Cystic pancreatic neuroendocrine tumors: a practical imaging approach.
Authors
Affiliations (4)
Affiliations (4)
- Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil.
- Beneficência Portuguesa de São Paulo, São Paulo, Brazil.
- FCM - UNICAMP, Campinas, Brazil.
- FCM - UNICAMP, Campinas, Brazil. [email protected].
Abstract
Cystic pancreatic neuroendocrine tumors (c-PanNETs) are an uncommon cystic phenotype of well-differentiated pancreatic neuroendocrine tumors, accounting for approximately 7-12% of PanNETs in several surgical series, although reported frequencies vary according to the definition of cystic morphology and cohort selection. Retrospective studies suggest that c-PanNETs may exhibit less aggressive clinicopathologic features than their solid counterparts; however, their imaging appearance frequently overlaps with other pancreatic cystic neoplasms, particularly branch-duct intraductal papillary mucinous neoplasms, mucinous cystic neoplasms, and atypical serous cystic neoplasms. Accurate preoperative recognition may have important implications for patient management and surgical planning. This review summarizes the imaging features of c-PanNETs across computed tomography, magnetic resonance imaging, and magnetic resonance cholangiopancreatography, as well as the complementary roles of endoscopic ultrasound and somatostatin receptor PET/CT. Particular attention is given to arterial hyperenhancement of the cyst wall, septations, mural nodules, or residual solid components; assessment of communication with the main pancreatic duct; and integration of complementary imaging findings. Because these features are not specific, their interpretation in combination with lesion morphology and ductal relationships is emphasized. Practical approaches to differential diagnosis and common interpretive pitfalls are also discussed. The review further addresses emerging quantitative imaging techniques, including radiomics and artificial intelligence, while recognizing that evidence specific to c-PanNETs remains limited. A practical diagnostic algorithm and structured reporting checklist are provided to support systematic interpretation and multidisciplinary communication. Recognition of the imaging spectrum of c-PanNETs, combined with systematic assessment of enhancement characteristics, ductal anatomy, and complementary imaging findings, may improve diagnostic confidence and support appropriate patient management.