Search

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.)

Dermatologists often diagnose or rule out early melanoma by evaluating the follow-up dermoscopic images of skin lesions. However, existing algorithms for early melanoma diagnosis are developed using single time-point images of lesions. Ignoring the temporal, morphological changes of lesions can lead to misdiagnosis in borderline cases. In this study, we propose a framework for automated early melanoma diagnosis using sequential dermoscopic images. To this end, we construct our method in three steps. First, we align sequential dermoscopic images of skin lesions using estimated Euclidean transformations, extract the lesion growth region by computing image differences among the consecutive images, and then propose a spatio-temporal network to capture the dermoscopic changes from aligned lesion images and the corresponding difference images. Finally, we develop an early diagnosis module to compute probability scores of malignancy for lesion images over time. We collected 179 serial dermoscopic imaging data from 122 patients to verify our method. Extensive experiments show that the proposed model outperforms other commonly used sequence models. We also compared the diagnostic results of our model with those of seven experienced dermatologists and five registrars. Our model achieved higher diagnostic accuracy than clinicians (63.69% vs. 54.33%, respectively) and provided an earlier diagnosis of melanoma (60.7% vs. 32.7% of melanoma correctly diagnosed on the first follow-up images). These results demonstrate that our model can be used to identify melanocytic lesions that are at high-risk of malignant transformation earlier in the disease process and thereby redefine what is possible in the early detection of melanoma.

Background/objective: Diagnostic tools such as dermoscopy, sequential digital dermoscopy imaging (SDDI), total body photography (TBP) and automated diagnostic tools are available to assist in early melanoma diagnosis. The use, accessibility and barriers of dermoscopy have been well studied; however, there are few similar studies regarding SDDI, TBP and automated diagnostic tools. We aim to understand the use of these diagnostic aids amongst Australian general practitioners (GPs) and dermatologists., Methods: Between June 2019 and January 2020, GPs and dermatologists across Australia were invited to participate in an online survey. Surveys were distributed through GP and dermatology organisations., Results: A total of 227 survey responses were received, 175 from GPs and 52 from dermatologists. Amongst GPs, 44.6% worked in a skin cancer clinic. Dermoscopy was used at least occasionally by 98.9% of all GPs. SDDI was used by 93.6% of skin cancer GPs, 80.8% of dermatologists and 45.3% of generalist GPs. TBP was used or recommended by 77.1% of generalist GPs, 82.3% of skin cancer GPs and 86.5% of dermatologists. The most common barriers to the use of TBP were cost, limited accessibility, poor patient compliance, and time required for both patients and doctors. Very few clinicians reported using automated diagnostic tools. There was an interest in future diagnostic aids for melanoma in 88% of GPs and dermatologists., Conclusion: Dermoscopy, SDDI and TBP were commonly used by responding Australian skin cancer GPs and dermatologists in this survey. Automated diagnostic tools were not reported to be used routinely. Several barriers were identified for use of TBP., (© 2021 The Australasian College of Dermatologists.)

Abstract: We report an unusual case of a 59-year-old man with recurrent right ear melanoma resulting in perineural spread to the right greater auricular nerve. Direct perineural spread to the greater auricular nerve is not commonly reported in melanoma. Our case demonstrates perineural spread along the greater auricular nerve on 18F-FDG PET/CT and MRI. This finding was supported by intraneural invasion noted at the surgical margin of the wide local excision of the right helix melanoma. Resolution of FDG activity and improved MRI appearances of the right greater auricular nerve were seen after immunotherapy treatment., Competing Interests: Conflicts of interest and sources of funding: none declared., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

T-cell-mediated immunity has the ability to produce durable antimelanoma responses, resulting in improved survival of patients with advanced melanoma. Antigen presentation is a key determinant of T-cell responses. Gamma-interferon-inducible lysosomal thiol reductase (GILT) is critical for MHC class II-restricted presentation of multiple melanoma antigens to CD4+ T cells. However, GILT expression in melanoma has not been defined. We evaluated GILT and MHC class II expression in human primary and metastatic melanomas and nevi using immunohistochemical analysis. GILT staining in melanocytes was observed in 70% of primary and 58% of metastatic melanomas versus 0% of nevi. When present, the GILT staining intensity in melanocytes was typically faint. Both GILT and MHC class II expression were increased in melanocytes of primary and metastatic melanomas compared with nevi. GILT staining in antigen-presenting cells (APCs) was detected in 100% of primary and metastatic melanomas versus 31% of nevi, and it was typically intense. GILT expression was increased in APCs of primary and metastatic melanomas compared with nevi, whereas MHC class II had equivalent high expression in APCs of all melanocytic lesions. GILT staining in keratinocytes was detected in 67% of primary melanomas versus 14% of nevi and 6% of metastatic melanomas. GILT, but not MHC class II, expression was increased in keratinocytes of primary melanomas compared with nevi and metastases. GILT expression is anticipated to result in improved presentation of melanoma antigens and more effective antimelanoma T-cell responses. GILT expression may be a biomarker of immune recognition of melanoma.

Cancer-associated fibroblasts (CAFs) can play an important role in tumor growth by creating a tumor-promoting microenvironment. Models to study the role of CAFs in the tumor microenvironment can be helpful for understanding the functional importance of fibroblasts, fibroblasts from different tissues, and specific genetic factors in fibroblasts. Mouse models are essential for understanding the contributors to tumor growth and progression in an in vivo context. Here, a protocol in which cancer cells are mixed with fibroblasts and introduced into mice to develop tumors is provided. Tumor sizes over time and final tumor weights are determined and compared among groups. The protocol described can provide more insight into the functional role of CAFs in tumor growth and progression.