Development of a new classification and scoring system for scalp conditions: Scalp Photographic Index (SPI).

BACKGROUND AND OBJECTIVES: There has been no validated tool for objectively quantifying the overall condition and characteristics of the scalp. This study aimed to establish and validate a new classification and scoring system for evaluating scalp conditions. METHODS: The Scalp Photographic Index (SPI) using a trichoscope grades five features of scalp conditions (dryness, oiliness, erythema, folliculitis, and dandruff) on a score of 0-3. To evaluate the validity of SPI, SPI grading was performed by three experts on the scalps of 100 subjects along with a dermatologist's assessment of the scalps and a scalp-related symptom survey. For reliability assessment, 20 healthcare providers performed SPI grading for the 95 selected photographs of the scalp. RESULTS: SPI grading and the dermatologist's scalp assessment showed good correlations for all five scalp features. Warmth showed a significant correlation with all features of SPI and the subjects' perception of a scalp pimple had a significant positive correlation with the folliculitis feature. SPI grading demonstrated good reliability with excellent internal consistency (Cronbach's α = 0.90) and strong inter- and intra-rater reliability (Kendall's W = 0.84, ICC(3,1)=0.94). CONCLUSIONS: SPI is an objective, reproducible, and validated numeric system for classifying and scoring scalp conditions.

Adversarial multimodal fusion with attention mechanism for skin lesion classification using clinical and dermoscopic images.

Accurate skin lesion diagnosis requires a great effort from experts to identify the characteristics from clinical and dermoscopic images. Deep multimodal learning-based methods can reduce intra- and inter-reader variability and improve diagnostic accuracy compared to the single modality-based methods. This study develops a novel method, named adversarial multimodal fusion with attention mechanism (AMFAM), to perform multimodal skin lesion classification. Specifically, we adopt a discriminator that uses adversarial learning to enforce the feature extractor to learn the correlated information explicitly. Moreover, we design an attention-based reconstruction strategy to encourage the feature extractor to concentrate on learning the features of the lesion area, thus, enhancing the feature vector from each modality with more discriminative information. Unlike existing multimodal-based approaches, which only focus on learning complementary features from dermoscopic and clinical images, our method considers both correlated and complementary information of the two modalities for multimodal fusion. To verify the effectiveness of our method, we conduct comprehensive experiments on a publicly available multimodal and multi-task skin lesion classification dataset: 7-point criteria evaluation database. The experimental results demonstrate that our proposed method outperforms the current state-of-the-art methods and improves the average AUC score by above 2% on the test set.

Molusco contagioso: actualización y casos clínicos / Molluscum contagiosum: an update and clinical cases

El molusco contagioso es una patología viral benigna muy frecuente, exclusiva del ser humano, y causada por un virus no clasificado del grupo de los Poxvirus. Las manifestaciones clínicas de la enfermedad inclu-yen lesiones en la piel, que pueden variar desde una pequeña pápula a un nódulo de mayor tamaño, pre-sentándose en forma solitaria o múltiple, dependien-do del estado inmunitario del paciente y del tiempo de evolución del proceso morboso. El estudio histo-patológico es importante para el diagnóstico, aunque en numerosas ocasiones éste se define clínicamen-te. Además del patrón histológico tradicional, y más frecuente, que exhibe hiperplasia e hipertrofia de la epidermis, se han descripto variantes poco usuales, cuyas características dependen, entre otros factores, de la sobreinfección y de la respuesta inmunitaria del paciente. En este trabajo se describen los rasgos ge-nerales del molusco contagioso y luego se presentan varios casos clínicos, uno de los cuales exhibe ma-nifestación inusual en la semimucosa del labio. Por último, se realizan comentarios referentes a la im-portancia que tiene para el odontólogo conocer esta patología y estar capacitado para detectarla, de modo de evitar sus complicaciones y su diseminación (AU)

