68Ga-DOTATOC PET/MRI combines the advantages of PET in the acquisition of metabolic-functional information with the high soft-tissue contrast of MRI. SUVs in tumors have been suggested to be a measure of somatostatin receptor expression. A challenge with receptor ligands is that the distribution volume is confined to tissues with tracer uptake, potentially limiting SUV quantification. In this study, various functional 3-dimensional SUV apparent diffusion coefficient (ADC) parameters and arterial tumor enhancement were tested for ability to characterize gastroenteropancreatic (GEP) neuroendocrine tumors (NETs). Methods: For this single-center, cross-sectional study, 22 patients with 24 histologically confirmed GEP NET lesions (15 men and 7 women; median age, 61 y; range, 43-81 y) who underwent hybrid 68Ga-DOTA PET/MRI at 3 T between January 2017 and July 2019 met the eligibility criteria. SUV, tumor-to-background ratio, total functional tumor volume, and mean and minimum ADC were measured on the basis of volumes of interest and examined with receiver-operating-characteristic analysis to determine cutoffs for differentiation between low- and intermediate-grade GEP NETs. The Spearman rank correlation coefficient was used to assess correlations between functional imaging parameters. Results: The ratio of PET-derived SUVmean and diffusion-weighted imaging-derived minimum ADC was introduced as a combined variable to predict tumor grade, outperforming single predictors. On the basis of a threshold ratio of 0.03, tumors could be classified as grade 2 with a sensitivity of 86% and a specificity of 100%. SUV and functional ADCs, as well as arterial contrast enhancement parameters, showed nonsignificant and mostly negligible correlations. Conclusion: Because receptor density and tumor cellularity appear to be independent, potentially complementary phenomena, the combined ratio of PET/MRI and SUVmean/ADCmin may be used as a novel biomarker allowing differentiation between grade 1 and grade 2 GEP NETs.
68Ga-DOTATOC PET/MRI combines the advantages of PET in the acquisition of metabolic-functional information with the high soft-tissue contrast of MRI. SUVs in tumors have been suggested to be a measure of somatostatin receptor expression. A challenge with receptor ligands is that the distribution volume is confined to tissues with tracer uptake, potentially limiting SUV quantification. In this study, various functional 3-dimensional SUV apparent diffusion coefficient (ADC) parameters and arterial tumor enhancement were tested for ability to characterize gastroenteropancreatic (GEP) neuroendocrine tumors (NETs). Methods: For this single-center, cross-sectional study, 22 patients with 24 histologically confirmed GEP NET lesions (15 men and 7 women; median age, 61 y; range, 43-81 y) who underwent hybrid 68Ga-DOTA PET/MRI at 3 T between January 2017 and July 2019 met the eligibility criteria. SUV, tumor-to-background ratio, total functional tumor volume, and mean and minimum ADC were measured on the basis of volumes of interest and examined with receiver-operating-characteristic analysis to determine cutoffs for differentiation between low- and intermediate-grade GEP NETs. The Spearman rank correlation coefficient was used to assess correlations between functional imaging parameters. Results: The ratio of PET-derived SUVmean and diffusion-weighted imaging-derived minimum ADC was introduced as a combined variable to predict tumor grade, outperforming single predictors. On the basis of a threshold ratio of 0.03, tumors could be classified as grade 2 with a sensitivity of 86% and a specificity of 100%. SUV and functional ADCs, as well as arterial contrast enhancement parameters, showed nonsignificant and mostly negligible correlations. Conclusion: Because receptor density and tumor cellularity appear to be independent, potentially complementary phenomena, the combined ratio of PET/MRI and SUVmean/ADCmin may be used as a novel biomarker allowing differentiation between grade 1 and grade 2 GEP NETs.
Authors: Julia Fruehwald-Pallamar; Christian Czerny; Marius E Mayerhoefer; Benjamin S Halpern; Christina Eder-Czembirek; Markus Brunner; Matthias Schuetz; Michael Weber; Laura Fruehwald; Andreas M Herneth Journal: Eur J Nucl Med Mol Imaging Date: 2011-04-05 Impact factor: 9.236
Authors: Lucas Goense; Sophie E Heethuis; Peter S N van Rossum; Francine E M Voncken; Jan J W Lagendijk; Marnix G E H Lam; Chris H Terhaard; Richard van Hillegersberg; Jelle P Ruurda; Stella Mook; Astrid L H M W van Lier; Steven H Lin; Gert J Meijer Journal: Nucl Med Commun Date: 2018-01 Impact factor: 1.690