ToF-SIMS imaging reveals changes in tumor cell lipids during metastatic progression of melanoma.

Most melanomas progress from radial to vertical growth phase before spreading locoregionally and distally. Much is still unknown about the metabolic changes in the tumor cells and their microenvironment during this metastatic progression. We aimed to gain new insight into the molecular characteristics of melanoma in regard to spatial lipidomics to deliver new knowledge regarding tumor metastatic progression. We included 10 fresh tumor samples from 10 patients including two in situ melanomas, two invasive primary melanomas, and six metastatic melanomas (four in-transit metastases and two distant metastases). In addition, we analyzed four healthy skin controls from the same patients. Time-of-flight imaging secondary ion mass spectrometry (ToF-SIMS) enabled detailed spatial-lipidomics that could be directly correlated with conventional histopathological analysis of consecutive H&E-stained tissue sections. Significant differences in the lipid profiles were found in primary compared to metastatic melanomas, notably an increase in phosphatidylethanolamine lipids relative to phosphatidylinositol lipids and an increase in GM3 gangliosides in the metastatic samples. Furthermore, analysis of the data from in transit versus distant metastases samples highlighted that specific phospholipids, and a difference in the long versus shorter chain GM3 gangliosides, discriminated the metastatic routes. Further studies are warranted to verify these preliminary findings. Lipidomic changes could serve as a novel biomarker for tumor progression and even serve as a target for novel treatments. Furthermore, analyzing the lipid profiles could help to differentiate between primary and metastatic melanomas in challenging cases.

Dermoscopic Findings in Intraepidermal Carcinoma: an Interobserver Agreement Study.

INTRODUCTION: A wide range of descriptive terms have been used for dermoscopic findings in intraepidermal carcinoma (IEC) and the clinical diagnostic accuracy of IEC can be challenging. Furthermore, dermoscopic findings in IEC have only rarely been evaluated in fair-skinned populations. OBJECTIVES: To measure the interobserver agreement between dermatologists for dermoscopic findings in IEC. Furthermore, to describe the frequency of these findings in a predominantly fair-skinned population. METHODS: One hundred dermoscopic images of histopathologically verified IECs were collected. The 11 most common dermoscopic findings described in previous studies were re-defined in a new terminology in a pre-study consensus meeting. Images were assessed by eight experienced international dermoscopists. The frequency of findings and the interobserver agreement was analyzed. RESULTS: Scales (83%), dotted/glomerular vessels (77%), pinkish-white areas (73%) and hemorrhage (46%) were the most commonly present dermoscopic findings. Pigmented structures were found in 32% and shiny white structures (follicular or stromal) in 54% of the IEC. Vascular structures (vessels and/or hemorrhage) could be seen in 89% of the lesions. Overall, the interobserver agreement for the respective dermoscopic findings was poor to moderate, with the highest kappa values noted for scales (0.55) and hemorrhage (0.54) and the lowest for pinkish-white areas (0.015). CONCLUSION: Our results confirm those of previous studies on dermoscopy in IEC, including the frequency of pigmented structures despite the fair-skinned population. The interobserver agreement was relatively low. The proposed new terminology and our findings can hopefully serve as a guideline for researchers, teachers and students on how to identify IEC.

Hyperspectral Imaging for Non-invasive Diagnostics of Melanocytic Lesions.

Malignant melanoma poses a clinical diagnostic problem, since a large number of benign lesions are excised to find a single melanoma. This study assessed the accuracy of a novel non-invasive diagnostic technology, hyperspectral imaging, for melanoma detection. Lesions were imaged prior to excision and histopathological analysis. A deep neural network algorithm was trained twice to distinguish between histopathologically verified malignant and benign melanocytic lesions and to classify the separate subgroups. Furthermore, 2 different approaches were used: a majority vote classification and a pixel-wise classification. The study included 325 lesions from 285 patients. Of these, 74 were invasive melanoma, 88 melanoma in situ, 115 dysplastic naevi, and 48 non-dysplastic naevi. The study included a training set of 358,800 pixels and a validation set of 7,313 pixels, which was then tested with a training set of 24,375 pixels. The majority vote classification achieved high overall sensitivity of 95% and a specificity of 92% (95% confidence interval (95% CI) 0.024-0.029) in differentiating malignant from benign lesions. In the pixel-wise classification, the overall sensitivity and specificity were both 82% (95% CI 0.005-0.005). When divided into 4 subgroups, the diagnostic accuracy was lower. Hyperspectral imaging provides high sensitivity and specificity in distinguishing between naevi and melanoma. This novel method still needs further validation.

