The SLICE-3D dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection.

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.

PRRX1 silencing is required for metastatic outgrowth in melanoma and is an independent prognostic of reduced survival in patients.

Paired related homeobox 1 (PRRX1) is an inducer of epithelial-to-mesenchymal transition (EMT) in different types of cancer cells. We detected low PRRX1 expression in nevus but increased levels in primary human melanoma and cell lines carrying the BRAFV600E mutation. High expression of PRRX1 correlates with invasiveness and enrichment of genes belonging to the EMT programme. Conversely, we found that loss of PRRX1 in metastatic samples is an independent prognostic predictor of poor survival for melanoma patients. Here, we show that stable depletion of PRRX1 improves the growth of melanoma xenografts and increases the number of distant spontaneous metastases, compared to controls. We provide evidence that loss of PRRX1 counteracts the EMT phenotype, impairing the expression of other EMT-related transcription factors, causing dysregulation of the ERK and signal transducer and activator of transcription 3 (STAT3) signaling pathways, and abrogating the invasive and migratory properties of melanoma cells while triggering the up-regulation of proliferative/melanocytic genes and the expression of the neural-crest-like markers nerve growth factor receptor (NGFR; also known as neurotrophin receptor p75NTR) and neural cell adhesion molecule L1 (L1CAM). Overall, our results indicate that loss of PRRX1 triggers a switch in the invasive programme, and cells de-differentiate towards a neural crest stem cell (NCSC)-like phenotype that accounts for the metastatic aggressiveness.

The Role of Line-Field Confocal Optical Coherence Tomography in Detecting Extramammary Paget Disease Recurrences: A Pilot Diagnostic Study.

Extramammary Paget disease (EMPD) is an uncommon adenocarcinoma of apocrine gland-rich areas, presenting significant diagnostic challenges due to its nonspecific clinical appearance and frequent misidentification as benign, inflammatory skin conditions. Traditional diagnostic methods such as biopsy are invasive and uncomfortable, often required repeatedly due to high recurrence rates. Dermoscopy and non-invasive imaging techniques have been used but provide limited diagnostic accuracy due to their constraints in depth penetration and resolution. Recent advancements in imaging technologies, such as line-field confocal optical coherence tomography (LC-OCT), show promise in enhancing diagnostic precision while minimizing invasive procedures. LC-OCT merges high-resolution imaging with deep penetration capabilities, capturing detailed horizontal and vertical skin images akin to histopathology. This study evaluated the diagnostic performance of LC-OCT in detecting EMPD and its recurrence in 17 clinically suspicious anogenital regions, belonging to six patients. Data were collected prospectively at the patient's bedside by an LC-OCT expert with poor training for EMPD, and, then, reviewed retrospectively by an independent LC-OCT expert with adequate training for EMPD and no concerns about time. The prospective examination yielded 64.7% accuracy (11 true results out of 17 total cases), 71.4% sensitivity (10 true positives out of 14 actual positives), and 33.3% specificity (1 true negative out of 3 actual negatives). The retrospective analysis achieved 94.1% accuracy (16 true results out of 17 total cases), 100% sensitivity (14 true positives out of 14 actual positives), and 66.7% specificity (2 true positives out of 3 actual positives), with the only false positive case being a difficult-to-diagnose concomitant presentation of a lichen sclerosus et atrophicus. Despite the need for specialized training, our results suggest that LC-OCT represents a valuable tool for accurately identifying EMPD and improving its management by reducing unnecessary biopsies. Further studies are needed to standardize its clinical application.

Actinic keratosis: Current challenges and unanswered questions.

