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Competing Interests: Conflicts of interest C Felmingham was supported by a Monash University Research Training Program Scholarship. Y Pan has previously reported for MoleMap Ltd. A Chamberlain was a reporting teledermatologist for MoleMap Ltd from 2009 to 2010. A Chamberlain has honoraria from Proctor & Gamble, Schering-Plough, CSL, Leo-Pharma; a consulting/advisory role for L'Oreal (La Roche Posay); and is on the Speakers Bureau for Novartis, Janssen, HealthCert International, Cancer Council of Victoria, Merck Sharp & Dohme. A Oakley is a diagnosing consultant for MoleMap Ltd; and was involved in another study of the MoleMap AI system (abstract published https://www.iproc.org/themes/1158-9th-world-congress-of-teledermatology-imaging-and-ai-for-skin-diseases-abstracts-2021). S Tucker is a diagnosing consultant for MoleMap Ltd and Dermatology Solutions. A Robinson is a sub-Investigator for Dermira, Galderma, Pfizer, Arcutis, Bristol Myers Squib, Leo Pharma, Argenx, Genesis Care; has had sponsored conference attendance from Lilly, and Janssen was on the steering committee for conference for Novartis; and on the Advisory Board for Lilly. P Foley has received grant support from AbbVie, Amgen, Bristol-Myers Squibb, Celgene, Eli Lilly, Galderma, Janssen, Leo Pharma, Merck, Novartis, Pfizer, Sanofi, and Sun Pharma; has served as an investigator for AbbVie, Amgen, Arcutis, Argenx, Aslan, AstraZeneca, Boehringer Ingelheim, Botanix, Bristol-Myers Squibb, Celgene, Celtaxsys, CSL, Cutanea, Dermira, Eli Lilly, Evelo, Galderma, Genentech, Geneseq, GlaxoSmithKline, Hexima, Janssen, Kymab, Leo, Merck, MedImmune, Novartis, Pfizer, Regeneron Pharmaceuticals Inc, Reistone, Roche, Sanofi, Sun Pharma, Teva, UCB Pharma, and Valeant; has served on advisory boards for AbbVie, Amgen, Aslan, Boehringer Ingelheim, Bristol-Myers Squibb, Celgene, Eli Lilly, Galderma, GlaxoSmithKline, Janssen, Leo, Mayne Pharma, Merck, Novartis, Pfizer, Sanofi, Sun Pharma, UCB Pharma, and Valeant; has served as a consultant for Aslan, Bristol-Myers Squibb, Eli Lilly, Galderma, GenesisCare, Hexima, Janssen, Leo Pharma, MedImmune, Mayne Pharma, Novartis, Pfizer, Roche, and UCB Pharma; has received travel grants from AbbVie, Eli Lilly, Galderma, Janssen, Leo Pharma, Merck, Novartis, Pfizer, Roche, Sun Pharma, and Sanofi; and has served as a speaker for or received honoraria from AbbVie, Amgen, Celgene, Eli Lilly, Galderma, GlaxoSmithKline, Janssen, Leo Pharma, Merck, Novartis, Pfizer, Roche, Sanofi, Sun Pharma, and Valeant. A Bowling is a shareholder, founder and consultant to MoleMap Ltd. Z Ge has received personal fees from MoleMap Ltd. M Haskett has received personal fees from MoleMap Ltd and is a shareholder in MoleMap Ltd. V Mar is supported by a National Health and Medical Research Council Early Career Fellowship; and has honoraria from Novartis, Merck, Bristol-Myers-Squibb, Janssen, and Eli Lily; and has had sponsored conference attendance from L'Oreal.

