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This systematic review aims to evaluate the prevalence of reductions in psychosocial wellbeing among patient with melanoma in situ (MIS). It also aims to identify factors associated with psychosocial reactions, the instruments used to measure psychosocial outcomes, and to evaluate existing intervention programs for supporting this population. Search strategies for different databases including PubMed, Embase, Scopus, PsycINFO, and Web of Science were designed and implemented. A total of 2378 records were identified, resulting in 22 included papers. Various aspects of psychosocial wellbeing were evaluated in the reviewed articles, with fear of cancer recurrence being the most frequently investigated among patients diagnosed with melanoma. Only 2 of the 22 studies reported data for MIS patients, indicating no significant difference in psychosocial welling between patients with MIS and those at higher stages. Regarding interventional support, there is a notable lack of interventions specifically addressing the psychosocial needs of MIS patients. Our findings highlight a significant research gap on psychosocial wellbeing following a MIS diagnosis and suggest a shortage of targeted psychosocial interventions for this growing patient population. The observed variability in measuring psychosocial aspects presents challenges in identifying the essential components of effective interventions. Future research should prioritize employing mixed methodologies and addressing the unique needs of MIS patients., (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Keratinocyte carcinomas such as basal cell carcinomas and squamous cell carcinomas are a major burden affecting morbidity and mortality in solid organ transplant recipients (SOTRs). Best treatment includes frequent skin checks for early detection and surgery for high incidence of skin cancers. Sirolimus is an immunosuppressive drug which may reduce the burden of skin cancer but may be poorly tolerated when given orally. Topical sirolimus has been proven effective at reducing the burden of skin cancers in animal models, and its safety has long been established in children with tuberous sclerosis. A recent 12-week phase II trial of topical sirolimus suggested it was safe and effective at reducing the early signs of skin cancer in the absence of major side effects. The aim of the SiroSkin trial is to determine whether topical sirolimus can fill a major gap in current therapies by reducing the onset and number of new skin cancers thus reducing burden of disease and cost-effectiveness., Methods: Protocol for a multi-centred phase III, participant- and clinician assessor-blinded, placebo-controlled randomised trial in SOTRs. A minimum 146 participants randomised 1:1 will be treated with 1% topical sirolimus versus placebo applied to the face on a regular basis for 24 weeks. Participation is 24 months in total-24 weeks of treatment and 18 months of follow-up. Outcomes include the number of keratinocyte carcinomas at 24 weeks of treatment compared to placebo and then at 12 and 24 months after initiation of treatment. Analysis will be as per protocol and intention to treat., Discussion: The results of this trial will inform management strategies for skin cancers in SOTRs and provide evidence for cost-effectiveness., Trial Registration: Clinicaltrials.gov NCT05860881. Registered on June 15, 2023, and on anzctr.org.au (registration number NCT05860881)., Competing Interests: Declarations. Ethics approval and consent to participate {24}: The study was approved by Metro South Human Research Ethics Committee on 18 April 2023 (HREC/2023/QMS/95325). All participants will have to provide written informed consent before participation. Consent for publication {32}: This is not applicable. No identifying images or other personal or clinical details of participants are presented here or will be presented in reports of the trial results. The participant information materials and informed consent form are available from the corresponding author on request. All authors listed above meet the authorship criteria according to the latest guidelines of the International Committee of Medical Journal Editors, and all authors agree with the manuscript. Competing interests {28}: The authors declare that they have no competing interests., (© 2024. The Author(s).)

Importance: There is poor accuracy and reproducibility for the histopathologic diagnosis of melanocytic skin lesions, and the provision of clinical information may improve this., Objective: To examine the impact of clinical information on the histopathologic diagnosis of melanocytic skin lesions., Evidence Review: PubMed, Embase, and Cochrane Library were searched for new records published from January 2018 to January 2024. References included in the 2018 Cancer Council Australia evidence review were also screened, and forward and backward citation searches were conducted., Findings: From 2224 records screened, 162 full-text studies were assessed, and 7 studies were included. Studies included pathologists from Austria, Germany, the US, Italy, the UK, and Australia. Patient populations had a mean age of 43 to 55 years and a proportion of female participants of 23% to 63%. The risk of bias assessment demonstrated that all studies had domains at unclear or high risk of bias. Clinical images increased diagnostic certainty (3 studies) and agreement between pathologists (2 studies) led to diagnostic upgrades in 7.6% to 16.7% of interpretations. Clinical diagnosis on the pathology requisition form reduced the odds of missing a melanoma with progression (1 study), while more clinical elements on the form correlated with higher re-excision rates (1 study). Among patients with distant metastases on long-term follow-up, a prior consensus diagnosis of melanoma was established on histopathology alone., Conclusions and Relevance: Providing clinical information to pathologists may improve diagnostic confidence and interobserver agreement and result in upgrading of the histopathologic diagnosis. While providing the clinical diagnosis may prevent missing a progressive melanoma, more research is needed to determine the appropriateness of histopathology upgrading when clinical images are provided and the impacts on patient outcomes.

Competing Interests: Conflicts of interest H.P.S. is a shareholder of MoleMap NZ Limited and e-derm consult GmbH, and undertakes regular ­teledermatological reporting for both companies. H.P.S. is a Medical Consultant for Canfield Scientific Inc. and a Medical Advisor for First Derm.

