Nonmelanocytic skin cancers (NMSCs) are currently the most common group of human cancers and include all tumors that are not melanomas. Increased exposure to sunlight over the past few years, the lack of regular and proper use of sunscreen, the aging of the population, and better screening techniques are the reasons for the escalation in their diagnosis. Squamous cell carcinoma (SCC) comprises nearly 37% of the tumors in this group and can originate from actinic keratosis (AK), which usually presents as pink, often scaly plaques, usually located on the face or scalp. Advances in dermatoscopy, as well as the development of other non-invasive skin imaging modalities such as high-frequency ultrasound (HFUS), reflectance confocal microscopy (RCM), and optical coherence tomography (OCT), have allowed for greatly increased sensitivity in diagnosing these lesions and monitoring their treatment. Since AK therapy is usually local, and SCCs must be removed surgically, non-invasive imaging methods enable to correctly qualify difficult lesions. This is especially important given that they are very often located on the face, and achieving an appropriate cosmetic result after treatments in this area is very important for the patients. In this review, the authors describe the use of non-invasive skin imaging methods in the diagnosis of actinic keratosis.

Basal cell carcinoma (BCC) is a common skin cancer that occurs due to various genetic and environmental factors. Diagnosis is made by a combination of clinical appearance, biopsy, imaging, and histopathological analysis. This review describes the current array of imaging modalities available to physicians to aid in the diagnosis of BCC. It is important to stay up-to-date with improvements in diagnostic screening, and knowledge of these options is instrumental in providing the best care to patients. Embase, Medline Industries, and PubMed were searched for articles within the past 10 years based on a search query that looked for imaging modalities used in the diagnosis and evaluation of a variety of dermatologic conditions. The search was further refined to focus on BCC and satisfy the inclusion/exclusion criteria determined by the authors. The research process was detailed in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses diagram. Dermoscopy is a non-invasive in vivo microscopic technique used to evaluate skin lesions. Features of dermoscopy cannot be visualized with the naked eye, and studies found that dermoscopy increased diagnostic accuracy. Reflectance confocal microscopy (RCM) examines skin morphology, and recent studies found that 100% of patients with BCC had tumor-free margins when diagnosed with RCM. It allows for a one-stop-shop for diagnosis. Optical spectroscopy samples multiple sites without removing tissue. It helps detect subtle biophysical differences, allowing for earlier diagnosis. High-frequency ultrasound (HFUS) helps determine tumor size, structure, depth of invasion and spread. Studies found statistically significant positive correlations between depth of spread and HFUS readings. Optical coherence tomography takes cross-sectional images to analyze histopathology and morphology. It produces high-resolution images, confers slightly more accurate results than a biopsy, and expedites the treatment process through an earlier diagnosis without a biopsy.These results will advance the fields of dermatology and radiology as they describe unique uses for these imaging modalities. There are a variety of ways to use microscopy, and these techniques may be applied to many different lesions and help revolutionize the diagnosis and treatment of skin cancer and other lesions without the need for multiple, sometimes disfiguring surgical procedures. With the increase in diagnostic accuracy and decrease in diagnosis time, advanced imaging studies will become an integral part of dermatologic diagnosis and be included in future management and treatment plans, especially in the case of BCC.