Background/objectives: Sequential digital dermoscopic imaging (SDDI) and total body photography (TBP) are recommended as a two-step surveillance method for individuals at high-risk of developing cutaneous melanoma. Dermoscopic features specific to melanoma have been well described, however, dynamic changes on serial imaging are less understood. This study aims to identify and compare dermoscopic features in developing melanomas and benign naevi that underwent SDDI and TBP to understand which dermoscopic features may be associated with a malignant change., Method: Histopathology reports from a private specialist dermatology clinic from January 2007 to December 2019 were reviewed. Histopathologically confirmed melanoma and benign naevi that underwent SDDI and TBP with a minimum follow-up interval of 3 months were included., Results: Eighty-nine melanomas (38.2% invasive, median Breslow thickness 0.35 mm, range: 0.2-1.45 mm) and 48 benign naevi were evaluated by three experienced dermatologists for dermoscopic changes. Features most strongly associated with melanoma included the development of neovascularisation, asymmetry and growth in pigment network, additional colours, shiny white structures, regression, structureless areas and change to a multi-component pattern. The presence of atypical vessels (p = 0.02) and shiny white structures (p = 0.02) were significantly associated with invasive melanoma., Conclusion: Evaluation for certain evolving dermoscopic features in melanocytic lesions monitored by SDDI and TBP is efficient in assisting clinical decision making. SDDI with TBP is an effective tool for early detection of melanoma., (© 2023 The Australasian College of Dermatologists.)

Introduction: Convolutional neural networks (CNNs) can diagnose skin cancers with impressive accuracy in experimental settings, however, their performance in the real-world clinical setting, including comparison to teledermatology services, has not been validated in prospective clinical studies., Methods and Analysis: Participants will be recruited from dermatology clinics at the Alfred Hospital and Skin Health Institute, Melbourne. Skin lesions will be imaged using a proprietary dermoscopic camera. The artificial intelligence (AI) algorithm, a CNN developed by MoleMap Ltd and Monash eResearch, classifies lesions as benign, malignant or uncertain. This is a preintervention/postintervention study. In the preintervention period, treating doctors are blinded to AI lesion assessment. In the postintervention period, treating doctors review the AI lesion assessment in real time, and have the opportunity to then change their diagnosis and management. Any skin lesions of concern and at least two benign lesions will be selected for imaging. Each participant's lesions will be examined by a registrar, the treating consultant dermatologist and later by a teledermatologist. At the conclusion of the preintervention period, the safety of the AI algorithm will be evaluated in a primary analysis by measuring its sensitivity, specificity and agreement with histopathology where available, or the treating consultant dermatologists' classification. At trial completion, AI classifications will be compared with those of the teledermatologist, registrar, treating dermatologist and histopathology. The impact of the AI algorithm on diagnostic and management decisions will be evaluated by: (1) comparing the initial management decision of the registrar with their AI-assisted decision and (2) comparing the benign to malignant ratio (for lesions biopsied) between the preintervention and postintervention periods., Ethics and Dissemination: Human Research Ethics Committee (HREC) approval received from the Alfred Hospital Ethics Committee on 14 February 2019 (HREC/48865/Alfred-2018). Findings from this study will be disseminated through peer-reviewed publications, non-peer reviewed media and conferences., Trial Registration Number: NCT04040114., Competing Interests: Competing interests: VM is supported by an NHMRC Early Career Fellowship. VM reports personal fees from Novartis, personal fees from Bristol-Myers-Squibb, personal fees from Merck, outside the submitted work. MH reports personal fees from MoleMap Ltd, during the conduct of the study; and is a shareholder in MoleMap Ltd. AB reports personal fees from MoleMap Ltd, during the conduct of the study; personal fees from Molemap Ltd, outside the submitted work; and is a shareholder in Molemap Ltd. AS reports personal fees from MoleMap Ltd, during the conduct of the study; personal fees from Molemap Ltd, outside the submitted work. ZG reports personal fees from MoleMap Ltd. NW and SM are former employees of the Cancer Collaborative Trials Group contracted to implement the SMARTI Study—Melanoma and Skin Cancer Trials (MASC Trials) Ltd. CF is supported by a Monash University Research Training Program Scholarship. RW, NA, WC