{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T20:41:45Z","timestamp":1792010505108,"version":"4.4.0"},"reference-count":25,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2022,7,26]],"date-time":"2022-07-26T00:00:00Z","timestamp":1658793600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acad Dermatol Venereol"],"published-print":{"date-parts":[[2022,11]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Preoperative assessment of whether a melanoma is invasive or <jats:italic>in\u2009situ<\/jats:italic> (MIS) is a common task that might have important implications for triage, prognosis and the selection of surgical margins. Several dermoscopic features suggestive of melanoma have been described, but only a few of these are useful in differentiating MIS from invasive melanoma.<\/jats:p><\/jats:sec><jats:sec><jats:title>Objective<\/jats:title><jats:p>The primary aim of this study was to evaluate how accurately a large number of international readers, individually as well as collectively, were able to discriminate between MIS and invasive melanomas as well as estimate the Breslow thickness of invasive melanomas based on dermoscopy images. The secondary aim was to compare the accuracy of two machine learning convolutional neural networks (CNNs) and the collective reader response.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We conducted an open, web\u2010based, international, diagnostic reader study using an online platform. The online challenge opened on 10 May 2021 and closed on 19 July 2021 (71\u2009days) and was advertised through several social media channels. The investigation included, 1456 dermoscopy images of melanomas (788 MIS; 474 melanomas \u22641.0\u2009mm and 194 &gt;1.0\u2009mm). A test set comprising 277 MIS and 246 invasive melanomas was used to compare readers and CNNs.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We analysed 22\u2009314 readings by 438 international readers. The overall accuracy (95% confidence interval) for melanoma thickness was 56.4% (55.7%\u201357.0%), 63.4% (62.5%\u201364.2%) for MIS and 71.0% (70.3%\u201372.1%) for invasive melanoma. Readers accurately predicted the thickness in 85.9% (85.4%\u201386.4%) of melanomas \u22641.0\u2009mm (including MIS) and in 70.8% (69.2%\u201372.5%) of melanomas &gt;1.0\u2009mm. The reader collective outperformed a <jats:italic>de novo<\/jats:italic> CNN but not a pretrained CNN in differentiating MIS from invasive melanoma.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Using dermoscopy images, readers and CNNs predict melanoma thickness with fair to moderate accuracy. Readers most accurately discriminated between thin (\u22641.0\u2009mm including MIS) and thick melanomas (&gt;1.0\u2009mm).<\/jats:p><\/jats:sec>","DOI":"10.1111\/jdv.18436","type":"journal-article","created":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T10:39:05Z","timestamp":1657967945000},"page":"2002-2007","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Assessment of melanoma thickness based on dermoscopy images: an open, web\u2010based, international, diagnostic study"],"prefix":"10.1111","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5398-6200","authenticated-orcid":false,"given":"S.","family":"Polesie","sequence":"first","affiliation":[{"name":"Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg  Gothenburg Sweden"},{"name":"Department of Dermatology and Venereology, Region V\u00e4stra G\u00f6taland Sahlgrenska University Hospital  Gothenburg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5033-5421","authenticated-orcid":false,"given":"M.","family":"Gillstedt","sequence":"additional","affiliation":[{"name":"Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg  Gothenburg Sweden"},{"name":"Department of Dermatology and Venereology, Region V\u00e4stra G\u00f6taland Sahlgrenska University Hospital  Gothenburg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0051-8016","authenticated-orcid":false,"given":"H.","family":"Kittler","sequence":"additional","affiliation":[{"name":"Department of Dermatology Medical University of Vienna  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3847-5664","authenticated-orcid":false,"given":"C.","family":"Rinner","sequence":"additional","affiliation":[{"name":"Center of Medical Statistics, Informatics and Intelligent Systems (CeMSIIS) Medical University of Vienna  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0391-7810","authenticated-orcid":false,"given":"P.","family":"Tschandl","sequence":"additional","affiliation":[{"name":"Department of Dermatology Medical University of Vienna  Vienna Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1326-8535","authenticated-orcid":false,"given":"J.","family":"Paoli","sequence":"additional","affiliation":[{"name":"Department of Dermatology and Venereology, Institute of Clinical Sciences, Sahlgrenska Academy University of Gothenburg  Gothenburg Sweden"},{"name":"Department of Dermatology and Venereology, Region V\u00e4stra G\u00f6taland Sahlgrenska University Hospital  Gothenburg Sweden"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2022,7,26]]},"reference":[{"key":"e_1_2_6_2_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1365-2133.2008.08713.x"},{"key":"e_1_2_6_3_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamadermatol.2017.6447"},{"key":"e_1_2_6_4_1","doi-asserted-by":"publisher","DOI":"10.1590\/abd1806-4841.20132017"},{"key":"e_1_2_6_5_1","doi-asserted-by":"publisher","DOI":"10.5826\/dpc.1103a79"},{"key":"e_1_2_6_6_1","unstructured":"Medical University of Vienna Department of Dermatology.DermaChallenge.2021. 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