{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T12:19:15Z","timestamp":1788524355476,"version":"build-2803163510"},"reference-count":23,"publisher":"Georg Thieme Verlag KG","funder":[{"name":"UMass Memorial Health"},{"DOI":"10.13039\/100007920","name":"University of Massachusetts Medical School","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100007920","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100024612","name":"MassVentures","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100024612","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000871","name":"Mayo Clinic","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100000871","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Endoscopy"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Clinicians struggle to accurately classify biliary strictures as benign or malignant. Current endoscopic retrograde cholangiopancreatography (ERCP)-based sampling modalities including brush cytology and forceps biopsy have poor sensitivity for pathologic confirmation of malignancy. Cholangioscopy allows for direct visualization and sampling of biliary pathology; however, this technology is also associated with inaccurate classification of biliary disease. Previously, an artificial intelligence (AI) system that analyzes cholangioscopy footage was found to be more accurate in diagnosing biliary malignancy than ERCP sampling techniques. The aim of this study was to validate this AI system on a new series of examinations.<\/jats:p>\n                  <jats:p>Three academic centers collected all available unedited cholangioscopy recordings. The videos were processed by the cholangioscopy AI system. After analyzing videos, the AI system provided predictions as to whether malignancy was present. AI performance in classifying strictures was compared with the performance of brush cytology and forceps biopsy.<\/jats:p>\n                  <jats:p>112 cholangioscopy examinations (containing 4 817 081 images) were generated from 99\n        patients. Of those examinations, 61 (54.5%) were for investigation of biliary strictures (31\n        [50.8%] benign, 30 [49.2%] malignant). For the correct classification of strictures, the AI\n        system was 80.0% sensitive and 90.3% specific. It was also significantly more accurate for\n        stricture classification (85.2%) than brush cytology (52.5%; P&lt;0.001), forceps biopsy (68.2%; P=0.04), and the\n        combination of brush cytology and forceps biopsy (66.7%; P=0.02).<\/jats:p>\n                  <jats:p>A previously developed cholangioscopy AI system was found to continually outperform standard ERCP sampling modalities for accurate identification of malignancy, without additional retraining, in a multicenter validation cohort.<\/jats:p>","DOI":"10.1055\/a-2650-0789","type":"journal-article","created":{"date-parts":[[2025,7,6]],"date-time":"2025-07-06T18:30:31Z","timestamp":1751826631000},"source":"Crossref","is-referenced-by-count":8,"title":["Multicenter validation of a cholangioscopy artificial intelligence system for the evaluation of biliary tract disease"],"prefix":"10.1055","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8654-1948","authenticated-orcid":false,"given":"Neil B.","family":"Marya","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"},{"name":"Program in Digital Medicine, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick D.","family":"Powers","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"},{"name":"Program in Digital Medicine, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jad P.","family":"AbiMansour","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Marcello","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikhil R.","family":"Thiruvengadam","sequence":"additional","affiliation":[{"name":"Gastroenterology, Loma Linda University, Loma Linda, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Navine","family":"Nasser-Ghodsi","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Prashanth","family":"Rau","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jaroslav","family":"Zivny","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Savant","family":"Mehta","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Marshall","sequence":"additional","affiliation":[{"name":"Gastroenterology, UMass Chan Medical School, Worcester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paul","family":"Leonor","sequence":"additional","affiliation":[{"name":"Gastroenterology, Loma Linda University, Loma Linda, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kendrick","family":"Che","sequence":"additional","affiliation":[{"name":"Gastroenterology, Loma Linda University, Loma Linda, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barham","family":"Abu Dayyeh","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0619-5235","authenticated-orcid":false,"given":"Andrew C.","family":"Storm","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bret T.","family":"Petersen","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ryan","family":"Law","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John A.","family":"Martin","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8886-0376","authenticated-orcid":false,"given":"Eric J.","family":"Vargas","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vinay","family":"Chandrasekhara","sequence":"additional","affiliation":[{"name":"Gastroenterology and Hepatology, Mayo Clinic, Rochester, United States"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"194","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1038\/s41575-020-0310-z","article-title":"Cholangiocarcinoma 2020: the next horizon in mechanisms and management","volume":"17","author":"JM Banales","year":"2020","journal-title":"Nat Rev Gastroenterol Hepatol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1664","DOI":"10.1002\/ijc.28161","article-title":"Biliary tract cancer incidence in the United States-Demographic and temporal variations by anatomic site","volume":"133","author":"FA Castro","year":"2013","journal-title":"Int J Cancer"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"685","DOI":"10.1016\/j.gie.2023.06.005","article-title":"American Society for Gastrointestinal Endoscopy guideline on the role of endoscopy in the diagnosis of malignancy in biliary strictures of undetermined etiology: summary and recommendations","volume":"98","author":"LL Fujii-Lau","year":"2023","journal-title":"Gastrointest Endosc"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"168","DOI":"10.1016\/j.gie.2014.09.017","article-title":"Comparative effectiveness of biliary brush cytology and intraductal biopsy for detection of