BACKGROUND: Non-invasive visualization of tumor biological and molecular processes of importance to diagnosis and treatment response is likely to be critical in individualized cancer therapy. Since conventional static (18)F-FDG PET with calculation of the semi-quantitative parameter standardized uptake value (SUV) may be subject to many sources of variability, we here present an approach of quantifying the (18)F-FDG uptake by analytic two-tissue compartment modeling, extracting kinetic tumor parameters from dynamic (18)F-FDG PET. Further, we evaluate the potential of such parameters in radiotherapy response assessment. MATERIAL AND METHODS: Male, athymic mice with prostate carcinoma xenografts were subjected to dynamic PET either untreated (n=8) or 24 h post-irradiation (7.5 Gy single dose, n=8). After 10 h of fasting, intravenous bolus injections of 10-15 MBq (18)F-FDG were administered and a 1 h dynamic PET scan was performed. 4D emission data were reconstructed using OSEM-MAP, before remote post-processing. Individual arterial input functions were extracted from the image series. Subsequently, tumor (18)F-FDG uptake was fitted voxel-by-voxel to a compartment model, producing kinetic parameter maps. RESULTS: The kinetic model separated the (18)F-FDG uptake into free and bound tracer and quantified three parameters; forward tracer diffusion (k(1)), backward tracer diffusion (k(2)), and rate of (18)F-FDG phosphorylation, i.e. the glucose metabolism (k(3)). The fitted kinetic model gave a goodness of fit (r(2)) to the observed data ranging from 0.91 to 0.99, and produced parametrical images of all tumors included in the study. Untreated tumors showed homogeneous intra-group median values of all three parameters (k(1), k(2) and k(3)), whereas the parameters significantly increased in the tumors irradiated 24 h prior to (18)F-FDG PET. CONCLUSIONS: This study demonstrates the feasibility of a two-tissue compartment kinetic analysis of dynamic (18)F-FDG PET images. If validated, extracted parametrical maps might contribute to tumor biological characterization and radiotherapy response assessment.
BACKGROUND: Non-invasive visualization of tumor biological and molecular processes of importance to diagnosis and treatment response is likely to be critical in individualized cancer therapy. Since conventional static (18)F-FDG PET with calculation of the semi-quantitative parameter standardized uptake value (SUV) may be subject to many sources of variability, we here present an approach of quantifying the (18)F-FDG uptake by analytic two-tissue compartment modeling, extracting kinetic tumor parameters from dynamic (18)F-FDG PET. Further, we evaluate the potential of such parameters in radiotherapy response assessment. MATERIAL AND METHODS: Male, athymic mice with prostate carcinoma xenografts were subjected to dynamic PET either untreated (n=8) or 24 h post-irradiation (7.5 Gy single dose, n=8). After 10 h of fasting, intravenous bolus injections of 10-15 MBq (18)F-FDG were administered and a 1 h dynamic PET scan was performed. 4D emission data were reconstructed using OSEM-MAP, before remote post-processing. Individual arterial input functions were extracted from the image series. Subsequently, tumor (18)F-FDG uptake was fitted voxel-by-voxel to a compartment model, producing kinetic parameter maps. RESULTS: The kinetic model separated the (18)F-FDG uptake into free and bound tracer and quantified three parameters; forward tracer diffusion (k(1)), backward tracer diffusion (k(2)), and rate of (18)F-FDG phosphorylation, i.e. the glucose metabolism (k(3)). The fitted kinetic model gave a goodness of fit (r(2)) to the observed data ranging from 0.91 to 0.99, and produced parametrical images of all tumors included in the study. Untreated tumors showed homogeneous intra-group median values of all three parameters (k(1), k(2) and k(3)), whereas the parameters significantly increased in the tumors irradiated 24 h prior to (18)F-FDG PET. CONCLUSIONS: This study demonstrates the feasibility of a two-tissue compartment kinetic analysis of dynamic (18)F-FDG PET images. If validated, extracted parametrical maps might contribute to tumor biological characterization and radiotherapy response assessment.
Authors: Alexandr Kristian; Line B Nilsen; Kathrine Røe; Mona-Elisabeth Revheim; Olav Engebråten; Gunhild M Mælandsmo; Ruth Holm; Eirik Malinen; Therese Seierstad Journal: Nucl Med Mol Imaging Date: 2013-06-21
Authors: Natalia Arteaga-Marrero; Cecilie Brekke Rygh; Jose F Mainou-Gomez; Tom C H Adamsen; Nataliya Lutay; Rolf K Reed; Dag R Olsen Journal: J Transl Med Date: 2015-12-18 Impact factor: 5.531
Authors: Moisés Mera Iglesias; David Aramburu Núñez; José Luis Del Olmo Claudio; Antonio López Medina; Iago Landesa-Vázquez; Francisco Salvador Gómez; Brandon Driscoll; Catherine Coolens; José L Alba Castro; Victor Muñoz Journal: Comput Math Methods Med Date: 2015-02-19 Impact factor: 2.238