Clinical and dermatoscopic criteria for the preoperative evaluation of cutaneous melanoma thickness

Background: Melanoma thickness measured according to the Breslow method is used to determine surgical margin and in patient selection for sentinel node biopsy. Previous studies did not confirm the reliability of melanoma palpability for clinical prediction of tumor thickness. Recently we reported the usefulness of epiluminescence microscopy (dermatoscopy) for in vivo detection of the phases of melanoma progression, as well as tumor depth. Objective: Our purpose was to determine whether the combination of clinical and dermatoscopic criteria could increase the accuracy in preoperative evaluation of melanoma thickness with respect to the clinical elevation and dermatoscopic assessments considered separately. Methods: In a blind retrospective study, 122 cutaneous melanomas were studied to evaluate the presence of several clinical and dermatoscopic criteria and their relation with the histologic thickness. An algorithm of combined criteria was constructed and statistically assessed. Results: Combinations of palpability, diameter of more than 15 mm, pigment network, gray-blue areas, and atypical vascular pattern allowed correct prediction of thickness in 89% of melanomas when categorized in two groups of less than 0.76 mm and more than 0.75 mm thickness, compared with 75% using palpability, and 80% using dermatoscopic criteria. Lower values were obtained in the further subdivision of melanomas into groups of 0.76 to 1.5 mm and more than 1.5 mm thickness. Conclusion: The combination of clinical and dermatoscopic criteria is a more precise guide for the preoperative evaluation of melanoma thickness than either is alone. However, further studies are needed to verify its applicability in establishing the surgical approach to cutaneous melanoma

Tents, Beds and Clothing: The Evocative Objects of Contemporary Art Textile

The vast collection of textiles, fabrics and fibres from Vesuvian sites, kept at the MANN (National Archaeological Museum of Naples), represents one of the most interesting and, until now, less explored bequests of a not marginal aspect of ancient culture, among whose ‘folds’ it is possible to trace important elements of an history that crosses the sphere of production, distribution, habits and society of Pompeii and, more generally, of Roman culture. The contribution intends to present the first results of a work of research and documentation on this precious textile material and the task of reinterpreting, that the research group is carrying out in order to illustrate a process of dissemination and cultural promotion of the complex knowledge that is kept in it

Epiluminescence microscopy: Criteria of cutaneous melanoma progression

Background: Cutaneous melanoma develops through a series of evolutionary steps (intraepidermal, radial, and vertical growth phases) that are traceable in specific histologic features. Epiluminescence microscopy (ELM) is an in vivo technique that enables the visualization of morphologic structures in pigmented lesions correlated with specific histologic architectural characteristics. Many ELM criteria associated with cutaneous melanoma have been described, but their correlation with tumor progression has not yet been established. Objective: In this preliminary study our purpose was to explore the possibility of recognizing ELM criteria that allow the in vivo detection of the various phases of melanoma progression as well as tumor depth. Methods: Seventy-two cutaneous melanomas (41 'thin' melanomas [TnM], 0.75 mm thickness) were investigated with ELM for the presence of nine standard ELM criteria; their significance was determined by calculating the chi-square test of independence. Results: A significant association is found between the presence of pigment network and TaM and between the presence of gray-blue areas, vascular pattern, and TkM. Moreover, pigment network plus radial streaming is the most significant association of ELM criteria in TnM, whereas gray-blue areas plus vascular pattern is the greatest in TkM. Conclusion: This study shows a good correlation between certain ELM criteria and the histologic architecture of cutaneous melanoma for a preoperative evaluation of the tumor thickness. Further investigation is needed for verifying on a larger number of cases our pilot estimates of sensitivity and specificity of ELM criteria in thin and thick melanomas

Pseudo ainhum and facial malformation secondary to Streeter's dysplasia

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Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions: Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis

Objective: To compare the reliability of a new 7-point checklist based on simplified epiluminescence microscopy (ELM) pattern analysis with the ABCD rule of dermatoscopy and standard pattern analysis for the diagnosis of clinically doubtful melanocytic skin lesions. Design: In a blind study, ELM images of 342 histologically proven melanocytic skin lesions were evaluated for the presence of 7 standard criteria that we called the 'ELM 7-point checklist.' For each lesion, 'overall' and 'ABCD scored' diagnoses were recorded. From a training set of 57 melanomas and 139 atypical non-melanomas, odds ratios were calculated to create a simple diagnostic model based on identification of major and minor criteria for the '7-point scored' diagnosis. A test set of 60 melanomas and 86 atypical non-melanomas was used for model validation and was then presented to 2 less experienced ELM observers, who recorded the ABCD and 7-point scored diagnoses. Settings: University medical centers. Patients: A sample of patients with excised melanocytic lesions. Main Outcome Measures: Sensitivity, specificity, and accuracy of the models for diagnosing melanoma. Results: From the total combined sets, the 7-point checklist gave a sensitivity of 95% and a specificity of 75% compared with 85% sensitivity and 66% specificity using the ABCD rule and 91% sensitivity and 90% specificity using standard pattern analysis (overall ELM diagnosis). Compared with the ABCD rule, the 7-point method allowed less experienced observers to obtain higher diagnostic accuracy values. Conclusions: The ELM 7-point checklist provides a simplification of standard pattern analysis because of the low number of features to identify and the scoring diagnostic system. As with the ABCD rule, it can be easily learned and easily applied and has proven to be reliable in diagnosing melanoma