Evaluation of Melanoma Thickness with Clinical Close-up and Dermoscopic Images Using a Convolutional Neural Network.

Convolutional neural networks (CNNs) have shown promise in discriminating between invasive and in situ melanomas. The aim of this study was to analyse how a CNN model, integrating both clinical close-up and dermoscopic images, performed compared with 6 independent dermatologists. The secondary aim was to address which clinical and dermoscopic features dermatologists found to be suggestive of invasive and in situ melanomas, respectively. A retrospective investigation was conducted including 1,578 cases of paired images of invasive (n = 728, 46.1%) and in situ melanomas (n = 850, 53.9%). All images were obtained from the Department of Dermatology and Venereology at Sahlgrenska University Hospital and were randomized to a training set (n = 1,078), a validation set (n = 200) and a test set (n = 300). The area under the receiver operating characteristics curve (AUC) among the dermatologists ranged from 0.75 (95% confidence interval 0.70-0.81) to 0.80 (95% confidence interval 0.75-0.85). The combined dermatologists' AUC was 0.80 (95% confidence interval 0.77-0.86), which was significantly higher than the CNN model (0.73, 95% confidence interval 0.67-0.78, p = 0.001). Three of the dermatologists significantly outperformed the CNN. Shiny white lines, atypical blue-white structures and polymorphous vessels displayed a moderate interobserver agreement, and these features also correlated with invasive melanoma. Prospective trials are needed to address the clinical usefulness of CNN models in this setting.

Clinical and Dermoscopic Approaches to Diagnosis of Frontal Fibrosing Alopecia: Results From a Multicenter Study of the International Dermoscopy Society.

INTRODUCTION: Frontal fibrosing alopecia (FFA) is a form of primary lymphocytic scarring alopecia characterized by a progressive recession of the fronto-temporal hairline. Although the clinical presentation of FFA is very typical, biopsy for histopathological examination is still recommended to confirm the diagnosis. Currently, a growing number of skin and mucosal inflammatory diseases are diagnosed with modern noninvasive techniques such as dermoscopy without the necessity of a biopsy. OBJECTIVES: The International Dermoscopy Society (IDS) aimed to test the ability of its members to diagnose classic FFA through clinical and dermoscopic parameters and to compare acquired data to the largest cohort studies published since 1994. METHODS: This is an observational, cross-sectional study describing patient demographics, clinical presentation and diagnostic tools used in a sample of FFA patients collected by IDS members. A literature search was then performed using Pubmed to review studies reporting more than 100 cases. RESULTS: IDS members submitted 188 cases demonstrating a predominant female population (98.4%). In 71.8% of the cases, the clinical presentation and the trichoscopic findings allowed for the diagnosis. Out of 24 revised studies, 13 showed that clinical and trichoscopic features were decisive for the diagnosis in almost all cases. CONCLUSIONS: Demographic and clinical data of our cohort were mostly comparable to previous reported data on FFA. The relevant role of the clinical and trichoscopic features in diagnosing FFA was confirmed by our study and the reviewed literature. Trichoscopy could be considered a worldwide-acknowledged non-invasive technique for the diagnosis of FFA.

Frequency of Publication of Dermoscopic Images in Inter-observer Studies: A Systematic Review.

Research interest in dermoscopy is increasing, but the complete dermoscopic image sets used in inter-observer studies of skin tumours are not often shared in research publications. The aim of this systematic review was to analyse what proportion of images depicting skin tumours are published in studies investigating inter-observer variations in the assessment of dermoscopic features and/or patterns. Embase, MEDLINE and Scopus databases were screened for eligible studies published from inception to 2 July 2020. For included studies the proportion of lesion images presented in the papers and/or supplements was extracted. A total of 61 studies (53 original studies and 8 shorter reports (i.e. research letters or concise reports)). published in the period 1997 to 2020 were included. These studies combined included 14,124 skin tumours, of which 373 (3%) images were published. This systematic review highlights that the vast majority of images included in dermoscopy research are not published. Data sharing should be a requirement for future studies, and must be enabled and standardized by the dermatology research community and editorial offices.

