New horizons in dermatological education: Skin cancer screening with virtual reality.

BACKGROUND: Technological advances in the field of virtual reality (VR) offer new opportunities in many areas of life, including medical education. The University of Münster has been using VR scenarios in the education of medical students for several years, especially for situations that are difficult to reproduce in reality (e.g., brain death). Due to the consistently positive feedback from students, a dermatological VR scenario for skin cancer screening was developed. OBJECTIVES: Presentation and first evaluation of the skin cancer screening VR scenario to determine to what extent the technical implementation of the scenario was evaluated overall by the students and how their subjective competence to perform a skin cancer screening changed over the course of the teaching unit (theory seminar, VR scenario, theoretical debriefing). METHODS: Students (n = 140) participating in the curricular pilot project during the 2023 summer term were surveyed throughout the teaching unit using several established questionnaires (System Usability Scale, Simulation Task-Load-Index, Realism and Presence Questionnaire) as well as additional questions on cybersickness and subjective learning. RESULTS: (i) The use of VR is technically feasible, (ii) students evaluate the VR scenario as a useful curricular supplement, and (iii) from the students' subjective perspective, a good learning outcome is achieved. Although preparation and follow-up appear to be important for overall learning, the greatest increase in subjective competence to perform a skin cancer screening is achieved by the VR scenario. CONCLUSIONS: Technically feasible and positively evaluated by students, VR can already be a useful addition to dermatology education, although costs are still high. As a visual discipline, dermatology offers special opportunities to create VR scenarios that are not always available or comfortable for patients in reality. Additionally, VR scenarios guarantee the same conditions for all students, which is essential for a high-quality education.

A 3-dimensional histology computer model of malignant melanoma and its implications for digital pathology.

BACKGROUND: Historically, cancer diagnoses have been made by pathologists using two-dimensional histological slides. However, with the advent of digital pathology and artificial intelligence, slides are being digitised, providing new opportunities to integrate their information. Since nature is 3-dimensional (3D), it seems intuitive to digitally reassemble the 3D structure for diagnosis. OBJECTIVE: To develop the first human-3D-melanoma-histology-model with full data and code availability. Further, to evaluate the 3D-simulation together with experienced pathologists in the field and discuss the implications of digital 3D-models for the future of digital pathology. METHODS: A malignant melanoma of the skin was digitised via 3 µm cuts by a slide scanner; an open-source software was then leveraged to construct the 3D model. A total of nine pathologists from four different countries with at least 10 years of experience in the histologic diagnosis of melanoma tested the model and discussed their experiences as well as implications for future pathology. RESULTS: We successfully constructed and tested the first 3D-model of human melanoma. Based on testing, 88.9% of pathologists believe that the technology is likely to enter routine pathology within the next 10 years; advantages include a better reflectance of anatomy, 3D assessment of symmetry and the opportunity to simultaneously evaluate different tissue levels at the same time; limitations include the high consumption of tissue and a yet inferior resolution due to computational limitations. CONCLUSIONS: 3D-histology-models are promising for digital pathology of cancer and melanoma specifically, however, there are yet limitations which need to be carefully addressed.

Lives of Skin Lesions in Monkeypox: Histomorphological, Immunohistochemical, and Clinical Correlations in a Small Case Series.

Monkeypox (mpox), a former rare viral zoonosis, has increasingly made it into the public eye since the major outbreak that started in May 2022. Mpox presents with skin lesions that change over time and go through different stages (macular, papular, pustular, and early and late ulceration). In this study, we evaluated skin biopsies of all stages. Therefore, five biopsies from four patients were analyzed histologically, immunohistochemically with anti-Vaccinia virus antibodies, and electron-microscopically. Notably, the early macular stage only showed subtle viropathic changes; it did not express of Orthopoxvirus proteins in immunohistochemistry and therefore can easily be missed histologically. In later stages, immunohistochemistry with anti-Vaccinia virus antibodies might be useful to distinguish mpox from differential diagnoses such as herpes virus infections. In the ulcerative stages, the identified occlusive vasculopathic changes could be an explanation for the severe pain of the lesions reported by some patients. Despite the small number of samples examined, our analysis suggests that the histological findings of mpox are highly dependent on the stage of the biopsied lesion. Therefore, knowledge of all different stages of histology is necessary to reliably diagnose mpox histologically, especially when molecular testing is not available.

Histology-based classifier to distinguish early mycosis fungoides from atopic dermatitis.

