{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T06:01:31Z","timestamp":1785391291374,"version":"3.55.0"},"reference-count":29,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100006306","name":"Sigrid Jus\u00e9liuksen S\u00e4\u00e4ti\u00f6","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006306","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100005744","name":"Lastentautien Tutkimuss\u00e4\u00e4ti\u00f6","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100005744","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010711","name":"Sy\u00f6p\u00e4s\u00e4\u00e4ti\u00f6","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100010711","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Hepatology Research"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Liver biopsy has shown prognostic significance in primary sclerosing cholangitis (PSC). However, histology is typically assessed manually based on coarse grading scales, making precise quantification difficult. We developed a neural network model to address the key histological features of liver tissue, including portal tracts, fibrosis, biliary epithelium, portal inflammation, and vasculature.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and Results<\/jats:title>\n                    <jats:p>\n                      Our training data included 603 liver sections from patients with PSC (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0478), other hepatobiliary diseases (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a0119), and normal controls (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a06), ensuring heterogeneity of the sample material. The model was validated and evaluated for its ability to predict key clinical endpoints in PSC: liver transplantation (LT) due to end\u2010stage liver disease (ESLD), and a composite endpoint comprising LT, cholangiocarcinoma (CCA), and liver\u2010related death, allowing evaluation with all relevant clinical outcomes. The model reliably identified the targeted histological features. AI\u2010derived portal inflammation and fibrosis demonstrated superior discriminatory performance compared with manual scoring, particularly for prediction of LT due to ESLD (AUC 0.81\u20130.82 vs. 0.86\u20130.87). AI\u2010derived blood vessels and biliary epithelium were also prognostic for LT due to ESLD (AUC 0.80, 0.83). In multivariable analysis adjusted for age and sex, AI\u2010derived portal inflammation remained independently associated with the composite endpoint (HR 2.51, 95% CI 1.04\u20136.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>AI\u2010measured portal inflammation is a robust predictor of clinical endpoints. Additionally, vascular area, fibrosis, and biliary epithelium showed prognostic value. AI\u2010based measures outperformed manual scores for several parameters. Overall, multiple AI\u2010derived parameters predicted LT due to ESLD, and comparable trends were observed for the composite endpoint. These findings highlight the importance of liver histology as a surrogate endpoint in patients with PSC.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/hepr.70254","type":"journal-article","created":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T05:39:00Z","timestamp":1785389940000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Histological AI\u2010Assisted Analysis Outperforms Pathologist Assessment in Predicting Disease Outcomes in PSC Patients"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9206-6990","authenticated-orcid":false,"given":"Anna M.","family":"Salonen","sequence":"first","affiliation":[{"name":"Department of Pathology Helsinki University and Helsinki University Hospital (HUH) HUS Diagnostic Center  Helsinki Finland"},{"name":"Section of Pediatric Surgery Pediatric Liver and Gut Research Group New Children's Hospital University of Helsinki and Helsinki University Hospital  Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4999-4280","authenticated-orcid":false,"given":"Iiris","family":"Nyholm","sequence":"additional","affiliation":[{"name":"Section of Pediatric Surgery Pediatric Liver and Gut Research Group New Children's Hospital University of Helsinki and Helsinki University Hospital  Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linn","family":"T\u00e4hti","sequence":"additional","affiliation":[{"name":"Aiforia Technologies Plc  Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matilda","family":"Sinkko","sequence":"additional","affiliation":[{"name":"Aiforia Technologies Plc  Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darshan","family":"Kumar","sequence":"additional","affiliation":[{"name":"Aiforia Technologies Plc  Helsinki 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and Helsinki University Hospital (HUH) HUS Diagnostic Center  Helsinki Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nelli","family":"Sj\u00f6blom","sequence":"additional","affiliation":[{"name":"Department of Dermatopathology University of Helsinki Helsinki University Hospital (HUH)  Helsinki 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