Background: Cutaneous confocal microscopy (CCM) facilitates in vivo visualization of skin at a cellular level. Use of a "store and forward" approach for remote-CCM interpretation (remote-CCM) across multiple sites has not been tested and may increase access to noninvasive diagnosis., Objectives: To test the diagnostic accuracy and safety of remote-CCM., Methods: We prospectively recruited lesions selected for biopsy for skin malignancy across 5 Australian tertiary dermatology centers. CCM, clinical and dermatoscopy images were acquired prebiopsy and accessed by a cloud-based platform for interpretation by CCM readers. CCM diagnosis was compared with histopathology results., Results: Among the 201 lesions included, melanoma was the most common malignancy (34/72, 47.2%). Of the 89 lesions (44.8%) potentially "saved" from biopsy, 80 (90%) were truly benign lesions and 9 (10.1%) were missed malignant lesions of melanoma in situ (n = 7) and squamous cell carcinoma (SCC) (n = 2). No invasive melanomas were missed. Sensitivity of remote-CCM for detection of malignancy was 89% (95% CI, 79%-95%) and specificity was 64% (95% CI, 55%-73%)., Limitations: The study recruited from high-risk populations and excluded lesions that were not biopsied., Conclusions: Remote-CCM has comparable accuracy to bedside CCM and safely reduces unnecessary biopsies. Potential SCCs are not appropriate for remote-CCM. Follow-up of borderline melanocytic lesions is recommended., Competing Interests: Conflicts of interest Dr Soyer is a shareholder of MoleMap NZ Limited and e-derm-consult GmbH and undertakes regular teledermatological reporting for both companies, is a medical consultant for Canfield Scientific Inc, and is a medical adviser for First Derm. Dr Mar has received speaker fees from Novartis, Bristol Myers Squibb, Merck, and Janssen; has received conference support from L’Oreal; and has participated in Advisory Boards for MSD and L’Oreal. Dr Guitera has received honoraria form MetaOptima Pty and has received a travel stipend from L’Oreal. Dr Lo has received fees for professional services from SkylineDx BV and an honorarium for editorial duties from The British Association of Dermatologists. Drs Ho, Collgros, Sinz, Melhoranse-Gouveia, Gallo, Chew, Koutsis, Schwartz-Aldea, Herbert, Ferguson, Grace Gribbin, Martin, Smith, and Cust and Author Ip have no conflicts of interest to declare., (Copyright © 2024 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: In Australia, artificial intelligence (AI) is increasingly being used in the field of melanoma diagnosis. Early diagnosis is arguably the most important prognostic factor for melanoma survival. The use of digital monitoring of naevi, especially dysplastic naevi, might reduce the number of biopsies needed in managing patients at risk of melanoma, especially in patients with high naevi counts., Objective: This article discusses advances in imaging and early diagnosis including the use of AI in this process., Discussion: The benefits of performing biopsies must be balanced with the potential to cause harm. Whole-body imaging can assist with more accurate detection of changing lesions and enable clinicians to focus on lesions where change is detected.

POT1 is the second most frequently reported gene (after CDKN2A ) in familial melanoma. Pathogenic variants are associated with earlier onset and/or multiple primary melanomas (MPMs). To date, POT1 phenotypical reports have been largely restricted to associated malignancies, and description of the dermatological landscape has been limited. We identified 10 variants in n=18 of 384 (4.7%) unrelated individuals (n=13 MPMs; n=5 single primary melanomas) of European ancestry. Five variants were rare (minor allele frequency <0.001) or novel (two loss-of-function (LOF), one splice acceptor and two missense) and were predicted to be functionally significant, in five unrelated probands with MPMs (≥3 melanomas). We performed three-dimensional total body photography on both individuals with confirmed pathogenic LOF variants to characterise the dermatological phenotype. Total body naevus counts (≥2 mm diameter) were significantly higher (p=7.72 ×10-12 ) in carriers compared with a control population. Majority of naevi were on the probands' back and lower limb regions, where only mild to moderate ultraviolet (UV) damage was observed. Conversely, the head/neck region, where both probands exhibited severe UV damage, had comparably fewer naevi. We hypothesise that carriage of functionally significant POT1 variants is associated with increased naevus counts generally, and naevi >5 mm in diameter specifically and the location of these are independent of UV damage., Competing Interests: Competing interests: PS is a shareholder of MoleMap Limited and e-derm consult and undertakes regular teledermatological reporting for both companies. PS is a medical consultant for Canfield Scientific and Blaze Bioscience MoleMap Australia Limited, and a medical advisor for First Derm. No other authors have conflicts to declare., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: A portion of approximately 2-20% of cutaneous melanoma (CM) are diagnosed as amelanotic/hypopigmented melanoma (AHM) and represent a challenge for early diagnosis., Objectives: Since the degree to which somatic mutations and copy number aberrations (CNA) in genes associated with skin-lightening or albinism may contribute to the loss of tumour pigmentation in AHM samples has not yet been addressed, we have investigated loss of function mutations of key pigmentation genes in matched germline and AHM as well as pigmented melanoma (PM) tumour DNA samples., Methods: An analysis of clinical and histopathological characteristics together with whole exome sequencing data of 34 fresh frozen primary CM, graded according to the amount of pigmentation present was performed. Together with germline and somatic variant analysis, 30 samples were previously analysed for CNA changes. This study focussed on germline and somatic variants in the coding region of 16 genes known to be associated with albinism/hypopigmentation or variation in human pigmentation in all samples. Chromosomal regions encompassing these 16 genes were examined for DNA copy loss or gain., Results: The finding that red hair related MC1R and TYR R402Q loss of activity gene variant alleles and genotypes are associated with AHM was validated in this study. Germline AHM-related gene variants were enriched in 70% (n=7 of 10) of AHM patients vs 8.3% (n=2 of 24) of PM patients. This surprisingly high frequency of rare germline variants in AHM patients constitutes the "first hit" and confirms that AHM patients are more likely to be albinism allele carriers than patients with PM. Next, in CNA analysis of each tumour sample, 50% (n=4 of 8) AHM samples with a pigmentation gene variant had LOH in the region containing the corresponding gene, and 25% (=2 of 8) had loss-of-heterozygosity (LOH) in chromosomal regions of two AHM-related genes., Conclusions: This study proposes that the likely molecular mechanism for development of amelanogenesis in AHM is carriage of an albinism/hypopigmentation allele followed by LOH of the corresponding gene in the tumour., (© The Author(s) 2024. Published by Oxford University Press on behalf of British Association of Dermatologists.)