BACKGROUND: Histopathological differentiation of early mycosis fungoides (MF) from benign chronic inflammatory dermatoses remains difficult and often impossible, despite the inclusion of all available diagnostic parameters. OBJECTIVE: To identify the most impactful histological criteria for a predictive diagnostic model to discriminate MF from atopic dermatitis (AD). METHODS: In this multicentre study, two cohorts of patients with either unequivocal AD or MF were evaluated by two independent dermatopathologists. Based on 32 histological attributes, a hypothesis-free prediction model was developed and validated on an independent patient's cohort. RESULTS: A reduced set of two histological features (presence of atypical lymphocytes in either epidermis or dermis) was trained. In an independent validation cohort, this model showed high predictive power (95% sensitivity and 100% specificity) to differentiate MF from AD and robustness against inter-individual investigator differences. LIMITATIONS: The study investigated a limited number of cases and the classifier is based on subjectively evaluated histological criteria. CONCLUSION: Aiming at distinguishing early MF from AD, the proposed binary classifier performed well in an independent cohort and across observers. Combining this histological classifier with immunohistochemical and/or molecular techniques (such as clonality analysis or molecular classifiers) could further promote differentiation of early MF and AD.

Comparison of Complication Rates Between Subpectoral vs Prepectoral Techniques in Prosthetic Breast Reconstruction.

BACKGROUND: The location of tissue expanders in implant-based breast reconstruction remains controversial due to variation in surgical techniques and devices. OBJECTIVES: The aim of this study was to provide a comprehensive assessment of early and late complication rates between prepectoral and subpectoral placement of tissue expanders. METHODS: A retrospective cohort study was conducted of all adult female patients who had undergone 2-stage implant-based breast reconstruction between 2013 and 2019 in our institution. Early complication was defined as complications that occurred within 30 days after surgery. Time-to-event analyses were performed and Cox proportional hazard models were used to adjust for confounders. RESULTS: In total, 854 patients were included; 76% of patients underwent a subpectoral tissue expander placement. After the first-stage procedure, the early complication rate was 34% and the late complication rate was 36.4%. After the second-stage procedure, the early complication rate was 16.3% and the late complication rate was 16.1%. Location of the tissue expander did not predict either overall early or late complication rates, regardless of the stages of reconstruction, after adjusting for confounders. Tissue expanders placed in prepectoral plane were associated with a higher hazard ratio (HR) for developing early and late infection after the first stage of reconstruction (HR, 2.1 and 2.4, respectively) as well as late infection after the second stage of reconstruction (HR, 5.3; all P < .05). CONCLUSIONS: Location of tissue expanders did not predict risk of complication. However, the prepectoral group was associated with an increased risk of developing infection.

Immunothrombotic Mechanisms Induced by Ingenol Mebutate Lead to Rapid Necrosis and Clearance of Anogenital Warts.

Ingenol mebutate (IM) is highly effective in the treatment of human papillomavirus (HPV)-induced anogenital warts (AGW) leading to fast ablation within hours. However, the exact mode of action is still largely unknown. We performed dermoscopy, in vivo confocal microscopy (CLM), histology, immunohistochemistry, and immunofluorescence to gain insights in mechanisms of IM treatment in AGW. In addition, we used in vitro assays (ELISA, HPV-transfection models) to further investigate in vivo findings. IM treatment leads to a strong recruitment of neutrophils with thrombosis of small skin vessels within 8 h, in a sense of immunothrombosis. In vivo and in vitro analyses showed that IM supports a prothrombotic environment by endothelial cell activation and von Willebrand factor (VWF) secretion, in addition to induction of neutrophil extracellular traps (NETosis). IM superinduces CXCL8/IL-8 expression in HPV-E6/E7 transfected HaCaT cells when compared to non-infected keratinocytes. Rapid ablation of warts after IM treatment can be well explained by the observed immunothrombosis. This new mechanism has so far only been observed in HPV-induced lesions and is completely different from the mechanisms we see in the treatment of transformed keratinocytes in actinic keratosis. Our initial findings indicate an HPV-specific effect, which could be also of interest for the treatment of other HPV-induced lesions. Larger studies are now needed to further investigate the potential of IM in different HPV tumors.

[Digitalization in dermatopathology]. / Digitalisierung in der Dermatopathologie.