Actinic keratoses (AK) are common skin lesions associated with chronic exposure to sun. They are believed to be precursors of malignancy as they potentially may progress to invasive squamous cell carcinomas. The goal of current therapies is to reduce the number of AK and to prevent future cancer development. This review aims at providing an overview of the hallmarks of AK and skin field cancerization. We discuss epidemiology trends, risk factors and the state of the art and evidence of the current treatments. We review key figures of AK prevalence from different countries with regard to skin cancer risk and the associated economic burden of AK. We discuss the mutational status in AK lesions and the difficulties encountered by clinicians in evaluating AK visible and invisible lesions, referring to the concept of field cancerization. Based on a systematic literature review, we further evaluate the available treatment options. The presence of subclinical skin alterations in the periphery of visible AK lesions has gained a particular attention as those non-visible lesions are known to contain the same genetic changes as those found in the AK lesions themselves, prompting the concept of 'field cancerization'. Therefore, AK treatment guidelines now recognize the importance of treating the field in patients with AK. A recent systematic literature review and network meta-analysis showed that 5-FU interventions were associated with the best efficacy and a satisfactory acceptability profile compared with other field-directed therapies used in the treatment of AK. Although AK are considered quite common, they lack an accurate descriptive definition and conclusive epidemiologic data. Limited public awareness is a barrier to early and effective treatment, including prevention strategies. While different treatment options are available, there is still a limited understanding of long-term outcomes of treatment as measured by recurrence of cancer prevention.

Understanding the Dermoscopic Patterns of Basal Cell Carcinoma Using Line-Field Confocal Tomography.

Basal cell carcinoma (BCC) is the most frequent malignancy in the general population. To date, dermoscopy is considered a key tool for the diagnosis of BCC; nevertheless, line-field confocal optical coherence tomography (LC-OCT), a new non-invasive optical technique, has become increasingly important in clinical practice, allowing for in vivo imaging at cellular resolution. The present study aimed to investigate the possible correlation between the dermoscopic features of BCC and their LC-OCT counterparts. In total, 100 histopathologically confirmed BCC cases were collected at the Dermatologic Clinic of the University of Siena, Italy. Predefined dermoscopic and LC-OCT criteria were retrospectively evaluated, and their frequencies were calculated. The mean (SD) age of our cohort was 65.46 (13.36) years. Overall, BCC lesions were mainly located on the head (49%), and they were predominantly dermoscopically pigmented (59%). Interestingly, all dermoscopic features considered had a statistically significant agreement with the LC-OCT criteria (all p < 0.05). In conclusion, our results showed that dermoscopic patterns may be associated with LC-OCT findings, potentially increasing accuracy in BCC diagnosis. However, further studies are needed in this field.

BCN20000: Dermoscopic Lesions in the Wild.

Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning from 2010 to 2016, collated at the Hospital Clínic in Barcelona, Spain. The BCN20000 dataset aims to address the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions in hard-to-diagnose locations such as those found in nails and mucosa, large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. Our dataset covers eight key diagnostic categories in dermoscopy, providing a diverse range of lesions for artificial intelligence model training. Furthermore, a ninth out-of-distribution (OOD) class is also present on the test set, comprised of lesions which could not be distinctively classified as any of the others. By providing a comprehensive collection of varied images, BCN20000 helps bridge the gap between the training data for machine learning models and the day-to-day practice of medical practitioners. Additionally, we present a set of baseline classifiers based on state-of-the-art neural networks, which can be extended by other researchers for further experimentation.

Predictive and Prognostic Factors in Melanoma Central Nervous System Metastases-A Cohort Study.

BACKGROUND: Melanoma is the cancer with the highest risk of dissemination to the central nervous system (CNS), one of the leading causes of mortality from this cancer. OBJECTIVE: To identify patients at higher risk of developing CNS metastases and to evaluate associated prognostic factors. METHODS: A cohort study (1998-2023) assessed patients who developed CNS melanoma metastases. Multivariate logistic regression was used to identify predictive factors at melanoma diagnosis for CNS metastasis. Cox regression analysis evaluated the CNS-independent metastasis-related variables impacting survival. RESULTS: Out of 4718 patients, 380 (8.05%) developed CNS metastases. Multivariate logistic regression showed that a higher Breslow index, mitotic rate ≥ 1 mm2, ulceration, and microscopic satellitosis were significant risk factors for CNS metastasis development. Higher patient age and the location of the primary tumor in the upper or lower extremities were protective factors. In survival analysis, post-CNS metastasis, symptomatic disease, prior non-CNS metastases, CNS debut with multiple metastases, elevated LDH levels, and leptomeningeal involvement correlated with poorer survival. CONCLUSION: Predictive factors in the primary tumor independently associated with brain metastases include microscopic satellitosis, ulceration, higher Breslow index, and trunk location. Prognostic factors for lower survival in CNS disease include symptomatic disease, multiple CNS metastases, and previous metastases from different sites.

