Neuroendocrine neoplasms (NENs) are a heterogeneous group of malignancies which arise from neuroendocrine cells and are divided into well-differentiated neuroendocrine tumors (NETs) and poorly differentiated neuroendocrine carcinomas (NECs). Currently, 18F-FDG-PET is the preferred choice for NECs, whereas 68Ga-DOTA-peptides PET is useful for the characterization of NETs.

The potential of radiomics has already been demonstrated in 18F-FDG-PET, but this is currently lacking for 68Ga-DOTA-peptides PET images. This research line is focused on the development of an accurate and robust segmentation algorithm for NETs and the exploration of potentials and pitfalls associated with a radiomics model on 68Ga-DOTA-TOC PET/CT images.


  • Filippo Molinari (Full Professor)
  • Bruno De Santi (PhD Student)