Search

Basal cell carcinoma (BCC) is the most common keratinocyte carcinoma and the most prevalent skin cancer in humans, worldwide. BCC is histologically characterized by the proliferation of basaloid cells, arranged in globular masses of varying size, often separated from the surrounding stroma by optically empty spaces. Although attributed to tumor retraction during tissue processing for the preparation of pathology slides, these spaces are also seen on cryostat sections. The aim of this study is to in vivo characterize amyloid and mucin deposits in primary BCC lesions through RCM, followed by histopathological correlation. We included twenty-two consecutive subjects totaling thirty-one primary BCCs. Each lesion underwent the same evaluation protocol which included: clinical and dermoscopic images, RCM imaging, excisional biopsy under local anesthesia, and histopathological examination (colloidal iron and cytokeratin 34betaE12 stains). Hypo-reflective peritumoral clefts and hyper-reflective globules were measured on RCM images and compared to mucin and amyloid deposits seen on histology slides. The mean differences between RCM and histology measurements in both mucin and amyloid were not statistically significant. There were medium and strong correlations between RCM and histology regarding mucin and amyloid deposits, respectively. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma (BCC) is the most prevalent skin cancer in the Caucasian population. A variety of different phenotypic presentations of BCC are possible. Although BCCs rarely metastasize, these tumors commonly destroy underlying tissues and should therefore be treated promptly. As vascular formation and angiogenesis are indicators of tumor development and progression, the presence of blood vessels, their morphology and architecture are important markers in skin lesions, providing critical information towards pathogenesis and diagnosis. BCC commonly lacks pigmentation, therefore it is important to emphasize the usefulness of vascular feature detection, recognition, quantification and interpretation. To answer the question of whether vascular patterns observed on dermoscopy, reflectance confocal microscopy (RCM) and histopathology might reflect the biologic behavior of BCCs, we undertook this review article. Several studies have sought, by various means, to identify vascular features associated with the more aggressive BCC phenotypes. Dermoscopic vascular pattern assessment can facilitate diagnostic discrimination between BCC subtypes, more aggressive BCCs displaying less or no pink coloration and a relative absence of central tumor vessels. RCM, a novel, non-invasive imaging technique, allows for the quantification of blood vessel size, density, and flow intensity in BCCs. BCCs are distinguished on RCM chiefly by vessels that branch and intertwine between neoplastic aggregates, a pattern strongly reflecting tumor neo-angiogenesis. The analysis of these vascular morphological and distribution patterns can provide further support in the diagnosis, assessment, or monitoring of BCCs. Histopathology shows significantly higher microvessel densities in the peritumoral stroma of BCCs, when compared to normal skin or benign tumors. This angiogenic response in the stroma is associated with local aggressiveness, therefore the quantification of peritumoralmicrovessels may further assist with tumor evaluation. How dermoscopy and RCM vascular patterns in BCC correlate with histopathological subtype and thus help in discriminating aggressive subtypes definitely deserves further investigation. [ABSTRACT FROM AUTHOR]

Taking into consideration that the immune system plays a very important role in the development of melanoma and non-melanoma skin cancers, which have a high prevalence in immunosuppressed patients and after prolonged ultraviolet radiation, the interest in developing novel therapies, in particular targeting the inflammation in cancer, has increased in the past years. The latest data suggest that therapies such as imiquimod (IMQ), ingenol mebutate (IM), 5-fluorouracil (5-FU), retinoids, and nonsteroidal anti-inflammatory drugs (NSAIDs) have been used with success in the topical treatment of some cancers. Herein, we review the topical treatment targeting the inflammation in skin cancer and the mechanisms involved in these processes. Currently, various associations have shown a superior success rate than monotherapy, such as systemic acitretin and topical IMQ, topical 5-FU with tretinoin cream, or IMQ with checkpoint inhibitor cytotoxic T lymphocyte antigen 4. Novel therapies targeting Toll-like receptor-7 (TLR-7) with higher selectivity than IMQ are also of great interest. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma is a slow growing non-melanoma skin cancer appearing as a non-healing, painless, and sometimes pruriginous sore, usually on sun-exposed areas. Although it rarely metastasizes, BCC diagnosis and treatment should not be delayed due to its local invasive potential. Currently, dermatoscopy is a well propagated and commonly employed tool in clinical practice, providing a fast and handy approach to clinical diagnosis, without the significant financial costs associated with other more sophisticated diagnostic means. Since the very first dermatoscopic descriptions of basal cell carcinoma, the list of dermatoscopic diagnostic criteria has been updated and renewed numerous times. Dermatoscopy significantly augments basal cell carcinoma detection by its capability of discriminating it from other skin lesions and inflammatory skin conditions. Moreover, current evidence suggests that this noninvasive, real-time imaging technique is also valuable in tumor management, seeing that it provides additional information related to histopathological subtype, presence or lack of pigmentation, lateral tumor extension, and tumor response to non-surgical treatments. In this paper, we aim to summarize time-honored as well as current knowledge on the value of dermatoscopy in the diagnosis, classification, and treatment of basal cell carcinoma. [ABSTRACT FROM AUTHOR]

Reflectance confocal microscopy (RCM) is a non-invasive imaging method designed to identify various skin diseases. Confocal based diagnosis may be subjective due to the learning curve of the method, the scarcity of training programs available for RCM, and the lack of clearly defined diagnostic criteria for all skin conditions. Given that in vivo RCM is becoming more widely used in dermatology, numerous deep learning technologies have been developed in recent years to provide a more objective approach to RCM image analysis. Machine learning-based algorithms are used in RCM image quality assessment to reduce the number of artifacts the operator has to view, shorten evaluation times, and decrease the number of patient visits to the clinic. However, the current visual method for identifying the dermal-epidermal junction (DEJ) in RCM images is subjective, and there is a lot of variation. The delineation of DEJ on RCM images could be automated through artificial intelligence, saving time and assisting novice RCM users in studying the key DEJ morphological structure. The purpose of this paper is to supply a current summary of machine learning and artificial intelligence's impact on the quality control of RCM images, key morphological structures identification, and detection of different skin lesion types on static RCM images. [ABSTRACT FROM AUTHOR]

Basal cell carcinoma (BCC) is the most common cancer worldwide and its incidence is constantly rising. Early diagnosis and treatment can significantly reduce patient morbidity and healthcare costs. The value of reflectance confocal microscopy (RCM) in non-melanoma skin cancer diagnosis is still under debate. This systematic review and meta-analysis were conducted to assess the diagnostic accuracy of RCM in primary BCC. PubMed, Google Scholar, Scopus, and Web of Science databases were searched up to July 05, 2019, to collect articles concerning primary BCC diagnosis through RCM. The studies' methodological quality was assessed by the QUADAS-2 tool. The meta-analysis was conducted using Stata 13.0, RevMan 5.0, and MetaDisc 1.4 software. We included 15 studies totaling a number of 4163 lesions. The pooled sensitivity and specificity were 0.92 (95% CI, 0.87–0.95; I2 = 85.27%) and 0.93 (95% CI, 0.85–0.97; I2 = 94.61%), the pooled positive and negative likelihood ratios were 13.51 (95% CI, 5.8–31.37; I2 = 91.01%) and 0.08 (95% CI, 0.05–0.14; I2 = 84.83%), and the pooled diagnostic odds ratio was 160.31 (95% CI, 64.73–397.02; I2 = 71%). Despite the heterogeneity and risk of bias, this study demonstrates that RCM, through its high sensitivity and specificity, may have a significant clinical impact on the diagnosis of primary BCC. [ABSTRACT FROM AUTHOR]