[Optical coherence tomography for the diagnosis and differentiation of cutaneous cysts: a case series]

Cutaneous cystic lesions (n = 35) were examined with optical coherence tomography. Cysts were visible as a hyporeflective roundish area with a clear margin; in some cases, the epidermis was thinned. Epidermal cysts, trichilemmal cysts, and hidrocystomas had a linear margin representing the epithelium of the cyst, whereas mucoid pseudocysts showed no linear margin. Trichilemmal and epidermal cysts presented with hyperreflective content that corresponds to keratin. By visualizing the margin and the content of the cyst, it was possible to differentiate between different types of cysts.

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma

Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists' decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists' diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists' confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists' willingness to adopt such XAI systems, promoting future use in the clinic.

Clinician's Ability to Identify Non-Melanoma Skin Cancer on 3D-Total Body Photography Sectors that Were Initially Identified during In-Person Skin Examination with Dermoscopy

INTRODUCTION

Non-melanoma skin cancer (NMSC) is a cause of significant morbidity and mortality in high-risk individuals. Total body photography (TBP) is currently used to monitor melanocytic lesions in patients with high risk for melanoma. The authors examined if three-dimensional (3D)-TBP could be useful for diagnosis of NMSC.

METHODS

Patients (n = 129; 52 female, 77 male) with lesions suspicious for NMSC who had not yet had a biopsy underwent clinical examination followed by examination of each lesion with 3D-TBP Vectra®WB360 (Canfield Scientific, Parsippany, NJ, USA) and dermoscopy.

RESULTS

The 129 patients had a total of 182 lesions. Histological examination was performed for 158 lesions; the diagnoses included basal cell carcinoma (BCC; n = 107), squamous cell carcinoma (SCC; n = 27), in-situ SCC (n = 15). Lesions were located in the head/neck region (n = 138), trunk (n = 21), and limbs (n = 23). Of the 182 lesions examined, 12 were not visible on 3D-TBP; reasons for not being visible included location under hair and on septal of nose. Two lesions appeared only as erythema in 3D-TBP but were clearly identifiable on conventional photographs. Sensitivity of 3D-TBP was lower than that of dermoscopy for BCC (73% vs. 79%, p = 0.327), higher for SCC (81% vs. 74%, p = 0.727), and lower for in-situ SCC (0% vs. 33%, p = 125). Specificity of 3D-TBP was lower than that of dermoscopy for BCC (77% vs. 82%, 0.581), lower for SCC (75% vs. 84%, p = 0.063), and higher for in-situ SCC (97% vs. 94%, p = 0.344). Diagnostic accuracy of 3D-TBP was lower than that of dermoscopy for BCC (75% vs. 80%), lower for SCC (76% vs. 82%), and lower for in-situ SCC (88% vs. 89%). Lesion location was not associated with diagnostic confidence in dermoscopy (p = 0.152) or 3D-TBP (p = 0.353). If only lesions with high confidence were included in the calculation, diagnostic accuracy increased for BCC (n = 27; sensitivity 85%, specificity 85%, diagnostic accuracy 85%), SCC (n = 10; sensitivity 90%, specificity 80%, diagnostic accuracy 83%), and for in-situ SCC (n = 2; sensitivity 0%, specificity 100%, diagnostic accuracy 95%).

CONCLUSION

Diagnostic accuracy appears to be slightly lower for 3D-TBP in comparison to dermoscopy. However, there is no statistically significant difference in the sensitivity and specificity of 3D-TBP and dermoscopy for NMSC. Diagnostic accuracy increases, if only lesions with high confidence are included in the calculation. Further studies are necessary to determine if 3D-TBP can improve management of NMSC.

Leptomeningeal Metastases in Melanoma Patients: An Update on and Future Perspectives for Diagnosis and Treatment

Leptomeningeal disease (LMD) is a devastating complication of cancer with a particularly poor prognosis. Among solid tumours, malignant melanoma (MM) has one of the highest rates of metastasis to the leptomeninges, with approximately 10-15% of patients with advanced disease developing LMD. Tumour cells that metastasise to the brain have unique properties that allow them to cross the blood-brain barrier, evade the immune system, and survive in the brain microenvironment. Metastatic colonisation is achieved through dynamic communication between metastatic cells and the tumour microenvironment, resulting in a tumour-permissive milieu. Despite advances in treatment options, the incidence of LMD appears to be increasing and current treatment modalities have a limited impact on survival. This review provides an overview of the biology of LMD, diagnosis and current treatment approaches for MM patients with LMD, and an overview of ongoing clinical trials. Despite the still limited efficacy of current therapies, there is hope that emerging treatments will improve the outcomes for patients with LMD.

Integrating Patient Data Into Skin Cancer Classification Using Convolutional Neural Networks: Systematic Review

Background

Recent years have been witnessing a substantial improvement in the accuracy of skin cancer classification using convolutional neural networks (CNNs). CNNs perform on par with or better than dermatologists with respect to the classification tasks of single images. However, in clinical practice, dermatologists also use other patient data beyond the visual aspects present in a digitized image, further increasing their diagnostic accuracy. Several pilot studies have recently investigated the effects of integrating different subtypes of patient data into CNN-based skin cancer classifiers.

Objective

This systematic review focuses on the current research investigating the impact of merging information from image features and patient data on the performance of CNN-based skin cancer image classification. This study aims to explore the potential in this field of research by evaluating the types of patient data used, the ways in which the nonimage data are encoded and merged with the image features, and the impact of the integration on the classifier performance.

Methods

Google Scholar, PubMed, MEDLINE, and ScienceDirect were screened for peer-reviewed studies published in English that dealt with the integration of patient data within a CNN-based skin cancer classification. The search terms skin cancer classification, convolutional neural network(s), deep learning, lesions, melanoma, metadata, clinical information, and patient data were combined.

