Mitigating SUV uncertainties using total body PET imaging.

Autor: Smith CLC; Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands. c.l.c.smith@amsterdamumc.nl.; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands. c.l.c.smith@amsterdamumc.nl., Zwezerijnen GJC; Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands.; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands., den Hollander ME; Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands., Weijland J; Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands., Yaqub M; Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands.; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands., Boellaard R; Department of Radiology and Nuclear Medicine, Amsterdam UMC location Vrije Universiteit Amsterdam, De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands.; Cancer Center Amsterdam, Imaging and Biomarkers, Amsterdam, The Netherlands.
Jazyk: angličtina
Zdroj: European journal of nuclear medicine and molecular imaging [Eur J Nucl Med Mol Imaging] 2024 Mar; Vol. 51 (4), pp. 1070-1078. Date of Electronic Publication: 2023 Nov 13.
DOI: 10.1007/s00259-023-06503-x
Abstrakt: Purpose: Standardised uptake values (SUV) are commonly used to quantify 18 F-FDG lesion uptake. However, SUVs may suffer from several uncertainties and errors. Long-axial field-of-view (LAFOV) PET/CT systems might enable image-based quality control (QC) by deriving 18 F-FDG activity and weight from total body (TB) 18 F-FDG PET images. In this study, we aimed to develop these image-based QC to reduce errors and mitigate SUV uncertainties.
Methods: Twenty-five out of 81 patient scans from a LAFOV PET/CT system were used to determine regression fits for deriving of image-derived activity and weight. Thereafter, the regression fits were applied to 56 independent 18 F-FDG PET scans from the same scanner to determine if injected activity and weight could be obtained accurately from TB and half-body (HB) scans. Additionally, we studied the impact of image-based values on the precision of liver SUVmean and lesion SUVpeak. Finally, 20 scans were acquired from a short-axial field-of-view (SAFOV) PET/CT system to determine if the regression fits also applied to HB scans from a SAFOV system.
Results: Both TB and HB 18 F-FDG activity and weight significantly predicted reported injected activity (r = 0.999; r = 0.984) and weight (r = 0.999; r = 0.987), respectively. After applying the regression fits, 18 F-FDG activity and weight were accurately derived within 4.8% and 3.2% from TB scans and within 4.9% and 3.1% from HB, respectively. Image-derived values also mitigated liver and lesion SUV variability compared with reported values. Moreover, 18 F-FDG activity and weight obtained from a SAFOV scanner were derived within 6.7% and 4.5%, respectively.
Conclusion: 18 F-FDG activity and weight can be derived accurately from TB and HB scans, and image-derived values improved SUV precision and corrected for lesion SUV errors. Therefore, image-derived values should be included as QC to generate a more reliable and reproducible quantitative uptake measurement.
(© 2023. The Author(s).)
Databáze: MEDLINE
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