Interobserver Agreement on Dermoscopic Features and their Associations with In Situ and Invasive Cutaneous Melanomas.

Several melanoma-specific dermoscopic features have been described, some of which have been reported as indicative of in situ or invasive melanomas. To assess the usefulness of these features to differentiate between these 2 categories, a retrospective, single-centre investigation was conducted. Dermoscopic images of melanomas were reviewed by 7 independent dermatologists. Fleiss' kappa (κ) was used to analyse interobserver agreement of predefined features. Logistic regression and odds ratios were used to assess whether specific features correlated with melanoma in situ or invasive melanoma. Overall, 182 melanomas (101 melanoma in situ and 81 invasive melanomas) were included. The interobserver agreement for melanoma-specific features ranged from slight to substantial. Atypical blue-white structures (κ=0.62, 95% confidence interval 0.59-0.65) and shiny white lines (κ=0.61, 95% confidence interval 0.58-0.64) had a substantial interobserver agreement. These 2 features were also indicative of invasive melanomas >1.0 mm in Breslow thickness. Furthermore, regression/peppering correlated with thin invasive melanomas. The overall agreement for classification of the lesions as invasive or melanoma in situ was moderate (κ=0.52, 95% confidence interval 0.49-0.56).

Discrimination Between Invasive and In Situ Melanomas Using Clinical Close-Up Images and a De Novo Convolutional Neural Network.

Background: Melanomas are often easy to recognize clinically but determining whether a melanoma is in situ (MIS) or invasive is often more challenging even with the aid of dermoscopy. Recently, convolutional neural networks (CNNs) have made significant and rapid advances within dermatology image analysis. The aims of this investigation were to create a de novo CNN for differentiating between MIS and invasive melanomas based on clinical close-up images and to compare its performance on a test set to seven dermatologists. Methods: A retrospective study including clinical images of MIS and invasive melanomas obtained from our department during a five-year time period (2016-2020) was conducted. Overall, 1,551 images [819 MIS (52.8%) and 732 invasive melanomas (47.2%)] were available. The images were randomized into three groups: training set (n = 1,051), validation set (n = 200), and test set (n = 300). A de novo CNN model with seven convolutional layers and a single dense layer was developed. Results: The area under the curve was 0.72 for the CNN (95% CI 0.66-0.78) and 0.81 for dermatologists (95% CI 0.76-0.86) (P < 0.001). The CNN correctly classified 208 out of 300 lesions (69.3%) whereas the corresponding number for dermatologists was 216 (72.0%). When comparing the CNN performance to each individual reader, three dermatologists significantly outperformed the CNN. Conclusions: For this classification problem, the CNN was outperformed by the dermatologist. However, since the algorithm was only trained and validated on 1,251 images, future refinement and development could make it useful for dermatologists in a real-world setting.

Can Dermoscopy Be Used to Predict if a Melanoma Is In Situ or Invasive?

BACKGROUND: The preoperative prediction of whether melanomas are invasive or in situ can influence initial management. OBJECTIVES: This study evaluated the accuracy rate, interobserver concordance, sensitivity and specificity in determining if a melanoma is invasive or in situ, as well as the ability to predict invasive melanoma thickness based on clinical and dermoscopic images. METHODS: In this retrospective, single-center investigation, 7 dermatologists independently reviewed clinical and dermoscopic images of melanomas to predict if they were invasive or in situ and, if invasive, their Breslow thickness. Fleiss' and Cohen's kappa (κ) were used for interobserver concordance and agreement with histopathological diagnosis. RESULTS: We included 184 melanomas (110 invasive and 74 in situ). Diagnostic accuracy ranged from 67.4% to 76.1%. Accuracy rates for in situ and invasive melanomas were 57.5% (95% confidence interval [CI], 53.1%-61.8%) and 81.7% (95% CI, 78.8%-84.4%), respectively. Interobserver concordance was moderate (κ = 0.47; 95% CI, 0.44-0.51). Sensitivity for predicting invasiveness ranged from 63.6% to 91.8% for 7 observers, while specificity was 32.4%-82.4%. For all correctly predicted invasive melanomas, agreement between predictions and correct thickness over or under 1.0 mm was moderate (κ = 0.52; 95% CI, 0.45-0.58). All invasive melanomas incorrectly predicted by any observer as in situ had a thickness <1.0 mm. All 32 melanomas >1.0 mm were correctly predicted to be invasive by all observers. CONCLUSIONS: Accuracy rates for predicting thick melanomas were excellent, melanomas inaccurately predicted as in situ were all thin, and interobserver concordance for predicting in situ or invasive melanomas was moderate. Preoperative dermoscopy of suspected melanomas is recommended for choosing appropriate surgical margins.

