Seborrheic keratoses mimicking melanoma unveiled by in vivo reflectance confocal microscopy

[Translated article] Reflectance Confocal Microscopy Terminology in Spanish: A Delphi Consensus Study

The terminology used to describe reflectance confocal microscopy (RCM) findings in both melanocytic and nonmelanocytic lesions has been standardized in English. We convened a panel of Spanish-speaking RCM experts and used the Delphi method to seek consensus on which Spanish terms best describe RCM findings in this setting. The experts agreed on 52 terms: 28 for melanocytic lesions and 24 for nonmelanocytic lesions. The resulting terminology will facilitate homogenization, leading to a better understanding of structures, more standardized descriptions in clinical registries, and easier interpretation of clinical reports exchanged between dermatologists.

Reflectance Confocal Microscopy Terminology in Spanish: A Delphi Consensus Study

The terminology used to describe reflectance confocal microscopy (RCM) findings in both melanocytic and nonmelanocytic lesions has been standardized in English. We convened a panel of Spanish-speaking RCM experts and used the Delphi method to seek consensus on which Spanish terms best describe RCM findings in this setting. The experts agreed on 52 terms: 28 for melanocytic lesions and 24 for nonmelanocytic lesions. The resulting terminology will facilitate homogenization, leading to a better understanding of structures, more standardized descriptions in clinical registries, and easier interpretation of clinical reports exchanged between dermatologists.

Melanoma clinicopathological groups characterized and compared with dermoscopy and reflectance confocal microscopy

BACKGROUND

Dermoscopic and reflectance confocal microscopy (RCM) correlations between morphologic groups of melanoma have not yet been described.

OBJECTIVE

Describe and compare dermoscopic and RCM features of cutaneous melanomas with histopathological confirmation.

METHODS

Single center, retrospective analysis of consecutive melanomas evaluated with RCM (2015-2019). Lesions were clinically classified as typical, nevus-like, amelanotic/nonmelanoma skin cancer (NMSC)-like, seborrheic keratosis (SK)-like and lentigo/lentigo maligna (LM)-like. Presence or absence of common facial and nonfacial melanoma dermoscopic and RCM patterns were recorded. Clusters were compared with typical lesions by multivariate logistic regression.

RESULTS

Among 583 melanoma lesions, significant differences between clusters were evident (compared to typical lesions). Observation of dermoscopic features (>50% of lesions) in amelanotic/NMSC-like lesions consistently displayed 3 patterns (atypical network, atypical vascular pattern + regression structures), and nevus-like and SK-like lesions and lentigo/LM-like lesions consistently displayed 2 patterns (atypical network + regression structures, and nonevident follicles + heavy pigmentation intensity). Differences were less evident with RCM, as almost all lesions were consistent with melanoma diagnosis.

LIMITATIONS

Small SK-like lesions sample, single RCM analyses (no reproduction of outcome).

CONCLUSION

RCM has the potential to augment our ability to consistently and accurately diagnose melanoma independently of clinical and dermoscopic features.

Characterizing Malignant Melanoma Clinically Resembling Seborrheic Keratosis Using Deep Knowledge Transfer

Simple Summary

Malignant melanomas (MMs) with aypical clinical presentation constitute a diagnostic pitfall, and false negatives carry the risk of a diagnostic delay and improper disease management. Among the most common, challenging presentation forms of MMs are those that clinically resemble seborrheic keratosis (SK). On the other hand, SK may mimic melanoma, producing ‘false positive overdiagnosis’ and leading to needless excisions. The evolving efficiency of deep learning algorithms in image recognition and the availability of large image databases have accelerated the development of advanced computer-aided systems for melanoma detection. In the present study, we used image data from the International Skin Image Collaboration archive to explore the capacity of deep knowledge transfer in the challenging diagnostic task of the atypical skin tumors of MM and SK.

Abstract

Malignant melanomas resembling seborrheic keratosis (SK-like MMs) are atypical, challenging to diagnose melanoma cases that carry the risk of delayed diagnosis and inadequate treatment. On the other hand, SK may mimic melanoma, producing a ‘false positive’ with unnecessary lesion excisions. The present study proposes a computer-based approach using dermoscopy images for the characterization of SΚ-like MMs. Dermoscopic images were retrieved from the International Skin Imaging Collaboration archive. Exploiting image embeddings from pretrained convolutional network VGG16, we trained a support vector machine (SVM) classification model on a data set of 667 images. SVM optimal hyperparameter selection was carried out using the Bayesian optimization method. The classifier was tested on an independent data set of 311 images with atypical appearance: MMs had an absence of pigmented network and had an existence of milia-like cysts. SK lacked milia-like cysts and had a pigmented network. Atypical MMs were characterized with a sensitivity and specificity of 78.6% and 84.5%, respectively. The advent of deep learning in image recognition has attracted the interest of computer science towards improved skin lesion diagnosis. Open-source, public access archives of skin images empower further the implementation and validation of computer-based systems that might contribute significantly to complex clinical diagnostic problems such as the characterization of SK-like MMs.

Advances in the Etiology, Detection, and Clinical Management of Seborrheic Keratoses

Seborrheic keratoses (SKs) are ubiquitous, generally benign skin tumors that exhibit high clinical variability. While age is a known risk factor, the precise roles of UV exposure and immune abnormalities are currently unclear. The underlying mechanisms of this benign disorder are paradoxically driven by oncogenic mutations and may have profound implications for our understanding of the malignant state. Advances in molecular pathogenesis suggest that inhibition of Akt and APP, as well as existing treatments for skin cancer, may have therapeutic potential in SK. Dermoscopic criteria have also become increasingly important to the accurate detection of SK, and other noninvasive diagnostic methods, such as reflectance confocal microscopy and optical coherence tomography, are rapidly developing. Given their ability to mimic malignant tumors, SK cases are often used to train artificial intelligence-based algorithms in the computerized detection of skin disease. These technologies are becoming increasingly accurate and have the potential to significantly augment clinical practice. Current treatment options for SK cause discomfort and can lead to adverse post-treatment effects, especially in skin of color. In light of the discontinuation of ESKATA in late 2019, promising alternatives, such as nitric-zinc and trichloroacetic acid topicals, should be further developed. There is also a need for larger, head-to-head trials of emerging laser therapies to ensure that future treatment standards address diverse patient needs.