Reliability and inter-observer agreement of dermoscopic diagnosis of melanoma and melanocytic naevi

The aim of this study was to analyse the reliability and the inter- observer agreement of dermoscopy in the diagnosis of melanocytic skin lesions. Nine dermatologists, with a different training experience and who routinely used dermoscopy in different hospitals in Italy, evaluated clinical and dermoscopy photographs of 15 melanocytic lesions (four invasive melanomas, four histologically common naevi, and seven naevi with histological atypia). A further series of dermoscopic photographs of 40 melanocytic lesions was evaluated to quantify inter-observer concordance in recognizing dermoscopic criteria. Compared to the true (histological) diagnosis, clinical diagnosis (categories: melanoma, common naevus, atypical naevus) was correct in 40% of cases (range, 27-53%). The percentage raised to 55% (40-73%) by the use of dermoscopy, with an average improvement of 15.6%. Concerning melanoma, clinical diagnosis resulted in a sensitivity of 41.9%, specificity of 77.8%, positive predictive value (PPV) of 36.1%, negative predictive value (NPV) of 81.8%. By using dermoscopy, an improvement of diagnostic performance was found (sensitivity 75%, specificity 88.8%, VPP 71.0%, VPN 90.7%). The inter-observer agreement in melanoma diagnosis, by using dermoscopy, was similar to that obtained by clinical examination (k statistics = 0.54 and 0.52, respectively). Concerning dermoscopic criteria, the best agreement among observers was found for pseudopods, a dermoscopic parameter related to the radial growth phase of melanoma. We conclude that dermoscopy is an useful tool for a non-invasive diagnosis of melanocytic skin lesions, improving the diagnostic performance compared to clinical examination

Three roots of melanoma

Segura et al1 describe morphologic features of melanomas with a nodular component using in vivo reflectance-mode confocal microscopy (RCM) and correlate these RCM findings with histopathologic findings. The most striking observation made by the investigators is the remarkable difference in epidermal involvement between nodular melanoma (NM) and superficial spreading melanoma (SSM) with a nodular component. At RCM, SSMs frequently showed epidermal disarrangement and pagetoid infiltration, whereas NMs exhibited a preserved epidermal pattern and few pagetoid cells.1 This new observation provides fertile ground for revisiting the conventional concept of melanoma development. We propose an alternative hypothesis based on recent observations made in stem cell research and demonstrate how this hypothesis can better account for the observed clinical and epidemiologic differences between melanoma subtypes

Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet

Skin cancer, a major form of cancer, is a critical public health problem with 123,000 newly diagnosed melanoma cases and between 2 and 3 million non-melanoma cases worldwide each year. The leading cause of skin cancer is high exposure of skin cells to UV radiation, which can damage the DNA inside skin cells leading to uncontrolled growth of skin cells. Skin cancer is primarily diagnosed visually employing clinical screening, a biopsy, dermoscopic analysis, and histopathological examination. It has been demonstrated that the dermoscopic analysis in the hands of inexperienced dermatologists may cause a reduction in diagnostic accuracy. Early detection and screening of skin cancer have the potential to reduce mortality and morbidity. Previous studies have shown Deep Learning ability to perform better than human experts in several visual recognition tasks. In this paper, we propose an efficient seven-way automated multi-class skin cancer classification system having performance comparable with expert dermatologists. We used a pretrained MobileNet model to train over HAM10000 dataset using transfer learning. The model classifies skin lesion image with a categorical accuracy of 83.1 percent, top2 accuracy of 91.36 percent and top3 accuracy of 95.34 percent. The weighted average of precision, recall, and f1-score were found to be 0.89, 0.83, and 0.83 respectively. The model has been deployed as a web application for public use at (https://saketchaturvedi.github.io). This fast, expansible method holds the potential for substantial clinical impact, including broadening the scope of primary care practice and augmenting clinical decision-making for dermatology specialists.Comment: This is a pre-copyedited version of a contribution published in Advances in Intelligent Systems and Computing, Hassanien A., Bhatnagar R., Darwish A. (eds) published by Chaturvedi S.S., Gupta K., Prasad P.S. The definitive authentication version is available online via https://doi.org/10.1007/978-981-15-3383-9_1