Frontal Fibrosing Alopecia: Role of Dermoscopy in Differential Diagnosis

Frontal fibrosing alopecia (FFA) is more common in postmenopausal women, but it can occur in younger women. Some authors consider FFA to be a distinct frontal variant of lichen planopilaris. From a clinical point of view, this relatively uncommon condition is characterized by progressive frontotemporal recession due to inflammatory destruction of hair follicles. Dermoscopy can be very useful, as the differential diagnosis between traction alopecia, alopecia areata, FFA and cicatricial marginal alopecia may be difficult. It is not clear whether or not treatment alters the natural history of the disease - the disease stabilized with time in most of the patients with or without continuing treatment. Here we report a case of a 50-year-old woman with FFA and discuss the relevance of dermoscopy in the differential diagnosis of this disease

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

n/

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

Comparative Analysis of AI Models for Atypical Pigmented Facial Lesion Diagnosis

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

Comparison of reflectance confocal microscopy and line-field optical coherence tomography for the identification of keratinocyte skin tumours

Background: Reflectance confocal microscopy (RCM) and line-field confocal optical coherence tomography (LC-OCT) are non-invasive imaging devices that can help in the clinical diagnosis of actinic keratosis (AK) and cutaneous squamous cell carcinoma (SCC). No studies are available on the comparison between these two technologies for the identification of the different features of keratinocyte skin tumours. Objectives: To compare RCM and LC-OCT findings in AK and SCC. Methods: A retrospective multicenter study was conducted. Tumours were imaged with RCM and LC-OCT devices before surgery, and the diagnosis was confirmed by histological examinations. LC-OCT and RCM criteria for AK/SCC were identified, and their presence/absence was evaluated in all study lesions. Gwet AC1 concordance index was calculated to compare RCM and LC-OCT. Results: We included 52 patients with 33 AKs and 19 SCCs. Irregular epidermis was visible in most tumours and with a good degree of agreement between RCM and LC-OCT (Gwet's AC1 0.74). Parakeratosis, dyskeratotic keratinocytes and both linear dilated and glomerular vessels were better visible at LC-OCT than RCM (p < 0.001). Erosion/ulceration was identified with both methods in more than half of the cases with a good degree of agreement (Gwet AC1 0.62). Conclusions: Our results suggest that both LC-OCT and hand-held RCM can help clinicians in the identification of AK and SCC, providing an in vivo and non-invasive identification of an irregular epidermis. LC-OCT proved to be more effective in identifying parakeratosis, dyskeratotic keratinocytes and vessels in this series