Real-life practice of reflectance confocal microscopy in France: A prospective multicenter study.

BACKGROUND: Studies demonstrating the potential utility of reflectance confocal microscopy (RCM) have been performed under experimental conditions. OBJECTIVE: To provide an overview of RCM practice in real-life. METHODS: A multicenter, prospective study carried out in 10 university dermatology departments in France. RESULTS: Overall, 410 patients were enrolled. One-half of the patients (48%) were referred by private practice dermatologists. They were referred for diagnosis (84.9%) or presurgical mapping (13%). For diagnosis, the lesions were located on the face (62%), arms and legs (14.9%), and trunk (13.6%), and presurgical mapping was almost exclusively on the face (90.9%). Among those referred for diagnosis, the main indication was suspicion of a skin tumor (92.8%). Of these, 50.6% were spared biopsies after RCM. When RCM indicated surgery, histology revealed malignant lesions in 72.7% of cases. The correlation between RCM and histopathology was high, with a correlation rate of 82.76% and a kappa coefficient of 0.73 (0.63; 0.82). LIMITATIONS: This study was performed in the settings of French tertiary referral hospitals. CONCLUSION: This study shows that in real-life RCM can be integrated into the workflow of a public private network, which enables a less invasive diagnostic procedure for patients.

Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions' Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection.

Melanoma is still a major health problem worldwide. Early diagnosis is the first step toward reducing its mortality, but it remains a challenge even for experienced dermatologists. Although computer-aided systems have been developed to help diagnosis, the lack of insight into their predictions is still a significant limitation toward acceptance by the medical community. To tackle this issue, we designed handcrafted expert features representing color asymmetry within the lesions, which are parts of the approach used by dermatologists in their daily practice. These features are given to an artificial neural network classifying between nevi and melanoma. We compare our results with an ensemble of 7 state-of-the-art convolutional neural networks and merge the 2 approaches by computing the average prediction. Our experiments are done on a subset of the International Skin Imaging Collaboration 2019 dataset (6296 nevi, 1361 melanomas). The artificial neural network based on asymmetry achieved an area under the curve of 0.873, sensitivity of 90%, and specificity of 67%; the convolutional neural network approach achieved an area under the curve of 0.938, sensitivity of 91%, and specificity of 82%; and the fusion of both approaches achieved an area under the curve of 0.942, sensitivity of 92%, and specificity of 82%. Merging the knowledge of dermatologists with convolutional neural networks showed high performance for melanoma detection, encouraging collaboration between computer science and medical fields.

Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions.

Early detection of melanoma remains a daily challenge due to the increasing number of cases and the lack of dermatologists. Thus, AI-assisted diagnosis is considered as a possible solution for this issue. Despite the great advances brought by deep learning and especially convolutional neural networks (CNNs), computer-aided diagnosis (CAD) systems are still not used in clinical practice. This may be explained by the dermatologist's fear of being misled by a false negative and the assimilation of CNNs to a "black box", making their decision process difficult to understand by a non-expert. Decision theory, especially game theory, is a potential solution as it focuses on identifying the best decision option that maximizes the decision-maker's expected utility. This study presents a new framework for automated melanoma diagnosis. Pursuing the goal of improving the performance of existing systems, our approach also attempts to bring more transparency in the decision process. The proposed framework includes a multi-class CNN and six binary CNNs assimilated to players. The players' strategies is to first cluster the pigmented lesions (melanoma, nevus, and benign keratosis), using the introduced method of evaluating the confidence of the predictions, into confidence level (confident, medium, uncertain). Then, a subset of players has the strategy to refine the diagnosis for difficult lesions with medium and uncertain prediction. We used EfficientNetB5 as the backbone of our networks and evaluated our approach on the public ISIC dataset consisting of 8917 lesions: melanoma (1113), nevi (6705) and benign keratosis (1099). The proposed framework achieved an area under the receiver operating curve (AUROC) of 0.93 for melanoma, 0.96 for nevus and 0.97 for benign keratosis. Furthermore, our approach outperformed existing methods in this task, improving the balanced accuracy (BACC) of the best compared method from 77% to 86%. These results suggest that our framework provides an effective and explainable decision-making strategy. This approach could help dermatologists in their clinical practice for patients with atypical and difficult-to-diagnose pigmented lesions. We also believe that our system could serve as a didactic tool for less experienced dermatologists.