The histomorphological analysis of tissue sections by specially trained dermatopathologists is a central component for making the dermatological diagnosis. It is the foundation for the understanding of clinical aspects, pathophysiology and not least the treatment of skin diseases and is therefore an essential part of modern dermatology. New technological developments in recent years offer a variety of possibilities to digitalize dermatopathology, which could significantly change and even revolutionize the work of dermatopathologists in the coming years; however, like any new development there are limiting factors and open questions that need to be discussed. This article is intended to provide an overview of the current state of the art and to highlight the corresponding opportunities and risks on the road to digital dermatopathology.

[Skin manifestations of COVID-19 and after COVID-19 vaccination]. / Hautveränderungen bei COVID-19 und nach COVID-19-Impfung.

Coronavirus disease 2019 (COVID-19) is a systemic disease induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that frequently presents with skin manifestations. The five most common skin lesions are pseudo-chilblain and maculopapular, urticarial, vesicular, and livedo/necrotizing skin lesions. These skin lesions are of diagnostic and prognostic relevance. For example, in children, typical skin lesions may indicate a life-threatening inflammatory syndrome, which rarely occurs after corona infection. Skin lesions have also been described after COVID-19 vaccination. These usually show an uncomplicated, self-limiting course and therefore do not represent a contraindication for completing the vaccination status in the vast majority of cases.

ExAID: A multimodal explanation framework for computer-aided diagnosis of skin lesions.

BACKGROUND AND OBJECTIVES: One principal impediment in the successful deployment of Artificial Intelligence (AI) based Computer-Aided Diagnosis (CAD) systems in everyday clinical workflows is their lack of transparent decision-making. Although commonly used eXplainable AI (XAI) methods provide insights into these largely opaque algorithms, such explanations are usually convoluted and not readily comprehensible. The explanation of decisions regarding the malignancy of skin lesions from dermoscopic images demands particular clarity, as the underlying medical problem definition is ambiguous in itself. This work presents ExAID (Explainable AI for Dermatology), a novel XAI framework for biomedical image analysis that provides multi-modal concept-based explanations, consisting of easy-to-understand textual explanations and visual maps, to justify the predictions. METHODS: Our framework relies on Concept Activation Vectors to map human-understandable concepts to those learned by an arbitrary Deep Learning (DL) based algorithm, and Concept Localisation Maps to highlight those concepts in the input space. This identification of relevant concepts is then used to construct fine-grained textual explanations supplemented by concept-wise location information to provide comprehensive and coherent multi-modal explanations. All decision-related information is presented in a diagnostic interface for use in clinical routines. Moreover, the framework includes an educational mode providing dataset-level explanation statistics as well as tools for data and model exploration to aid medical research and education processes. RESULTS: Through rigorous quantitative and qualitative evaluation of our framework on a range of publicly available dermoscopic image datasets, we show the utility of multi-modal explanations for CAD-assisted scenarios even in case of wrong disease predictions. We demonstrate that concept detectors for the explanation of pre-trained networks reach accuracies of up to 81.46%, which is comparable to supervised networks trained end-to-end. CONCLUSIONS: We present a new end-to-end framework for the multi-modal explanation of DL-based biomedical image analysis in Melanoma classification and evaluate its utility on an array of datasets. Since perspicuous explanation is one of the cornerstones of any CAD system, we believe that ExAID will accelerate the transition from AI research to practice by providing dermatologists and researchers with an effective tool that they can both understand and trust. ExAID can also serve as the basis for similar applications in other biomedical fields.

Derazantinib: an investigational drug for the treatment of cholangiocarcinoma.

INTRODUCTION: This review evaluates the clinical role of fibroblast growth factor receptor 2 (FGFR2) inhibition with derazantinib in patients with intrahepatic cholangiocarcinoma (iCCA) harboring actionable oncogenic FGFR2 fusions/rearrangements, mutations and amplifications. FGFR inhibitors such as derazantinib are currently being evaluated to address the unmet medical need of patients with previously treated, locally advanced or metastatic iCCA harboring such genetic aberrations. AREAS COVERED: We summarize the pharmacokinetics, and the emerging safety and efficacy data of the investigational FGFR inhibitor derazantinib. We discuss the future directions of this novel therapeutic agent for iCCA. EXPERT OPINION: Derazantinib is a potent FGFR1‒3 kinase inhibitor which also has activity against colony stimulating factor-1‒receptor (CSF1R) and vascular endothelial growfth factor receptor‒2 (VEGFR2), suggesting a potentially differentiated role in the treatment of patients with iCCA. Derazantinib has shown clinically meaningful efficacy with durable objective responses, supporting the therapeutic potential of derazantinib in previously treated patients with iCCA harboring FGFR2 fusions/rearrangements, mutations and amplifications. The clinical safety profile of derazantinib was well manageable and compared favorably to the FGFR inhibitor class, particularly with a low incidence of drug-related hand-foot syndrome, stomatitis, retinal and nail toxicity. These findings support the need for increased molecular profiling of cholangiocarcinoma patients.