AI image classification algorithms have shown promising results when applied to skin cancer detection. Most public skin cancer image datasets are comprised of dermoscopic photos and are limited by selection bias, lack of standardization, and lend themselves to development of algorithms that can only be used by skilled clinicians. The SLICE-3D ("Skin Lesion Image Crops Extracted from 3D TBP") dataset described here addresses those concerns and contains images of over 400,000 distinct skin lesions from seven dermatologic centers from around the world. De-identified images were systematically extracted from sensitive 3D Total Body Photographs and are comparable in optical resolution to smartphone images. Algorithms trained on lower quality images could improve clinical workflows and detect skin cancers earlier if deployed in primary care or non-clinical settings, where photos are captured by non-expert physicians or patients. Such a tool could prompt individuals to visit a specialized dermatologist. This dataset circumvents many inherent limitations of prior datasets and may be used to build upon previous applications of skin imaging for cancer detection., (© 2024. The Author(s).)

In recent years, there has been a surge in the development of AI-based Software as a Medical Device (SaMD), particularly in visual specialties such as dermatology. In Australia, the Therapeutic Goods Administration (TGA) regulates AI-based SaMD to ensure its safe use. Proper labelling of these devices is crucial to ensure that healthcare professionals and the general public understand how to use them and interpret results accurately. However, guidelines for labelling AI-based SaMD in dermatology are lacking, which may result in products failing to provide essential information about algorithm development and performance metrics. This review examines existing labelling guidelines for AI-based SaMD across visual medical specialties, with a specific focus on dermatology. Common recommendations for labelling are identified and applied to currently available dermatology AI-based SaMD mobile applications to determine usage of these labels. Of the 21 AI-based SaMD mobile applications identified, none fully comply with common labelling recommendations. Results highlight the need for standardized labelling guidelines. Ensuring transparency and accessibility of information is essential for the safe integration of AI into health care and preventing potential risks associated with inaccurate clinical decisions., (© 2024 The Authors. Australasian Journal of Dermatology published by John Wiley & Sons Australia, Ltd on behalf of Australasian College of Dermatologists.)

Artificial intelligence (AI) algorithms for skin lesion classification have reported accuracy at par with and even outperformance of expert dermatologists in experimental settings. However, the majority of algorithms do not represent real-world clinical approach where skin phenotype and clinical background information are considered. We review the current state of AI for skin lesion classification and present opportunities and challenges when applied to total body photography (TBP). AI in TBP analysis presents opportunities for intrapatient assessment of skin phenotype and holistic risk assessment by incorporating patient-level metadata, although challenges exist for protecting patient privacy in algorithm development and improving explainable AI methods., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: A common terminology for diagnosis is critically important for clinical communication, education, research and artificial intelligence. Prevailing lexicons are limited in fully representing skin neoplasms., Objectives: To achieve expert consensus on diagnostic terms for skin neoplasms and their hierarchical mapping., Methods: Diagnostic terms were extracted from textbooks, publications and extant diagnostic codes. Terms were hierarchically mapped to super-categories (e.g. 'benign') and cellular/tissue-differentiation categories (e.g. 'melanocytic'), and appended with pertinent-modifiers and synonyms. These terms were evaluated using a modified-Delphi consensus approach. Experts from the International-Skin-Imaging-Collaboration (ISIC) were surveyed on agreement with terms and their hierarchical mapping; they could suggest modifying, deleting or adding terms. Consensus threshold was >75% for the initial rounds and >50% for the final round., Results: Eighteen experts completed all Delphi rounds. Of 379 terms, 356 (94%) reached consensus in round one. Eleven of 226 (5%) benign-category terms, 6/140 (4%) malignant-category terms and 6/13 (46%) indeterminate-category terms did not reach initial agreement. Following three rounds, final consensus consisted of 362 terms mapped to 3 super-categories and 41 cellular/tissue-differentiation categories., Conclusions: We have created, agreed upon, and made public a taxonomy for skin neoplasms and their hierarchical mapping. Further study will be needed to evaluate the utility and completeness of the lexicon., (© 2024 European Academy of Dermatology and Venereology.)

