PURPOSE: Every PET scanner suffers of the partial volume effect (PVE), that is a loss of contrast in small lesions causing a worsening in standardized uptake value (SUV) accuracy, that is critical if quantitative PET/CT imaging is used for diagnosis and therapy. METHODS: In order to quantify PVE and optimize our clinical protocols to minimize this effect in a last generation PET/CT scanner, we utilized a cylindrical phantom equipped with ten mini- and micro-volume hollow spheres. The lesion detectability and the SUV accuracy were evaluated at a fixed spheres to background intrinsic contrast (activity concentration ratio 8:1) but in different scan conditions: (a) acquisition modality (3D vs. 2D), (b) number of subset per iteration, (c) type of post-reconstruction filter and (d) activity concentration (i.e. total counts). Also the effect of different absorber thickness was evaluated. RESULTS: Small lesion detectability resulted better in images acquired in 3D mode rather than 2D, mainly because of the lower noise produced by the fully-3D algorithm. The number of reconstruction iterations and the post-processing filter used affected both the contrast underestimation and the spatial resolution. Decreasing the (18)F activity injected according to the low-dose protocol, the small lesions could be distinguished from the background down to a diameter of 6.2mm and the SUV accuracy did not deteriorate. Adding absorber thickness around the phantom, the image noise slightly increased while SUV accuracy did not change. CONCLUSIONS: The hybrid PET/CT scanner we evaluated showed good performances, mainly in 3D acquisition modality. The phantom measurements showed that the most appropriate reconstruction protocol derived from a compromise between the contrast accuracy and the noise variance in PET images. The low-dose protocol clinically used demonstrated no loss in SUV accuracy and an adequate lesion detectability for lesions down to 6.2mm in diameter.
PURPOSE: Every PET scanner suffers of the partial volume effect (PVE), that is a loss of contrast in small lesions causing a worsening in standardized uptake value (SUV) accuracy, that is critical if quantitative PET/CT imaging is used for diagnosis and therapy. METHODS: In order to quantify PVE and optimize our clinical protocols to minimize this effect in a last generation PET/CT scanner, we utilized a cylindrical phantom equipped with ten mini- and micro-volume hollow spheres. The lesion detectability and the SUV accuracy were evaluated at a fixed spheres to background intrinsic contrast (activity concentration ratio 8:1) but in different scan conditions: (a) acquisition modality (3D vs. 2D), (b) number of subset per iteration, (c) type of post-reconstruction filter and (d) activity concentration (i.e. total counts). Also the effect of different absorber thickness was evaluated. RESULTS: Small lesion detectability resulted better in images acquired in 3D mode rather than 2D, mainly because of the lower noise produced by the fully-3D algorithm. The number of reconstruction iterations and the post-processing filter used affected both the contrast underestimation and the spatial resolution. Decreasing the (18)F activity injected according to the low-dose protocol, the small lesions could be distinguished from the background down to a diameter of 6.2mm and the SUV accuracy did not deteriorate. Adding absorber thickness around the phantom, the image noise slightly increased while SUV accuracy did not change. CONCLUSIONS: The hybrid PET/CT scanner we evaluated showed good performances, mainly in 3D acquisition modality. The phantom measurements showed that the most appropriate reconstruction protocol derived from a compromise between the contrast accuracy and the noise variance in PET images. The low-dose protocol clinically used demonstrated no loss in SUV accuracy and an adequate lesion detectability for lesions down to 6.2mm in diameter.
Authors: Anna Margherita Maffione; Alice Ferretti; Gaia Grassetto; Elena Bellan; Carlo Capirci; Sotirios Chondrogiannis; Marcello Gava; Maria Cristina Marzola; Lucia Rampin; Claudia Bondesan; Patrick M Colletti; Domenico Rubello Journal: Eur J Nucl Med Mol Imaging Date: 2013-02-16 Impact factor: 9.236
Authors: Yaser H Gholami; Hushan Yuan; Moses Q Wilks; Lee Josephson; Georges El Fakhri; Marc D Normandin; Zdenka Kuncic Journal: Sci Rep Date: 2020-11-20 Impact factor: 4.379