Molluscum contagiosum is a very common benign viral pathologythat affects exclusively humans and is caused by an unclassified virus of the Poxvirus family. Clinical manifestations include skin lesions such as papule or nodule, which may range from a small papule to a larger nodule, presenting either solitary or multiple, depending on the immune status of the patient and the time of evolution of the morbid process. Histopathological study is important for the diagnosis, although in numerous occasions it is defined clinically. Classical and more frequent histology pattern exhibits hyperplasia and hypertrophy of the epidermis; however, distinct characteristics may occur depending on factors like superinfection and immune response of patients. This article describes general aspects of molluscum contagiosum and exposes several clinical cases, one of which exhibits an unusual manifestation in the semimucosa of the lip. Finally, comments are made regarding the importance for dentists to learn about the existence of this pathology and be able to recognize it in order to avoid its complications and spread (AU)

Prediction of skin disease using a new cytological taxonomy based on cytology and pathology with deep residual learning method.

With the development of artificial intelligence, technique improvement of the classification of skin disease is addressed. However, few study concerned on the current classification system of International Classification of Diseases, Tenth Revision (ICD)-10 on Diseases of the skin and subcutaneous tissue, which is now globally used for classification of skin disease. This study was aimed to develop a new taxonomy of skin disease based on cytology and pathology, and test its predictive effect on skin disease compared to ICD-10. A new taxonomy (Taxonomy 2) containing 6 levels (Project 2-4) was developed based on skin cytology and pathology, and represents individual diseases arranged in a tree structure with three root nodes representing: (1) Keratinogenic diseases, (2) Melanogenic diseases, and (3) Diseases related to non-keratinocytes and non-melanocytes. The predictive effects of the new taxonomy including accuracy, precision, recall, F1, and Kappa were compared with those of ICD-10 on Diseases of the skin and subcutaneous tissue (Taxonomy 1, Project 1) by Deep Residual Learning method. For each project, 2/3 of the images were included as training group, and the rest 1/3 of the images acted as test group according to the category (class) as the stratification variable. Both train and test groups in the Projects (2 and 3) from Taxonomy 2 had higher F1 and Kappa scores without statistical significance on the prediction of skin disease than the corresponding groups in the Project 1 from Taxonomy 1, however both train and test groups in Project 4 had a statistically significantly higher F1-score than the corresponding groups in Project 1 (P = 0.025 and 0.005, respectively). The results showed that the new taxonomy developed based on cytology and pathology has an overall better performance on predictive effect of skin disease than the ICD-10 on Diseases of the skin and subcutaneous tissue. The level 5 (Project 4) of Taxonomy 2 is better on extension to unknown data of diagnosis system assisted by AI compared to current used classification system from ICD-10, and may have the potential application value in clinic of dermatology.

Dermatosis específicas de la embarazada (DEE). Propuesta de nueva clasificación / Pregnant specific dermatoses (DEE). Proposal for a new classification

En el presente trabajo se realiza una breve descripción de las dermatosis específicas de la embarazada (DEE). Se considera que la afección específica más frecuente son las pápulas y placas urticarianas pruriginosas del embarazo (PPUPE), y en segundo lugar los prurigos vinculados del embarazo (PVE). Se aporta una propuesta de nueva clasificación de las dermatosis específicas de la embarazada (DEE). En la clasificación se consideran dos grupos de afecciones. Grupo A: dermatosis específicas de la embarazada (DEE), y dentro de él: a) como enfermedad más frecuente las pápulas y placas urticarianas pruriginosas del embarazo (PPUPE); b) seguidas de los prurigos, tanto sea el precoz como el tardío, a los cuales se los une bajo el término de prurigos vinculados del embarazo (PVE) como entidad también frecuente c) la foliculitis pruriginosa del embarazo (FPE). Como afecciones menos frecuentes dentro de este grupo: a) dermatitis papulosa de Spangler (DPS); b) erupción toxémica del embarazo (ETE); c) herpes gestationis (HG); d) impétigo herpetiforme (IH). Grupo B: afección específica de la embarazada sin lesiones en piel: colestasis intrahepática del embarazo (CIE). (AU)