Melanomas arise de novo or in the context of a precursor lesion. Lesions typically grow radially and then undergo a vertical growth phase proceeding to local invasion and metastasis. This review describes the utility of different imaging modalities in diagnosis and melanocytic lesion monitoring. A literature search was performed in November 2023 utilizing EMBASE, Medline, and PubMed. The PRISMA diagram demonstrates the review process. Reflectance confocal microscopy (RCM) utilizes near-infrared light to help diagnose dermatologic lesions. RCM was found to demonstrate nearly two times the positive predictive value compared to dermoscopy. The introduction of the Berlin Ultrasound (US) Morphology Criteria permitted a 65-80% improvement in diagnostic sensitivity. US with fine-needle aspiration cytology (FNAC) accurately predicts the necessity for sentinel lymph node biopsy and lymphadenectomy, sparing patients with metastasis and prompting biopsy for equivocal lesions. Single-photon emission computed tomography/computed tomography (SPECT/CT) is an adjunctive tool to anatomically and functionally assess lymphatic invasion. SPECT/CT improves the detection of sentinel nodes while decreasing operating time and improving cosmetic outcomes. 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) with small voxel reconstruction demonstrated increased specificity and sensitivity for detecting in-transit metastases of melanomas, specifically in the limbs. Dermoscopy allows providers to cost-effectively recognize common lesion patterns. Multiphoton microscopy assigns a weight-based score based on malignant features. Optical coherence angiography captures images of vessels to help diagnose equivocal lesions. Utilization of imaging techniques may increase diagnostic accuracy, reduce unnecessary procedures, and help guide treatment plans. Additional research is needed to further characterize the utility of these techniques in order to improve the diagnosis and treatment of melanomas.

BACKGROUND: The objective of this study is to systematically analyze the current state of the literature regarding novel artificial intelligence (AI) machine learning models utilized in non-invasive imaging for the early detection of nonmelanoma skin cancers. Furthermore, we aimed to assess their potential clinical relevance by evaluating the accuracy, sensitivity, and specificity of each algorithm and assessing for the risk of bias.
METHODS: Two reviewers screened the MEDLINE, Cochrane, PubMed, and Embase databases for peer-reviewed studies that focused on AI-based skin cancer classification involving nonmelanoma skin cancers and were published between 2018 and 2023. The search terms included skin neoplasms, nonmelanoma, basal-cell carcinoma, squamous-cell carcinoma, diagnostic techniques and procedures, artificial intelligence, algorithms, computer systems, dermoscopy, reflectance confocal microscopy, and optical coherence tomography. Based on the search results, only studies that directly answered the review objectives were included and the efficacy measures for each were recorded. A QUADAS-2 risk assessment for bias in included studies was then conducted.
RESULTS: A total of 44 studies were included in our review; 40 utilizing dermoscopy, 3 using reflectance confocal microscopy (RCM), and 1 for hyperspectral epidermal imaging (HEI). The average accuracy of AI algorithms applied to all imaging modalities combined was 86.80%, with the same average for dermoscopy. Only one of the three studies applying AI to RCM measured accuracy, with a result of 87%. Accuracy was not measured in regard to AI based HEI interpretation.
CONCLUSIONS: AI algorithms exhibited an overall favorable performance in the diagnosis of nonmelanoma skin cancer via noninvasive imaging techniques. Ultimately, further research is needed to isolate pooled diagnostic accuracy for nonmelanoma skin cancers as many testing datasets also include melanoma and other pigmented lesions.

Porokeratosis is a heterogeneous group of keratinising disorders characterised by the presence of particular microscopic structural changes, namely the presence of the cornoid lamella. This structure develops as a consequence of a defective isoprenoid pathway, critical for cholesterol synthesis. Commonly recognised variants include disseminated superficial actinic porokeratosis, disseminated superficial porokeratosis, porokeratosis of Mibelli, palmoplantar porokeratosis (including porokeratosis palmaris et plantaris disseminata and punctate porokeratosis), linear porokeratosis, verrucous porokeratosis (also known as genitogluteal porokeratosis), follicular porokeratosis and porokeratoma. Apart from the clinical presentation and epidemiology of each variant listed, this review aims at providing up-to-date information on the precise genetic background, introduces imaging methods facilitating the diagnosis (conventional and ultraviolet-induced fluorescence dermatoscopy, reflectance confocal microscopy and pathology), discusses their oncogenic potential and reviews the literature data on the efficacy of the treatment used, including the drugs directly targeting the isoprenoid-mevalonate pathway.

