Pancreatic cystic lesions are being discovered as incidental lesions during cross-sectional imaging studies of the abdomen with increasing frequency. Endoscopic ultrasound is an important diagnostic modality for managing pancreatic cystic lesions. There are various types of pancreatic cystic lesions, from benign to malignant. Endoscopic ultrasound has a multifactorial role in delineating the morphology of pancreatic cystic lesions, ranging from fluid and tissue acquisition for analysis—fine needle aspiration and through-the-needle biopsy, respectively—to advanced imaging techniques, such as contrast-harmonic mode endoscopic ultrasound and EUS-guided needle-based confocal laser endomicroscopy. In this review, we will summarize and provide an update on the specific role of EUS in the management of pancreatic cystic lesions.

Hereditary pancreatic cancer, which includes patients with familial pancreatic cancer (FPC) and hereditary pancreatic cancer syndromes, accounts for about 10% of all pancreatic cancer diagnoses. The early detection of pre-cancerous pancreatic cysts has increasingly become a focus of interest in recent years as a potential avenue to lower pancreatic cancer incidence and mortality. Intraductal papillary mucinous cystic neoplasms (IPMNs) are recognized precursor lesions of pancreatic cancer. IPMNs have high prevalence in patients with hereditary pancreatic cancer and their relatives. While various somatic mutations have been identified in IPMNs, certain germline mutations associated with hereditary cancer syndromes have also been identified in IPMNs, suggesting a role in their formation. While the significance for the higher prevalence of IPMNs or similar germline mutations in these high-risk patients remain unclear, IPMNs do represent pre-malignant lesions that need close surveillance. This review summarizes the available literature on the incidence and prevalence of IPMNs in inherited genetic predisposition syndromes and FPC and speculates if IPMN and pancreatic cancer surveillance in these high-risk individuals needs to change.

The rate of incidentally detected pancreatic cystic lesions (PCLs) has increased over the past decade and was recently reported at 8%. These lesions pose a unique challenge, as each subtype of PCL carries a different risk of malignant transformation, ranging from 0% (pancreatic pseudocyst) to 34–68% (main duct intraductal papillary mucinous neoplasm). It is imperative to correctly risk-stratify the malignant potential of these lesions in order to provide the correct care course for the patient, ranging from monitoring to surgical intervention. Even with the multiplicity of guidelines (i.e., the American Gastroenterology Association guidelines and Fukuoka/International Consensus guidelines) and multitude of diagnostic information, risk stratification of PCLs falls short. Studies have reported that 25–64% of patients undergoing PCL resection have pancreatic cysts with no malignant potential, and up to 78% of mucin-producing cysts resected harbor no malignant potential on pathological evaluation. Clinicians are now incorporating artificial intelligence technology to aid in the management of these difficult lesions. This review article focuses on advancements in artificial intelligence within digital pathomics, radiomics, and genomics as they apply to the diagnosis and risk stratification of PCLs.