{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T23:10:53Z","timestamp":1782861053201,"version":"3.54.5"},"reference-count":44,"publisher":"SAGE Publications","issue":"2","license":[{"start":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T00:00:00Z","timestamp":1759881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T00:00:00Z","timestamp":1759881600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Vet Pathol"],"published-print":{"date-parts":[[2026,3]]},"abstract":"<jats:p>\n                    Canine cutaneous mast cell tumors (ccMCTs) are frequent neoplasms with variable biological behaviors. Internal tandem duplication mutations in\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    exon 11 (\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD) are associated with poor prognosis but predict therapeutic response to tyrosine kinase inhibitors. In a previous work, deep learning algorithms managed to predict the presence of\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD on digitalized hematoxylin and eosin-stained histological slides (whole-slide images, WSIs) in up to 87% of cases, suggesting the existence of morphological features characterizing ccMCTs carrying\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD. This 3-stage blinded study aimed to identify morphological features indicative of\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD and to evaluate the ability of human observers to learn this task. 17 untrained pathologists first classified 8 WSIs and 200 image patches (highly relevant for algorithmic classification) of ccMCTs as either positive or negative for\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD. Second, they self-trained to recognize\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD by looking at the same WSIs and patches correctly sorted. Third, pathologists classified 15 new WSIs and 200 new patches according to\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD status. In addition, participants reported microscopic features they considered relevant for their decision. Without training, participants correctly classified the\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD status of 63%\u201388% of WSIs and 43%\u201355% of patches. With self-training, 25%\u201338% of WSIs and 55%\u201356% of patches were correctly classified. High cellular pleomorphism, anisokaryosis, and sparse cytoplasmic granulation were commonly suggested as features associated with\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD-positive ccMCTs, none of which showed reliable predictivity in a follow-up study. The results indicate that transfer of algorithmic skills to the human observer is difficult. A\n                    <jats:italic toggle=\"yes\">c-KIT<\/jats:italic>\n                    -11-ITD-specific morphological feature remains to be extracted from the artificial intelligence model.\n                  <\/jats:p>","DOI":"10.1177\/03009858251380284","type":"journal-article","created":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T10:44:03Z","timestamp":1759920243000},"page":"369-379","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":2,"title":["Artificial intelligence predicts\n                    <i>c-KIT<\/i>\n                    exon 11 genotype by phenotype in canine cutaneous mast cell tumors: Can human observers learn it?"],"prefix":"10.1177","volume":"63","author":[{"given":"Chlo\u00e9","family":"Puget","sequence":"first","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1299-8716","authenticated-orcid":false,"given":"Jonathan","family":"Ganz","sequence":"additional","affiliation":[{"name":"Technische Hochschule Ingolstadt, Ingolstadt, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2402-9997","authenticated-orcid":false,"given":"Christof A.","family":"Bertram","sequence":"additional","affiliation":[{"name":"University of Veterinary Medicine Vienna, Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Conrad","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Malte","family":"Baeblich","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne","family":"Voss","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharina","family":"Landmann","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-0279-7482","authenticated-orcid":false,"given":"Alexander F. H.","family":"Haake","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Spree","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Svenja","family":"Hartung","sequence":"additional","affiliation":[{"name":"Sieklandstra\u00dfe, Tecklenburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leonore","family":"Aeschlimann","sequence":"additional","affiliation":[{"name":"University of Bern, Bern, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Soto","sequence":"additional","affiliation":[{"name":"University of Bern, Bern, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3049-0103","authenticated-orcid":false,"given":"Simone","family":"de Brot","sequence":"additional","affiliation":[{"name":"University of Bern, Bern, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martina","family":"Dettwiler","sequence":"additional","affiliation":[{"name":"Vetscope Pathologie Dettwiler, Riehen, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heike","family":"Aupperle-Lellbach","sequence":"additional","affiliation":[{"name":"LABOKLIN GmbH &amp; Co.KG, Bad Kissingen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2903-1535","authenticated-orcid":false,"given":"Pompei","family":"Bolfa","sequence":"additional","affiliation":[{"name":"Ross University School of Veterinary Medicine, Basseterre, Saint Kitts and Nevis"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1280-6138","authenticated-orcid":false,"given":"Alexander","family":"Bartel","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matti","family":"Kiupel","sequence":"additional","affiliation":[{"name":"Michigan State University, East Lansing, MI"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharina","family":"Breininger","sequence":"additional","affiliation":[{"name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg, Erlangen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5294-5247","authenticated-orcid":false,"given":"Marc","family":"Aubreville","sequence":"additional","affiliation":[{"name":"Flensburg University of Applied Sciences, Flensburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6308-0568","authenticated-orcid":false,"given":"Robert","family":"Klopfleisch","sequence":"additional","affiliation":[{"name":"Freie Universit\u00e4t Berlin, Berlin, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2025,10,8]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-55288-y"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1177\/0300985821999831"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1177\/03009858211067478"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1177\/0300985819890686"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.0045-16.2016"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.09.257"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2022.1024449"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1002\/path.5898"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.3389\/fvets.2023.1188795"},{"key":"e_1_3_3_11_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0177-5"},{"key":"e_1_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-021-23458-5"},{"key":"e_1_3_3_13_2","doi-asserted-by":"publisher","DOI":"10.5214\/ans.0972.7531.200408"},{"key":"e_1_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.esmoop.2022.100400"},{"key":"e_1_3_3_15_2","first-page":"1","article-title":"From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology","author":"El Nahhas OSM","year":"2024","unstructured":"El Nahhas OSM, van Treeck M, W\u00f6lflein G, et al. 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