Use of PRAME Immunostaining to Distinguish Melanoma in Situ From Lentigo Senilis

PRAME (PReferentially expressed Antigen in MElanoma) is an antigen that is expressed by malignant cells in melanoma, as well as other cancers such as breast carcinoma, renal cell carcinoma, and leukemia. PRAME immunohistochemistry has proved effective in identifying malignant melanocytes in melanoma lesions, but it is unclear if it may be used to distinguish melanoma from benign melanocytic conditions, such as lentigo senilis. In particular, melanoma in situ may be confused with lentigo senilis clinically and histologically, thus PRAME immunostaining is potentially useful for differentiating these two lesions. We evaluated 31 samples of lentigo senilis, 26 of melanoma in situ, and 17 of sun-damaged skin with PRAME immunostain. We found that there is significantly greater PRAME expression in melanoma in situ compared to both lentigo senilis and sun-damaged skin. Although these benign skin lesions contain some cells that are immunoreactive for PRAME, these cells are sparse compared to the dense PRAME-positive cells in melanoma in situ. This suggests that PRAME immunostaining could be a clinically useful tool for distinguishing melanoma in situ from lentigo senilis. However, it should be combined with other data, such as clinical impression and histology with H&E stain, given the possibility for false positive results

Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

Currently, diagnosis of skin diseases is based primarily on visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide objective information to support clinical decision-making. Noninvasive skin imaging techniques provide complementary information to the clinician. In recent years, optical coherence tomography has become a powerful skin imaging technique. According to specific functional needs, skin architecture varies across different parts of the body, as do the textural characteristics in OCT images. There is, therefore, a critical need to systematically analyze OCT images from different body sites, to identify their significant qualitative and quantitative differences. Sixty-three optical and textural features extracted from OCT images of healthy and diseased skin are analyzed and in conjunction with decision-theoretic approaches used to create computational models of the diseases. We demonstrate that these models provide objective information to the clinician to assist in the diagnosis of abnormalities of cutaneous microstructure, and hence, aid in the determination of treatment. Specifically, we demonstrate the performance of this methodology on differentiating basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) from healthy tissue

Is photoacoustic imaging clinically safe: evaluation of possible thermal damage due to laser-tissue interaction

Photoacoustic imaging is a breakthrough imaging modality that combines the spatial resolution of ultrasound imaging with the contrast of optical imaging. This imaging technique is being pushed towards clinical acceptance for many applications, such as noninvasive diagnosis and management of a multitude of neoplastic lesions. However, a rigorous evaluation of the tissue thermal response to the laser illumination is required prior to the clinical translation. In this study, we assessed the temperature rise profile and microstructural damage of the skin due to the laser-tissue interaction using in-vivo mouse models. We compared the effect of two different laser frequencies (10 Hz and 30 Hz) on the skin and studied if the use of a cooling method could be clinically useful in preventing tissue necrosis. Two biopsies were taken from each mouse 48 hours after laser exposure; one from the skin directly exposed to the laser and one from neighboring healthy tissue. When the lower frequency laser was used, no necrosis was found on histologic analysis. However, when the higher frequency laser was used, necrosis was noted in the epidermis, dermal collagen, and hair follicles at the site of laser exposure. Use of the cooling method with the higher frequency laser led to no tissue necrosis. Overall, it appears that photoacoustic imaging is likely safe when lower frequency lasers are used, and the implementation of the cooling method seems to mitigate necrosis when the use of a higher frequency laser is warranted. This opens up exciting new possibilities for a noninvasive way of diagnosing and evaluating a variety of lesions, including malignant tumors. However, some further studies are needed before photoacoustic imaging can be clinically used in human subjects

Next-generation sequencing in dermatology

Over the past decade, Next-Generation Sequencing (NGS) has advanced our understanding, diagnosis, and management of several areas within dermatology. NGS has emerged as a powerful tool for diagnosing genetic diseases of the skin, improving upon traditional PCR-based techniques limited by significant genetic heterogeneity associated with these disorders. Epidermolysis bullosa and ichthyosis are two of the most extensively studied genetic diseases of the skin, with a well-characterized spectrum of genetic changes occurring in these conditions. NGS has also played a critical role in expanding the mutational landscape of cutaneous squamous cell carcinoma, enhancing our understanding of its molecular pathogenesis. Similarly, genetic testing has greatly benefited melanoma diagnosis and treatment, primarily due to the high prevalence of BRAF hot spot mutations and other well-characterized genetic alterations. Additionally, NGS provides a valuable tool for measuring tumor mutational burden, which can aid in management of melanoma. Lastly, NGS demonstrates promise in improving the sensitivity of diagnosing cutaneous T-cell lymphoma. This article provides a comprehensive summary of NGS applications in the diagnosis and management of genodermatoses, cutaneous squamous cell carcinoma, melanoma, and cutaneous T-cell lymphoma, highlighting the impact of NGS on the field of dermatology

Ethnic distribution of populations in the highest and lowest dermatologist-dense areas: is there more to the story?

Several studies in the past decade have highlighted the lack of adequate dermatological care in skin of color (SOC) patients. This inquiry has led to further research to identify the sources of this disparity. Previous studies have highlighted the uneven geographic distribution of dermatologists, with a higher density of dermatologists in urban areas compared to other areas. However, the exact ethnic populations served by these dermatologists has remained largely uncharacterized. The purpose of this study was to compare the ethnic distributions in the ten highest and lowest dermatologist-dense areas across the United States to determine if there is equal access to dermatological care for minorities. Stratified by ethnicities, the highest dermatologist-dense areas consisted of 60% White alone (not Hispanic or Latino), 13% Hispanic or Latino, 13% Asian alone, and 12% Black or African American. Conversely, the least dermatologist-dense areas consisted of 45% White alone (not Hispanic or Latino), 28% Black or African American, 21% Hispanic or Latino, and 4% Asian alone. Our analysis highlights the presence of larger proportions of SOC patients in the lowest dermatologist-dense areas and this lack of access to dermatologists may contribute to inferior dermatological care and outcomes in Hispanic or Latino, and Black or African American minorities

An intelligent despeckling method for swept source optical coherence tomography images of skin

Optical Coherence Optical coherence tomography is a powerful high-resolution imaging method with a broad biomedical application. Nonetheless, OCT images suffer from a multiplicative artefacts so-called speckle, a result of coherent imaging of system. Digital filters become ubiquitous means for speckle reduction. Addressing the fact that there still a room for despeckling in OCT, we proposed an intelligent speckle reduction framework based on OCT tissue morphological, textural and optical features that through a trained network selects the winner filter in which adaptively suppress the speckle noise while preserve structural information of OCT signal. These parameters are calculated for different steps of the procedure to be used in designed Artificial Neural Network decider that select the best denoising technique for each segment of the image. Results of training shows the dominant filter is BM3D from the last category