malignant biliary strictures: a systematic review and meta-analysis","volume":"81","author":"U Navaneethan","year":"2015","journal-title":"Gastrointest Endosc"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"884","DOI":"10.1016\/j.gie.2021.11.029","article-title":"Impact of trimodality sampling on detection of malignant biliary strictures compared with patients with primary sclerosing cholangitis","volume":"95","author":"S Baroud","year":"2022","journal-title":"Gastrointest Endosc"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"653","DOI":"10.1007\/s10120-018-0793-2","article-title":"Application of artificial intelligence using a convolutional neural network for detecting gastric cancer in endoscopic images","volume":"21","author":"T Hirasawa","year":"2018","journal-title":"Gastric Cancer"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1016\/j.cgh.2023.03.015","article-title":"Development of a computer-aided prediction tool for evaluating brushing samples of biliary strictures","volume":"22","author":"NB Marya","year":"2024","journal-title":"Clin Gastroenterol Hepatol"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"1335","DOI":"10.1136\/gutjnl-2020-322821","article-title":"Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis","volume":"70","author":"NB Marya","year":"2021","journal-title":"Gut"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"1121","DOI":"10.1016\/j.gie.2020.08.024","article-title":"Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses","volume":"93","author":"NB Marya","year":"2021","journal-title":"Gastrointest Endosc"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"31","DOI":"10.4253\/wjge.v11.i1.31","article-title":"Role of digital single-operator cholangioscopy in the diagnosis and treatment of biliary disorders","volume":"11","author":"P Karagyozov","year":"2019","journal-title":"World J Gastrointest Endosc"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"1059","DOI":"10.1016\/j.gie.2021.06.027","article-title":"Diagnostic accuracy and interobserver agreement of digital single-operator cholangioscopy for indeterminate biliary strictures","volume":"94","author":"PMC Stassen","year":"2021","journal-title":"Gastrointest Endosc"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/j.gie.2022.08.021","article-title":"Identification of patients with malignant biliary strictures using a cholangioscopy-based deep learning artificial intelligence (with video)","volume":"97","author":"NB Marya","year":"2023","journal-title":"Gastrointest Endosc"},{"key":"ref14","doi-asserted-by":"publisher","first-page":"409","DOI":"10.2217\/hep.15.30","article-title":"Liver transplantation in the management of perihilar cholangiocarcinoma","volume":"2","author":"AF Gulamhusein","year":"2015","journal-title":"Hepat Oncol"},{"key":"ref15","doi-asserted-by":"publisher","first-page":"2170","DOI":"10.1002\/sim.2677","article-title":"Confidence intervals for predictive values with an emphasis to case-control studies","volume":"26","author":"ND Mercaldo","year":"2007","journal-title":"Stat Med"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"1471","DOI":"10.1007\/s10620-019-05866-2","article-title":"Cholangioscopy biopsies improve detection of cholangiocarcinoma when combined with cytology and FISH, but not in patients with PSC","volume":"65","author":"K Kaura","year":"2020","journal-title":"Dig Dis Sci"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1136\/gutjnl-2018-317817","article-title":"Integrating next-generation sequencing to endoscopic retrograde cholangiopancreatography (ERCP)-obtained biliary specimens improves the detection and management of patients with malignant bile duct strictures","volume":"69","author":"AD Singhi","year":"2020","journal-title":"Gut"},{"key":"ref18","doi-asserted-by":"publisher","first-page":"773","DOI":"10.1016\/j.gie.2016.08.020","article-title":"Cost utility of ERCP-based modalities for the diagnosis of cholangiocarcinoma in primary sclerosing cholangitis","volume":"85","author":"B Njei","year":"2017","journal-title":"Gastrointest Endosc"},{"key":"ref19","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1055\/a-2034-3803","article-title":"Artificial intelligence for diagnosing neoplasia on digital cholangioscopy: development and multicenter validation of a convolutional neural network model","volume":"55","author":"C Robles-Medranda","year":"2023","journal-title":"Endoscopy"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.gie.2021.08.015","article-title":"Digital single-operator cholangioscopy interobserver study using a new classification: the Mendoza Classification (with video)","volume":"95","author":"M Kahaleh","year":"2022","journal-title":"Gastrointest Endosc"},{"key":"ref21","doi-asserted-by":"publisher","first-page":"1568","DOI":"10.1053\/j.gastro.2023.07.010","article-title":"AGA Clinical Practice Update on the role of artificial intelligence in colon polyp diagnosis and management: commentary","volume":"165","author":"J Samarasena","year":"2023","journal-title":"Gastroenterology"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.gie.2023.02.026","article-title":"A real-time interpretable artificial intelligence model for the cholangioscopic diagnosis of malignant biliary stricture (with videos)","volume":"98","author":"X Zhang","year":"2023","journal-title":"Gastrointest Endosc"},{"key":"ref24","doi-asserted-by":"publisher","first-page":"475","DOI":"10.1016\/j.gie.2023.08.022","article-title":"Re-establishing the purpose of cholangioscopy-based artificial intelligence for biliary strictures","volume":"99","author":"NB Marya","year":"2024","journal-title":"Gastrointest Endosc"},{"key":"ref25","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1055\/a-1061-7067","article-title":"Limited diagnostic accuracy and clinical impact of single-operator peroral cholangioscopy for indeterminate biliary strictures","volume":"52","author":"AB de Vries","year":"2020","journal-title":"Endoscopy"}],"container-title":["Endoscopy"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.thieme-connect.de\/products\/ejournals\/pdf\/10.1055\/a-2650-0789.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T22:44:55Z","timestamp":1755557095000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.thieme-connect.de\/DOI\/DOI?10.1055\/a-2650-0789"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,6]]},"references-count":23,"URL":"https:\/\/doi.org\/10.1055\/a-2650-0789","archive":["Portico","CLOCKSS"],"relation":{},"ISSN":["0013-726X","1438-8812"],"issn-type":[{"value":"0013-726X","type":"print"},{"value":"1438-8812","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,7,6]]},"published":{"date-parts":[[2025,7,6]]}}}