Skin tumours

Imaging the elemental distribution within human malignant melanomas using Laser-Induced Breakdown Spectroscopy

The diagnosis of malignant melanoma, often an inconspicuous but highly aggressive tumor, is most commonly done by histological examination, while additional diagnostic methods on the level of elements and molecules are constantly being developed. Several studies confirmed differences in the chemical composition of healthy and tumor tissue. Our study presents the potential of the LIBS (Laser-Induced-Breakdown Spectroscopy) technique as a diagnostic tool in malignant melanoma (MM) based on the quantitative changes in elemental composition in cancerous tissue. Our patient group included 17 samples of various types of malignant melanoma and one sample of healthy skin tissue as a control. To achieve a clear perception of results, we have selected two biogenic elements (calcium and magnesium), which showed a dissimilar distribution in cancerous tissue from its healthy surroundings. Moreover, we observed indications of different concentrations of these elements in different subtypes of malignant melanoma, a hypothesis that requires confirmation in a more extensive sample set. The information provided by the LIBS Imaging method could potentially be helpful not only in the diagnostics of tumor tissue but also be beneficial in broadening the knowledge about the tumor itself.

Is thermography an effective screening tool for differentiating benign and malignant skin lesions in the head and neck? A systematic review

The aim of this study was to assess, through a systematic review, the status of infrared thermography (IRT) as a diagnostic tool for skin neoplasms of the head and neck region and in order to validate its effectiveness in differentiating benign and malignant lesions. A search was carried out in the LILACS, PubMed/MEDLINE, SCOPUS, Web of Science and EMBASE databases including studies published between 2004 and 2024, written in the Latin-Roman alphabet. Accuracy studies with patients aged 18 years or over presenting benign and malignant lesions in the head and neck region that evaluated the performance of IRT in differentiating these lesions were included. Lesions of mesenchymal origin and studies that did not mention histopathological diagnosis were excluded. The systematic review protocol was registered in the PROSPERO database (CRD42023416079). Reviewers independently analyzed titles, abstracts, and full-texts. After extracting data, the risk of bias of the selected studies was assessed using the QUADAS - 2 tool. Results were narratively synthesized and the certainty of evidence was measured using the GRADE approach. The search resulted in 1,587 records and three studies were included. Only one of the assessed studies used static IRT, while the other two studies used cold thermal stress. All studies had an uncertain risk of bias. In general, studies have shown wide variation in the accuracy of IRT for differentiating between malignant and benign lesions, with a low level of certainty in the evidence for both specificity and sensitivity.

The Impact of and Adaptations Due to the COVID-19 Pandemic on the Histopathological Diagnosis of Skin Pathologies, Including Non-Melanocyte and Melanoma Skin Cancers-A Single-Center Study in Romania

Background and Objectives: The COVID-19 pandemic has globally affected health systems and services. Non-melanoma skin cancers (NMSCs) are the most common malignancies around the world. This study aimed to analyze the differences in the benign and malignant histopathological diagnoses performed on radical excision skin tumors and skin biopsies in the dermatopathology ward in Mures Clinical County Hospital, Targu Mures, Romania, 1 year prior to and during the COVID-19 pandemic, to emphasize the changes in the diagnostic process as per the new regulations. Materials and Methods: A total of 1168 histopathological diagnoses were included in the study—302 from the COVID-19 period and 866 from the non-COVID-19 period—considering the number, type, and frequency of the histopathological diagnoses as variables to be analyzed. Results: In the COVID-19 period, out of the 55 NMSC and melanoma histopathological diagnoses, 50.9% (n = 28) were BCCs, 20% (n = 11) were SCCs, 10.9% (n = 6) were basosquamous cell carcinomas, and 18.18% (n = 10) were melanoma cases. Regarding the non-COVID-19 period, out of the 173 NMSC and melanoma histopathological diagnoses, 46.82% (n = 81) were BCCs, 22.54% (n = 39) were SCCs, 7.51% (n = 13) were basosquamous cell carcinomas, and 23.12% (n = 40) were melanoma cases. Conclusions: During the COVID-19 pandemic, a decrease in histopathological diagnoses at the dermatopathology ward in our hospital was observed, for both benign and malignant pathologies, especially for NMSCs and melanomas, compared to the same period 1 year prior to the pandemic.

The Mast Cell-SCF-CB1 Interaction Is a Key Player in Seborrheic Keratosis

Mast cell (MC) is an important player in the development of skin diseases, including atopic dermatitis, psoriasis, and urticaria. It is reported that MC infiltration and activation are observed around various types of tumors and speculated that MCs play key roles in their pathogenesis. As MCs in human seborrheic keratosis (SK) have not been well investigated, here we focused on the MCs in SK. The number of c-Kit and tryptase-positive MCs was significantly increased around the SK compared with the marginal lesion. Degranulated MCs were also increased around the tumors. Furthermore, MC growth factor, stem cell factor (SCF), expression within the SK was significantly upregulated compared with the marginal lesion. Interestingly, one of the cognitive regulators of SCF expression, cannabinoid receptor type 1 (CB1) immunoreactivity was downregulated within the SK. Our results suggest that MCs play important roles in the pathogenesis of SK and that SCF can be also deeply involved in the development of SKs. Our current results highlight the CB1-SCF-MC interaction as a novel mechanism of SK development and this also will be utilized for developing a novel treatment.

Bi-directional Dermoscopic Feature Learning and Multi-scale Consistent Decision Fusion for Skin Lesion Segmentation

Accurate segmentation of skin lesion from dermoscopic images is a crucial part of computer-aided diagnosis of melanoma. It is challenging due to the fact that dermoscopic images from different patients have non-negligible lesion variation, which causes difficulties in anatomical structure learning and consistent skin lesion delineation. In this paper, we propose a novel bi-directional dermoscopic feature learning (biDFL) framework to model the complex correlation between skin lesions and their informative context. By controlling feature information passing through two complementary directions, a substantially rich and discriminative feature representation is achieved. Specifically, we place biDFL module on the top of a CNN network to enhance high-level parsing performance. Furthermore, we propose a multi-scale consistent decision fusion (mCDF) that is capable of selectively focusing on the informative decisions generated from multiple classification layers. By analysis of the consistency of the decision at each position, mCDF automatically adjusts the reliability of decisions and thus allows a more insightful skin lesion delineation. The comprehensive experimental results show the effectiveness of the proposed method on skin lesion segmentation, achieving state-of-the-art performance consistently on two publicly available dermoscopic image databases.