In the present work, a brief description of the specific dermatoses of the pregnant woman (DEE) is made. The most common specific condition is considered to be pruritic urticarial papules and plaques of pregnancy (PPUPE), and secondly, prurigos associated with pregnancy (PVE). A proposal for a new classification of pregnant-specific dermatoses (DEE) is provided. Two groups of conditions are considered in the classification. Group A: pregnant-specific dermatosis (EED), and within it: a) as the most frequent disease, pruritic urticarial papules and plaques of pregnancy (PPUPE); b) followed by prurigos, both early and late, to which they are associated under the term of linked prurigos of pregnancy (PVE); as also frequent entity; c) the pruritic folliculitis of pregnancy (FPE). As less frequent conditions within this group: a) Spangler's papular dermatitis (DPS); b) toxic eruption of pregnancy (TEE); c) herpes gestationis (HG); d) impetigo herpetiformis (IH). Group B: specific condition of the pregnant woman without skin lesions: intrahepatic cholestasis of pregnancy (ICD). (AU)

Developing a Recognition System for Diagnosing Melanoma Skin Lesions Using Artificial Intelligence Algorithms.

In recent years, computerized biomedical imaging and analysis have become extremely promising, more interesting, and highly beneficial. They provide remarkable information in the diagnoses of skin lesions. There have been developments in modern diagnostic systems that can help detect melanoma in its early stages to save the lives of many people. There is also a significant growth in the design of computer-aided diagnosis (CAD) systems using advanced artificial intelligence. The purpose of the present research is to develop a system to diagnose skin cancer, one that will lead to a high level of detection of the skin cancer. The proposed system was developed using deep learning and traditional artificial intelligence machine learning algorithms. The dermoscopy images were collected from the PH2 and ISIC 2018 in order to examine the diagnose system. The developed system is divided into feature-based and deep leaning. The feature-based system was developed based on feature-extracting methods. In order to segment the lesion from dermoscopy images, the active contour method was proposed. These skin lesions were processed using hybrid feature extractions, namely, the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) methods to extract the texture features. The obtained features were then processed using the artificial neural network (ANNs) algorithm. In the second system, the convolutional neural network (CNNs) algorithm was applied for the efficient classification of skin diseases; the CNNs were pretrained using large AlexNet and ResNet50 transfer learning models. The experimental results show that the proposed method outperformed the state-of-art methods for HP2 and ISIC 2018 datasets. Standard evaluation metrics like accuracy, specificity, sensitivity, precision, recall, and F-score were employed to evaluate the results of the two proposed systems. The ANN model achieved the highest accuracy for PH2 (97.50%) and ISIC 2018 (98.35%) compared with the CNN model. The evaluation and comparison, proposed systems for classification and detection of melanoma are presented.

Prevention and occupational hazards for the skin during COVID-19 pandemic.

The life of medical specialists worldwide has dramatically changed due to the spread of the coronavirus disease 2019 (COVID-19) pandemic. Health care professionals (HCPs) have personally faced the outbreak by being on the first line of the battlefield with the disease and, as such, compose a significant number of people who have contracted COVID-19. We propose a classification and discuss the pathophysiology, clinical findings, and treatments and prevention of the occupational skin hazards COVID-19 poses to HCPs. The multivariate pattern of occupational skin diseases during the COVID-19 pandemic can be classified into four subgroups: mechanical skin injury, moisture-associated skin damage, contact reactions, and exacerbation of preexisting dermatoses. The clinical pattern is versatile, and the most affected skin sites were the ones in contact with the protective equipment. Dermatologists should recognize the plethora of HCPs' occupational skin reactions that are occurring during the COVID-19 pandemic and implement treatment and preventive strategies.

Drug Induced Cutaneous Manifestations due to Treatment of Gastrointestinal Disorders.

Cutaneous manifestations due to drugs used in the treatment of gastrointestinal disorders are multiple and common. Adequate diagnosis is of great importance, bearing in mind that the therapeutic regimen depends on its diagnosis. In this review, we provided an overview of the most common drug-induced skin lesions with a detailed explanation of the disease course, presentation and treatment, having in mind that in recent years, novel therapeutic modalities have been introduced in the treatment of various gastrointestinal disorders, and that incidence of cutaneous adverse reactions has been on the rise.

Cutaneous Manifestations of COVID-19: A Systematic Review.