Prognostic Value of the Neutrophil-to-lymphocyte Ratio, Platelet-to- lymphocyte Ratio and Monocyte-to-lymphocyte Ratio in Melanoma Patients: A Cohort Study.

The prognostic value of the neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio in patients with melanoma has yielded controversial results in the literature. A retrospective single-centre cohort study was conducted from 1998 to 2020, including patients diagnosed with invasive melanoma. A total of 2,721 patients were included in the study. The median follow-up was 8.23 years (IQR 4.41-13.25). The median baseline neutrophil- lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio values increased significantly (p < 0.001) with the increasing American Joint Committee on Cancer stage. The optimal cut-off values for neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio were determined as 2.1, 184 and 0.2, respectively. In the multivariate analysis, high levels of neutrophil-lymphocyte ratio (≥ 2.1), platelet-lymphocyte ratio (≥ 184) and monocyte-lymphocyte ratio (≥ 0.2) were independently associated with significantly shorter melanoma-specific survival (neutrophil-lymphocyte ratio: HR 1.30, 95% CI 1.06-1.60, p = 0.013; platelet-lymphocyte ratio: HR 1.37, 95% CI 1.06-1.76, p = 0.014; monocyte- lymphocyte ratio: HR 1.29, 95% CI 1.05-1.58, p = 0.015) and overall survival (neutrophil-lymphocyte ratio: HR 1.39, 95% CI 1.19-1.64, p < 0.001; platelet- lymphocyte ratio: HR 1.44, 95% CI 1.19-1.74, p < 0.001; monocyte-lymphocyte ratio: HR 1.42, 95% CI 1.21-1.66, p < 0.001). High levels of neutrophil- lymphocyte ratio and monocyte-lymphocyte ratio were also associated with poor relapse-free survival, while platelet-lymphocyte ratio was not. In conclusion, baseline neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and monocyte-lymphocyte ratio were identified as independent predictors for the prognosis of melanoma.

A protocol for annotation of total body photography for machine learning to analyze skin phenotype and lesion classification.

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.

Dermatoscopic patterns of cutaneous metastases: A multicentre cross-sectional study of the International Dermoscopy Society.

BACKGROUND: The detection of cutaneous metastases (CMs) from various primary tumours represents a diagnostic challenge. OBJECTIVES: Our aim was to evaluate the general characteristics and dermatoscopic features of CMs from different primary tumours. METHODS: Retrospective, multicentre, descriptive, cross-sectional study of biopsy-proven CMs. RESULTS: We included 583 patients (247 females, median age: 64 years, 25%-75% percentiles: 54-74 years) with 632 CMs, of which 52.2% (n = 330) were local, and 26.7% (n = 169) were distant. The most common primary tumours were melanomas (n = 474) and breast cancer (n = 59). Most non-melanoma CMs were non-pigmented (n = 151, 95.6%). Of 169 distant metastases, 54 (32.0%) appeared on the head and neck region. On dermatoscopy, pigmented melanoma metastases were frequently structureless blue (63.6%, n = 201), while amelanotic metastases were typified by linear serpentine vessels and a white structureless pattern. No significant difference was found between amelanotic melanoma metastases and CMs of other primary tumours. CONCLUSIONS: The head and neck area is a common site for distant CMs. Our study confirms that most pigmented melanoma metastasis are structureless blue on dermatoscopy and may mimic blue nevi. Amelanotic metastases are typified by linear serpentine vessels and a white structureless pattern, regardless of the primary tumour.