Morphological evaluation of melanocytic lesions with three-dimensional line-field confocal optical coherence tomography: correlation with histopathology and reflectance confocal microscopy. A pilot study.

BACKGROUND: Line-field confocal optical coherence tomography (LC-OCT) is a new in vivo emerging technique that provides cellular resolution, allows deep imaging (400 µm) and produces real-time images in both the horizontal and vertical plane and in three dimensions. No previous description of different subtypes of melanocytic lesions and their correlation with histopathology and reflectance confocal microscopy has been reported. AIM: To describe the features of melanocytic lesions by LC-OCT and their correlation with histopathology and reflectance confocal microscopy (RCM) findings. METHODS: Selected melanocytic benign lesions and melanomas were imaged in vivo with RCM and LC-OCT at the Fundación Hospital Clinic (Barcelona, Spain). A minimum area of 4 × 4 mm (block image) at four depths (stratum granulosum, suprabasal, layer dermoepidermal junction and upper dermis) were acquired with RCM and a minimum of three cubes with LC-OCT. Horizontal, vertical sections and three-dimensional (3D) cubes of LC-OCT were matched with RCM (Vivablock two-dimensional composite mosaic) and histopathology, with ~5 µm lateral resolution accuracy (the same cell nuclei were measured in X, Y and Z) and evaluated by three observers experienced in using RCM and histopathology. RESULTS: In total, 12 melanocytic tumours (2 in situ melanomas, 2 invasive melanomas, 4 atypical naevi, 2 intradermal naevi, 1 compound naevus and 1 junctional naevus) were included. High correlation with 5 µm accuracy between RCM and LC-OCT was observed for each tumour. The 3D images of melanocytic lesions were obtained with cellular resolution and correlated with both RCM and histopathology, allowing an understanding of the architecture and precise correlation at the cellular level with RCM. Similarities between LC-OCT and RCM for the described diagnostic features and architecture (nests of melanocytic cells, ringed and meshwork pattern, and cellular details of tumour cells as dendritic and pagetoid cells) were confirmed. The main advantage of diagnosis by RCM fixed probe was the ability to produce larger scans of the lesion using mosaicing compared with an LC-OCT handheld probe. CONCLUSION: LC-OCT allows the architectural and cellular description of different types of melanocytic lesions. LC-OCT showed high correlation with histopathology (vertical sections) and RCM (horizontal sections) in melanocytic lesions. Diagnostic criteria for RCM were similar to those for LC-OCT.

Non-invasive scoring of cellular atypia in keratinocyte cancers in 3D LC-OCT images using Deep Learning.

Diagnosis based on histopathology for skin cancer detection is today's gold standard and relies on the presence or absence of biomarkers and cellular atypia. However it suffers drawbacks: it requires a strong expertise and is time-consuming. Moreover the notion of atypia or dysplasia of the visible cells used for diagnosis is very subjective, with poor inter-rater agreement reported in the literature. Lastly, histology requires a biopsy which is an invasive procedure and only captures a small sample of the lesion, which is insufficient in the context of large fields of cancerization. Here we demonstrate that the notion of cellular atypia can be objectively defined and quantified with a non-invasive in-vivo approach in three dimensions (3D). A Deep Learning (DL) algorithm is trained to segment keratinocyte (KC) nuclei from Line-field Confocal Optical Coherence Tomography (LC-OCT) 3D images. Based on these segmentations, a series of quantitative, reproducible and biologically relevant metrics is derived to describe KC nuclei individually. We show that, using those metrics, simple and more complex definitions of atypia can be derived to discriminate between healthy and pathological skins, achieving Area Under the ROC Curve (AUC) scores superior than 0.965, largely outperforming medical experts on the same task with an AUC of 0.766. All together, our approach and findings open the door to a precise quantitative monitoring of skin lesions and treatments, offering a promising non-invasive tool for clinical studies to demonstrate the effects of a treatment and for clinicians to assess the severity of a lesion and follow the evolution of pre-cancerous lesions over time.

