Pancreaticobiliary endoscopy, encompassing endoscopic ultrasound (EUS), endoscopic retrograde cholangiopancreatography (ERCP), and digital single-operator cholangioscopy (DSOC), is essential for diagnosing and managing pancreatic and biliary diseases. However, these procedures are limited by operator dependency, variable diagnostic accuracy, and technical complexity. Artificial intelligence (AI), particularly through machine learning (ML) and deep learning (DL), has emerged as a promising tool to address these challenges. Early studies show that AI can enhance lesion detection, improve differentiation of pancreatic masses, classify cystic lesions, and aid in diagnosing malignant biliary strictures. AI has also been used to predict post-ERCP pancreatitis risk and reduce radiation exposure during ERCP. Despite this promise, current AI models are largely experimental—limited by small, single-center datasets, lack of external validation, and no FDA-approved systems for these indications. Major barriers include inconsistent data acquisition, limited interoperability across hardware platforms, and integration into real-time workflows. Future progress depends on multicenter data sharing, standardized imaging protocols, interpretable AI design, and regulatory pathways for model deployment and updates. AI can be developed as a valuable partner to endoscopists, enhancing diagnostic accuracy, reducing complications, and supporting more efficient, personalized care in pancreaticobiliary endoscopy.

Esophageal cancer cases are predicted to reach 957,000 by 2040. Prior mortality rates average 6.5% in men and 2.2% in women, with a poor 5-year prognosis of 20%. A deficiency in screening guidelines, an incomplete understanding of pathophysiology, and limited treatment options contributed to this poor prognosis. Now, as technology and knowledge evolve, endoscopy serves a primary role in improving morbidity and mortality around esophageal cancer, in which early detection and treatment play a profound role. Advances in diagnostic modalities, including higher frequency ultrasound, acquisition of larger specimens, and nodal characterization, all improve esophageal cancer diagnostic accuracy and treatment planning. This is primarily due to earlier detection of precursor lesions, eradication with complete resection, and more informed surveillance. Prior management with esophagectomy has now evolved to include endoscopic submucosal dissection, mucosal resection, ablation, stent placement, fiducial markers for radiotherapy, sponge vacuum, and more. These endoluminal remedies are curative, palliative, or post-intervention solutions, thereby reducing the surgical risk, morbidity, and mortality associated with esophageal cancer. This review article details the diagnostic and therapeutic role of endoscopy in esophageal cancer.

Incremental innovation in endoscopic ultrasound-guided biopsy: does the tip make the difference?

A proportion of patients who undergo intraoperative cholangiogram (IOC) do not have bile duct stones at the time of endoscopic retrograde cholangiopancreatography (ERCP), either due to the spontaneous passage of stones or a false-positive IOC. Glucagon has been utilized as an inexpensive tool to allow the passage of micro-choledocholithiasis to the duodenum and resolve filling defects caused by stones or air bubbles. The purpose of our study is to understand the change in diagnostic accuracy of IOC to detect choledocholithiasis with intraoperative glucagon. We conducted a retrospective study at a tertiary care center on adult patients who underwent laparoscopic cholecystectomy with IOC. The diagnostic accuracy of IOC was assessed before and after the administration of intravenous glucagon. Of 1455 patients, 374 (25.7%) received intraoperative glucagon, and 103 of these 374 patients (27.5%) showed resolution of the filling defect with the passage of contrast to the duodenum. Pre- and post-glucagon administration comparison showed enhancement in specificity from 78% to 83%, an increase in positive predictive value from 67.3% to 72.4%, and an improvement in the diagnostic accuracy of IOC from 81.5% to 84.3%. Our findings suggest that intraoperative glucagon administration carries the potential to reduce the rate of false-positive IOCs, thereby reducing the performance of unnecessary ERCPs.