European consensus-based interdisciplinary guideline for diagnosis, treatment and prevention of actinic keratoses, epithelial UV-induced dysplasia and field cancerization on behalf of European Association of Dermato-Oncology, European Dermatology Forum, European Academy of Dermatology and Venereology and Union of Medical Specialists (Union Européenne des Médecins Spécialistes).

A collaboration of multidisciplinary experts from the European Association of Dermato-Oncology, the European Dermatology Forum, the European Academy of Dermatology and Venereology, and the European Union of Medical Specialists was formed to develop European recommendations on AK diagnosis and treatment, based on current literature and expert consensus. This guideline addresses the epidemiology, diagnostics, risk stratification and treatments in immunocompetent as well as immunosuppressed patients. Actinic keratoses (AK) are potential precursors of cutaneous squamous cell carcinoma (cSCC) and display typical histopathologic and immunohistochemical features of this malignancy in an early stage. They can develop into cSSC in situ and become invasive in a low percentage of cases. AK is the most frequent neoplasia in white populations, frequently occurring within a cancerous field induced by ultraviolet radiation. Since it cannot be predicted, which lesion will progress to cSCC and when treatment is usually recommended. The diagnosis of AK and field cancerization is made by clinical examination. Dermatoscopy, confocal microscopy, optical coherence tomography or line-field confocal-OCT can help in the differential diagnosis of AK and other skin neoplasms. A biopsy is indicated in clinically and/or dermatoscopically suspicious and/or treatment-refractory lesions. The choice of treatment depends on patients' and lesion characteristics. For single non-hyperkeratotic lesions, the treatment can be started upon patient's request with destructive treatments or topical treatments. For multiple lesions, field cancerization treatment is advised with topical treatments and photodynamic therapy. Preventive measures such as sun protection, self-examination and repeated field cancerization treatments of previously affected skin areas in high-risk patients are advised.

A Narrative Review: Opportunities and Challenges in Artificial Intelligence Skin Image Analyses Using Total Body Photography.

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.

Sphingolipid paracrine signaling impairs keratinocyte adhesion to promote melanoma invasion.

Melanoma is the deadliest form of skin cancer due to its propensity to metastasize. It arises from melanocytes, which are attached to keratinocytes within the basal epidermis. Here, we hypothesize that, in addition to melanocyte-intrinsic modifications, dysregulation of keratinocyte functions could initiate early-stage melanoma cell invasion. We identified the lysolipid sphingosine 1-phosphate (S1P) as a tumor paracrine signal from melanoma cells that modifies the keratinocyte transcriptome and reduces their adhesive properties, leading to tumor invasion. Mechanistically, tumor cell-derived S1P reduced E-cadherin expression in keratinocytes via S1P receptor dependent Snail and Slug activation. All of these effects were blocked by S1P2/3 antagonists. Importantly, we showed that epidermal E-cadherin expression was inversely correlated with the expression of the S1P-producing enzyme in neighboring tumors and the Breslow thickness in patients with early-stage melanoma. These findings support the notion that E-cadherin loss in the epidermis initiates the metastatic cascade in melanoma.

Criterios dermatoscópicos de halo nevo y halo melanoma / Dermoscopy criteria of halo nevi and halo melanoma

El fenómeno halo es más común en lesiones melanocíticas benignas. Se han reportado casos de halo nevo en individuos con antecedentes personales o familiares de melanoma como también melanomas con halo lo que ha suscitado preocupaciones acerca del diagnóstico y manejo de estas lesiones. El halo nevo pertenece al grupo de los simuladores de melanoma. A través de una técnica no invasiva como es la dermatoscopia se puede diferenciar las características dermatoscópicas del halo nevo y halo melanoma

Halo phenomenon appears more often in benign melanocytic lesions. There have been reports of halo nevi in individuals with personal or family history of melanoma as well as melanomas with halo, raising concerns about the diagnosis and management of these lesions. Halo nevus belongs to the group of melanoma simulators. Dermoscopic features of halo nevus and melanoma can be differentiated through a noninvasive technique such as dermoscopy.