Deep Learning for Basal Cell Carcinoma Detection for Reflectance Confocal Microscopy.

Basal cell carcinoma (BCC) is the most common skin cancer, with over 2 million cases diagnosed annually in the United States. Conventionally, BCC is diagnosed by naked eye examination and dermoscopy. Suspicious lesions are either removed or biopsied for histopathological confirmation, thus lowering the specificity of noninvasive BCC diagnosis. Recently, reflectance confocal microscopy, a noninvasive diagnostic technique that can image skin lesions at cellular level resolution, has shown to improve specificity in BCC diagnosis and reduced the number needed to biopsy by 2-3 times. In this study, we developed and evaluated a deep learning-based artificial intelligence model to automatically detect BCC in reflectance confocal microscopy images. The proposed model achieved an area under the curve for the receiver operator characteristic curve of 89.7% (stack level) and 88.3% (lesion level), a performance on par with that of reflectance confocal microscopy experts. Furthermore, the model achieved an area under the curve of 86.1% on a held-out test set from international collaborators, demonstrating the reproducibility and generalizability of the proposed automated diagnostic approach. These results provide a clear indication that the clinical deployment of decision support systems for the detection of BCC in reflectance confocal microscopy images has the potential for optimizing the evaluation and diagnosis of patients with skin cancer.

Combined PARP1-Targeted Nuclear Contrast and Reflectance Contrast Enhance Confocal Microscopic Detection of Basal Cell Carcinoma.

Reflectance confocal microscopy (RCM) with endogenous backscattered contrast can noninvasively image basal cell carcinomas (BCCs) in skin. However, BCCs present with high nuclear density, and the relatively weak backscattering from nuclei imposes a fundamental limit on contrast, detectability, and diagnostic accuracy. We investigated PARPi-FL, an exogenous nuclear poly(adenosine diphosphate ribose) polymerase (PARP1)-targeted fluorescent contrast agent, and fluorescence confocal microscopy toward improving BCC diagnosis. Methods: We tested PARP1 expression in 95 BCC tissues using immunohistochemistry, followed by PARPi-FL staining in 32 fresh surgical BCC specimens. The diagnostic accuracy of PARPi-FL contrast was evaluated in 83 surgical specimens. The optimal parameters for permeability of PARPi-FL through intact skin was tested ex vivo on 5 human skin specimens and in vivo in 3 adult Yorkshire pigs. Results: We found significantly higher PARP1 expression and PARPi-FL binding in BCCs than in normal skin structures. Blinded reading of RCM-and-fluorescence confocal microscopy images by 2 experts demonstrated a higher diagnostic accuracy for BCCs with combined fluorescence and reflectance contrast than for RCM alone. Optimal parameters (time and concentration) for PARPi-FL transepidermal permeation through intact skin were successfully determined. Conclusion: Combined fluorescence and reflectance contrast may improve noninvasive BCC diagnosis with confocal microscopy.

Line-field confocal optical coherence tomography as a tool for three-dimensional in vivo quantification of healthy epidermis: A pilot study.

Epidermal three-dimensional (3D) topography/quantification has not been completely characterized yet. The recently developed line-field confocal optical coherence tomography (LC-OCT) provides real-time, high-resolution, in-vivo 3D imaging of the skin. This pilot study aimed at quantifying epidermal metrics (epidermal thicknesses, dermal-epidermal junction [DEJ] undulation and keratinocyte number/shape/size) using 3D LC-OCT. For each study participant (8 female, skin-type-II, younger/older volunteers), seven body sites were imaged with LC-OCT. Epidermal metrics were calculated by segmentations and measurements assisted by artificial intelligence (AI) when appropriate. Thicknesses of epidermis/SC, DEJ undulation and keratinocyte nuclei volume varied across body sites. Evidence of keratinocyte maturation was observed in vivo: keratinocyte nuclei being small/spherical near the DEJ and flatter/elliptical near the skin surface. Skin microanatomy can be quantified by combining LC-OCT and AI. This technology could be highly relevant to understand aging processes and conditions linked to epidermal disorders. Future clinical/research applications are to be expected in this scenario.