Background/objectives: Artificial intelligence (AI) holds remarkable potential to improve care delivery in dermatology. End users (health professionals and general public) of AI-based Software as Medical Devices (SaMD) require relevant labelling information to ensure that these devices can be used appropriately. Currently, there are no clear minimum labelling requirements for dermatology AI-based SaMDs., Methods: Common labelling recommendations for AI-based SaMD identified in a recent literature review were evaluated by an Australian expert panel in digital health and dermatology via a modified Delphi consensus process. A nine-point Likert scale was used to indicate importance of 10 items, and voting was conducted to determine the specific characteristics to include for some items. Consensus was achieved when more than 75% of the experts agreed that inclusion of information was necessary., Results: There was robust consensus supporting inclusion of all proposed items as minimum labelling requirements; indication for use, intended user, training and test data sets, algorithm design, image processing techniques, clinical validation, performance metrics, limitations, updates and adverse events. Nearly all suggested characteristics of the labelling items received endorsement, except for some characteristics related to performance metrics. Moreover, there was consensus that uniform labelling criteria should apply across all AI categories and risk classes set out by the Therapeutic Goods Administration., Conclusions: This study provides critical evidence for setting labelling standards by the Therapeutic Goods Administration to safeguard patients, health professionals, consumers, industry, and regulatory bodies from AI-based dermatology SaMDs that do not currently provide adequate information about how they were developed and tested., (© 2024 The Authors. Australasian Journal of Dermatology published by John Wiley & Sons Australia, Ltd on behalf of Australasian College of Dermatologists.)

Introduction: Artificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However, clinical application is limited when algorithms are presented with 'untrained' or out-of-distribution lesion categories, often misclassifying benign lesions as malignant, or misclassifying malignant lesions as benign. Another limitation often raised is the lack of clinical context (e.g., medical history) used as input for the AI decision process. The increasing use of Total Body Photography (TBP) in clinical examinations presents new opportunities for AI to perform holistic analysis of the whole patient, rather than a single lesion. Currently there is a lack of existing literature or standards for image annotation of TBP, or on preserving patient privacy during the machine learning process., Methods: This protocol describes the methods for the acquisition of patient data, including TBP, medical history, and genetic risk factors, to create a comprehensive dataset for machine learning. 500 patients of various risk profiles will be recruited from two clinical sites (Australia and Spain), to undergo temporal total body imaging, complete surveys on sun behaviors and medical history, and provide a DNA sample. This patient-level metadata is applied to image datasets using DICOM labels. Anonymization and masking methods are applied to preserve patient privacy. A two-step annotation process is followed to label skin images for lesion detection and classification using deep learning models. Skin phenotype characteristics are extracted from images, including innate and facultative skin color, nevi distribution, and UV damage. Several algorithms will be developed relating to skin lesion detection, segmentation and classification, 3D mapping, change detection, and risk profiling. Simultaneously, explainable AI (XAI) methods will be incorporated to foster clinician and patient trust. Additionally, a publicly released dataset of anonymized annotated TBP images will be released for an international challenge to advance the development of new algorithms using this type of data., Conclusion: The anticipated results from this protocol are validated AI-based tools to provide holistic risk assessment for individual lesions, and risk stratification of patients to assist clinicians in monitoring for skin cancer., Competing Interests: HS is a shareholder of MoleMap NZ Limited and e-derm consult GmbH and undertakes regular teledermatological reporting for both companies, Medical Consultant for Canfield Scientific Inc., Blaze Bioscience Inc., and a Medical Advisor for First Derm. JM and SP are co-founders of Diagnosis Dermatologica and Athena Care and investors in Dermavision. JM received honorarium from Canfield Scientific for consultancy and Fotofinder for educational activities. NA was employed by V7. BD was employed by Canfield Scientific Inc. SG was employed by ISAHIT. PF and HN were employed by Torus Actions & Belle.ai. AG was employed by IBM Research. SG-V and JQ were employed by Coronis Computing SL. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Primiero, Betz-Stablein, Ascott, D’Alessandro, Gaborit, Fricker, Goldsteen, González-Villà, Lee, Nazari, Nguyen, Ntouskos, Pahde, Pataki, Quintana, Puig, Rezze, Garcia, Soyer and Malvehy.)

Background: Actinic keratoses (AK) are pre-malignant skin lesions caused by chronic sun exposure. Progression from an AK to intraepidermal carcinoma (IEC) and a cutaneous squamous cell carcinoma (SCC) is well known but the rate of transformation to an invasive SCC is highly variable. Since no definitive biomarkers are available, treatment decisions are made ad hoc., Objectives: To fully characterise our AK to SCC progression series, we performed microRNA (miRNA) microarray expression profiling of normal and photodamaged skin, as well as AKs, IEC, and invasive SCCs., Methods: The study recruited 27 patients who donated fresh biopsies of normal skin, photodamaged skin, AK, IEC, and SCC ( n  = 67 specimens). All miRbase (v.21) miRNAs were profiled to identify miRNAs related to SCC progression. miRNAs were validated using qRT-PCR and in vitro phenotypic assays., Results: There were 234 robustly expressed miRNAs across the tissue collection, which resulted in 20 miRNA that were differentially expressed ((cor) p  ≤ 0.05 and ≥ 10 fold) between normal skin and SCC. Hierarchical clustering all samples illustrated that AKs, IEC, and SCCs were largely indistinguishable, which confirms the premalignant status of an AK. A panel of miRNAs showed significant dysregulation between normal and photodamaged skin and AK. Importantly, we found miR-34a-5p and miR-31-5p had significant differential expression between AKs and IEC and IEC and SCC respectively. Phenotypic assays determined that the miR-31 duplex had opposing effects on SCC cell lines which suggests that dysregulation of this duplex may be related to the dynamic control of progression of transformed keratinocytes., Conclusions: This study confirmed the continuum of AK with IEC and SCC highlighting that miRNA expression plays a role in keratinocyte transformation. Development of our putative miRNA biomarker candidates is warranted to aid in clinical management of patients experiencing high AK load to determine the most appropriate treatment., Competing Interests: HPS is a shareholder of MoleMap NZ Limited and e‐derm consult GmbH and undertakes regular teledermatological reporting for both companies. HPS is a Medical Consultant for Canfield Scientific Inc., MetaOptima and Revenio Research Oy and a Medical Advisor for First Derm., (© 2024 The Authors. Skin Health and Disease published by John Wiley & Sons Ltd on behalf of British Association of Dermatologists.)