and MW have nothing to disclose. The study is sponsored by Monash University and endorsed by MASC Trials Ltd., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Lentigo maligna (LM) is a common subtype of in situ melanoma on chronically sun-exposed skin, particularly the head and neck of older patients. Although surgery is the standard treatment, there is associated morbidity, and options such as imiquimod cream or radiotherapy may be used if surgery is refused or inappropriate. Complete response rates following imiquimod treatment are variable in the literature. The aim of this study was to evaluate the host immune response both before and following treatment with imiquimod to better identify likely responders. Paired pre- and post-imiquimod treatment specimens were available for 27 patients. Patients were treated with imiquimod 5 days per week for 12 weeks; at 16 weeks, lesions were excised for histological assessment. Of the 27 patients, 16 were responders and 11 failed to clear the disease. PDL1 protein expression was increased, accompanied by a unique gene signature in lesions from patients that subsequently histologically cleared LM by 16 weeks. This comprised 57 upregulated immune genes in signaling networks for antigen presentation, type I interferon signaling, and T-cell activation. This may represent an early responder group to imiquimod, and this unique gene signature potentially can be used as a biomarker of LM response to imiquimod., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Importance: Mitotic rate is now recognized as having independent prognostic significance in melanoma survival. However, its clinicopathologic associations have not been the focus of any previous study., Objective: To identify a set of patient and tumor characteristics associated with high-mitotic-rate melanoma with the aim of facilitating the earlier detection of aggressive primary invasive melanoma., Design, Setting, and Participants: Cross-sectional study of patients from a multidisciplinary melanoma clinic based in a public hospital. A total of 2397 cases from January 2006 to December 2011 were reviewed by the Victorian Melanoma Service, and 1441 patients with 1500 primary invasive melanomas were included in the study., Main Outcomes and Measures: Mitotic rate was measured as number of mitoses per mm2 and analyzed as ordered categories (0, <1, 1 and <2, 2, 3-4, 5-9, and ≥10) according to patient demographics, phenotypic markers, historical data, tumor presentation, and histopathologic features., Results: Melanomas with higher mitotic rates were more likely to occur in men (odds ratio [OR], 1.5; 95% CI, 1.3-1.8), patients 70 years or older (OR, 2.1; 95% CI, 1.7-2.8), and those with a history of solar keratosis (OR, 1.3; 95% CI, 1.1-1.6). These melanomas occurred more frequently on the head and neck (OR, 1.4; 95% CI, 1.0-1.9) and presented more often as amelanotic (OR, 1.9; 95% CI, 1.4-2.5) and rapidly growing (≥2 mm/mo) lesions (OR, 12.5; 95% CI, 8.4-18.5). An association was seen with the nodular melanoma subtype (vs superficial spreading [reference]) (OR, 2.5; 95% CI, 1.8-3.4), greater tumor thickness (vs ≤1 mm [reference]) (>1-4 mm: OR, 4.5; 95% CI, 3.2-6.1; >4 mm: OR, 12.6; 95% CI, 7.5-21.1), and ulceration (OR, 2.0; 95% CI, 1.5-2.7). These histopathologic features, along with amelanosis and rate of growth, remained as significant associations with high mitotic rate in the overall multivariate analysis., Conclusions and Relevance: High-mitotic-rate primary cutaneous melanoma is associated with aggressive histologic features and atypical clinical presentation. It has a predilection for the head and neck region and is more likely to be seen in elderly men with a history of cumulative solar damage who present clinically with rapidly developing disease.

Background: Merkel cell carcinoma (MCC) is an aggressive cutaneous malignancy with a high mortality rate. Diagnosis is often delayed., Objectives: To characterize the dermoscopic features of MCC., Methods: Clinical and dermoscopic images of 12 biopsy-proven MCCs were analysed in a retrospective manner, with existing dermoscopic criteria being scored independently by three dermatologists., Results: The four most frequent clinical features were cherry red colour, shiny surface, sharp circumscription and nodular morphology. Significant dermoscopic features included linear irregular and polymorphous vessels, poorly focused vessels, milky pink areas, white areas, structureless areas and architectural disorder. Pigmented structures were absent from all lesions., Conclusions: The dermoscopic features described herein help the clinician to distinguish MCC from other benign and malignant red nodules. Increasing recognition of the presenting features will facilitate earlier diagnosis of MCC and reduced mortality., (© 2013 The Authors BJD © 2013 British Association of Dermatologists.)