Real-Time Reflectance Confocal Microscopy of Cutaneous Graft-versus-Host Disease Correlates with Histopathology.

Reflectance confocal microscopy (RCM) allows noninvasive, real-time evaluation of the skin at a resolution akin to histopathology (HP), but its application in cutaneous graft-versus-host disease (GVHD) has not been extensively assessed. We describe RCM features of cutaneous GVHD including acute (aGVHD), late acute, chronic (cGVHD; sclerotic and nonsclerotic subtypes), and inactive GVHD and correlate RCM with same-site HP for a subset of patients. Thirty-two adult and pediatric allogeneic hematopoietic cell transplantation (allo-HCT) recipients with cutaneous GVHD received RCM imaging of ≥1 lesions (n = 44), 13 of which necessitated skin biopsy. RCM images were deidentified and assessed by 2 RCM experts blinded to clinical and HP findings to reach a consensus on the features and patterns of the inflammatory dermatoses. Major RCM features (present in ≥65% of lesional sites) and patterns were reported. To determine the correlation between RCM and HP, detection of cellular features and patterns of inflammatory dermatoses were compared using percent agreement and prevalence-adjusted, bias-adjusted kappa estimates. Seven patients with early or late aGVHD (7 lesions) had irregular honeycombing, spongiosis, dermoepidermal junction (DEJ) and dermal inflammation, and melanophages; those with early aGVHD also had hyperkeratosis, dilated vessels, and coarse connective tissue. Both groups had an interface dermatitis pattern. Eighteen patients with nonsclerotic cGVHD (24 lesions) had irregular honeycombing, spongiosis, DEJ and dermal inflammation, dilated vessels, coarse connective tissue, and interface and spongiotic dermatitis patterns. Three sclerotic patients with cGVHD (7 lesions) had irregular honeycombing, DEJ and dermal inflammation with an interface dermatitis pattern. Four patients with inactive GVHD (6 lesions) showed minimal inflammation. RCM and HP had similar detection rates for 6 of 13 features and overall patterns important for diagnosis in 2 patients with late aGVHD (2 lesions; 15%) and 10 with nonsclerotic cGVHD (11 lesions; 85%) necessitating skin biopsy. RCM can detect features commonly reported in cutaneous GVHD and is comparable to HP. Additional characterization of cutaneous GVHD by RCM may enable future use in diagnosing, monitoring, or predicting disease in real time.

Ensemble Method of Convolutional Neural Networks with Directed Acyclic Graph Using Dermoscopic Images: Melanoma Detection Application.

The early detection of melanoma is the most efficient way to reduce its mortality rate. Dermatologists achieve this task with the help of dermoscopy, a non-invasive tool allowing the visualization of patterns of skin lesions. Computer-aided diagnosis (CAD) systems developed on dermoscopic images are needed to assist dermatologists. These systems rely mainly on multiclass classification approaches. However, the multiclass classification of skin lesions by an automated system remains a challenging task. Decomposing a multiclass problem into a binary problem can reduce the complexity of the initial problem and increase the overall performance. This paper proposes a CAD system to classify dermoscopic images into three diagnosis classes: melanoma, nevi, and seborrheic keratosis. We introduce a novel ensemble scheme of convolutional neural networks (CNNs), inspired by decomposition and ensemble methods, to improve the performance of the CAD system. Unlike conventional ensemble methods, we use a directed acyclic graph to aggregate binary CNNs for the melanoma detection task. On the ISIC 2018 public dataset, our method achieves the best balanced accuracy (76.6%) among multiclass CNNs, an ensemble of multiclass CNNs with classical aggregation methods, and other related works. Our results reveal that the directed acyclic graph is a meaningful approach to develop a reliable and robust automated diagnosis system for the multiclass classification of dermoscopic images.

