Background: Cutaneous melanoma (CM) poses significant diagnostic challenges due to its biological heterogeneity and the subjective interpretation of histopathologic criteria. While early and accurate diagnosis remains critical for patient outcomes, conventional pathology is limited by interobserver variability and diagnostic ambiguity, especially in borderline lesions. Objective: This narrative review explores the integration of digital pathology (DP) and artificial intelligence (AI)—including deep learning (DL), machine learning (ML), and interpretable models—into the histopathologic workflow for CM diagnosis. Methods: We systematically searched PubMed, Scopus, and Web of Science (2013–2025) for studies using whole slide imaging (WSI) and AI to assist melanoma diagnosis. We categorized findings across five domains: WSI-based classification models, feature extraction (e.g., mitoses, ulceration), spatial modeling and TIL analysis, molecular prediction (e.g., BRAF mutation), and interpretable pipelines based on nuclei morphology. Results: We included 87 studies with diverse AI methodologies. Convolutional neural networks (CNNs) achieved diagnostic accuracy comparable to expert dermatopathologists. U-Net and Mask R-CNN models enabled robust detection of critical histologic features, while nuclei-level analyses offered explainable classification strategies. Spatial and morphometric modeling allowed quantification of tumor–immune interactions, and select models inferred molecular alterations directly from H&E slides. However, generalizability remains limited due to small, homogeneous datasets and lack of external validation. Conclusions: AI-enhanced digital pathology holds transformative potential in CM diagnosis, offering accuracy, reproducibility, and interpretability. Yet, clinical integration requires multicentric validation, standardized protocols, and attention to workflow, ethical, and medico-legal challenges. Future developments, including multimodal AI and integration into molecular tumor boards, may redefine diagnostic precision in melanoma.

Despite recent progress and the publishing of several clinical guidelines on the management of advanced basal cell carcinoma, there is still no comprehensive set of clinical guidelines addressing the complexity inherent to the use of Hedgehog pathway inhibitors in the treatment of advanced basal cell carcinoma in real-world clinical practice. To develop practical and valuable tools that help specialists improve the clinical management of these patients, we sought the opinion of expert physicians with extensive knowledge and experience in the treatment of advanced basal cell carcinoma.

Purpose: To improve the diagnostic accuracy and optimal management of pediatric melanomas. Methods: We conducted a retrospective descriptive, multicenter study of the epidemiological, clinical, and dermoscopic characteristics of histopathologically proven melanomas diagnosed in patients less than 18 years old. Data on sociodemographic variables, clinical and dermoscopic characteristics, histopathology, local extension, therapy and follow-up, lymph node staging, and outcome were collected from the databases of three Italian dermatology units. We performed a clinical evaluation of the morphological characteristics of each assessed melanoma, using both classic ABCDE criteria and the modified ABCDE algorithm for pediatric melanoma to evaluate which of the two algorithms best suited our series. Results: The study population consisted of 39 patients with a histologically confirmed diagnosis of pediatric melanoma. Comparing classic ABCDE criteria with the modified ABCDE algorithm for pediatric melanomas, the modified pediatric ABCDE algorithm was less sensitive than the conventional criteria. Dermoscopically, the most frequent finding was the presence of irregular streaks/pseudopods (74.4%). When evaluating the total number of different suspicious dermoscopy criteria per lesion, 64.1% of the lesion assessments recognized two dermoscopic characteristics, 20.5% identified three, and 15.4% documented four or more assessments. Conclusions: Contrary to what has always been described in the literature, from a clinical point of view, about 95% of our cases presented in a pigmented and non-amelanotic form, and these data must be underlined in the various prevention campaigns where pediatric melanoma is currently associated with a more frequently amelanotic form. All the pediatric melanomas analyzed presented at least two dermoscopic criteria of melanoma, suggesting that this could be a key for the dermoscopic diagnosis of suspected pediatric melanoma, making it possible to reach an early diagnosis even in this age group.

Background: Cutaneous melanoma (CM) is one of the most lethal tumors among skin cancers and its incidence is rising worldwide. Recent data support the role of microRNAs (miRNAs) in melanoma carcinogenesis and their potential use as disease biomarkers. Methods: We quantified the expression of miR-146a-5p and miR-21-5p in 170 formalin-fixed paraffin embedded (FFPE) samples of CM, namely 116 superficial spreading melanoma (SSM), 26 nodular melanoma (NM), and 28 lentigo maligna melanoma (LMM). We correlated miRNA expression with specific histopathologic features including Breslow thickness (BT), histological subtype, ulceration and regression status, and mitotic index. Results: miR-146a-5p and miR-21-5p were significantly higher in NM compared to SSM and LMM. The positive correlation between miR-146a-5p and miR-21-5p expression and BT was confirmed for both miRNAs in SSM. Considering the ulceration status, we assessed that individual miR-21-5p expression was significantly higher in ulcerated CMs. The increased combined expression of the two miRNAs was strongly associated with ulceration (p = 0.0093) and higher mitotic rate (≥1/mm²) (p = 0.0005). We demonstrated that the combination of two-miRNA expression and prognostic features (BT and ulceration) can better differentiate cutaneous melanoma prognostic groups, considering overall survival and time-to-relapse clinical outcomes. Specifically, miRNA expression can further stratify prognostic groups among patients with BT ≥ 0.8 mm but without ulceration. Our findings provide further insights into the characterization of CM with specific prognostic features. The graphical abstract was created with BioRender.com.