Pancreatic Neuroendocrine Neoplasms.
Authors
Affiliations (8)
Affiliations (8)
- Department of Radiology, University of Iowa Health Care, Iowa City, IA, USA,. Electronic address: [email protected].
- Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA,. Electronic address: [email protected].
- Department of Radiology, Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, USA,. Electronic address: [email protected].
- Department of Radiology, University of Colorado, Aurora, CO, USA,. Electronic address: [email protected].
- Abdominal Radiology and Martinos Center for Biomedical Imaging, Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA,. Electronic address: [email protected].
- Department of Radiology, City of Hope National Medical Center, Duarte, CA,. Electronic address: [email protected].
- Department of Radiology, The University of Arizona, Tuscon, AZ, USA,. Electronic address: [email protected].
- Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA,. Electronic address: [email protected].
Abstract
Pancreatic neuroendocrine neoplasms are heterogeneous tumors whose incidence has risen with advances in, and increased use of, cross sectional and endoscopic imaging. They range from well differentiated, often indolent neuroendocrine tumors to aggressive neuroendocrine carcinomas. Most PNENs are non-functional and detected incidentally, whereas functional tumors present with hormone related clinical syndromes. Accurate diagnosis and staging rely on multimodality imaging. Pancreatic protocol CT and MRI remain first-line tools for anatomic assessment, providing information on tumor morphology, vascular involvement, and metastatic disease. MRI, particularly with diffusion weighted and hepatobiliary contrast imaging adds strength for detecting hepatic metastases. Functional imaging with somatostatin receptor (SSTR) PET/CT or PET/MRI is essential for identifying SSTR expressing disease, guiding management, evaluating heterogeneity, and selecting candidates for peptide receptor radionuclide therapy. Dual tracer imaging with SSTR PET and ¹⁸F FDG provides prognostic insight and detects dedifferentiated tumor components. Ongoing challenges include standardized surveillance and response assessment to therapy. Emerging radiomics and artificial intelligence tools may hold promise for improving personalized management strategies.