Bilateral diffuse uveal melanocytic proliferation with multifocal diffuse integumentary melanocytic proliferation paraneoplastic syndrome: A case report.

Bilateral diffuse uveal melanocytic proliferation (B-DUMP) is a rare paraneoplastic syndrome typically presenting with bilateral visual loss. B-DUMP is associated with extraocular systemic malignancies with the most common being lung cancer in males and uro-gynaecological cancer in females (mainly ovarian cancer). Cutaneous and/or mucosal involvement in patients with B-DUMP has been reported but it is not well characterised. Herein, we present a female in her 70s with diagnosis of stage IV vaginal clear-cell carcinoma and metastatic melanoma of unknown primary that developed progressive bilateral loss of visual acuity compatible with 'B-DUMP'. Simultaneously, she developed multifocal bilateral bluish-greyish patches on the skin that were shown to have a proliferation of dermal melanocytes. We propose that the clinical and histopathologic cutaneous findings seen in patients with B-DUMP be termed 'diffuse integumentary melanocytic proliferation (DIMP)'.

Identification of an Immature Subset of PMN-MDSC Correlated to Response to Checkpoint Inhibitor Therapy in Patients with Metastatic Melanoma.

PMN-MDSCs support tumor progression and resistance to ICI therapy through their suppressive functions but their heterogeneity limits their use as biomarkers in cancer. Our aim was to investigate the phenotypic and functional subsets of PMN-MDSCs to identify biomarkers of response to ICI therapy. We isolated low-density CD15+ PMNs from patients with metastatic melanoma and assessed their immune-suppressive capacities. Expression of CD10 and CD16 was used to identify mature and immature subsets and correlate them to inhibition of T cell proliferation or direct cytotoxicity. Frequencies of the PMN-MDSCs subsets were next correlated to the radiological response of 36 patients receiving ICI therapy. Mature activated cells constituted the major population of PMN-MDSCs. They were found in a higher proportion in the pre-treatment blood of patients non responders to ICI. A subset of immature cells characterized by intermediate levels of CD10 and CD16, the absence of expression of SIRPα and a strong direct cytotoxicity to T cells was increased in patients responding to ICI. The paradoxical expansion of such cells during ICI therapy suggests a role of PMNs in the inflammatory events associated to efficient ICI therapy and the usefulness of their monitoring in patients care.

Line field confocal optical coherence tomography: An adjunctive tool in the diagnosis of autoimmune bullous diseases.

Autoimmune bullous diseases (AIBDs) still represent a considerable a source of morbidity and mortality: early identification of a specific AIBD is often difficult due to overlapping clinical and/or laboratory features and time-consuming invasive laboratory tests. We aimed to investigate the potential role of a new imaging technology, line-field confocal optical coherence tomography (LC-OCT), in the non-invasive diagnosis of AIBDs. LC-OCT was performed at lesional, perilesional and contralateral healthy sites in 30 patients, before histology and direct immunofluorescence. LC-OCT examination was able to identify the level of split (subcorneal/suprabasal/subepidermal/sublamina densa), to provide detailed images of the bulla roof morphology and content (eg, erythrocytes/acantholytic cells/polymorphonucleates). Areas of intra/subepidermal detachment were also detected also at clinically normal perilesional skin sites. LC-OCT can support physicians, real time and at bed-site, in the differential diagnosis of various AIBDs and their mimickers. Moreover, it can be used for the identification of subclinical lesions and therapy tapering.

Reflectance confocal microscopy terminology glossary for melanocytic skin lesions: A systematic review.