Terahertz (THz) imaging has long held promise for skin cancer detection but has been hampered by the lack of practical technological implementation. In this article, we introduce a technique for discriminating several skin pathologies using a coherent THz confocal system based on a THz quantum cascade laser. High resolution in vivo THz images (with diffraction limited to the order of 100  μ m) of several different lesion types were acquired and compared against one another using the amplitude and phase values. Our system successfully separated pathologies using a combination of phase and amplitude information and their respective surface textures. The large scan field (50 × 40 mm) of the system allows macroscopic visualization of several skin lesions in a single frame. Utilizing THz imaging for dermatological assessment of skin lesions offers substantial additional diagnostic value for clinicians. THz images contain information complementary to the information contained in the conventional digital images., Competing Interests: X.Q., K.B., J.T., T.G., P.D., D.I., E.H.L., M.S.S., H.P.S., and A.D.R. are authors of relevant patents. T.M. is an executive of OscillaDx Pty Ltd. H.P.S. is a shareholder of MoleMap NZ Limited and e-derm consult GmbH and undertakes regular teledermatological reporting for both companies. H.P.S. is a Medical Consultant for Canfield Scientific Inc, Blaze Bioscience Inc, and a Medical Advisor for First Derm. The other authors declare that there are no conflicts of interest related to this article. The research was conducted to refine and develop the imaging technology. The authors declare that this study received funding from OscillaDx Pty Ltd, Brisbane, with involvement in the study design., (© 2024 Author(s).)

Early detection of melanoma is critical to good patient outcomes, but we still know little about the mechanisms of early melanoma development. Normal epidermis has many of the sequence variants and genetic architecture disruptions found in both benign nevi, melanomas, and other skin cancers, yet continues to behave more or less normally. One hypothesis is that many melanocytes in this context are "tumor competent" but are regulated by the microenvironment provided by the surrounding keratinocytes to inhibit progress to nevi or melanoma. There is evidence of accumulating disorder in several measures of the genomic and epigenomic landscape from normal skin through nevi to melanoma that may be key to promoting nevogenesis and melanomagenesis., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, we attempted to evaluate agreement among experts on exemplar images not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanoma-specific features. These features were peppering/granularity (0.91), shiny white streaks (0.89), typical pigment network (0.83), blotch irregular (0.82), negative network (0.81), irregular globules (0.78), dotted vessels (0.77), and blue-whitish veil (0.76). By utilizing an exemplar dataset, a good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication, and machine learning experiments., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

While the average lifetime risk of melanoma worldwide is approximately 3%, those with inherited high-penetrance mutations face an increased lifetime risk of 52-84%. In countries of low melanoma incidence, such as in Southern Europe, familial melanoma genetic testing may be warranted when there are two first degree relatives with a melanoma diagnosis. Testing criteria for high incidence countries such as USA, or with very-high incidence, such as Australia and New Zealand, would require a threshold of 3 to 4 affected family members. A mutation in the most common gene associated with familial melanoma, CDKN2A, is identified in approximately 10-40% of those meeting testing criteria. However, the use of multi-gene panels covering additional less common risk genes can significantly increase the diagnostic yield. Currently, genetic testing for familial melanoma is typically conducted by qualified genetic counsellors, however with increasing demand on testing services and high incidence rate in certain countries, a mainstream model should be considered. With appropriate training, dermatologists are well placed to identify high risk individuals and offer melanoma genetic test in dermatology clinics. Genetic testing should be given in conjunction with pre- and post-test consultation. Informed patient consent should cover possible results, the limitations and implications of testing including inconclusive results, and potential for genetic discrimination. Previous studies reporting on participant outcomes of genetic testing for familial melanoma have found significant improvements in both sun protective behavior and screening frequency in mutation carriers.