Cryosurgery of Periocular Moderately Aggressive Basal Cell Carcinoma.

Uncertainty exists regarding the results of treating basal cell carcinomas with a more aggressive growth pattern than nodular growth with cryosurgery. Over the years, some medium aggressive, well-defined basal cell carcinomas have been treated with cryosurgery at the combined ophthalmology-dermatology recipiency at Sahlgrenska University Hospital, Gothenburg in Sweden. The medical records of these patients were reviewed to analyse the results. A total of 53 cryosurgeries were performed in 52 patients during 2009 to 2016. None of these patients had a recurrence within the first 3 years. There were 2 recurrent tumours after 5 years and 1 after 9 years. It is concluded that cryosurgery is an effective treatment option for well-defined basal cell carcinomas with an intermediate growth pattern.

Generating Hyperspectral Skin Cancer Imagery using Generative Adversarial Neural Network.

In this study we develop a proof of concept of using generative adversarial neural networks in hyperspectral skin cancer imagery production. Generative adversarial neural network is a neural network, where two neural networks compete. The generator tries to produce data that is similar to the measured data, and the discriminator tries to correctly classify the data as fake or real. This is a reinforcement learning model, where both models get reinforcement based on their performance. In the training of the discriminator we use data measured from skin cancer patients. The aim for the study is to develop a generator for augmenting hyperspectral skin cancer imagery.

Incidence of Kaposi Sarcoma in Sweden is Decreasing.

Kaposi sarcoma is a rare skin cancer, and epidemiological research into Kaposi sarcoma is therefore scarce. The current epidemiological situation for Kaposi sarcoma in Sweden is unknown. The authors hypothesized that the incidence of Kaposi sarcoma should have decreased after the introduction of antiretroviral therapy in 1996. Using data from the Swedish Cancer Registry, this study aimed to determine the incidence rates and survival for Kaposi sarcoma in Sweden from 1993 to 2016. The results showed that a total of 657 patients (74.0% men, 26.0% women) were diagnosed with Kaposi sarcoma in Sweden during 1993 to 2016. The overall incidence per 100,000, age-standardized to the world population, decreased from 0.40 to 0.10 (p = 0.003) for both sexes combined, from 0.76 to 0.14 (p=0.003) for men, and from 0.07 to 0.06 (p = 0.86) for women. The 10-year overall survival rate was significantly lower for the study population (30%) compared with the age- and sex-matched Swedish population (56%) (p < 0.00001). Over the study period, incidence rates of Kaposi sarcoma decreased significantly in men, especially during the late 1990s.

TOF-SIMS imaging reveals tumor heterogeneity and inflammatory response markers in the microenvironment of basal cell carcinoma.

Basal cell carcinoma (BCC) is the most common skin malignancy. In fact, it is as common as the sum of all other skin malignancies combined and the incidence is rising. In this focused and histology-guided study, tissue from a patient diagnosed with aggressive BCC was analyzed by imaging mass spectrometry in order to probe the chemistry of the complex tumor environment. Time-of-flight secondary ion mass spectrometry using a (CO2)6 k + gas cluster ion beam allowed a wide range of lipid species to be detected. Their distributions were then imaged in the tissue that contained small tumor islands that were histologically classified as more/less aggressive. Maximum autocorrelation factor (MAF) analysis highlighted chemical differences between the tumors and the surrounding stroma. A closer inspection of the distribution of individual ions, selected based on the MAF loadings, showed heterogeneity in signal between different microtumors, suggesting the potential of chemically grading the aggressiveness of each individual tumor island. Sphingomyelin lipids were found to be located in stroma containing inflammatory cells.

Evaluation of the Diagnostic Accuracy of an Online Artificial Intelligence Application for Skin Disease Diagnosis.