Results

A total of 11 publications fulfilled the inclusion criteria. All of them reported an overall improvement in different skin lesion classification tasks with patient data integration. The most commonly used patient data were age, sex, and lesion location. The patient data were mostly one-hot encoded. There were differences in the complexity that the encoded patient data were processed with regarding deep learning methods before and after fusing them with the image features for a combined classifier.

Conclusions

This study indicates the potential benefits of integrating patient data into CNN-based diagnostic algorithms. However, how exactly the individual patient data enhance classification performance, especially in the case of multiclass classification problems, is still unclear. Moreover, a substantial fraction of patient data used by dermatologists remains to be analyzed in the context of CNN-based skin cancer classification. Further exploratory analyses in this promising field may optimize patient data integration into CNN-based skin cancer diagnostics for patients’ benefits.

Medical treatment of advanced cutaneous squamous-cell carcinoma

Considering the rising incidence, cutaneous squamous-cell carcinoma (cSCC) has a high clinical relevance. In patients with localized cSCC, complete surgical resection is indicated. Radiotherapy should be performed in patients with non-resectable tumours or in patients who are not suitable for surgery. Systemic therapy is reserved for cSCC that are neither surgically nor radiotherapeutically curable due to their extensive local spread and/or local or distant metastasis. In the absence of prospective randomized phase 3 trials to evaluate and compare the efficacy and safety of chemotherapeutics, epidermal growth factor receptor (EGFR) inhibitors and anti-PD-1 antibodies, no final recommendation for systemic therapy can be given for patients with locally advanced or metastatic cSCC. Anti-PD-1 antibodies currently show promising results with response rates of up to 50% in both locally advanced and metastatic cSCC. Anti-PD-1 antibodies appear to achieve higher response rates compared with EGFR inhibitors, and the duration of response appears to be superior to both chemotherapy and EGFR inhibitors. Compared with chemotherapy, the side effect profile of anti-PD-1 antibodies appears to be favourable. Altogether, PD-1 inhibitors are expected to become the new standard of care for patients with locally advanced and metastatic cSCC. Currently, placebo-controlled clinical trials are investigating the adjuvant use of cemiplimab and pembrolizumab in patients undergoing resection and radiotherapy of high-risk cSCC. Patients not eligible for anti-PD-1 treatment, e.g. in organ transplant recipients, or in patients refractory to anti-PD-1 may be offered EGFR inhibitors and/or chemotherapies. Chemotherapies appear to be superior to EGFR inhibitors in terms of response rates, whereas EGFR inhibitors have a more favourable toxicity profile. EGFR inhibitors are therefore more suitable for multimorbid and/or frail elderly patients. By combining EGFR inhibitors with local therapy such as surgery or radiotherapy, response rates and duration of response may be improved.

Anti-PD-1 and Novel Combinations in the Treatment of Melanoma-An Update

Until recently, distant metastatic melanoma was considered refractory to systemic therapy. A better understanding of the interactions between tumors and the immune system and the mechanisms of regulation of T-cells led to the development of immune checkpoint inhibitors. This review summarizes the current novel data on the treatment of metastatic melanoma with anti-programmed cell death protein 1 (PD-1) antibodies and anti-PD-1-based combination regimens, including clinical trials presented at major conference meetings. Immune checkpoint inhibitors, in particular anti-PD-1 antibodies such as pembrolizumab and nivolumab and the combination of nivolumab with the anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibody ipilimumab can achieve long-term survival for patients with metastatic melanoma. The anti-PD-1 antibodies nivolumab and pembrolizumab were also approved for adjuvant treatment of patients with resected metastatic melanoma. Anti-PD-1 antibodies appear to be well tolerated, and toxicity is manageable. Nivolumab combined with ipilimumab achieves a 5 year survival rate of more than 50% but at a cost of high toxicity. Ongoing clinical trials investigate novel immunotherapy combinations and strategies (e.g., Talimogene laherparepvec (T-VEC), Bempegaldesleukin (BEMPEG), incorporation or sequencing of targeted therapy, incorporation or sequencing of radiotherapy), and focus on poor prognosis groups (e.g., high tumor burden/LDH levels, anti-PD-1 refractory melanoma, and brain metastases).

Schnitzler syndrome

Schnitzler syndrome is a very rare acquired systemic disease with many similarities to hereditary autoinflammatory syndromes. The main characteristics are generalized exanthema and IgM monoclonal gammopathy. Other clinical features include fever, muscle, bone, and/or joint pain, and lymphadenopathy. About 15-20% of patients with Schnitzler syndrome develop lymphoproliferative diseases and, in rare cases, amyloid A (AA) amyloidosis can occur if the disease is not treated. Activation of the innate immune system, especially interleukin (IL)-1β, is central to the pathogenesis of disease. Consequently, complete control of disease symptoms can be achieved in 80% of patients by treatment with the IL-1 receptor antagonist anakinra.

[Schnitzler syndrome]

Schnitzler syndrome is a very rare acquired systemic disease with many similarities to hereditary autoinflammatory syndromes. The main characteristics are generalized exanthema and a monoclonal gammopathy with IgM. Other clinical features include fever, muscle, bone and/or joint pain, and lymphadenopathy. About 15-20% of patients with Schnitzler syndrome develop lymphoproliferative diseases and, in rare cases, amyloid A (AA) amyloidosis can occur if the disease is not treated. Activation of the innate immune system, especially interleukin(IL)-1β, is central in the pathogenesis of the disease. Consequently, complete control of disease symptoms can be achieved in 80% of patients by treatment with the IL-1 receptor antagonist anakinra.