{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,13]],"date-time":"2026-10-13T00:37:01Z","timestamp":1791851821541,"version":"4.3.4"},"reference-count":27,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T00:00:00Z","timestamp":1762128000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["1153046"],"award-info":[{"award-number":["1153046"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["2006551"],"award-info":[{"award-number":["2006551"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["1135285"],"award-info":[{"award-number":["1135285"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000925","name":"National Health and Medical Research Council","doi-asserted-by":"publisher","award":["2009923"],"award-info":[{"award-number":["2009923"]}],"id":[{"id":"10.13039\/501100000925","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,2,18]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>High naevus counts and ultraviolet photodamage are strong risk factors for melanoma. However, whole-of-body measures fail to capture variability across body sites. Three-dimensional total body photography (3D-TBP) and artificial intelligence (AI) allow us the opportunity to automate the extraction of site-specific distributions of naevi and photodamage.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>To identify distinct phenotypic patterns associated with melanoma in a cohort of people at high risk of advanced melanoma, using combined 3D-TBP, AI and unsupervised clustering.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Participants with a history of melanoma (diagnosed aged &amp;gt; 50\u2005years) underwent 3D-TBP. Site-specific photodamage and naevus counts were assessed using density-based spatial clustering of applications with noise to identify body site-dependent phenotypic patterns. Melanoma prevalence (none, single, multiple) relative to phenotypic pattern was evaluated using population prevalence ratios (PPRs).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Analysis of 117 individuals found four phenotypic patterns of increasing severity: moderate V-neck photodamage with few naevi [median 38; interquartile range (IQR) 27\u201372] in 28 patients (24%); moderate generalized photodamage with several naevi (median 155; IQR 90\u2013259) in 31 patients (26%); moderate V-neck photodamage with many naevi (median 204) in 20 patients (17%); and severe generalized photodamage with few naevi (median 37; IQR 21\u201372) naevi in 38 patients (32%). No individuals had severe photodamage and several-to-many naevi. Interpattern comparisons revealed that participants with the mildest phenotypic pattern were least likely to be affected by invasive melanomas [PPR 1.51, 95% confidence interval (CI) 1.01\u20132.26], whereas those with the most severe phenotypic pattern were more likely to be affected by multiple invasive melanomas (PPR 2.00, 95% CI 1.06\u20133.77). The prevalence of melanoma in situ was consistent across patterns. Melanoma was more likely at sites of large naevi (&amp;gt; 5\u2005mm; P &amp;lt; 0.05) in those with moderate photodamage patterns but were independent of naevi (&amp;gt; 2\u2005mm) in individuals with severe photodamage patterns. From a control cohort unaffected by melanoma (n = 114), only 18 (15.8%) matched with a high-risk phenotypic pattern.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Three-dimensional TBP phenotyping of an older Australian cohort at high risk of invasive melanoma revealed four distinct phenotypic patterns associated with risk of the disease. Individuals with severe photodamage and relatively few naevi had a significantly higher risk of developing multiple invasive melanomas. For individuals with moderate photodamage, the risk of invasive melanoma was positively associated with the number of naevi. Thus, comprehensive phenotypes may be more predictive for the diagnosis and site of invasive melanoma, which may help with nuanced risk stratification and customized surveillance.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bjd\/ljaf440","type":"journal-article","created":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T13:04:47Z","timestamp":1762002287000},"page":"531-539","source":"Crossref","is-referenced-by-count":4,"title":["Three dimensional total body photography identifies cutaneous phenotypes associated with late-onset invasive melanoma risk"],"prefix":"10.1093","volume":"194","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9680-3120","authenticated-orcid":false,"given":"Sam","family":"Kahler","sequence":"first","affiliation":[{"name":"Frazer Institute, The University of Queensland, Dermatology Research Centre , Brisbane, QLD ,","place":["Australia"]},{"name":"Department of Dermatology, Princess Alexandra Hospital , Brisbane, QLD 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Faculty of Medicine, QLD ,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7145-4673","authenticated-orcid":false,"given":"Chantal","family":"Rutjes","sequence":"additional","affiliation":[{"name":"Frazer Institute, The University of Queensland, Dermatology Research Centre , Brisbane, QLD ,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3876-501X","authenticated-orcid":false,"given":"Brigid","family":"Betz-Stablein","sequence":"additional","affiliation":[{"name":"Frazer Institute, The University of Queensland, Dermatology Research Centre , Brisbane, QLD ,","place":["Australia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1728-8085","authenticated-orcid":false,"given":"Monika","family":"Janda","sequence":"additional","affiliation":[{"name":"Frazer Institute, The University of Queensland, 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