Artificial intelligence (AI) algorithms for automated classification of skin diseases are available to the consumer market. Studies of their diagnostic accuracy are rare. We assessed the diagnostic accuracy of an open-access AI application (Skin Image Search™) for recognition of skin diseases. Clinical images including tumours, infective and inflammatory skin diseases were collected at the Department of Dermatology at the Sahlgrenska University Hospital and uploaded for classification by the online application. The AI algorithm classified the images giving 5 differential diagnoses, which were then compared to the diagnoses made clinically by the dermatologists and/or histologically. We included 521 images portraying 26 diagnoses. The diagnostic accuracy was 56.4% for the top 5 suggested diagnoses and 22.8% when only considering the most probable diagnosis. The level of diagnostic accuracy varied considerably for diagnostic groups. The online application demonstrated low diagnostic accuracy compared to a dermatologist evaluation and needs further development.

Nonsurgical Options for the Treatment of Basal Cell Carcinoma.

OBJECTIVES: The aim of this review article is to summarize the effectiveness, potential adverse events, and indications of the main nonsurgical treatment alternatives for basal cell carcinoma. METHODS: An extensive literature review was carried out. The most relevant articles were discussed and selected by the authors in order to provide a brief but evidence-based overview of the most common nonsurgical methods used for treating basal cell carcinoma. RESULTS: Although surgery and Mohs micrographic surgery are often considered the optimal treatment options for basal cell carcinoma, these tumors can also be treated successfully with destructive techniques (eg, curettage alone, cryosurgery, or electrodesiccation), photodynamic therapy, topical drugs (eg, 5-fluorouracil, imiquimod, or ingenol mebutate), radiotherapy, or hedgehog pathway inhibitors. When choosing between these alternatives, physicians must take into consideration the tumor's size, location, and histopathological subtype. Special care should be taken when treating recurrent tumors. Furthermore, physician experience is of great importance when using destructive techniques. Finally, patient preference, potential adverse events, and cosmetic outcome should also be considered. CONCLUSIONS: Dermatologists and physicians treating basal cell carcinoma should have knowledge of and experience with the large arsenal of therapeutic alternatives available for the successful, safe, and individualized management of patients with basal cell carcinoma.

A prospective, randomized, within-subject study of ALA-PDT for actinic keratoses using different irradiation regimes.

BACKGROUND: Photodynamic therapy (PDT) can be used to treat large fields of actinic keratoses (AKs) with high clearance rates. A notable downside is the amount of pain that accompany the treatment. This study aimed to optimize the illumination protocol during conventional PDT in order to reduce pain without compromising treatment effectiveness. METHODS: In this prospective, randomized study with a split-face design, patients with, symmetrically distributed AKs were included. All patients were treated using a ALA 78 mg/g gel. One side was illuminated with the Aktilite® CL-128 lamp and the other side with the RhodoLED® lamp in which the light intensity gradually increased to a maximum of 60%. Both sides received a total light dose of 37 J/cm2 . Pain during the treatment was measured using a visual analogue scale. The clinical effectiveness of the 2 treated sides was assessed after 12 weeks. RESULTS: Twenty-nine patients with 399 AKs were included. Illumination with the gradually increasing light intensity resulted in a decrease in the median visual analogue scale score by 1.1 points. Clearance rates were similar between the 2 lamps. CONCLUSION: Minimizing the light intensity during the illumination phase of PDT reduces pain, while still preserving a high clearance rate of AKs.

Chemical imaging of aggressive basal cell carcinoma using time-of-flight secondary ion mass spectrometry.

A set of basal cell carcinoma samples, removed by Mohs micrographic surgery and pathologically identified as having an aggressive subtype, have been analyzed using time-of-flight secondary ion mass spectrometry (SIMS). The SIMS analysis employed a gas cluster ion beam (GCIB) to increase the sensitivity of the technique for the detection of intact lipid species. The GCIB also allowed these intact molecular signals to be maintained while surface contamination and delocalized chemicals were removed from the upper tissue surface. Distinct mass spectral signals were detected from different regions of the tissue (epidermis, dermis, hair follicles, sebaceous glands, scar tissue, and cancerous tissue) allowing mass spectral pathology to be performed. The cancerous regions of the tissue showed a particular increase in sphingomyelin signals that were detected in both positive and negative ion mode along with increased specific phosphatidylserine and phosphatidylinositol signals observed in negative ion mode. Samples containing mixed more and less aggressive tumor regions showed increased phosphatidylcholine lipid content in the less aggressive areas similar to a punch biopsy sample of a nonaggressive nodular lesion.