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Rare Solid Pancreatic Lesions on Cross-Sectional Imaging.
Ana Veron Sanchez1, Nuria Santamaria Guinea2, Silvia Cayon Somacarrera3
1Hôpital Universitaire de Bruxelles, Institut Jules Bordet, 1070 Brussels, Belgium.
Diagnostics (Basel, Switzerland)
|August 26, 2023
Summary
This review highlights rare solid pancreatic lesions beyond common pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine neoplasms (pNENs). Recognizing their diverse origins and imaging features is crucial for accurate diagnosis and patient management.
Area of Science:
- Gastroenterology and Hepatology
- Oncology
- Radiology
Background:
- The pancreas harbors various solid lesions, with pancreatic ductal adenocarcinoma (PDAC) being the most prevalent malignancy.
- Beyond PDAC and pancreatic neuroendocrine neoplasms (pNENs), rare solid pancreatic lesions arise from diverse cell lines, exhibiting a spectrum of behaviors from benign to highly aggressive.
Purpose of the Study:
- To review and characterize rare solid pancreatic lesions, emphasizing their diverse origins and clinical significance.
- To underscore the diagnostic challenges posed by these rare entities due to their low incidence and often incidental detection.
Main Methods:
- Comprehensive literature review of rare solid pancreatic lesions, including intrapancreatic accessory spleen, pancreatic tuberculosis, and various neoplasms.
- Analysis of cross-sectional imaging features in conjunction with clinical and biological context for diagnostic contribution.
Main Results:
- The review encompasses a wide array of rare solid pancreatic lesions, such as pancreatic schwannoma, solitary fibrous tumors, acinar cell carcinoma, and others.
- Typical imaging features on cross-sectional modalities are identified as key contributors to the diagnostic process for these uncommon lesions.
Conclusions:
- Accurate diagnosis of rare solid pancreatic lesions is essential for optimal patient management.
- Despite diagnostic challenges stemming from rarity, characteristic imaging findings significantly aid in achieving correct diagnoses when integrated with clinical data.