Background: Nodular melanoma (NM) is a challenge to diagnose early due to its rapid growth and more atypical clinical presentation, making it the largest contributor to melanoma mortality., Objectives: Our study aim was to perform a rare-variant allele (RVA) analysis of whole-exome sequencing of patients with NM and non-NM (minor allele frequency ≤ 1% non-Finnish European) for a set of 500 candidate genes potentially implicated in melanoma., Methods: This study recruited 131 participants with NM and 194 with non-NM from South-east Queensland and patients with NM from Victoria to perform a comparative analysis of possible genetic differences or similarities between the two melanoma cohorts., Results: Phenotypic analysis revealed that a majority of patients diagnosed with NM were older males with a higher frequency of fair skin and red hair than is seen in the general population. The distribution of common melanoma polygenic risk scores was similar in patients with NM and non-NM, with over 28% in the highest quantile of scores. There was also a similar frequency of carriage of familial/high-penetrant melanoma gene and loss-of-function variants. We identified 39 genes by filtering 500 candidate genes based on the greatest frequency in NM compared with non-NM cases. The genes with RVAs of greatest frequency in NM included PTCH1, ARID2 and GHR. Rare variants in the SMO gene, which interacts with PTCH1 as ligand and receptor, were also identified, providing evidence that the Hedgehog pathway may contribute to NM risk. There was a cumulative effect in carrying multiple rare variants in the NM-associated genes. A 14.8-fold increased ratio for NM compared with non-NM was seen when two RVAs of the 39 genes were carried by a patient., Conclusions: This study highlights the importance of considering frequency of RVA to identify those at risk of NM in addition to known high penetrance genes., Competing Interests: Conflicts of interest H.P.S. is a shareholder of MoleMap NZ Limited and e-derm consult GmbH and undertakes regular teledermatological reporting for both companies. H.P.S. is a medical consultant for Canfield Scientific Inc. and MoleMap Australia Pty Ltd, and a medical advisor for First Derm. V.J.M. has received speaker fees from Bristol Myers Squibb, Janssen, Merck and Novartis, and has participated in advisory boards for L’Oreal and MSD. The other authors have no conflicts of interest to declare., (© The Author(s) 2023. Published by Oxford University Press on behalf of British Association of Dermatologists.)

MITF E318K moderates melanoma risk. Only five MITF E318K homozygous cases have been reported to date, one in association with melanoma. This novel report uses 3D total-body-photography (TBP) to describe the dermatological phenotype of a homozygous MITF E318K individual. The case, a 32-year-old male, was diagnosed with his first of six primary melanomas at 26 years of age. Five melanomas were located on the back and one in the groin. Two were superficial spreading. Three arose from pre-existing naevi and one was a rare naevoid melanoma. 3D-TBP revealed a high naevus count (n = 162) with pigmentation varying from light to dark. Most naevi generally (n = 90), and large (>5 mm diameter) and clinically atypical naevi specifically were located on the back where sun damage was mild. In contrast, naevi count was low (n = 25 total) on the head/neck and lower limbs where sun damage was severe. Thus, melanoma location correlated with naevi density, rather than degree of sun damage. In addition to the MITF E318K homozygosity, there was heterozygosity for four other moderate-risk variants, which may contribute to melanoma risk. Further research is warranted to explore whether melanomas in E318K heterozygous and other homozygotes coincide with regions of high naevi density as opposed to sun damage. This could inform future melanoma screening/surveillance., (© 2023 The Authors. Pigment Cell & Melanoma Research published by John Wiley & Sons Ltd.)

Background: As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer., Objective: This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI-assisted smartphone applications (apps) and web-based services for skin diseases with emphasis on skin cancer detection., Methods: An initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance., Results: Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non-medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web-based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users., Conclusions: The utilisation of AI-assisted smartphone apps and web-based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of these apps into clinical practice., (© 2023 The Authors. Journal of the European Academy of Dermatology and Venereology published by John Wiley & Sons Ltd on behalf of European Academy of Dermatology and Venereology.)

Introduction: Three-dimensional (3D) total body photography may improve early detection of melanoma and facilitate surveillance, leading to better prognosis and lower healthcare costs. The Australian Centre of Excellence in Melanoma Imaging and Diagnosis (ACEMID) cohort study will assess long-term outcomes from delivery of a precision strategy of monitoring skin lesions using skin surface imaging technology embedded into health services across Australia., Methods and Analysis: A prospective cohort study will enrol 15 000 participants aged 18 years and above, across 15 Australian sites. Participants will attend study visits according to their melanoma risk category: very high risk, high risk or low/average risk, every 6, 12 and 24 months, respectively, over 3 years. Participants will undergo 3D total body photography and dermoscopy imaging at study visits. A baseline questionnaire will be administered to collect sociodemographic, phenotypic, quality of life and sun behaviour data. A follow-up questionnaire will be administered every 12 months to obtain changes in sun behaviour and quality of life. A saliva sample will be collected at the baseline visit from a subsample., Ethics and Dissemination: The ACEMID cohort study was approved by the Metro South Health Human Research Ethics Committee (approval number: HREC/2019/QMS/57206) and the University of Queensland Human Research Ethics Committee (approval number: 2019003077). The findings will be reported through peer-reviewed and lay publications and presentations at conferences., Trial Registration Number: ACTRN12619001706167., Competing Interests: Competing interests: HPS is a shareholder of MoleMap NZ and E-derm-Consult and undertakes regular teledermatological reporting for both companies. HPS is a Medical Consultant for Canfield Scientific, Blaze Bioscience and a Medical Advisor for First Derm. VM has received speakers fees from Novartis, Bristol Myers Squibb, Merck, Janssen and conference sponsorship from L’Oreal. PF-P has consulted for Leo, Amgen, Abbvie, UCB, Sanofi, Janssen, Novartis, BMS, MSD, Pfizer and Lilly. PF-P has received speakers fees from Janssen, Leo, Amgen, Sanofi, Lilly, Abbvie, UCB, Novartis, Merck and Pfizer., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Competing Interests: Competing interests: PS is a shareholder of MoleMap Limited and e-derm consult and undertakes regular teledermatological reporting for both companies. PS is a medical consultant for Canfield Scientific, Blaze Bioscience and MoleMap Australia Limited, and a medical advisor for First Derm.