BACKGROUND: Rosacea is a chronic inflammatory dermatological condition in humans, and its pathogenesis remains unclear. However, the development of rosacea is suspected to be related to Demodex, a microscopic commensal organism that resides in or near hair follicles and sebaceous glands. Although Demodex is known to be a host-specific, obligate commensal organism, it is currently difficult to be cultured in vitro to parasitize and infect other animal hosts. Therefore, direct evidence for a pathogenic role of Demodex in rosacea is currently lacking.
CONCLUSIONS: As circumstantial evidence, non-invasive skin-detecting techniques have shown abnormally elevated numbers of Demodex in rosacea patients. Increased cytokine levels such as IL-10, IL-8, and IL-12p70 have been observed in human sebocytes following the Demodex challenge, and acaricides have been found to be effective in rosacea therapy, all point to a close relationship between Demodex and rosacea. Based on these findings, we conducted a comprehensive literature review to summarize the current state of knowledge, research insights, and clinical treatment recommendations for Demodex-associated rosacea, with the ultimate goal of improving patient outcomes.

BACKGROUND: Melanoma, the deadliest form of skin cancer, poses a significant public health challenge worldwide. Early detection is crucial for improved patient outcomes. Non-invasive skin imaging techniques allow for improved diagnostic accuracy; however, their use is often limited due to the need for skilled practitioners trained to interpret images in a standardized fashion. Recent innovations in artificial intelligence (AI)-based techniques for skin lesion image interpretation show potential for the use of AI in the early detection of melanoma.
OBJECTIVE: The aim of this study was to evaluate the current state of AI-based techniques used in combination with non-invasive diagnostic imaging modalities including reflectance confocal microscopy (RCM), optical coherence tomography (OCT), and dermoscopy. We also aimed to determine whether the application of AI-based techniques can lead to improved diagnostic accuracy of melanoma.
METHODS: A systematic search was conducted via the Medline/PubMed, Cochrane, and Embase databases for eligible publications between 2018 and 2022. Screening methods adhered to the 2020 version of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Included studies utilized AI-based algorithms for melanoma detection and directly addressed the review objectives.
RESULTS: We retrieved 40 papers amongst the three databases. All studies directly comparing the performance of AI-based techniques with dermatologists reported the superior or equivalent performance of AI-based techniques in improving the detection of melanoma. In studies directly comparing algorithm performance on dermoscopy images to dermatologists, AI-based algorithms achieved a higher ROC (>80%) in the detection of melanoma. In these comparative studies using dermoscopic images, the mean algorithm sensitivity was 83.01% and the mean algorithm specificity was 85.58%. Studies evaluating machine learning in conjunction with OCT boasted accuracy of 95%, while studies evaluating RCM reported a mean accuracy rate of 82.72%.
CONCLUSIONS: Our results demonstrate the robust potential of AI-based techniques to improve diagnostic accuracy and patient outcomes through the early identification of melanoma. Further studies are needed to assess the generalizability of these AI-based techniques across different populations and skin types, improve standardization in image processing, and further compare the performance of AI-based techniques with board-certified dermatologists to evaluate clinical applicability.

