Background: Total-body PET scanners with axial field of views (FOVs) longer than 1 m enable new applications to study multiple organs (e.g., the brain-gut-axis) simultaneously. As the spatial resolution and the associated partial volume effect (PVE) can vary significantly along the FOV, detailed knowledge of the contrast recovery coefficients (CRCs) is a prerequisite for image analysis and interpretation of quantitative results. The aim of this study was to determine the CRCs, as well as voxel noise, for multiple isotopes throughout the 1.06 m axial FOV of the Biograph Vision Quadra PET/CT system (Siemens Healthineers).
Materials And Methods: Cylindrical phantoms equipped with three different sphere sizes (inner diameters 7.86 mm, 28 and 37 mm) were utilized for the PVE evaluation. The 7.86 mm sphere was filled with F-18 (8:1 and 4:1), Ga-68 (8:1) and Zr-89 (8:1). The 28 mm and 37 mm spheres were filled with F-18 (8:1). Background concentration in the respective phantoms was of ~ 3 kBq/ml. The phantoms were measured at multiple positions in the FOV (axial: 0, 10, 20, 30, 40 and 50 cm, transaxial: 0, 10, 20 cm). The data were reconstructed with the standard clinical protocol, including PSF correction and TOF information with up to 10 iterations for maximum ring differences (MRDs) of 85 and 322; CRCs, as well as voxel noise levels, were determined for each position.
Results: F-18 CRCs (SBR 8:1 and 4:1) of the 7.86 mm sphere decreased up to 18% from the center FOV (cFOV) toward the transaxial edge and increased up to 17% toward the axial edge. Noise levels were below 15% for the default clinical reconstruction parameters. The larger spheres exhibited a similar pattern. Zr-89 revealed ~ 10% lower CRCs than F-18 but larger noise (9.1% (F-18), 19.1% (Zr-89); iteration 4, cFOV) for the default reconstruction. Zr-89 noise levels in the cFOV significantly decreased (~ 28%) when reconstructing the data with MRD322 compared with MRD85 along with a slight decrease in CRC values. Ga-68 exhibited the lowest CRCs for the three isotopes and noise characteristics comparable to those of F-18.
Conclusions: Distinct differences in the PVE within the FOV were detected for clinically relevant isotopes F-18, Ga-68 and Zr-89, as well as for different sphere sizes. Depending on the positions inside the FOV, the sphere-to-background ratios, count statistics and isotope used, this can result in an up to 50% difference between CRCs. Hence, these changes in PVE can significantly affect the quantitative analysis of patient data. MRD322 resulted in slightly lower CRC values, especially in the center FOV, whereas the voxel noise significantly decreased compared with MRD85.
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http://dx.doi.org/10.1186/s40658-023-00554-7 | DOI Listing |
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Accurate 3D point cloud object detection is crucially important for autonomous driving vehicles. The sparsity of point clouds in 3D scenes, especially for smaller targets like pedestrians and bicycles that contain fewer points, makes detection particularly challenging. To solve this problem, we propose a single-stage voxel-based 3D object detection method, namely PFENet.
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