IPMN-LEARN: A linear support vector machine learning model for predicting low-grade intraductal papillary mucinous neoplasms.

Backgrounds/aims: We aimed to build a machine learning tool to help predict low-grade intraductal papillary mucinous neoplasms (IPMNs) in order to avoid unnecessary surgical resection. IPMNs are precursors to pancreatic cancer. Surgical resection remains the only recognized treatment for IPMNs yet carries some risks of morbidity and potential mortality.

Evaluating triage protocols for endoscopic ultrasound-guided fine needle biopsies of the pancreas.

Introduction: Pancreatic endoscopic ultrasound-guided fine needle biopsy (EUS-FNB) acquires both direct smear and small core biopsy specimens. The triage protocols for pancreatic FNBs to cytopathology (CP) or gastrointestinal surgical pathology (GIP) are controversial and vary by institution.

Material And Methods: Pancreatic EUS-FNBs obtained with the SharkCore FNB were reviewed from January 2014 to June 2019.

Diagnostic yield of the SharkCore EUS-guided fine-needle biopsy.

Introduction: Endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) is the standard diagnostic procedure for many intrathoracic and intra-abdominal lesions. Next-generation fine-needle biopsies (FNBs) can increase diagnostic yield by procuring tissue suitable for histological processing. We evaluate the diagnostic yield and operating characteristics of the SharkCore (SC; Medtronic Corp.