Mohammad Amin Mosleh-Shirazi1,2, Zahra Nasiri-Feshani3, Pardis Ghafarian4,5, Mehrosadat Alavi1,6, Gholamhasan Haddadi1,7, Ali Ketabi8,9. 1. Ionizing and Non-Ionizing Radiation Protection Research Centre, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran. 2. Physics Unit, Department of Radio-oncology, Shiraz University of Medical Sciences, Shiraz, Iran. 3. Department of Radiology, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran. nz551@yahoo.com. 4. Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran. 5. PET/CT and Cyclotron Center, Masih Daneshvari Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 6. Department of Nuclear Medicine, Shiraz University of Medical Sciences, Shiraz, Iran. 7. Department of Radiology, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran. 8. Ionizing and Non-Ionizing Radiation Protection Research Centre, School of Paramedical Sciences, Shiraz University of Medical Sciences, Shiraz, Iran. ketabi110@gmail.com. 9. Physics Unit, Department of Radio-oncology, Shiraz University of Medical Sciences, Shiraz, Iran. ketabi110@gmail.com.
Abstract
PURPOSE: SUVpeak is a recommended quantification metric except for small lesions. We aimed to assess the averaged standard uptake value (SUVN) as an alternative to SUVpeak for small-lesion quantification. MATERIALS AND METHODS: NEMA-like phantom images were reconstructed using OSEM, OSEM + PSF, OSEM + TOF and OSEM + TOF + PSF with two post-smoothing Gaussian filters for different background activity levels. SUVmax, SUVN (N = 5, 10, 15, 20, 25, 30, 35 or 40 hottest voxels), and SUVpeak, relative percent error, contrast recovery, and volume recovery coefficients were quantified and assessed. RESULTS: SUVN did not have the limitations of SUVpeak for smaller lesions. In the smallest insert at 2.68 kBq/ml, optimum N values for OSEM, OSEM + PSF, OSEM + TOF and OSEM + TOF + PSF were 10, 5, 15, and 10 for SUVN, respectively. The same N values were obtained for metabolic tumor volumes (MTVs) for all reconstruction algorithms. At 5.30 kBq/ml, N = 5 was optimum for SUVN and MTVs. For the larger inserts, the optimum N increased and tended towards the maximum (similar to SUVpeak). CONCLUSIONS: SUVN is more accurate than SUVmax or SUVpeak for small lesions, while being as accurate in larger ones. This harmonizing capacity of SUVN can be beneficial for the quantitative analysis of small tumor volumes.
PURPOSE: SUVpeak is a recommended quantification metric except for small lesions. We aimed to assess the averaged standard uptake value (SUVN) as an alternative to SUVpeak for small-lesion quantification. MATERIALS AND METHODS: NEMA-like phantom images were reconstructed using OSEM, OSEM + PSF, OSEM + TOF and OSEM + TOF + PSF with two post-smoothing Gaussian filters for different background activity levels. SUVmax, SUVN (N = 5, 10, 15, 20, 25, 30, 35 or 40 hottest voxels), and SUVpeak, relative percent error, contrast recovery, and volume recovery coefficients were quantified and assessed. RESULTS: SUVN did not have the limitations of SUVpeak for smaller lesions. In the smallest insert at 2.68 kBq/ml, optimum N values for OSEM, OSEM + PSF, OSEM + TOF and OSEM + TOF + PSF were 10, 5, 15, and 10 for SUVN, respectively. The same N values were obtained for metabolic tumor volumes (MTVs) for all reconstruction algorithms. At 5.30 kBq/ml, N = 5 was optimum for SUVN and MTVs. For the larger inserts, the optimum N increased and tended towards the maximum (similar to SUVpeak). CONCLUSIONS: SUVN is more accurate than SUVmax or SUVpeak for small lesions, while being as accurate in larger ones. This harmonizing capacity of SUVN can be beneficial for the quantitative analysis of small tumor volumes.
Entities:
Keywords:
FDG-PET/CT; Image reconstruction; SUV; Small lesions; Uptake quantification
Authors: Charlotte S van der Vos; Daniëlle Koopman; Sjoerd Rijnsdorp; Albert J Arends; Ronald Boellaard; Jorn A van Dalen; Mark Lubberink; Antoon T M Willemsen; Eric P Visser Journal: Eur J Nucl Med Mol Imaging Date: 2017-07-08 Impact factor: 9.236