International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling.

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.

Recycled melanoma-secreted melanosomes regulate tumor-associated macrophage diversification.

Extracellular vesicles (EVs) are important mediators of communication between cells. Here, we reveal a new mode of intercellular communication by melanosomes, large EVs secreted by melanocytes for melanin transport. Unlike small EVs, which are disintegrated within the receiver cell, melanosomes stay intact within them, gain a unique protein signature, and can then be further transferred to another cell as "second-hand" EVs. We show that melanoma-secreted melanosomes passaged through epidermal keratinocytes or dermal fibroblasts can be further engulfed by resident macrophages. This process leads to macrophage polarization into pro-tumor or pro-immune cell infiltration phenotypes. Melanosomes that are transferred through fibroblasts can carry AKT1, which induces VEGF secretion from macrophages in an mTOR-dependent manner, promoting angiogenesis and metastasis in vivo. In melanoma patients, macrophages that are co-localized with AKT1 are correlated with disease aggressiveness, and immunotherapy non-responders are enriched in macrophages containing melanosome markers. Our findings suggest that interactions mediated by second-hand extracellular vesicles contribute to the formation of the metastatic niche, and that blocking the melanosome cues of macrophage diversification could be helpful in halting melanoma progression.

[COMPREHENSIVE GUIDELINES AND INDICATIONS FOR DIGITAL MONITORING OF PATIENTS AT HIGH-RISK FOR MELANOMA: A POSITION PAPER BY THE ISRAELI ASSOCIATION FOR DERMATOLOGY].

INTRODUCTION: Early detection may lead to reduced morbidity and mortality from melanoma. This study aims to establish guidelines for selecting patients suitable for digital monitoring of skin lesions. METHODS: A literature review was conducted, followed by consensus among experts appointed by the Israeli Dermatology Association. RESULTS: Two effective methods for early melanoma diagnosis were identified: Total-body photography (TBP) and digital dermoscopy. TBP involves capturing clinical images of the entire skin area for long-term monitoring (6-12 months). Digital dermoscopy focuses on close-up images of distinct lesions for short-term monitoring (3-4 months). Various risk factors for melanoma were identified, including genetic and familial factors, as well as demographic and phenotypic characteristics. Based on these risk factors and feasibility of clinical follow-up, a comprehensive list of indications for TBP was developed, categorized into three groups based on the expected level of benefit. Digital dermoscopy surveillance is recommended for patients with flat or slightly raised skin lesions showing dermoscopic features that do not definitively indicate melanoma. DISCUSSION: TBP significantly improves early melanoma detection, enhancing sensitivity and specificity while reducing unnecessary biopsies. However, due to its high cost and limited coverage by the Israeli public health care system, prioritizing patients who would benefit most from TBP is crucial. The compiled list of indications aligns with international recommendations and provides further details within the article.

Perifollicular linear projections: A dermatoscopic criterion for the diagnosis of lentigo maligna on the face.

BACKGROUND: Lentigo maligna (LM) can mimic benign, flat, pigmented lesions and can be challenging to diagnose. OBJECTIVE: To describe a new dermatoscopic feature termed "perifollicular linear projections (PLP)" as a diagnostic criterion for LM on the face. METHODS: Retrospective study on reflectance confocal microscopy and dermatoscopy images of flat facial pigmented lesions originating from 2 databases. PLP were defined as short, linear, pigmented projections emanating from hair follicles. Dermatoscopy readers were blinded to the final histopathologic diagnosis. RESULTS: From 83 consecutive LMs, 21/83 (25.3%) displayed "bulging of hair follicles" on reflectance confocal microscopy and 18 of these 21 (85.7%), displayed PLP on dermatoscopy. From a database of 2873 consecutively imaged and biopsied lesions, 252 flat-pigmented facial lesions were included. PLP was seen in 47/76 melanomas (61.8%), compared with 7/176 lesions (3.9%) with other diagnosis (P < .001). The sensitivity was 61.8% (95% CI, 49.9%-72.7%), specificity 96.0% (95% CI, 92.9%-98.4%). PLP was independently associated with LM diagnosis on multivariate analysis (OR 26.1 [95% CI, 9.6%-71.0]). LIMITATIONS: Retrospective study. CONCLUSION: PLP is a newly described dermatoscopic criterion that may add specificity and sensitivity to the early diagnosis of LM located on the face. We postulate that PLP constitutes an intermediary step in the LM progression model.

[MOCK MOLE: PRODUCING SYNTHETIC IMAGES THAT RECAPITULATE CONFOCAL PATTERNS OF MELANOCYTIC NEVI VIA DEEP-LEARNING MODELS].

INTRODUCTION: Melanocytic nevi present microscopic patterns, which differ in their associated melanoma risk, and can be non-invasively recognized under Reflectance Confocal Microscopy (RCM). AIMS: To train a Generative Adversarial Network (GAN) deep-learning model to produce synthetic images that recapitulate RCM patterns of nevi, enabling reliable classification by human readers and by a Convolutional Neural Network (CNN) computer model. METHODS: A dataset of RCM images of nevi, presenting a uniform pattern, were chosen and classified into one of three patterns - Meshwork, Ring or Clod. Images were used for training a GAN model, which in turn, produced synthetic images recapitulating RCM patterns of nevi. A random sample of synthetic images was classified by two independent human readers and by a CNN model. Human and computer-model classifications were compared. RESULTS: The training set for the GAN model included 1496 RCM images, including 977 images (65.3%) with Meshwork pattern, 261 (17.4%) with Ring and 258 (17.2%) with Clod pattern. The GAN model produced 6000 synthetic RCM-like images. Of these, 302 images were randomly chosen and classified by human readers, including 83 (27.5%) classified as Meshwork, 131 (43.4%) as Ring, and 88 (29.1%) as Clod pattern. Human inter-observer concordance in pattern classification was 91.7%, and human-to-CNN concordance was 87.7%. CONCLUSIONS: We demonstrate feasibility of producing synthetic images, which recapitulate RCM patterns of nevi and can be reproducibly recognized by human readers and by deep-learning models. Synthetic image datasets may allow teaching RCM patterns to novices, training of computer models, and data sharing between research centers.