BACKGROUND: Reflectance confocal microscopy (RCM) has quickly transitioned from a research tool to an adjunct diagnostic bedside tool, providing the opportunity for noninvasive evaluation of skin lesions with histologic resolution. RCM is an optical imaging technique that uses near-infrared excitation wavelengths and safe low-power lasers. En-face images of different skin layers (up to the superficial dermis) are acquired in grayscale based on the reflective indices of tissue components. Melanin has the highest reflective index (contrast) and appears bright on RCM.
OBJECTIVE: We present a review of the current literature on the use of RCM in the diagnosis and management of pigmentary disorders.
METHODS: We reviewed PubMed and Ovid Medline databases from January 2000 to June 2021, using MeSH key terms: \"reflectance confocal microscopy, confocal laser scanning microscopy, pigmentary disorders, treatment, melasma, vitiligo, freckles, solar lentigo, lentigo, tattoo, complications, melanoma, skin cancers, pigmented lesions, post inflammatory, melanin, photoaging\" to identify studies and review articles discussing the use of RCM in the diagnosis and management of pigmentary disorders.
RESULTS: RCM findings of pigmentary disorders were divided into the following categories: (1) disorders of increased pigmentation (post-inflammatory hyperpigmentation, melasma, Riehl\'s melanosis, solar lentigines, ephelides, hori nevus, naevus of Ota, café-au-lait macules, melanocytic nevus, melanoma, nevus spilus, labial mucosal melanosis, and mucosal melanoma), (2) disorders of decreased pigmentation or depigmentation (post-inflammatory hypopigmentation, vitiligo, nevus depigmentosus, halo nevus), and (3) exogenous pigmentation (tattoo, ochronosis).
CONCLUSIONS: RCM has been explored and proven valuable for the evaluation and management of pigmentary disorders including melasma, vitiligo, solar lentigines, tattoo, and tattoo-related complications.

Eccrine poroma (EP) is a relatively rare benign adnexal neoplasm that usually affects elderly patients. Its pathogenesis is still under investigation, but recent gene studies have revealed gene fusions as key incidences resulting in oncogenetic pathways. It often presents as a solitary, firm papule, mostly asymptomatic, located on the soles or palms. Due to its clinical and dermoscopic variability, it is characterized as the great imitator. We performed a literature review, aiming to summarize current data on the pathogenetic mechanisms, new dermoscopic features, and novel diagnostic tools that may aid in early diagnosis and proper management of this rare adnexal tumor. Furthermore, we reviewed the possible pathogenetic associations between EP and its malignant counterpart, namely eccrine porocarcinoma. This systematic approach may aid in understanding the pathogenetic mechanisms and how to use novel histopathologic markers and imaging methods to overcome the diagnostic dilemma of this rare tumor.

Vitiligo is a multifaceted autoimmune depigmenting disorder affecting around 0.5 to 2.0% of individuals globally. Standardizing diagnosis and therapy tracking can be arduous, as numerous clinical evaluation methods are subject to interobserver variability and may not be validated. Therefore, there is a need for diagnostic tools that are objective, dependable, and preferably non-invasive.
UNASSIGNED: This systematic review provides a comprehensive overview of the non-invasive objective skin measurement methods that are currently used to evaluate the diagnosis, severity, and progression of vitiligo, as well as the advantages and limitations of each technique.
UNASSIGNED: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was used for the systematic review. Scopus, Embase, Cochrane Library, and Web of Science databases were comprehensively searched for non-invasive imaging and biophysical skin measuring methods to diagnose, evaluate the severity of, or monitor the effects of vitiligo treatment. The risk of bias in included articles was assessed using the QUADAS-2 quality assessment scale.
UNASSIGNED: An extensive literature search resulted in 64 studies for analysis, describing eight imaging techniques (reflectance confocal microscopy, computer-aided imaging analysis, optical coherence tomography, infrared photography, third-harmonic generation microscopy, multiphoton microscopy, ultraviolet light photography, and visible light/digital photograph), and three biophysical approaches (dermoscopy, colorimetry, spectrometry) used in diagnosing and assessing vitiligo. Pertinent information about functionality, mechanisms of action, sensitivity, and specificity was obtained for all studies, and insights into the strengths and limitations of each diagnostic technique were addressed. Methodological study quality was adequate; however, statistical analysis was not achievable because of the variety of methods evaluated and the non-standardized reporting of diagnostic accuracy results.
UNASSIGNED: The results of this systematic review can enhance clinical practice and research by providing a comprehensive overview of the spectrum of non-invasive imaging and biophysical techniques in vitiligo assessment. Studies with larger sample sizes and sound methodology are required to develop verified methods for use in future practice and research.
UNASSIGNED: (PROSPERO) database, (CRD42023395996).