Objective: To determine the efficacy of imiquimod cream, 5%, in the treatment of lentigo maligna (LM)., Design: Open-label before-and-after interventional study., Setting: A multidisciplinary melanoma clinic at a major tertiary hospital., Patients: Forty-three patients with biopsy-proven LM of greater than 5 mm in diameter completed this study., Interventions: Imiquimod cream, 5%, was applied to the lesion 5 days a week for 12 weeks. The original lesion was excised with a 5-mm margin., Main Outcome Measures: The primary outcome was histopathologic evidence of LM in the excision specimen assessed independently by 2 of 3 dermatopathologists. Visible inflammation during treatment and macroscopic clearance were recorded., Results: When 5 of the 43 patients with discordant histopathologic assessment of the excision specimen were excluded, 20 of 38 patients (53% [95% confidence interval, 36%-69%]) demonstrated histopathologic clearance of LM after imiquimod treatment. Visible inflammation was significantly associated with histopathologic clearance (P = .04), but the positive predictive value was low (62%). Macroscopic clearance showed some association with histopathologic clearance (P = .11). Dermatopathologist concordance for all 43 specimens was substantial (κ = 0.77; 95% confidence interval, 0.57-0.96)., Conclusions: Imiquimod cream, 5%, has limited efficacy in the treatment of LM when determined by histopathologic assessment of the entire treated area. The clinical signs of visible inflammation during treatment and apparent lesion clearance cannot be relied on to assess efficacy.

Background: Teledermoscopy is a rapidly developing field of dermatology with studies demonstrating excellent agreement with face-to-face diagnosis. However, we are unaware of studies evaluating interobserver variability in diagnosis between dermatologists from different continents. This evaluation is important to determine the robustness of teledermoscopy and allow comparisons to be made between different studies., Objectives: To assess the interobserver diagnostic variability between five independent experienced dermatologists (A-E) in New Zealand, Australia and the U.S.A., Methods: Images from 979 lesions from 206 patients were distributed to five dermatologists. The lesions were viewed and diagnoses recorded using MoleMap Diagnose (MoleMap, Auckland, New Zealand) software. The diagnoses were analysed for interobserver variability., Results: There was excellent agreement between four of five dermatologists (A-D) for lesions that were agreed upon as melanoma (κ = 0·81-0·97) and benign naevus (κ = 0·77-0·82).The fifth dermatologist (E) made a more frequent diagnosis of atypical naevus and melanoma than the others. For nonmelanocytic lesions, there was moderate to very good agreement for seborrhoeic keratosis (κ = 0·64-0·80) and basal cell carcinoma (κ = 0·55-0·67), but poor agreement for invasive squamous cell carcinoma (SCC) (κ = 0·05-0·15). Agreement for actinic keratosis (κ = 0·32-0·67) and SCC in situ (κ = 0·15-0·32) was only moderate. When atypical and benign naevi were grouped together and actinic keratosis and SCC in situ grouped together, there was better agreement among all dermatologists. There was good ability to distinguish malignant from benign lesions (κ = 0·57-0·93)., Conclusions: There was good agreement among dermatologists A-D but dermatologist E varied from the group with more frequent diagnosis of melanoma and atypical naevus. This difference could be due to different definition of terms with lack of consensus guidelines in definition of atypical naevus, lack of familiarity with the specific patient population and/or diagnostic drift., (© 2010 The Authors. BJD © 2010 British Association of Dermatologists.)

Background: Intraepidermal carcinoma (IEC), superficial basal cell carcinoma (sBCC), and psoriasis are common entities that may all present as well-defined, brightly erythematous plaques. Currently, there are limited data on the dermatoscopic features that differentiate these diagnoses., Objective: We sought to describe the most significant morphologic findings seen on dermatoscopy of IEC, sBCC, and psoriasis, and formulate a diagnostic model based on these features., Method: We conducted a retrospective observational study using macrophotography and dermatoscopy to evaluate the presence or absence of dermatoscopic features and formulated diagnostic models for each diagnosis. A convenient sample of 300 lesions was collected from 255 patients from two hospital dermatology clinics and 4 private dermatology practices. These comprised 150 cases of sBCC, 100 cases of psoriasis, and 50 cases of IEC., Results: The most significant dermatoscopic features of IEC were a clustered vascular pattern, glomerular vessels, and hyperkeratosis. When all 3 features were observed together, the diagnostic probability for IEC was 98%. sBCCs were characterized by a scattered vascular pattern, arborizing microvessels, telangiectatic or atypical vessels, milky-pink background, and brown dots/globules; the diagnostic probability was 99% if 4 of these 6 features were identified. For psoriasis, the significant features identified were a homogenous vascular pattern, red dots, and light-red background, yielding a diagnostic probability of 99% if all 3 features were present., Limitations: Lack of evaluation of interobserver/intraobserver reproducibility is a limitation., Conclusion: Dermatoscopy is valuable in the diagnosis and differentiation of IEC, sBCC, and psoriasis because of consistent dermatoscopic morphology.