Abstract
Dynamic positron emission tomography (PET) imaging is a standard art of molecular imaging technology for visualization and quantitative assessment of biochemical and physiopathological activity at cellular and molecular levels in humans and laboratory animals. Tracer kinetic modeling approach developed and validated in last decades is now widely used to extract parameters from dynamic PET data. In the study of neuroendocrine tumors (NETs), the kinetic parameters such as tracer uptake rate constant Ki estimated from dynamic PET with FDA approved 18 F-FDG and 68 Ga-DOTATATE tracers are suggested to improve the accuracy of NET detection, characterization, grading, staging, and predicting/monitoring NET responses to treatment including peptide receptor radionuclide therapy. The whole-body parametric Ki images generated from shortened dynamic PET using robust parametric imaging algorithm such as machine learning-based approach is potential for clinical and research in NET. In addition, dynamic PET can provide valuable information, such as biological distribution and radiation dose in tissue, in the study of new radioactive tracer in NET. It is expected that quantitative dynamic PET imaging in NET will be widely used for the imaging of somatostatin receptors and evaluation of therapeutic drugs and probes.