Background: Immunosuppressive drugs such as tacrolimus have revolutionized our ability to transplant organs between individuals. Tacrolimus acts systemically to suppress the activity of T-cells within and around transplanted organs. However, tacrolimus also suppresses T-cell function in the skin, contributing to a high incidence of skin cancer and associated mortality and morbidity in solid organ transplant recipients. Here, we aimed to identify a compound capable of re-establishing antitumor T-cell control in the skin despite the presence of tacrolimus., Methods: In this study, we performed time-resolved fluorescence resonance energy transfer to identify molecules capable of antagonizing the interaction between tacrolimus and FKBP12. The capacity of these molecules to rescue mouse and human T-cell function in the presence of tacrolimus was determined in vitro, and the antitumor effect of the lead compound, Q-2361, was assessed in "regressor" models of skin cancer in immunosuppressed mice. Systemic CD8 T-cell depletion and analyses of intratumoral T-cell activation markers and effector molecule production were performed to determine the mechanism of tumor rejection. Pharmacokinetic studies of topically applied Q-2361 were performed to assess skin and systemic drug exposure., Results: Q-2361 potently blocked the interaction between tacrolimus and FKBP12 and reversed the inhibition of the nuclear factor of activated T cells activation by tacrolimus following T-cell receptor engagement in human Jurkat cells. Q-2361 rescued T-cell function in the presence of tacrolimus, rapamycin, and everolimus. Intratumoral injection of Q-2361-induced tumor regression in mice systemically immune suppressed with tacrolimus. Mechanistically, Q-2361 treatment permitted T-cell activation, proliferation, and effector function within tumors. When CD8 T cells were depleted, Q-2361 could not induce tumor regression. A simple solution-based Q-2361 topical formulation achieved high and sustained residence in the skin with negligible drug in the blood., Conclusions: Our findings demonstrate that the local application of Q-2361 permits T-cells to become activated driving tumor rejection in the presence of tacrolimus. The data presented here suggests that topically applied Q-2361 has great potential for the reactivation of T-cells in the skin but not systemically, and therefore represents a promising strategy to prevent or treat skin malignancies in immunosuppressed organ transplant recipients., Competing Interests: Competing interests: The use of Q-2361 as disclosed in this study has been patented (WO2021248189), with JWW, BWD, AH, T-AC, RP, and KB as coinventors. All other authors declare that they have no competing interests., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Sentinel node biopsy (SNB) has evolved from offering staging and prognostication to a procedure that guides therapeutic management. The aim was to evaluate the rate of SNB for patients with high-risk melanoma and assess factors that may have impacted on the procedure being performed., Methods: Data of patients with primary invasive cutaneous melanoma from 01 January 2009 to 31 December 2019 were obtained from the Queensland Oncology Repository. High-risk melanoma was defined as ≥0.8 mm thick or < 0.8 mm with ulceration present (AJCC eighth edition pT1 b -pT 4 )., Results: 14 006 (33.8%) of 41 412 patients diagnosed with cutaneous invasive melanoma were in the high-risk group. 2923(20.9%) patients had SNB, with the rate increasing from 14.2% (2009) to 36.8% (2019) (P = 0.002), and an increasing proportion being performed in public hospitals over the 11 year period (P = 0.02). Older age (OR0.96 (0.959-0.964) (P < 0.001)), female (OR0.91 (0.830-0.998) (P = 0.03)), head and neck primary (OR0.38 (0.33-0.45) (P < 0.001)), and pT 1b (OR0.22 (0.19-0.25) (P < 0.001)) were factors associated with SNB not being performed. Travel out of the Hospital and Health Services of residence for SNB occurred in 26.2%. Although the travel rate decreased from 24.7% (2009) to 23.0% (2019) (P = 0.04), the absolute number increased due to the increase in SNB rate. Those most likely to travel were younger, from remote areas, or from affluent backgrounds., Conclusion: In this first Australian population-based study, there was an increased adherence to SNB guideline, although overall SLNB rates remain low, with nearly 2/3 of eligible cases not having the procedure in 2019. Although travel rates decreased marginally, the overall number increased. This study highlights the crucial need to further improve access to SNB for melanoma surgery for the Queensland population., (© 2023 Royal Australasian College of Surgeons.)

We investigated whether human preferences hold the potential to improve diagnostic artificial intelligence (AI)-based decision support using skin cancer diagnosis as a use case. We utilized nonuniform rewards and penalties based on expert-generated tables, balancing the benefits and harms of various diagnostic errors, which were applied using reinforcement learning. Compared with supervised learning, the reinforcement learning model improved the sensitivity for melanoma from 61.4% to 79.5% (95% confidence interval (CI): 73.5-85.6%) and for basal cell carcinoma from 79.4% to 87.1% (95% CI: 80.3-93.9%). AI overconfidence was also reduced while simultaneously maintaining accuracy. Reinforcement learning increased the rate of correct diagnoses made by dermatologists by 12.0% (95% CI: 8.8-15.1%) and improved the rate of optimal management decisions from 57.4% to 65.3% (95% CI: 61.7-68.9%). We further demonstrated that the reward-adjusted reinforcement learning model and a threshold-based model outperformed naïve supervised learning in various clinical scenarios. Our findings suggest the potential for incorporating human preferences into image-based diagnostic algorithms., (© 2023. The Author(s).)

