BACKGROUND: Accuracy in the quantification of the SUV is a critical point in PET because proper quantification of tumor uptake is essential for therapy monitoring and prognosis evaluation. Recent advances such as time-of-flight (TOF) and point-spread-function (PSF) reconstructions have dramatically improved detectability. However, first experiences with these techniques have shown a consistent tendency to measure markedly high SUV values, bewildering nuclear medicine physicians and referring clinicians. PURPOSE: We investigated different reconstruction and quantification procedures to determine the optimum protocol for an accurate SUV quantification in last generation PET scanners. METHODS: Both phantom and patient images were evaluated. A complete set of experiments was performed using a body phantom containing 6 spheres with different background levels and contrasts. Whole-body FDG PET/CT of 20 patients with breast and lung cancer was evaluated. One hundred five foci were identified by 2 experienced nuclear medicine physicians.Each acquisition was reconstructed both with classical and advanced (TOF, PSF) reconstruction techniques. Each sphere and each in vivo lesion was quantified with different parameters as follows: SUV(max), SUV(mean), and SUV(50) (mean within a 50% isocontour). RESULTS: This study has confirmed that quantification with SUV(max) produces important overestimation of metabolism in new generation PET scanners. This is a relevant result because, currently, SUV(max) is the standard parameter for quantification. SUV(50) has been shown as the best alternative, especially when applied to images reconstructed with PSF + TOF. CONCLUSIONS: SUV(50) provides accurate quantification and should replace SUV(max) in PET tomographs incorporating advanced reconstruction techniques. PSF + TOF reconstruction is the optimum for both detection and accurate quantification.
BACKGROUND: Accuracy in the quantification of the SUV is a critical point in PET because proper quantification of tumor uptake is essential for therapy monitoring and prognosis evaluation. Recent advances such as time-of-flight (TOF) and point-spread-function (PSF) reconstructions have dramatically improved detectability. However, first experiences with these techniques have shown a consistent tendency to measure markedly high SUV values, bewildering nuclear medicine physicians and referring clinicians. PURPOSE: We investigated different reconstruction and quantification procedures to determine the optimum protocol for an accurate SUV quantification in last generation PET scanners. METHODS: Both phantom and patient images were evaluated. A complete set of experiments was performed using a body phantom containing 6 spheres with different background levels and contrasts. Whole-body FDG PET/CT of 20 patients with breast and lung cancer was evaluated. One hundred five foci were identified by 2 experienced nuclear medicine physicians.Each acquisition was reconstructed both with classical and advanced (TOF, PSF) reconstruction techniques. Each sphere and each in vivo lesion was quantified with different parameters as follows: SUV(max), SUV(mean), and SUV(50) (mean within a 50% isocontour). RESULTS: This study has confirmed that quantification with SUV(max) produces important overestimation of metabolism in new generation PET scanners. This is a relevant result because, currently, SUV(max) is the standard parameter for quantification. SUV(50) has been shown as the best alternative, especially when applied to images reconstructed with PSF + TOF. CONCLUSIONS: SUV(50) provides accurate quantification and should replace SUV(max) in PET tomographs incorporating advanced reconstruction techniques. PSF + TOF reconstruction is the optimum for both detection and accurate quantification.
Authors: Maria J Garcia-Velloso; Maria J Ribelles; Macarena Rodriguez; Alejandro Fernandez-Montero; Lidia Sancho; Elena Prieto; Marta Santisteban; Natalia Rodriguez-Spiteri; Miguel A Idoate; Fernando Martinez-Regueira; Arlette Elizalde; Luis J Pina Journal: Eur Radiol Date: 2016-12-21 Impact factor: 5.315
Authors: Johannes Schwenck; Hansjoerg Rempp; Gerald Reischl; Stephan Kruck; Arnulf Stenzl; Konstantin Nikolaou; Christina Pfannenberg; Christian la Fougère Journal: Eur J Nucl Med Mol Imaging Date: 2016-08-24 Impact factor: 9.236
Authors: Nicolas Aide; Charline Lasnon; Adam Kesner; Craig S Levin; Irene Buvat; Andrei Iagaru; Ken Hermann; Ramsey D Badawi; Simon R Cherry; Kevin M Bradley; Daniel R McGowan Journal: Eur J Nucl Med Mol Imaging Date: 2021-06-03 Impact factor: 9.236