{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T00:02:29Z","timestamp":1779840149866,"version":"3.53.1"},"reference-count":19,"publisher":"Georg Thieme Verlag KG","issue":"CP","license":[{"start":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T00:00:00Z","timestamp":1771459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Endosc Int Open"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Cholangiocarcinoma (CCa) is a complex malignancy of the biliary tract, classified as intrahepatic, perihilar, or distal. Digital single-operator cholangioscopy (D-SOC) enhances evaluation of biliary strictures, although it remains limited by suboptimal biopsy yield and technical constraints. Artificial intelligence (AI), particularly convolutional neural networks (CNNs), has emerged as a promising adjunct. However, performance across anatomical subtypes is not well defined. This study evaluated diagnostic performance of an AI-based model in detecting CCa lesions by location.<\/jats:p>\n                  <jats:p>A YOLOv8-based CNN was trained and validated using 315,993 D-SOC images from 183\n        patients across six international high-volume centers. Images were labeled as benign or\n        malignant based on expert consensus. Frame-based analysis assessed diagnostic performance\n        using macro-average F1-score, precision, and recall. Subgroup analysis explored anatomical\n        site-specific performance.<\/jats:p>\n                  <jats:p>Among the included patients (mean age 66.1\u00b112.1 years; 64.5% male), 43.2% had perihilar, 37.2% intrahepatic, and 19.7% distal biliary strictures. The model demonstrated high overall performance: F1 score 95.3%, precision 95.5%, and recall 95.1%. Site-specific analysis revealed an F1 score of 89.6% for distal strictures and 91.1% for perihilar strictures. Receiver operating characteristic curves showed areas under the curve of 0.980 for intrahepatic strictures and 0.990 for perihilar and distal strictures.<\/jats:p>\n                  <jats:p>This is the first study to demonstrate AI-based diagnostic performance across CCa topography using a large, multicenter D-SOC dataset. Although anatomical complexity affects detection, the model\u2019s high precision and generalizability suggest potential for clinical utility. These results support application of an AI-enhanced algorithm decision algorithm for cholangioscopy.<\/jats:p>","DOI":"10.1055\/a-2813-3447","type":"journal-article","created":{"date-parts":[[2026,2,20]],"date-time":"2026-02-20T00:42:15Z","timestamp":1771548135000},"source":"Crossref","is-referenced-by-count":0,"special_numbering":"S","title":["Mapping malignancy: Multicenter study addressing topographic challenges in biliary stricture artificial intelligence analysis"],"prefix":"10.1055","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0340-0830","authenticated-orcid":false,"given":"Miguel","family":"Mascarenhas","sequence":"first","affiliation":[{"name":"Centro Hospitalar Universit\u00e1rio de S\u00e3o Jo\u00e3o, Porto District, Portugal","place":["Porto"],"department":["Gastroenterology Department"]},{"name":"University of Porto Faculty of Medicine, Portugal","place":["Porto"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Antonio Miguel","family":"Pinto da Costa","sequence":"first","affiliation":[{"name":"Hospital Universitario Puerta de Hierro Majadahonda, S\u00e3o Paulo, Brazil","place":["S\u00e3o Paulo"],"department":["Gastroenterology and Hepatology Department"]},{"name":"Hospital das Cl\u00ednicas da Faculdade de Medicina da Universidade de S\u00e3o Paulo, Spain","place":["Madrid"],"department":["Gastrointestinal Endoscopy Department"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9230-0953","authenticated-orcid":false,"given":"Matheus Ferreira","family":"de Carvalho","sequence":"additional","affiliation":[{"name":"Hospital das Cl\u00ednicas da Faculdade de Medicina da Universidade de S\u00e3o Paulo, Spain","place":["Madrid"],"department":["Gastrointestinal Endoscopy Department"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiago","family":"Ribeiro","sequence":"additional","affiliation":[{"name":"Centro Hospitalar Universit\u00e1rio de 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