PET-CT imaging of neuroendocrine tumors - In relationship to treatment, quality of life and artificial intelligence

Neuroendocrine tumors (NET) are often slow growing and patients can survive for long. Generally NET overexpresses somatostatin receptors which can be targeted for both imaging and treatment. Theragnostic aspects of NET with imaging of somatostatin receptors through positron emitting tomography - computed tomography (PET-CT) and treatment targeting somatostatin receptors is an evolving landscape were more knowledge are needed. Further could automatic quantification of NET with artificial intelligence (AI) increase the impact of PET-CT for prognostication, predication and evaluation of response to therapy.

The overall aim of this thesis is to increase the knowledge about the uptake of radiolabeled somatostatin analogs with 68Ga-DOTA-TATE/TOC in NET and to develop an automatic method for quantification of NET with AI.