{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T12:51:25Z","timestamp":1788267085719,"version":"build-2803163510"},"reference-count":11,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2023,3,24]],"date-time":"2023-03-24T00:00:00Z","timestamp":1679616000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"funder":[{"DOI":"10.13039\/100000054","name":"National Cancer Institute","doi-asserted-by":"publisher","award":["P30 CA008748"],"award-info":[{"award-number":["P30 CA008748"]}],"id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Acad Dermatol Venereol"],"published-print":{"date-parts":[[2023,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Existing artificial intelligence for melanoma detection has relied on analysing images of lesions of clinical interest, which may lead to missed melanomas. Tools analysing the entire skin surface are lacking.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To determine if melanoma can be distinguished from other skin lesions using data from automated analysis of 3D\u2010images.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Single\u2010centre, retrospective, observational convenience sample of patients diagnosed with melanoma at a tertiary care cancer hospital. Eligible participants were those with a whole\u2010body 3D\u2010image captured within 90\u2009days prior to the diagnostic skin biopsy. 3D\u2010images were obtained as standard of care using VECTRA WB360 Whole Body 3\u2010dimensional Imaging System (Canfield Scientific). Automated data from image processing (i.e. lesion size, colour, border) for all eligible participants were exported from VECTRA DermaGraphix research software for analysis. The main outcome was the area under the receiver operating characteristic curve (AUC).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 35 patients contributed 23,538 automatically identified skin lesions &gt;2\u2009mm in largest diameter (102\u20133021 lesions per participant). All were White patients and 23 (66%) were males. The median (range) age was 64\u2009years (26\u201389). There were 49 lesions of melanoma and 22,489 lesions that were not melanoma. The AUC for the prediction model was 0.94 (95% CI: 0.92\u20130.96). Considering all lesions in a patient\u2010level analysis, 14 (28%) melanoma lesions had the highest predicted score or were in the 99th percentile among all lesions for an individual patient.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In this proof\u2010of\u2010concept pilot study, we demonstrated that automated analysis of whole\u2010body 3D\u2010images using simple image processing techniques can discriminate melanoma from other skin lesions with high accuracy. Further studies with larger, higher quality, and more representative 3D\u2010imaging datasets would be needed to improve and validate these results.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jdv.18924","type":"journal-article","created":{"date-parts":[[2023,1,28]],"date-time":"2023-01-28T02:40:40Z","timestamp":1674873640000},"page":"945-950","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["<scp>3D Whole\u2010body<\/scp>\n                    skin imaging for automated melanoma detection"],"prefix":"10.1111","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1793-1851","authenticated-orcid":false,"given":"M. A.","family":"Marchetti","sequence":"first","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7652-8512","authenticated-orcid":false,"given":"Z. H.","family":"Nazir","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"},{"name":"Zucker School of Medicine at Hofstra\/Northwell  Hempstead New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6864-8888","authenticated-orcid":false,"given":"J. K.","family":"Nanda","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"},{"name":"Department of Dermatology, Renaissance School of Medicine Stony Brook University  Stony Brook New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0747-2479","authenticated-orcid":false,"given":"S. W.","family":"Dusza","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0050-401X","authenticated-orcid":false,"given":"B. M.","family":"D'Alessandro","sequence":"additional","affiliation":[{"name":"Canfield Scientific, Inc.  Parsippany New Jersey USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2431-3370","authenticated-orcid":false,"given":"J.","family":"DeFazio","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7320-1901","authenticated-orcid":false,"given":"A. C.","family":"Halpern","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0639-2677","authenticated-orcid":false,"given":"V. M.","family":"Rotemberg","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6068-0114","authenticated-orcid":false,"given":"A. A.","family":"Marghoob","sequence":"additional","affiliation":[{"name":"Dermatology Service, Department of Medicine Memorial Sloan Kettering Cancer Center  New York New York USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2023,3,24]]},"reference":[{"key":"e_1_2_13_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaad.2020.03.121"},{"key":"e_1_2_13_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaad.2020.03.122"},{"key":"e_1_2_13_4_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejca.2021.06.049"},{"key":"e_1_2_13_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/bjd.13121"},{"key":"e_1_2_13_6_1","doi-asserted-by":"publisher","DOI":"10.36849\/JDD.2020.4766"},{"key":"e_1_2_13_7_1","unstructured":"VECTRA 3D Whole Body 3D Imaging. Canfield.https:\/\/www.canfieldsci.com\/imaging\u2010systems\/vectra\u2010wb360\u2010imaging\u2010system\/. Accessed 10 August 2022."},{"key":"e_1_2_13_8_1","doi-asserted-by":"publisher","DOI":"10.1159\/000517218"},{"key":"e_1_2_13_9_1","doi-asserted-by":"publisher","DOI":"10.2307\/2336755"},{"key":"e_1_2_13_10_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.292.22.2771"},{"key":"e_1_2_13_11_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMsr1905447"},{"key":"e_1_2_13_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jid.2021.12.003"}],"container-title":["Journal of the European Academy of Dermatology and Venereology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/jdv.18924","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1111\/jdv.18924","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1111\/jdv.18924","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T14:29:39Z","timestamp":1692628179000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1111\/jdv.18924"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,24]]},"references-count":11,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2023,5]]}},"alternative-id":["10.1111\/jdv.18924"],"URL":"https:\/\/doi.org\/10.1111\/jdv.18924","archive":["Portico"],"relation":{},"ISSN":["0926-9959","1468-3083"],"issn-type":[{"value":"0926-9959","type":"print"},{"value":"1468-3083","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,24]]},"assertion":[{"value":"2022-09-21","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-01-16","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-03-24","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}