Objective: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is currently a pandemic. Although pulmonary health has been the primary focus of studies during the early days of COVID-19, development of a comprehensive understanding of this emergent disease requires knowledge of all possible disease manifestations in affected patients. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA)-compliant review focuses on cutaneous manifestations reported in COVID-19 patients. Approach: Literature review was conducted using the PubMed database to examine various cutaneous manifestations related to the SARS-CoV-2 infection. Published articles (n = 56) related to search criteria from the onset of the COVID-19 pandemic to June 30, 2020, were included. The primary literature articles included in this study were mainly from France, Spain, Italy, and the United Kingdom. Results: Unique to many other symptoms of COVID-19, its cutaneous manifestations have been found in people of all age groups, including children. The cutaneous manifestations of COVID-19 are varied and include maculopapular, chilblain-like, urticarial, vesicular, livedoid, and petechial lesions. In addition, rashes are common in multisystem inflammatory syndrome in children, a new and serious health condition that shares symptoms with Kawasaki disease and is likely related to COVID-19. In addition, personal protective equipment-related skin wounds are of serious concern since broken cutaneous barriers can create an opening for potential COVID-19 infections. Innovation and Conclusion: As this virus continues to spread silently, mainly through asymptomatic carriers, an accurate and rapid identification of these cutaneous manifestations may be vital to early diagnosis and lead to possible better prognosis in COVID-19 patients. This systematic review and photo atlas provide a detailed analysis of the skin pathologies related to COVID-19. Study of these cutaneous manifestations and their pathogenesis, as well their significance in human health will help define COVID-19 in its entirety, which is a prerequisite to its effective management.

Skin lesions of face and scalp - Classification by a market-approved convolutional neural network in comparison with 64 dermatologists.

BACKGROUND: The clinical differentiation of face and scalp lesions (FSLs) is challenging even for trained dermatologists. Studies comparing the diagnostic performance of a convolutional neural network (CNN) with dermatologists in FSL are lacking. METHODS: A market-approved CNN (Moleanalyzer-Pro, FotoFinder Systems) was used for binary classifications of 100 dermoscopic images of FSL. The same lesions were used in a two-level reader study including 64 dermatologists (level I: dermoscopy only; level II: dermoscopy, clinical close-up images, textual information). Primary endpoints were the CNN's sensitivity and specificity in comparison with the dermatologists' management decisions in level II. Generalizability of the CNN results was tested by using four additional external data sets. RESULTS: The CNN's sensitivity, specificity and ROC AUC were 96.2% [87.0%-98.9%], 68.8% [54.7%-80.1%] and 0.929 [0.880-0.978], respectively. In level II, the dermatologists' management decisions showed a mean sensitivity of 84.2% [82.2%-86.2%] and specificity of 69.4% [66.0%-72.8%]. When fixing the CNN's specificity at the dermatologists' mean specificity (69.4%), the CNN's sensitivity (96.2% [87.0%-98.9%]) was significantly higher than that of dermatologists (84.2% [82.2%-86.2%]; p < 0.001). Dermatologists of all training levels were outperformed by the CNN (all p < 0.001). In confirmation, the CNN's accuracy (83.0%) was significantly higher than dermatologists' accuracies in level II management decisions (all p < 0.001). The CNN's performance was largely confirmed in three additional external data sets but particularly showed a reduced specificity in one Australian data set including FSL on severely sun-damaged skin. CONCLUSIONS: When applied as an assistant system, the CNN's higher sensitivity at an equivalent specificity may result in an improved early detection of face and scalp skin cancers.

Immunotherapies in cutaneous pathologies: an overview.

Skin is a vital protective organ, the main role of which is to provide a physical barrier and to prevent the entry of pathogens. Various pathologies, such as atopic dermatitis (AD), psoriasis (PSO), or skin cancers, can affect the skin, and all show a high and increasing prevalence. Many antibodies are currently used in the treatment of these diseases. However, various studies are underway for the development of new biologics directed against specific targets. In this review, we describe current biologics used in skin pathologies as well as antibodies in development. We also discuss various immunotherapy examples that use new delivery technologies, such as microneedle patch, nanoparticles (NPs), liposomes, or gel formulation.

The Application of Ultra-High-Frequency Ultrasound in Dermatology and Wound Management.