BACKGROUND: There is lack of uniformity in the reflectance confocal microscopy (RCM) terminology for melanocytic lesions. OBJECTIVE: To review published RCM terms for melanocytic lesions and identify redundant, synonymous terms. METHODS: A systematic review of original research articles adhering to Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines was conducted until August 15, 2018. Two investigators gathered all published RCM terms used to describe melanoma and melanocytic nevi. Synonymous terms were grouped based on similarity in definition and in histopathologic correlation. RESULTS: Out of 156 full-text screened articles, 59 studies met the inclusion criteria. We identified 209 terms; 191 (91.4%) corresponding to high-magnification/cellular-level terms and 18 (8.6%) corresponding to low-magnification/architectural patterns terms. The overall average use frequency of RCM terms was 3.1 times (range, 1-31). By grouping of individual RCM terms based on likely synonymous definitions and by eliminating terms lacking clear definition, the total number of RCM terms could be potentially reduced from 209 to 40 terms (80.8% reduction). LIMITATIONS: Non-English and non-peer-reviewed articles were excluded. CONCLUSIONS: This systematic review of published RCM terms identified significant terminology redundancy. It provides the basis for subsequent terminology consensus on melanocytic neoplasms.

Role of community pharmacists in skin cancer screening: A descriptive study of skin cancer risk factors prevalence and photoprotection habits in Barcelona, Catalonia, Spain.

BACKGROUND: Skin cancer incidence is increasing alarmingly, despite current efforts trying to improve its early detection. Community pharmacists have proven success in implementing screening protocols for a number of diseases because of their skills and easy access. OBJECTIVE: To evaluate the prevalence of skin cancer risk factors and the photoprotection habits with a questionnaire in community pharmacy users. METHODS: A research group consisting of pharmacists and dermatologists conducted a descriptive cross-sectional study to assess photoprotection habits and skin cancer risk factors by using a validated questionnaire in 218 community pharmacies in Barcelona from May 23rd to June 13th 2016. All participants received health education on photoprotection and skin cancer prevention. Patients with ≥1 skin cancer risk factor were referred to their physician, as they needed further screening of skin cancer. RESULTS: A total of 5,530 participants were evaluated. Of those, only 20.2% participants had received a total body skin examination for skin cancer screening in the past by a physician and 57.1% reported using a SPF 50+ sunscreen. 53.9% participants presented ≥1 skin cancer risk factor: 11.8% participants reported having skin cancer familial history and 6.2% reported skin cancer personal history; pharmacists found ≥10 melanocytic nevi in 43.8% participants and chronically sun-damaged skin in 21.4%. Lesions suspicious for melanoma were reported in 10.9% of the participants and urgent dermatological evaluation was recommended. CONCLUSIONS: Pharmacists can detect people with skin cancer risk factors amongst their users. This intervention can be considered in multidisciplinary strategies of skin cancer screening.

Role of community pharmacists in skin cancer screening: A descriptive study of skin cancer risk factors prevalence and photoprotection habits in Barcelona, Catalonia, Spain

Background: Skin cancer incidence is increasing alarmingly, despite current efforts trying to improve its early detection. Community pharmacists have proven success in implementing screening protocols for a number of diseases because of their skills and easy access. Objective: To evaluate the prevalence of skin cancer risk factors and the photoprotection habits with a questionnaire in community pharmacy users. Methods: A research group consisting of pharmacists and dermatologists conducted a descriptive cross-sectional study to assess photoprotection habits and skin cancer risk factors by using a validated questionnaire in 218 community pharmacies in Barcelona from May 23rd to June 13th 2016. All participants received health education on photoprotection and skin cancer prevention. Patients with ≥1 skin cancer risk factor were referred to their physician, as they needed further screening of skin cancer. Results: A total of 5,530 participants were evaluated. Of those, only 20.2% participants had received a total body skin examination for skin cancer screening in the past by a physician and 57.1% reported using a SPF 50+ sunscreen. 53.9% participants presented ≥1 skin cancer risk factor: 11.8% participants reported having skin cancer familial history and 6.2% reported skin cancer personal history; pharmacists found ≥10 melanocytic nevi in 43.8% participants and chronically sun-damaged skin in 21.4%. Lesions suspicious for melanoma were reported in 10.9% of the participants and urgent dermatological evaluation was recommended. Conclusions: Pharmacists can detect people with skin cancer risk factors amongst their users. This intervention can be considered in multidisciplinary strategies of skin cancer screening

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