Jaroslav Ptáček1, Pavel Karhan2, Petr Fiala3. 1. Department of Medical Physics and Radiation Protection, University Hospital Olomouc, Olomouc, Czech Republic; Clinic of Nuclear Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic. Electronic address: jaroslav.ptacek@fnol.cz. 2. Department of Medical Physics and Radiation Protection, University Hospital Olomouc, Olomouc, Czech Republic; Clinic of Nuclear Medicine, Faculty of Medicine and Dentistry, Palacký University Olomouc, Olomouc, Czech Republic. 3. Department of Medical Physics and Radiation Protection, University Hospital Olomouc, Olomouc, Czech Republic.
Abstract
INTRODUCTION: The aim of this study was to determine the optimal image matrix and half-width of the Gaussian filter after iterative reconstruction of the PET image with point-spread function (PSF) and time-of-flight (TOF) correction, based on measuring the recovery coefficient (RC) curves. The measured RC curves were compared to those from an older system which does not use PSF and TOF corrections. MATERIALS AND METHODS: The measurements were carried out on a NEMA IEC Body Phantom. We measured the RC curves based on SUVmax and SUVA50 in source spheres with different diameters. The change in noise level for different reconstruction parameter settings and the relation between RC curves and the administered activity were also evaluated. RESULTS: With an increasing size of image matrix and reduction in the half-width of the post-reconstruction Gaussian filter, there was a significant increase in image noise and overestimation of the SUV. The local increase in SUV, observed for certain filtrations and objects with a diameter below 13mm, was caused by PSF correction. The decrease in administered activity, while maintaining the same conditions of acquisition and reconstruction, also led to overestimation of readings of the SUV and additionally to deterioration in reproducibility. CONCLUSION: This study proposes a suitable size for the image matrix and filtering for displaying PET and SUV measurements. The benefits were demonstrated as improved image parameters for the newer instrument, these even being found using relatively strong filtration of the reconstructed images.
INTRODUCTION: The aim of this study was to determine the optimal image matrix and half-width of the Gaussian filter after iterative reconstruction of the PET image with point-spread function (PSF) and time-of-flight (TOF) correction, based on measuring the recovery coefficient (RC) curves. The measured RC curves were compared to those from an older system which does not use PSF and TOF corrections. MATERIALS AND METHODS: The measurements were carried out on a NEMA IEC Body Phantom. We measured the RC curves based on SUVmax and SUVA50 in source spheres with different diameters. The change in noise level for different reconstruction parameter settings and the relation between RC curves and the administered activity were also evaluated. RESULTS: With an increasing size of image matrix and reduction in the half-width of the post-reconstruction Gaussian filter, there was a significant increase in image noise and overestimation of the SUV. The local increase in SUV, observed for certain filtrations and objects with a diameter below 13mm, was caused by PSF correction. The decrease in administered activity, while maintaining the same conditions of acquisition and reconstruction, also led to overestimation of readings of the SUV and additionally to deterioration in reproducibility. CONCLUSION: This study proposes a suitable size for the image matrix and filtering for displaying PET and SUV measurements. The benefits were demonstrated as improved image parameters for the newer instrument, these even being found using relatively strong filtration of the reconstructed images.
Authors: Pedro Fragoso Costa; Walter Jentzen; Alissa Brahmer; Ilektra-Antonia Mavroeidi; Fadi Zarrad; Lale Umutlu; Wolfgang P Fendler; Christoph Rischpler; Ken Herrmann; Maurizio Conti; Robert Seifert; Miriam Sraieb; Manuel Weber; David Kersting Journal: BMC Cancer Date: 2022-08-18 Impact factor: 4.638