The management of lower extremity wounds is frequently performed by means of clinical examination, representing a challenge for the clinician due to the various conditions that can potentially enter differential diagnosis. Several diagnostic techniques are available in the dermatologist's arsenal as a support to diagnosis confirmation, including dermoscopy and ultrasonography. Recently, a novel ultrasonographic technique involving the use of ultra-high ultrasound frequencies has entered the scene, and appears a promising tool in the diagnostic workup of skin ulcerative lesions. The focus of this review is to discuss the potential role of ultra-high-frequency ultrasonography in the diagnostic workup of wounds in the light of the current applications of the technique.

Skin Disease Classification using Neural Network.

BACKGROUND: In this study, a novel and fully automatic skin disease classification approach is proposed using statistical feature extraction and Artificial Neural Network (ANN) based classification using first and second order statistical moments, the entropy of different color channels and texture-based features. AIMS: The basic aim of our study is to develop an automated system for skin disease classification that can help a general physician to automatically detect the lesion and classify it to disease types. METHOD: The performance of the proposed approach is corroborated by extensive experiments performed on a dataset of 588 images containing 6907 lesion regions. RESULTS: The results show that the proposed methodology can be effectively used to construct a skin disease classification system. CONCLUSION: Our proposed method is designed for a specific skin tone. Future investigation is needed to analyze the impact of different skin tones on the performance of lesions detection and classification system.

Rosai-Dorfman disease: an overview.

CONTEXT: Rosai-Dorfman disease is an uncommon histiocytic disorder most frequently presenting as bilateral cervical lymphadenopathy in children and young adults. Extranodal disease occurs in a significant proportion of patients. It has been recently classified as part of the 'R group' of histiocytoses by the Histiocyte Society in 2016. Cutaneous Rosai-Dorfman disease is regarded as a separate disease entity that falls into the 'C group' of histiocytoses according to this classification system. The pathogenesis was previously poorly understood; however, recent evidence demonstrating clonality in a subset of cases raises the possibility of a neoplastic process. A possible association with IgG4-related disease remains controversial. OBJECTIVES: To provide a comprehensive review of Rosai-Dorfman disease, including nodal, extranodal and cutaneous forms, with a particular emphasis on new insights into the possible clonal nature of the disease; to discuss the recently revised classification of the histiocytoses by the Histiocyte Society; and to summarise the findings from the literature regarding the controversial association with IgG4-related disease. DATA SOURCES: This review is based on published peer-reviewed English literature. CONCLUSIONS: Classic Rosai-Dorfman disease, which may be sporadic or familial, is considered a separate entity from cutaneous disease, which is reflected in the revised classification of histiocytoses. An increase in IgG4-positive plasma cells may be seen in Rosai-Dorfman disease. This finding in isolation is of limited significance and should be interpreted with caution. Studies investigating the molecular profile of the disease show that in at least a subset of cases the disease is a clonal process. The classification of Rosai-Dorfman disease is therefore likely to change as our understanding of the aetiopathogenesis evolves.

Giant variant of acquired perforating dermatosis, clinically masquerading as a sarcoma: A report of a rare case.

Acquired perforating dermatosis is a group of disease characterized by transepidermal elimination of altered dermal constituents of unknown pathogenesis. The giant variant was first described in 2006, as an emerging entity with seven reported cases to date. Here is an 83-year-old male presented with a 4-year history of gradually enlarging soft tisssue mass with ulcerartions at the left knee joint. Imaging revealed an extra-articular, single, heterogeneous, multinodular mass, suspicious for a soft tissue sarcoma. Wide local excision of the mass showed fleshy, hemorrhagic nodules communicating with epidermal ulcers. Microscopy showed cystic spaces straddling dermis and subcutis, containing eosinophilic, amorphous, granular material extruding through epidermal craters, surrounded by exuberant myofibroblastic proliferation. Trichrome and van-Gieson stains confirmed that the extruded material is collagen and the histology was compatible with the giant variant of acquired perforating collagenosis. Awareness of histological appearance prevents misdiagnosis and overtreatment of this entity, masquerading as a sarcoma clinically.

