{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T09:04:43Z","timestamp":1785229483646,"version":"3.55.0"},"reference-count":38,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T00:00:00Z","timestamp":1783468800000},"content-version":"vor","delay-in-days":7,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["pathsocjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["The Journal of Pathology CR"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Ductal carcinoma\n                    <jats:italic>in situ<\/jats:italic>\n                    (DCIS) spans a biologic continuum from atypical ductal hyperplasia (ADH) to high\u2010grade lesions with variable risk of progression to invasive ductal carcinoma (IDC), yet morphologic assessment by hematoxylin and eosin (H&amp;E) remains diagnostically limited, particularly at the benign versus ADH\/low\u2010grade DCIS boundary. TRPV4, a mechanosensitive ion channel with pathology\u2010dependent subcellular localization in DCIS, offers a biologically motivated immunohistochemical (IHC) marker that may refine classification beyond routine H&amp;E assessment. We tested whether deep learning models trained on TRPV4 IHC outperform H&amp;E\u2010based models across the DCIS progression spectrum. We assembled a multi\u2010institutional cohort of H&amp;E and TRPV4 IHC whole\u2010slide images from 108 patients, comprising an internal development cohort (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200969), an external test cohort (\n                    <jats:italic>n<\/jats:italic>\n                    \u2009=\u200939), yielding 24,248 annotated tiles. Histopathological tiles from annotated regions were grouped into four ordered classes: normal\/benign, ADH\/low\u2010grade DCIS, high\u2010grade DCIS, and IDC. Xception and EfficientNet\u2010B0 convolutional neural networks were trained with patient\u2010level three\u2010fold cross\u2010validation on the development cohort and evaluated as ensembles on the external test cohort. On external patient\u2010level testing, H&amp;E ensembles achieved macro\u2010F1 values of 0.43\u20130.44 and macro\u2010AUC values of 0.73\u20130.80, whereas TRPV4 IHC ensembles improved performance to macro\u2010F1 values of 0.68\u20130.72 and macro\u2010AUC values of 0.91\u20130.92, corresponding to a 54.5\u201367.4% relative improvement in patient\u2010level macro\u2010F1. Patient\u2010level per\u2010class analyses showed the largest AUC gains with TRPV4 IHC versus H&amp;E for ADH\/low\u2010grade DCIS (0.94\u20130.95 versus 0.61\u20130.70) and IDC (0.77\u20130.85 versus 0.61\u20130.69). Per\u2010class analyses showed the largest gains with TRPV4 IHC versus H&amp;E for ADH\/low\u2010grade DCIS (AUC, 0.83\u20130.84 versus 0.70\u20130.81) and IDC (AUC, 0.74\u20130.79 versus 0.65\u20130.66). These findings support TRPV4 IHC as a mechanistically grounded complement to H&amp;E that improves patient\u2010level discrimination across the DCIS progression spectrum, with the strongest gains for ADH\/low\u2010grade DCIS and IDC, in a pilot multi\u2010institutional setting.\n                  <\/jats:p>","DOI":"10.1002\/2056-4538.70106","type":"journal-article","created":{"date-parts":[[2026,7,8]],"date-time":"2026-07-08T10:29:56Z","timestamp":1783506596000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Mechanosensitive\n                    <scp>TRPV4<\/scp>\n                    immunohistochemistry improves deep learning\u2010based classification of ductal carcinoma\n                    <i>in situ<\/i>\n                    beyond H&amp;E morphology"],"prefix":"10.1002","volume":"12","author":[{"given":"Janghyun","family":"Yoo","sequence":"first","affiliation":[{"name":"Department of Physics and Astronomy College of Natural Sciences, Seoul National University  Seoul South Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raghav","family":"Karthikeyan","sequence":"additional","affiliation":[{"name":"Department of Anatomy and Cell Biology School of Medicine and Health Sciences, George Washington University  Washington DC USA"},{"name":"Thomas Jefferson Science and Technology High School  Alexandria VA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kashi","family":"Kamat","sequence":"additional","affiliation":[{"name":"Department of Anatomy and Cell Biology School of Medicine and Health Sciences, George Washington University  Washington DC USA"},{"name":"Thomas Jefferson Science and Technology High School  Alexandria VA USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christopher","family":"Chan","sequence":"additional","affiliation":[{"name":"Department of Anatomy and Cell Biology School of Medicine and Health Sciences, George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shabnam","family":"Samankan","sequence":"additional","affiliation":[{"name":"Department of Pathology School of Medicine and Health Sciences, George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elham","family":"Arbzadeh","sequence":"additional","affiliation":[{"name":"Department of Pathology School of Medicine and Health Sciences, George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Arnold","family":"Schwartz","sequence":"additional","affiliation":[{"name":"Department of Pathology School of Medicine and Health Sciences, George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patricia S","family":"Latham","sequence":"additional","affiliation":[{"name":"Department of Pathology School of Medicine and Health Sciences, George Washington University  Washington DC USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2312-6357","authenticated-orcid":false,"given":"Inhee","family":"Chung","sequence":"additional","affiliation":[{"name":"Department of Anatomy and Cell Biology School of Medicine and Health Sciences, George Washington University  Washington DC USA"},{"name":"Department of Biomedical Engineering School of Engineering and Applied Science, George Washington University  Washington DC 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