Image Gallery: Super‐high magnification dermoscopy can identify pigmented cells: correlation with reflectance confocal microscopy

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concordance and time estimation of store and forward mobile teledermatology compared to classical face to face consultation

Smartphones have overcome the limitations of image quality seen in older devices and opened a new field of telemedicine called "mobile teledermatology". Technological advances and the need to reduce health service costs will strongly promote the development of telemedicine. For this reason, we evaluated the concordance be tween store-and-forward mobile teledermatology and the classical face-to-face dermatological visit. We also measured the time taken to submit a teleconsultation using a smartphone. Before conventional face-to-face visit, a final-year resident of the 3-year course for general practitioners collected medical history, took digital images of skin diseases with a smartphone and, measuring the time required to complete this operation, transmitted them to an expert teledermatologist. In 391 patients we obtained a concordance between face-to-face and store-and-forward diagnosis of 91.05% (Cohen κ coefficient = 0.906). On average only few minutes needs to be added to a no

An Updated Algorithm Integrated With Patient Data for the Differentiation of Atypical Nevi From Early Melanomas: the idScore 2021

Introduction: It is well known that multiple patient-related risk factors contribute to the development of cutaneous melanoma, including demographic, phenotypic and anamnestic factors. Objectives: We aimed to investigate which MM risk factors were relevant to be incorporated in a risk scoring-classifier based clinico-dermoscopic algorithm. Methods: This retrospective study was performed on a monocentric dataset of 374 atypical melanocytic skin lesions sharing equivocal dermoscopic features, excised in the suspicion of malignancy. Dermoscopic standardized images of 258 atypical nevi (aN) and 116 early melanomas (eMM) were collected along with objective lesional data (i.e., maximum diameter, specific body site and body area) and 7 dermoscopic data. All cases were combined with a series of 10 MM risk factors, including demographic (2), phenotypic (5) and anamnestic (3) ones. Results: The proposed iDScore 2021 algorithm is composed by 9 variables (age, skin phototype I/II, personal/familiar history of MM, maximum diameter, location on the lower extremities (thighs/legs/ ankles/back of the feet) and 4 dermoscopic features (irregular dots and globules, irregular streaks, blue gray peppering, blue white veil). The algorithm assigned to each lesion a score from 0 to 18, reached an area under the ROC curve of 92% and, with a score threshold ≥ 6, a sensitivity (SE) of 98.2% and a specificity (SP) of 50.4%, surpassing the experts in SE (+13%) and SP (+9%).Conclusions: An integrated checklist combining multiple anamnestic data with selected relevant dermoscopic features can be useful in the differential diagnosis and management of eMM and aN exhibiting with equivocal features

Line-field confocal optical coherence tomography: a new tool for non-invasive differential diagnosis of pustular skin disorders

Background The spectrum of pustular skin disorders (PSD) is large and particularly challenging, including inflammatory, infectious and amicrobial diseases. Moreover, although pustules represent the unifying clinical feature, they can be absent or not fully developed in the early stage of the disease. The line-field confocal optical coherence tomography (LC-OCT) is a recently developed imaging technique able to perform a non-invasive, in vivo, examination of the epidermis and upper dermis, reaching very high image resolution and virtual histology. Objectives We aimed to investigate the potentialities of LC-OCT in the non-invasive differential diagnosis of a series of 11 PSD with different aetiology, microscopic features, body location and incidence rates. Materials and Methods Complete LC-OCT imaging (i.e. 2D/3D frames, videos) was performed on a total of 19 patients (10 females and 9 males) aged between 35 and 79 years. Images were blindly evaluated and compared with corresponding histopathologic findings. Results The LC-OCT imaging was able to detect with high accuracy the pustule structure including shape, margins, morphology and cellular content, along with peculiar epidermal and adnexal alterations in each condition, including: Acute Generalized Exanthematous Pustulosis, Generalized pustular psoriasis, Generalized pustular figurate erythema, Subcorneal Pustular Dermatosis, Intraepidermal IgA pustulosis, Palmoplantar pustulosis, Palmoplantar pustular psoriasis. Herpetic whitlow, Acrodermatitis continua of Hallopeau, Vesicopustular Sweet syndrome and Vesicopustular Eosinophilic cellulitis, with pustular appearance, were also compared. Conclusions The new LC-OCT can represent a rapid, non-invasive and painless tool which can help differentiating among PSD of different aetiology and microscopic morphology in clinical mimickers in daily practice

UVA-1 phototherapy as adjuvant treatment for eosinophilic fasciitis: in vitro and in vivo functional characterization

Introduction: Eosinophilic fasciitis (EF) is a rare autoimmune disease causing progressive induration of dermal, hypodermal, and muscularis fascia. The exact pathogenesis is yet to be fully understood, and a validated therapy protocol still lacks. We here aimed to realize a clinical–functional characterization of these patients. Materials and methods: A total of eight patients (five males, 45 years average) were treated with adjuvant high-dose UVA-1 phototherapy (90 J/cm), after having received the standard systemic immunosuppressive protocol (oral methylprednisolone switched to methotrexate). Body lesion mapping, Localized Scleroderma Assessment Tool (LoSCAT), Dermatology Life Quality Index (DLQI), High-Resolution Ultrasound (HRUS) (13-17MHz), and ultra HRUS (55–70 MHz) were performed at each examination time taking specific anatomical points. Gene expression analysis at a molecular level and in vitro UVA-1 irradiation was realized on lesional fibroblasts primary cultures. Results: The LoSCAT and the DLQI showed to decrease significantly starting from the last UVA-1 session. A significant reduction in muscularis fascia thickness (−50% on average) was estimated starting from 3 months after the last UVA-1 session and maintained up to 12 months follow-up. Tissues was detected by HRUS. The UVA-1 in vitro irradiation of lesional skin sites cells appeared not to affect their viability. Molecular genes analysis revealed a significant reduction of IL-1ß and of TGF-ß genes after phototherapy, while MMPs 1,2,9 gene expression was enhanced. Comment: These preliminary in vivo and in vitro findings suggest that UVA-1 phototherapy is a safe and useful adjuvant therapy able to elicit anti-inflammatory effects and stimulate tissue matrix digestion and remodeling at lesional sites

