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Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the forefront of artificial intelligence (AI) revolution, conventional pathology, which commonly relies on examination of tissue samples on a glass slide, is falling behind in leveraging this technology. On the other hand, ex vivo confocal laser scanning microscopy (ex vivo CLSM), owing to its digital workflow features, has a high potential to benefit from integrating AI tools into the assessment and decision-making process. Aim of this work was to explore a preliminary application of CNN in digitally stained ex vivo CLSM images of cutaneous squamous cell carcinoma (cSCC) for automated detection of tumor tissue. Thirty-four freshly excised tissue samples were prospectively collected and examined immediately after resection. After the histologically confirmed ex vivo CLSM diagnosis, the tumor tissue was annotated for segmentation by experts, in order to train the MobileNet CNN. The model was then trained and evaluated using cross validation. The overall sensitivity and specificity of the deep neural network for detecting cSCC and tumor free areas on ex vivo CLSM slides compared to expert evaluation were 0.76 and 0.91, respectively. The area under the ROC curve was equal to 0.90 and the area under the precision-recall curve was 0.85. The results demonstrate a high potential of deep learning models to detect cSCC regions on digitally stained ex vivo CLSM slides and to distinguish them from tumor-free skin.

Until now, the clinical differentiation between a nevus and a melanoma is still challenging in some cases. Line-field confocal optical coherence tomography (LC-OCT) is a new tool with the aim to change that. The aim of the study was to evaluate LC-OCT for the discrimination between nevi and melanomas. A total of 84 melanocytic lesions were examined with LC-OCT and 36 were also imaged with RCM. The observers recorded the diagnoses, and the presence or absence of the 18 most common imaging parameters for melanocytic lesions, nevi, and melanomas in the LC-OCT images. Their confidence in diagnosis and the image quality of LC-OCT and RCM were evaluated. The most useful criteria, the sensitivity and specificity of LC-OCT vs. RCM vs. histology, to differentiate a (dysplastic) nevus from a melanoma were analyzed. Good image quality correlated with better diagnostic performance (Spearman correlation: 0.4). LC-OCT had a 93% sensitivity and 100% specificity compared to RCM (93% sensitivity, 95% specificity) for diagnosing a melanoma (vs. all types of nevi). No difference in performance between RCM and LC-OCT was observed (McNemar’s p value = 1). Both devices falsely diagnosed dysplastic nevi as non-dysplastic (43% sensitivity for dysplastic nevus diagnosis). The most significant criteria for diagnosing a melanoma with LC-OCT were irregular honeycombed patterns (92% occurrence rate; 31.7 odds ratio (OR)), the presence of pagetoid spread (89% occurrence rate; 23.6 OR) and the absence of dermal nests (23% occurrence rate, 0.02 OR). In conclusion LC-OCT is useful for the discrimination between melanomas and nevi.

Vitiligo is an acquired pigmentary disorder. In vivo reflectance confocal microscopy (RCM) reproducible imaging technique has already been reported to be useful in the diagnosis of other skin diseases. To define RCM features of vitiligo on different clinical stages. A total of 125 patients with a clinical diagnosis of vitiligo were included in this study. After informed consent, lesional skins of those vitiligo patients were characterized by using RCM. Five patients with inflammatory cell infiltration observed at the edge of skin lesions and another 5 patients without inflammatory cell infiltration were selected. Biopsies were performed at same sites of the RCM examination areas for histological and immune-histological analysis. In the active stage of vitiligo, the RCM examination revealed that the bright dermal papillary rings presented at the dermoepidermal junction level in normal skin lost their integrity or totally disappeared, border between vitiligo lesion and normal skin became unclear, and highly refractile cells that referred to infiltrated inflammatory cells could be seen within the papillary dermis at the edge of the lesions. In the stable stage of vitiligo, the RCM showed a complete loss of melanin in lesional skin and a clear border between lesional and normal skin. A simple clinical examination with RCM may reliably and efficiently allow evaluation of the stability status of vitiligo lesions.

Objective To summarize the image features of dermatoscopy and reflectance confocal microscopy (RCM) in children with scabies, and to explore the clinical significance in the diagnosis of children scabies. Methods A retrospective analysis was conducted on 102 children scabies diagnosed clinically in the dermatology outpatient department of Tianjin Children's Hospital from April 2018 to June 2022. All children were examined by dermatoscopy and RCM, and images were collected. Results 102 patients, 92 patients (90.2%) showed characteristic dermoscopic manifestations: white tunnels and small brown or dark brown triangular structures at their ends. 91 patients (89.2%) showed characteristic reflectance confocal microscopic manifestations: tunnels, scabies mites, feces, and eggs in the epidermal layer. All patients showed different degrees of non‐specific manifestations of dermoscopy and RCM. Conclusion Children scabies have typical dermatoscopic and reflectance confocal microscopic characteristics, and dermatoscopy and RCM are effective non‐invasive diagnostic methods with high clinical application value in the diagnosis and differential diagnosis of children scabies.

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.

Oral squamous cell carcinoma (OSCC) is the most prevalent form of cancer of lips and oral cavity, and its diagnostic delay, caused by misdiagnosis at the early stages, is responsible for high mortality ratios. Biopsy and histopathological assessment are the gold standards for OSCC diagnosis, but they are time-consuming, invasive, and do not always enable the patient’s compliance, mainly in cases of follow-up with the need for more biopsies. The use of adjunctive noninvasive imaging techniques improves the diagnostic approach, making it faster and better accepted by patients. The present review aims to focus on the most consolidated diagnostic techniques, such as vital staining and tissue autofluorescence, and to report the potential role of some of the most promising innovative techniques, such as narrow-band imaging, high-frequency ultrasounds, optical coherence tomography, and in vivo confocal microscopy. According to their contribution to OSCC diagnosis, an ideal three-step diagnostic procedure is proposed, to make the diagnostic path faster, better, and more accurate.

