{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T02:07:56Z","timestamp":1789092476509,"version":"build-2803163510"},"reference-count":49,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["220727\/Z\/20\/Z"],"award-info":[{"award-number":["220727\/Z\/20\/Z"]}],"id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["pathsocjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Pathology"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Ductular reactions (DRs) are dynamic and complex multicellular responses that occur as a result of various hepatic injuries. Precise identification and quantification of the extent of DRs is a cornerstone of pre\u2010clinical modelling of liver disease, with links to inflammation, fibrosis, regeneration, and disease severity. Here, we apply a deep learning model, Deep Understanding Convolutional Kernel (DUCK\u2010Net), to the automated detection and segmentation of DRs in whole\u2010slide histopathological images of murine models of liver damage. Following annotation of a training dataset by a specialist liver histopathologist, we demonstrate accelerated performance and accurate detection, achieving a mean Dice coefficient (model\u2010expert segmentation overlap) of 85.4% and a specificity of 98%, indicating minimal false positives. Evaluation of model validity and utility was achieved with a histological time course of cholestatic injury and recovery using 3,5\u2010diethoxycarbonyl\u20101,4\u2010dihydrocollidine diet (DDC) in mice. When assessed against a multiple linear regression model incorporating core epithelial and stromal components of the DR as quantified using immunohistochemistry (IHC), DUCK\u2010Net predicted the spatiotemporal response to injury and repair\/resolution with a coefficient of determination (\n                    <jats:italic>R<\/jats:italic>\n                    <jats:sup>2<\/jats:sup>\n                    ) of 0.88. Moreover, DUCK\u2010Net kinetics strongly correlated with published spatial transcriptomic (Stereo\u2010seq) analysis of the DDC model, demonstrating that H&amp;E\u2010based segmentation captured molecular DR dynamics comparable to or exceeding that of individual IHC markers without the need for immunostaining. DUCK\u2010Net provides a novel and accessible platform for rapid, accurate histological quantification of liver injury reflective of the matrix\u2010rich, multicellular regenerative niche observed in DRs. \u00a9 2026 The Author(s).\n                    <jats:italic>The Journal of Pathology<\/jats:italic>\n                    published by John Wiley &amp; Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.\n                  <\/jats:p>","DOI":"10.1002\/path.70113","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T03:06:12Z","timestamp":1788923172000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["<scp>DUCK<\/scp>\n                    \u2010Net: automated deep learning segmentation of ductular reactions in murine liver injury captures multicellular niche dynamics from H&amp;E morphology"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0124-6398","authenticated-orcid":false,"given":"Nathalie","family":"Feeley","sequence":"first","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kai","family":"Williams","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caitlin","family":"McCaffrey","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"},{"name":"Department of Oncology University of Oxford  Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7505-6584","authenticated-orcid":false,"given":"Daniel","family":"Field","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyle","family":"Davies","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hugh","family":"Warden","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Luke","family":"Boulter","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9962-9356","authenticated-orcid":false,"given":"Steve","family":"Thorn","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"},{"name":"Department of Oncology University of Oxford  Oxford UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tak Yung","family":"Man","sequence":"additional","affiliation":[{"name":"Institute of Regeneration and Repair University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0419-0257","authenticated-orcid":false,"given":"Wei\u2010Yu","family":"Lu","sequence":"additional","affiliation":[{"name":"Institute of Regeneration and Repair University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3614-8002","authenticated-orcid":false,"given":"Stephen J","family":"Wigmore","sequence":"additional","affiliation":[{"name":"Department of Clinical Surgery University of Edinburgh  Edinburgh UK"},{"name":"Centre for Medical Informatics, Usher Institute University of Edinburgh  Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ewen 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 Edinburgh UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3213-7688","authenticated-orcid":false,"given":"Rachel V","family":"Guest","sequence":"additional","affiliation":[{"name":"Institute of Genetics and Cancer University of Edinburgh  Edinburgh UK"},{"name":"Department of Clinical Surgery University of Edinburgh  Edinburgh 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