.6) mm and 5.6 (6.4) mm at 1 and 10 cm off axis, respectively. The sensitivity (average at 0 and 10 cm) was 9.6 cps/kBq. The scatter fraction was 36.6% (low energy threshold: 425 keV). The NEC peak rate (k=1) was 75.2 kcps at 12.9 kBq/cc. The hot contrasts for 10, 13, 17, and 22 mm spheres were 41%, 51%, 62%, and 73% and the cold contrasts for 28 and 37 mm spheres were 68% and 72%., Conclusions: The Discovery-600 has good performance for the NEMA NU 2-2007 parameters, particularly in improved sensitivity compared to the scanners of the same Discovery family, D-ST and D-STE.

Purpose: In this study we evaluate the number of data partitions (gates) needed to sort 4D-PET and 4D-CT data to obtain motion-free images as a function of lesion size and motion displacement., Methods: Plexiglas spheres of various diameters (8, 10, 15, 20, and 25 mm) were filled with a radioactive solution of water and 18F. A PET/CT study was acquired for each sphere in a rest condition to reconstruct a motion-free image as a reference in terms of radioactivity concentration and spatial distribution. Each sphere was then moved sinusoidally in the superior-inferior direction over different motion displacements (5, 10, 15, 20, and 25 mm) with a periodic motion of 4 s. During motion a 4D-CT scan followed by a 4D-PET scan were acquired. Each set of 4D-CT and 4D-PET data was retrospectively sorted to generate one, two, four, six, eight, ten, and 12 partitions (gates) over the whole cycle of motion. 4D-PET gates were reconstructed by using the corresponding 4D-CT gates for attenuation correction, while PET data acquired, with the sphere in the rest condition were corrected for attenuation by using the corresponding CT image set. For each series of PET images, data analysis was performed by measuring (1) the maximum value of the radioactivity concentration (RACmax) in a VOI encompassing the radioactivity distribution over the volume of motion and (2) the axial-profile of the radioactivity distribution (Ax-p)., Results: The results show that radioactivity concentration is strongly underestimated due to motion in most conditions considered in this study. In particular, the underestimation of RACmax for the smallest sphere varied from -10.6% to -66.3% with motion displacements ranging from 5 to 25 mm. For the largest sphere, errors ranged from -1.4% to -26.7%. The 4D-PET/CT methodology allows motion-free or nearly motion-free images to be obtained. It also permits both radioactivity concentration (RACmax) and Ax-p to be recovered with residual differences with respect to the rest condition, depending on the number of partitions used to process the data. Within the limitation of the regular sinusoidal motion, used to simulate a general breathing condition, a scheme describing the number of partitions needed to obtain nearly motion-free images with Ax-p differences of around 10% with respect to the rest data is presented as a function of the lesion size and motion displacement. Such a scheme is proposed to guide the setup of a 4D-PET/CT acquisition and processing protocol for clinical applications., Conclusions: By using the 4D-PET/CT acquisition technique, it is possible to compensate for the degradation effect of lesion motion on the reconstructed PET images.

In this study we evaluated pre- (PR-R) and post-reconstruction (PO-R) count-dependent Metz filters for PET brain studies in order to increase signal-to-noise ratio. A set of studies using a 3D Hoffman brain phantom was performed at various count levels, and a reference image set was created from extremely high count images. Several combinations of PR-R and PO-R filtering were considered to find the optimal means of processing, including: Hann filter alone; PR-R Metz filter without or with a PO-R low pass filter; and PO-R Metz filter without or with a PR-R low pass filter. A formula was established to correlate the optimal PO-R Metz filter order with the net counts. Resolution [full width at half-maximum (FWHM) and fill width at tenth maximum (FWTM)], normalized residual mean square differences (NRMSD) between the ideal and the processed images, noise reduction and contrast were used as parameters for the evaluation of the different filter combinations. Resolution is decreased by all filter combinations that can effectively control noise; however, FWTM increases less than FWHM. NRMSD indicates that the use of Hann and (optimal) PO-R Metz filter is the most powerful combination from among those tested. A close correlation (r = 0.969) was found between the net counts and the optimal order of the PO-R Metz filter. At the count levels of clinical studies the PO-R Metz filter was found to control noise much more effectively and enhance the contrast when compared to the routinely used Hann filter alone, and produced images of better quality.