Search

Background: "Idiopathic pancreatitis" is diagnosed when clinical, laboratory and conventional radiologic methods do not provide a clear etiology for the episode. Given its associated morbidity and mortality, it is important to determine the cause of pancreatitis to provide early treatment and prevent recurrence., Methods: The aim of this systematic review was to evaluate the utility of endoscopic ultrasound (EUS) in determining an etiology in patients classified as having idiopathic pancreatitis and to assess how EUS performed compared with other modalities. A PubMed search for relevant articles (January 2000-November 2014) was performed using the search terms "(pancreatitis or idiopathic pancreatitis or unexplained pancreatitis) and (EUS or endoscopic ultrasound).", Results: The search yielded a total of 963 articles, and 13 studies were included in the final review. In some studies, the yield of EUS was higher than magnetic resonance cholangiopancreatography in idiopathic pancreatitis. EUS more accurately detected biliary stones, whereas magnetic resonance cholangiopancreatography more often identified pancreatic duct abnormalities. The yield of EUS was lower in patients postcholecystectomy but was not influenced by gender, severity of pancreatitis, or recurrent disease. The most frequent diagnoses by EUS for those with idiopathic pancreatitis were biliary tract disease (41%). Overall, EUS identified additional diagnostic information in 61% of patients with idiopathic pancreatitis., Conclusions: Given the high incidence of microlithiasis and/or biliary sludge as a cause of idiopathic pancreatitis as well as the safety and high accuracy, EUS should be considered 1st for evaluation of idiopathic pancreatitis if conventional cross-sectional radiography fails to reveal a cause.

Stones in the biliary tract are routinely identified using MRCP (magnetic resonance cholangiopancreatography). The noisy nature of the images, as well as varying intensity, size and location of the stones, defeat most automatic detection algorithms, making computer-aided diagnosis difficult. This paper proposes a multi-stage segment-based scheme for semi-automated detection of choledocholithiasis and cholelithiasis in the MRCP images, producing good performance in tests, differentiating them from "normal" MRCP images. With the high success rate of over 90%, refinement of the scheme could be applicable in the clinical environment as a tool in aiding diagnosis, with possible applications in telemedicine.