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Updated: May 9, 2025

Application of End-to-end Anastomosis in Robotic Central Pancreatectomy
Published on: June 2, 2018
Pancreatic Neuroendocrine Tumors-A Descriptive Study of the Presenting Features in a 20-Year Surgical Resection
Jassimran Singh1, Hallbera Gudmundsdottir2, Thorvardur R Halfdanarson3
1Department of Internal Medicine, Saint Vincent Hospital, Worcester, MA.
Objectives:
Pancreatic neuroendocrine tumors (pNETs) are uncommon, comprising 3%-7% of pancreatic tumors. With increasing incidence due to advanced imaging techniques, there is a need for detailed characterization of these tumors. This study aims to describe the clinical features, diagnostic evaluations, and pathology characteristics of pNETs in a large cohort from a single tertiary center, and to compare these findings with other larger cohort studies.
Methods:
We conducted a retrospective analysis of 866 patients with pNETs who underwent surgical resection at Mayo Clinic, Rochester, from March 2000 to December 2019. Data on demographics, clinical presentation, laboratory tests, imaging, and pathology were extracted and analyzed. Descriptive statistics were used to summarize the data.
Results:
The cohort had a median age of 57 years. Nonfunctional tumors were much more prevalent (77.5%), with functional tumors primarily being insulinomas (75.9%). Common presenting symptoms included gastrointestinal (45.3%) and nongastrointestinal symptoms (30.7%). Chromogranin A levels were elevated in 57.5% of patients. Imaging revealed enhancing lesions in most cases, with computed tomography scans performed in 90.9% of patients. Endoscopic ultrasound (EUS) identified tumors in 98.1% of cases, with EUS-FNA showing a sensitivity of 82%. Ki-67 index, used in 58.1% of cases, indicated grade 2 tumors as the most common (55.9%). Metastasis was observed in 39.4% of patients at the time of diagnosis, predominantly in the liver.
Conclusion:
This study provides a comprehensive description of pNET characteristics in a large surgical cohort. Findings highlight the predominance of nonfunctional tumors and the importance of imaging and EUS in diagnosis. The data can aid in inter-institutional comparisons and enhance understanding of pNETs, contributing to improved patient management and future research.