Importance: The extent to which major high-risk features of squamous cell carcinomas (SCCs) in organ transplant recipients (OTRs) differ from SCCs in the general population is not known., Objective: To quantify the relative frequency of perineural invasion, invasion below the dermis, lack of cellular differentiation, and tumor diameter greater than 20 mm in SCCs in OTRs and the general population, by anatomic site., Design, Setting, and Participants: This dual-cohort study in Queensland, Australia, included a cohort of OTRs at high risk of skin cancer ascertained from 2012 to 2015 (Skin Tumours in Allograft Recipients [STAR] study) and a population-based cohort ascertained from 2011 (QSkin Sun and Health Study). The STAR study comprised population-based lung transplant recipients and kidney and liver transplant recipients at high risk of skin cancer recruited from tertiary centers and diagnosed with histopathologically confirmed SCC from 2012 to 2015. The QSkin participants were recruited from Queensland's general adult population, and primary SCCs diagnosed from 2012 to 2015 were ascertained through Medicare (national health insurance scheme) and linked with histopathology records. Data analysis was performed from July 2022 to April 2023., Main Outcomes and Measures: Prevalence ratio (PR) of head/neck location, perineural invasion, tumor invasion to/beyond subcutaneous fat, poor cellular differentiation, and tumor diameter greater than 20 mm among SCCs in OTRs vs the general population., Results: There were 741 SCCs excised from 191 OTRs (median [IQR] age, 62.7 [56.7-67.1] years; 149 [78.0%] male) and 2558 SCCs from 1507 persons in the general population (median [IQR] age, 63.7 [58.0-68.8] years; 955 [63.4%] male). The SCCs developed most frequently on the head/neck in OTRs (285, 38.6%), but on arms/hands in the general population (896, 35.2%) (P < .001). After adjusting for age and sex, perineural invasion was more than twice as common in OTRs as in population cases (PR, 2.37; 95% CI, 1.70-3.30), as was invasion to/beyond subcutaneous fat (PR, 2.37; 95% CI, 1.78-3.14). Poorly vs well-differentiated SCCs were more than 3-fold more common in OTRs (PR, 3.45; 95% CI, 2.53-4.71), and prevalence of tumors greater than 20 mm vs 20 mm or smaller was moderately higher in OTRs (PR, 1.52; 95% CI, 1.08-2.12)., Conclusions and Relevance: In this dual-cohort study, SCCs in OTRs had significantly worse prognostic features than SCCs in the general population, reinforcing the necessity of early diagnosis and definitive management of SCCs in OTRs.

Artificial intelligence algorithms to classify melanoma are dependent on their training data, which limits generalizability. The objective of this study was to compare the performance of an artificial intelligence model trained on a standard adult-predominant dermoscopic dataset before and after the addition of additional pediatric training images. The performances were compared using held-out adult and pediatric test sets of images. We trained two models: one (model A) on an adult-predominant dataset (37,662 images from the International Skin Imaging Collaboration) and the other (model A+P) on an additional 1,536 pediatric images. We compared performance between the two models on adult and pediatric held-out test images separately using the area under the receiver operating characteristic curve. We then used Gradient-weighted Class Activation Maps and background skin masking to understand the contributions of the lesion versus background skin to algorithm decision making. Adding images from a pediatric population with different epidemiological and visual patterns to current reference standard datasets improved algorithm performance on pediatric images without diminishing performance on adult images. This suggests a way that dermatologic artificial intelligence models can be made more generalizable. The presence of background skin was important to the pediatric-specific improvement seen between models. Our study highlights the importance of carefully curated and labeled data from diverse inputs to improve the generalizability of AI models for dermatology, in this case applied to dermoscopic images of adult and pediatric lesions to improve melanoma detection., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Risk prediction tools have been developed for keratinocyte cancers (KCs) to effectively categorize individuals with different levels of skin cancer burden. Few have been clinically validated nor routinely used in clinical settings., Objectives: To assess whether risk prediction tool categories associate with interventions including chemoprophylaxis for skin cancer, and health-care costs in a dermatologist-run screening clinic., Methods: Adult participants who presented to a walk-in screening facility were invited to participate. A self-completed KC risk prediction tool was used to classify participants into one of the five risk categories. Participants subsequently underwent full skin examination by a dermatologist. Dermatological interventions and skin cancer-related medical prescriptions were documented. Total health-care costs, both to the health-care system and patients were evaluated., Results: Of the 507 participants recruited, 5-fluorouracil cream and nicotinamide were more frequently prescribed in the higher risk groups as chemoprophylaxis (p < 0.005). A significant association with high predicted risk was also observed in the use of cryotherapy and curettage and cautery (p < 0.05). The average health-care costs associated with a skin check visit increased from $90 ± 37 (standard deviation) in the lowest risk group to $149 ± 97 in the highest risk group (p < 0.0001)., Conclusions: We observed a positive association between higher predicted risk of skin cancer and the prescription of chemoprophylaxis and health-care costs involved with opportunistic community skin cancer screening. A clinical use of risk stratification may be to provide an opportunity for clinicians to discuss skin cancer prevention and chemoprophylaxis with individual patients., (© 2023 The Authors. Australasian Journal of Dermatology published by John Wiley & Sons Australia, Ltd on behalf of Australasian College of Dermatologists.)