Early diagnosis is essential for completely eradicating skin cancer and maximizing patients’ clinical benefits. Emerging optical imaging modalities such as reflectance confocal microscopy (RCM), optical coherence tomography (OCT), magnetic resonance imaging (MRI), near-infrared (NIR) bioimaging, positron emission tomography (PET), and their combinations provide non-invasive imaging data that may help in the early detection of cutaneous tumors and surgical planning. Hence, they seem appropriate for observing dynamic processes such as blood flow, immune cell activation, and tumor energy metabolism, which may be relevant for disease evolution. This review discusses the latest technological and methodological advances in imaging techniques that may be applied for skin cancer detection and monitoring. In the first instance, we will describe the principle and prospective clinical applications of the most commonly used imaging techniques, highlighting the challenges and opportunities of their implementation in the clinical setting. We will also highlight how imaging techniques may complement the molecular and histological approaches in sharpening the non-invasive skin characterization, laying the ground for more personalized approaches in skin cancer patients.

Background Reflectance confocal microscopy (RCM) and line‐field confocal optical coherence tomography (LC‐OCT) are non‐invasive imaging devices that can help in the clinical diagnosis of actinic keratosis (AK) and cutaneous squamous cell carcinoma (SCC). No studies are available on the comparison between these two technologies for the identification of the different features of keratinocyte skin tumours. Objectives To compare RCM and LC‐OCT findings in AK and SCC. Methods A retrospective multicenter study was conducted. Tumours were imaged with RCM and LC‐OCT devices before surgery, and the diagnosis was confirmed by histological examinations. LC‐OCT and RCM criteria for AK/SCC were identified, and their presence/absence was evaluated in all study lesions. Gwet AC1 concordance index was calculated to compare RCM and LC‐OCT. Results We included 52 patients with 33 AKs and 19 SCCs. Irregular epidermis was visible in most tumours and with a good degree of agreement between RCM and LC‐OCT (Gwet's AC1 0.74). Parakeratosis, dyskeratotic keratinocytes and both linear dilated and glomerular vessels were better visible at LC‐OCT than RCM (p < 0.001). Erosion/ulceration was identified with both methods in more than half of the cases with a good degree of agreement (Gwet AC1 0.62). Conclusions Our results suggest that both LC‐OCT and hand‐held RCM can help clinicians in the identification of AK and SCC, providing an in vivo and non‐invasive identification of an irregular epidermis. LC‐OCT proved to be more effective in identifying parakeratosis, dyskeratotic keratinocytes and vessels in this series.

Background Vivascope 2500 ex vivo confocal microscopy (EVCM) is an emerging optical imaging device that allows nuclear level resolution of freshly excised tissues. EVCM provides, rapid real‐time pathological examination in many subspecialties of pathology including skin, prostate, breast, liver, etc. In contrast to traditional time‐consuming frozen sectioning and histological analysis. Aims To evaluate the current state of EVCM utilization. Materials and Methods This study highlights the advantages, limitations, and prospects of EVCM in skin pathology. Results Our findings demonstrate that EVCM is a promising adjunctive tool to assess margins in Mohs surgery and to provide rapid, accurate diagnosis of cutaneous tumors, infectious and inflammatory diseases. Conclusion EVCM is a revolutionary device that can be used as an adjunct to paraffin‐fixed, hematoxylin and eosin‐stained slides and frozen sectioning. Additional refinements are required before EVCM can be used as an alternative to frozen sectioning or traditional tissue processing.

Background Merkel cell carcinoma (MCC) is a rare, aggressive, cutaneous tumour with high mortality and frequently delayed diagnosis. Clinically, it often manifests as a rapidly growing erythematous to purple nodule usually located on the lower extremities or face and scalp of elderly patients. There is limited available data on the dermoscopic findings of MCC, and there are no specific features that can be used to definitively diagnose MCC. Aim of the study Here, we aimed to summarize existing published literature on dermatoscopic and reflectance confocal microscopy (RCM) features of MCC. Materials and methods To find relevant studies, we searched the PubMed and Scopus databases from inception to April 12, 2023. Our goal was to identify all pertinent research that had been written in English. The following search strategy was employed: (“ dermoscopy” OR “ dermatoscopy” OR “ videodermoscopy” OR “ videodermatoscopy” OR “ reflectance confocal microscopy”) AND “ Merkel cell carcinoma”. Two dermatologists, DK and GE, evaluated the titles and abstracts separately for eligibility. For inclusion, only works written in English were taken into account. Results In total 16 articles were retrieved (68 cases). The main dermoscopic findings of MCC are a polymorphous vascular pattern including linear irregular, arborizing, glomerular, and dotted vessels on a milky red background, with shiny or non-shiny white areas. Pigmentation was lacking in all cases. The RCM images showed a thin and disarranged epidermis, and small hypo-reflective cells that resembled lymphocytes arranged in solid aggregates outlined by fibrous tissue in the dermis. Additionally, there were larger polymorphic hyper-reflective cells that likely represented highly proliferative cells. Conclusion Dermoscopic findings of MCC may play a valuable role in evaluating MCC, aiding in the early detection and differentiation from other skin lesions. Further prospective case-control studies are needed to validate these results.