Canadian Burden of Skin Disease From 1990 to 2017: Results From the Global Burden of Disease 2017 Study [Formula: see text].

BACKGROUND: Skin diseases can have high morbidity that can be costly to society and individuals. To date, there has been no comprehensive assessment of the burden of skin disease in Canada. OBJECTIVES: To evaluate the burden of 18 skin and subcutaneous diseases from 1990 to 2017 in Canada using the Global Burden of Disease (GBD) data. METHODS: The 2017 GBD study measures health loss from 359 diseases and injuries in 195 countries; we evaluated trends in population health in Canada from 1990 to 2017 using incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs). Data are presented as rates (per 100 000), counts, or percent change with the uncertainty interval in brackets. RESULTS: From 1990 to 2017 for all skin diseases, DALY rates increased by 8% to 971 per 100 000 (674-1319), YLD rates increased by 8% to 897 per 100 000 (616-1235), YLL rates increased by 4% to 74 per 100 000 (53-89), and death rates increased by 18% to 5 per 100 000 (3-6). DALY rates for melanoma increased by 2% to 54 per 100 000 (39-68), for keratinocyte carcinoma by 14% to 17 per 100 000 (16-19), and for skin and subcutaneous disease by 8% to 900 per 100 000 (619-1233). The observed over expected ratios were higher for skin and subcutaneous disease (1.37) and keratinocyte carcinoma (1.17) and were lower for melanoma (0.73). CONCLUSIONS: The burden of skin disease has increased in Canada since 1990. These results can be used to guide health policy regarding skin disease in Canada.

Review-Current Concepts in Inflammatory Skin Diseases Evolved by Transcriptome Analysis: In-Depth Analysis of Atopic Dermatitis and Psoriasis.

During the last decades, high-throughput assessment of gene expression in patient tissues using microarray technology or RNA-Seq took center stage in clinical research. Insights into the diversity and frequency of transcripts in healthy and diseased conditions provide valuable information on the cellular status in the respective tissues. Growing with the technique, the bioinformatic analysis toolkit reveals biologically relevant pathways which assist in understanding basic pathophysiological mechanisms. Conventional classification systems of inflammatory skin diseases rely on descriptive assessments by pathologists. In contrast to this, molecular profiling may uncover previously unknown disease classifying features. Thereby, treatments and prognostics of patients may be improved. Furthermore, disease models in basic research in comparison to the human disease can be directly validated. The aim of this article is not only to provide the reader with information on the opportunities of these techniques, but to outline potential pitfalls and technical limitations as well. Major published findings are briefly discussed to provide a broad overview on the current findings in transcriptomics in inflammatory skin diseases.

Diagnoses of hospitalized patients with skin abnormalities prompting biopsy by consulting dermatologists: A 3-year review from a tertiary care center.

BACKGROUND: Dermatologists play an important role in diagnosing and managing hospitalized patients with cutaneous abnormalities. Skin biopsies remain an indispensable tool for aiding dermatologists in accurate diagnosis and treatment. We aimed to determine the range of conditions, and the most common conditions, prompting skin biopsy by dermatology hospital consultation (HCON) services to aid in evaluation of hospitalized patients. METHODS: All hospitalized patients seen by a single tertiary care center dermatology HCON service between 2015 and 2018 who had associated skin biopsies were identified. Histologic features and clinical diagnoses of each patient were classified into 13 histologic reaction pattern categories. RESULTS: Eight hundred and thirty one inpatients evaluated by our dermatology HCON service had 914 skin biopsies. The most frequent diagnostic categories prompting biopsy were vasculopathic (17.6%), interface dermatitis (16.5%), infectious (12.6%), and spongiotic dermatitis (10.9%). The most frequent diagnostic categories included drug reaction (13.2%), leukocytoclastic vasculitis (8.5%), skin cancer (5.4%), graft-vs-host disease (3.5%), connective tissue disease (3.3%), and calciphylaxis (3.0%). CONCLUSION: Our study suggests a variety of serious diseases affecting inpatients prompts biopsy by dermatology consultation services. Educational curricula for dermatology and pathology residents, fellows, and staff designed with these data may enhance knowledge that improves the quality of inpatient dermatology care.