Child-computer interaction, ubiquitous technologies, and big data

In this forum we celebrate research that helps to successfully bring the benefits of computing technologies to children, older adults, people with disabilities, and other populations that are often ignored in the design of mass-marketed products. The children’s technology landscape is changing quickly. The ubiquity of interactive technologies means children can access them just about anytime, anywhere. At the same time, these technologies constantly collect data from and about children, bringing them into the age of big data, voluntarily or not. These developments have the potential to significantly change children’s relationship to technology and the long-term impact of technology use. To discuss these changes, the child-computer-interaction community held a special interest group (SIG) meeting during the CHI 2018 conference

Skin Lesion Segmentation Ensemble with Diverse Training Strategies

This paper presents a novel strategy to perform skin lesion segmentation from dermoscopic images. We design an effective segmentation pipeline, and explore several pre-training methods to initialize the features extractor, highlighting how different procedures lead the Convolutional Neural Network (CNN) to focus on different features. An encoder-decoder segmentation CNN is employed to take advantage of each pre-trained features extractor. Experimental results reveal how multiple initialization strategies can be exploited, by means of an ensemble method, to obtain state-of-the-art skin lesion segmentation accuracy

Non-invasive scoring of cellular atypia in keratinocyte cancers in 3D LC-OCT images using Deep Learning

Diagnosis based on histopathology for skin cancer detection is today's gold standard and relies on the presence or absence of biomarkers and cellular atypia. However it suffers drawbacks: it requires a strong expertise and is time-consuming. Moreover the notion of atypia or dysplasia of the visible cells used for diagnosis is very subjective, with poor inter-rater agreement reported in the literature. Lastly, histology requires a biopsy which is an invasive procedure and only captures a small sample of the lesion, which is insufficient in the context of large fields of cancerization. Here we demonstrate that the notion of cellular atypia can be objectively defined and quantified with a non-invasive in-vivo approach in three dimensions (3D). A Deep Learning (DL) algorithm is trained to segment keratinocyte (KC) nuclei from Line-field Confocal Optical Coherence Tomography (LC-OCT) 3D images. Based on these segmentations, a series of quantitative, reproducible and biologically relevant metrics is derived to describe KC nuclei individually. We show that, using those metrics, simple and more complex definitions of atypia can be derived to discriminate between healthy and pathological skins, achieving Area Under the ROC Curve (AUC) scores superior than 0.965, largely outperforming medical experts on the same task with an AUC of 0.766. All together, our approach and findings open the door to a precise quantitative monitoring of skin lesions and treatments, offering a promising non-invasive tool for clinical studies to demonstrate the effects of a treatment and for clinicians to assess the severity of a lesion and follow the evolution of pre-cancerous lesions over time.© 2022. The Author(s)

Pigmented nodular melanoma: the predictive value of dermoscopic features using multivariate analysis

BACKGROUND: Nodular melanoma (NM), representing 10-30% of all melanomas, plays a major role in global mortality related to melanoma. Nonetheless, the literature on dermoscopy of NM is scanty. OBJECTIVES: To assess odds ratios (ORs) to quantify dermoscopic features of pigmented NM vs. pigmented superficial spreading melanoma (SSM), and pigmented nodular nonmelanocytic and benign melanocytic lesions. METHODS: To assess the presence or absence of global patterns and dermoscopic criteria, digitized images of 457 pigmented skin lesions from patients with a histopathological diagnosis of NM (n = 75), SSM (n = 93), and nodular nonmelanocytic and benign melanocytic lesions (n = 289; namely, 39 basal cell carcinomas, 85 seborrhoeic keratoses, 81 blue naevi, and 84 compound/dermal naevi) were retrospectively collected and blindly evaluated by three observers. RESULTS: Multivariate analysis showed that ulceration (OR 4.07), homogeneous disorganized pattern (OR 10.76), and homogeneous blue pigmented structureless areas (OR 2.37) were significantly independent prognostic factors for NM vs. SSM. Multivariate analysis of dermoscopic features of NM vs. nonmelanocytic and benign melanocytic lesions showed that the positive correlating features leading to a significantly increased risk of NM were asymmetric pigmentation (OR 6.70), blue-black pigmented areas (OR 7.15), homogeneous disorganized pattern (OR 9.62), a combination of polymorphous vessels and milky-red globules/areas (OR 23.65), and polymorphous vessels combined with homogeneous red areas (OR 33.88). CONCLUSIONS: Dermoscopy may be helpful in improving the recognition of pigmented NM by revealing asymmetric pigmentation, blue-black pigmented areas, homogeneous disorganized pattern and abnormal vascular structures, including polymorphous vessels, milky-red globules/areas and homogeneous red areas