INTRODUCTION: Dynamic (18)F-FDG PET allows the study of glucose distribution in tissues as a function of time and space. Using pharmacokinetics, the temporal uptake pattern of (18)F-FDG may be separated into components reflecting perfusion and metabolism. Bevacizumab is an angiogenesis inhibitor which prevents the growth of new blood vessels, and may potentially lead to normalization of the blood circulation in the tumor. The purpose of the study was to explore the use of dynamic PET as a tool for monitoring treatment effect, reflected by changes in perfusion and metabolism. MATERIALS AND METHODS: Twelve athymic nude mice, bearing the bilateral triple-negative human breast cancer xenograft MAS98.12 were treated with bevacizumab (5 mg/kg i.p.). Dynamic PET data was acquired prior to and 24 and 72 hours after treatment for 1 hour after injection of 10 MBq (18)F-FDG and fitted with a FDG two-tissue compartment model. The changes in the rate constants k1, k3, MRFDG and the vascular fraction νB were assessed. To evaluate the effect of treatment regimes, 30 mice, randomized in 5 groups, received either vehicle (0.9% NaCl), bevacizumab (5 mg/kg i.p.), doxorubicin (8 mg/kg i.v.) or bevacizumab and doxorubicin either together, or doxorubicin 24 hours after bevacizumab treatment. Tumor volume was measured twice a week. RESULTS: The perfusion-related rate parameter k1 and the metabolic rate constant k3 decreased significantly 24 hours after treatment. This decrease was followed by an increase, albeit non-significant, at 72 hours post treatment. Doxorubicin given 24 hours after bevacizumab showed less antitumor effect compared to concomitant treatment. CONCLUSIONS: Dynamic PET can detect changes in tumor perfusion and metabolism following anti-angiogenic therapy in mouse xenograft models. Longitudinal dynamic PET, used to assess the efficacy of anti-angiogenic treatment, can identify the time frame of potential tumor vasculature re-normalization and allow optimal timing of supplementary therapy (radiation or chemotherapy).
INTRODUCTION: Dynamic (18)F-FDG PET allows the study of glucose distribution in tissues as a function of time and space. Using pharmacokinetics, the temporal uptake pattern of (18)F-FDG may be separated into components reflecting perfusion and metabolism. Bevacizumab is an angiogenesis inhibitor which prevents the growth of new blood vessels, and may potentially lead to normalization of the blood circulation in the tumor. The purpose of the study was to explore the use of dynamic PET as a tool for monitoring treatment effect, reflected by changes in perfusion and metabolism. MATERIALS AND METHODS: Twelve athymic nude mice, bearing the bilateral triple-negative humanbreast cancer xenograft MAS98.12 were treated with bevacizumab (5 mg/kg i.p.). Dynamic PET data was acquired prior to and 24 and 72 hours after treatment for 1 hour after injection of 10 MBq (18)F-FDG and fitted with a FDG two-tissue compartment model. The changes in the rate constants k1, k3, MRFDG and the vascular fraction νB were assessed. To evaluate the effect of treatment regimes, 30 mice, randomized in 5 groups, received either vehicle (0.9% NaCl), bevacizumab (5 mg/kg i.p.), doxorubicin (8 mg/kg i.v.) or bevacizumab and doxorubicin either together, or doxorubicin 24 hours after bevacizumab treatment. Tumor volume was measured twice a week. RESULTS: The perfusion-related rate parameter k1 and the metabolic rate constant k3 decreased significantly 24 hours after treatment. This decrease was followed by an increase, albeit non-significant, at 72 hours post treatment. Doxorubicin given 24 hours after bevacizumab showed less antitumor effect compared to concomitant treatment. CONCLUSIONS: Dynamic PET can detect changes in tumor perfusion and metabolism following anti-angiogenic therapy in mouse xenograft models. Longitudinal dynamic PET, used to assess the efficacy of anti-angiogenic treatment, can identify the time frame of potential tumor vasculature re-normalization and allow optimal timing of supplementary therapy (radiation or chemotherapy).
Authors: Andrew B Rosenkrantz; Thomas Koesters; Anne-Kristin Vahle; Kent Friedman; Rachel M Bartlett; Samir S Taneja; Yu-Shin Ding; Jean Logan Journal: Clin Nucl Med Date: 2015-04 Impact factor: 7.794
Authors: Jianhua Zhou; Huaijun Wang; Huiping Zhang; Amelie M Lutz; Lu Tian; Dimitre Hristov; Jürgen K Willmann Journal: Cancer Res Date: 2016-05-20 Impact factor: 12.701
Authors: Ralf S Eschbach; Wolfgang P Fendler; Philipp M Kazmierczak; Marcus Hacker; Axel Rominger; Janette Carlsen; Heidrun Hirner-Eppeneder; Jessica Schuster; Matthias Moser; Lukas Havla; Moritz J Schneider; Michael Ingrisch; Lukas Spaeth; Maximilian F Reiser; Konstantin Nikolaou; Clemens C Cyran Journal: PLoS One Date: 2015-02-10 Impact factor: 3.240