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Most melanomas progress from radial to vertical growth phase before spreading locoregionally and distally. Much is still unknown about the metabolic changes in the tumor cells and their microenvironment during this metastatic progression. We aimed to gain new insight into the molecular characteristics of melanoma in regard to spatial lipidomics to deliver new knowledge regarding tumor metastatic progression. We included 10 fresh tumor samples from 10 patients including two in situ melanomas, two invasive primary melanomas, and six metastatic melanomas (four in‐transit metastases and two distant metastases). In addition, we analyzed four healthy skin controls from the same patients. Time‐of‐flight imaging secondary ion mass spectrometry (ToF‐SIMS) enabled detailed spatial‐lipidomics that could be directly correlated with conventional histopathological analysis of consecutive H&E‐stained tissue sections. Significant differences in the lipid profiles were found in primary compared to metastatic melanomas, notably an increase in phosphatidylethanolamine lipids relative to phosphatidylinositol lipids and an increase in GM3 gangliosides in the metastatic samples. Furthermore, analysis of the data from in transit versus distant metastases samples highlighted that specific phospholipids, and a difference in the long versus shorter chain GM3 gangliosides, discriminated the metastatic routes. Further studies are warranted to verify these preliminary findings. Lipidomic changes could serve as a novel biomarker for tumor progression and even serve as a target for novel treatments. Furthermore, analyzing the lipid profiles could help to differentiate between primary and metastatic melanomas in challenging cases. [ABSTRACT FROM AUTHOR]

Diagnosing atypical pigmented facial lesions (aPFLs) is a challenging topic for dermatologists. Accurate diagnosis of these lesions is crucial for effective patient management, especially in dermatology, where visual assessment plays a central role. Incorrect diagnoses can result in mismanagement, delays in appropriate interventions, and potential harm. AI, however, holds the potential to enhance diagnostic accuracy and provide reliable support to clinicians. This work aimed to evaluate and compare the effectiveness of machine learning (logistic regression of lesion features and patient metadata) and deep learning (CNN analysis of images) models in dermoscopy diagnosis and the management of aPFLs. This study involved the analysis of 1197 dermoscopic images of facial lesions excised due to suspicious and histologically confirmed malignancy, classified into seven classes (lentigo maligna—LM; lentigo maligna melanoma—LMM; atypical nevi—AN; pigmented actinic keratosis—PAK; solar lentigo—SL; seborrheic keratosis—SK; and seborrheic lichenoid keratosis—SLK). Image samples were collected through the Integrated Dermoscopy Score (iDScore) project. The statistical analysis of the dataset shows that the patients mean age was 65.5 ± 14.2, and the gender was equally distributed (580 males—48.5%; 617 females—51.5%). A total of 41.7% of the sample constituted malignant lesions (LM and LMM). Meanwhile, the benign lesions were mainly PAK (19.3%), followed by SL (22.2%), AN (10.4%), SK (4.0%), and SLK (2.3%). The lesions were mainly localised in the cheek and nose areas. A stratified analysis of the assessment provided by the enrolled dermatologists was also performed, resulting in 2445 evaluations of the 1197 images (2.1 evaluations per image on average). The physicians demonstrated higher accuracy in differentiating between malignant and benign lesions (71.2%) than in distinguishing between the seven specific diagnoses across all the images (42.9%). The logistic regression model obtained a precision of 39.1%, a sensitivity of 100%, a specificity of 33.9%, and an accuracy of 53.6% on the test set, while the CNN model showed lower sensitivity (58.2%) and higher precision (47.0%), specificity (90.8%), and accuracy (59.5%) for melanoma diagnosis. This research demonstrates how AI can enhance the diagnostic accuracy in complex dermatological cases like aPFLs by integrating AI models with clinical data and evaluating different diagnostic approaches, paving the way for more precise and scalable AI applications in dermatology, showing their critical role in improving patient management and the outcomes in dermatology. [ABSTRACT FROM AUTHOR]

An 11-month-old girl presented with an erythematous nodule on the chest, which had been growing for 8 months. The tumor was composed of uniform polygonal and spindle-shaped cells, forming nodules and fascicles. The diagnosis of neurothekeoma was based upon the histology and immunohistochemistry.

Background: The differential diagnosis of atypical melanocytic palmoplantar skin lesions (aMPLs) represents a diagnostic challenge, including atypical nevi (AN) and early melanomas (MMs) that display overlapping clinical and dermoscopic features. We aimed to set up a multicentric dataset of aMPL dermoscopic cases paired with multiple anamnestic risk factors and demographic and morphologic data. Methods: Each aMPL case was paired with a dermoscopic and clinical picture and a series of lesion-related data (maximum diameter value; location on the palm/sole in 17 areas; histologic diagnosis; and patient-related data (age, sex, family history of melanoma/sunburns, phototype, pheomelanin, eye/hair color, multiple/dysplastic body nevi, and traumatism on palms/soles). Results: A total of 542 aMPL cases—113 MM and 429 AN—were collected from 195 males and 347 females. No sex prevalence was found for melanomas, while women were found to have relatively more nevi. Melanomas were prevalent on the heel, plantar arch, and fingers in patients aged 65.3 on average, with an average diameter of 17 mm. Atypical nevi were prevalent on the plantar arch and palmar area of patients aged 41.33 on average, with an average diameter of 7 mm. Conclusions: Keeping in mind the risk profile of an aMPL patient can help obtain a timely differentiation between malignant/benign cases, thus avoiding delayed and inappropriate excision, respectively, with the latter often causing discomfort/dysfunctional scarring, especially at acral sites. [ABSTRACT FROM AUTHOR]

Standard treatment for lentigo maligna (LM) is surgical excision, yet insights into the frequency of and risk factors for incomplete excisions remain limited. The primary objectives were to assess the incomplete excision rate (IER) in primary LM and to explore potential risk factors for incomplete excisions. A retrospective analysis was conducted encompassing consecutive histopathologically confirmed LMs from 2014-2020. Descriptive statistics were used for LM characteristics and IER, while uni- and multivariate analyses were used for calculating risk factors. The study included 395 LMs with an IER of 16.7% (n = 66). Risk factors for higher incomplete excision rates included: head and neck lesions (p = 0.0014), clinical excision margins < 5 mm (p = 0.040), and utilization of preoperative partial biopsies (p = 0.023). Plastic surgeons had higher IERs than dermatologists (p = 0.036). Lesion diameter (p = 0.20) and surgeon experience (p = 0.20) showed no associations with incomplete excisions, yet LMs with a diameter ≥ 20 mm exhibited higher incomplete excision rates (23.2%) compared with those < 10 mm (12.9%). LMs should be excised with at least 5-mm clinical margins, especially in the head and neck area. LMs ≥ 20 mm may be more surgically challenging. Higher incomplete excision rates associated with the use of preoperative biopsies and/or plastic surgeons may reflect challenging anatomical locations, larger lesion diameter, and/or ill-defined borders. [ABSTRACT FROM AUTHOR]

The correction notice for the article "Pattern Analysis of Benign and Malignant Atypical Melanocytic Skin Lesions of Palms and Soles" in the journal Life (2075-1729) adds Harald Kittler as an author and updates the author affiliations and contributions. The scientific conclusions of the original publication remain unchanged, and the correction was approved by the Academic Editor. The authors include Linda Tognetti, Alessandra Cartocci, Harald Kittler, and others. [Extracted from the article]