Skin cancer classification via convolutional neural networks: systematic review of studies involving human experts.

BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinicopathological practice. OBJECTIVE: The objective of the study was to systematically analyse the current state of research on reader studies involving melanoma and to assess their potential clinical relevance by evaluating three main aspects: test set characteristics (holdout/out-of-distribution data set, composition), test setting (experimental/clinical, inclusion of metadata) and representativeness of participating clinicians. METHODS: PubMed, Medline and ScienceDirect were screened for peer-reviewed studies published between 2017 and 2021 and dealing with AI-based skin cancer classification involving melanoma. The search terms skin cancer classification, deep learning, convolutional neural network (CNN), melanoma (detection), digital biomarkers, histopathology and whole slide imaging were combined. Based on the search results, only studies that considered direct comparison of AI results with clinicians and had a diagnostic classification as their main objective were included. RESULTS: A total of 19 reader studies fulfilled the inclusion criteria. Of these, 11 CNN-based approaches addressed the classification of dermoscopic images; 6 concentrated on the classification of clinical images, whereas 2 dermatopathological studies utilised digitised histopathological whole slide images. CONCLUSIONS: All 19 included studies demonstrated superior or at least equivalent performance of CNN-based classifiers compared with clinicians. However, almost all studies were conducted in highly artificial settings based exclusively on single images of the suspicious lesions. Moreover, test sets mainly consisted of holdout images and did not represent the full range of patient populations and melanoma subtypes encountered in clinical practice.

Delayed skin reaction after mRNA-1273 vaccine against SARS-CoV-2: a rare clinical reaction.

BACKGROUND: The coronavirus disease 2019 (COVID-19) is associated with a wide clinical spectrum of skin manifestations, including urticarial, vesicular, vasculitic and chilblain-like lesions. Recently, delayed skin reactions have been reported in 1% individuals following mRNA vaccination against SARS-CoV-2. The exact pathophysiology and the risk factors still remain unclear. PATIENTS AND METHODS: 6821 employees and patients were vaccinated at our institutions between February and June 2021. Every patient received two doses of the mRNA-1273 vaccine in our hospitals, and reported back in case of any side effects which were collected in our hospital managed database. RESULTS: Eleven of 6821 vaccinated patients (0.16%) developed delayed skin reactions after either the first or second dose of the mRNA-1273 vaccine against SARS-CoV-2. Eight of 11 patients (73%) developed a rash after the first dose, while in 3/11 (27%), the rash occurred after the second dose. More females (9/11) were affected. Four of 11 patients required antihistamines, with two needing additional topical steroids. All the cutaneous manifestations resolved within 14 days. None of the skin reactions after the first dose of the vaccine prevented the administration of the second dose. There were no long-term cutaneous sequelae in any of the affected individuals. CONCLUSION: Our data suggests that skin reactions after the use of mRNA-1273 vaccine against SARS-CoV-2 are possible, but rare. Further studies need to be done to understand the pathophysiology of these lesions.

Psoriasis on the Leg: Site-specific Histopathological and Immuno-histochemical Features and Diagnostic Difficulties.

The histopathology of psoriasis can lack classical features on certain anatomical sites. The aim of this study was to detail the histopathology and immunophenotype of psoriasis on the legs, in order to differentiate it from other inflammatory dermatoses, such as stasis dermatitis. The histopathology of psoriasis on the legs was retrospectively compared with psoriasis on the trunk and stasis dermatitis. Statistically, psoriasis on the legs was significantly less likely to show typical histological criteria of psoriasis, such as regular hyperplasia, suprapapillary thinning, and "kissing vessels". The most valuable criteria to distinguish psoriasis on the legs from stasis dermatitis were the presence of neutrophils in the cornified layer and staggered parakeratosis. In addition, an immunohistochemical panel (Ki-67, Bcl-2alpha, S100A7, CD3, MPO, CK10, CK16) revealed that staining with Ki-67 and MPO could be diagnostically useful. Since the cornified layer contains important histopathological clues to differentiate psoriasis on the legs from stasis dermatitis, clinicians should refrain from unnecessary rubbing during disinfection before taking a biopsy.