Reflectance confocal microscopy: Diagnostic criteria of common benign and malignant neoplasms, dermoscopic and histopathologic correlates of key confocal criteria, and diagnostic algorithms

Reflectance confocal microscopy (RCM) is a high-resolution, noninvasive tool that is currently approved by the US Food and Drug Administration for obtaining and interpreting images of the skin and cutaneous neoplasms with the goal of decreasing unnecessary biopsy procedures in patients with benign lesions. The second article in this continuing medical education series focuses on identifying key criteria for the diagnosis of common skin cancers-melanoma, basal cell carcinoma, and squamous cell carcinoma. We contrast these findings with RCM features of common benign lesions-melanocytic nevi, solar lentigo, seborrheic keratosis, lichen planus-like keratosis, and sebaceous hyperplasia. We also correlate the dermoscopic and histopathologic findings with the RCM features.

Clinical management of very small pigmented lesions: Improved clinical outcome through dermoscopy and reflectance confocal microscopy combination

INTRODUCTION

Small-sized pigmented lesions (SSPL) <3 mm in diameter are common pitfall in the daily dermatology practice. Dermoscopy alone is hampered by the lack of specific features inversely proportional to the diameter of the lesions and its performance is highly operator-dependent. Reflectance confocal microscopy (RCM) has been demonstrated to be effective in the diagnosis of several difficult lesions where dermoscopy lacks to provide conclusive information.

MATERIALS AND METHODS

A total of 179 lesions with uncertain or equivocal clinical and dermoscopy appearance were selected. Dermoscopist has been requested to express a diagnostic suspect when possible. Equivocal lesions underwent RCM performed by expert for second-level evaluation before surgical excision for histological diagnosis. Results have been later statistically analysed.

RESULTS

Dermoscopy was not diagnostic in large number of lesions with low concordance histology (39.1%) instead of a much high concordance when combined with RCM (93.9%).

CONCLUSIONS

Small-sized pigmented lesions were more likely to be located on the face area. Diagnosis of pigmented BCC was relatively easy on dermoscopy and also in the case of small lesions showing typical signs of BCC. LM and MM have been seen to be particularly difficult to be diagnosed using only dermoscopy. The combination of digital dermoscopy and RCM represents the correct approach of SSPL.

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

BACKGROUND

There is lack of uniformity in reflectance confocal microscopy (RCM) terminology for nonmelanocytic lesions (NMLs).

OBJECTIVE

To review published RCM terms for NMLs and identify likely synonymous terms.

METHODS

We conducted a systematic review of original research articles published up to August 19, 2017, adhering to Preferred Reporting Items for Systemic Reviews and Meta-Analyses guidelines. Two investigators gathered all published RCM terms used to describe basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and seborrheic keratosis/solar lentigo/lichen planus-like keratosis (SK/SL/LPLK). Synonymous terms were grouped on the basis of similarity in definition and histopathologic correlates.

RESULTS

The inclusion criteria was met by 31 studies. Average frequency of use per term was 1.6 (range 1-8). By grouping synonymous terms, the number of terms could be reduced from 58 to 18 for BCC, 58 to 36 for SCC, 23 to 12 for SK/SL/LPLK, and from 139 to 66 terms (52.5% reduction) in total. The frequency of term usage stratified by anatomic layer (suprabasal epidermis vs epidermal basal layer, dermoepidermal junction, and superficial dermis) was 27 (25.7%) versus 78 (74.2%) for BCC; 60 (64.5%) versus 33 (34.5%) for SCC, and 15 (45.4%) versus 18 (54.5%) for SK/SL/LPLK, respectively.

LIMITATIONS

Articles that were not peer reviewed were excluded.

CONCLUSION

Systematic review of published RCM terms provides the basis for future NMLs terminology consensus.

Lesions Mimicking Melanoma at Dermoscopy Confirmed Basal Cell Carcinoma: Evaluation with Reflectance Confocal Microscopy

Background: Atypical basal cell carcinoma (BCC), characterized by equivocal dermoscopic features typical of malignant melanoma (MM), can be difficult to diagnose. Reflectance confocal microscopy (RCM) enables in vivo imaging at nearly histological resolution. Objectives: To evaluate with RCM atypical melanocytic lesions identified in dermoscopy, according to common RCM criteria for the differential diagnosis of BCC, and to identify representative RCM parameters for superficial (sBCCs) and nonsuperficial (nsBCCs) basal cell carcinomas (BCCs). Methods: A retrospective analysis of consecutive patients evaluated with RCM, selecting excised lesions classified at dermoscopy with ≥1 score from the re visited 7-point checklist, mimicking melanoma, registered between 2010 and 2016. Cluster analysis identified BCC subclassifications. Results: Of 178 atypical lesions, 34 lesions were diagnosed as BCCs with RCM. Lesions were confirmed BCCs with histopathology. Dermoscopic features included atypical network (55.9%) and regression structures (35.5%) associated with sBCCs, and an atypical vascular pattern (58.8%) and irregular blotches (58.8%) with nsBCCs. Hierarchical cluster analysis identified 2 clusters: cluster 1 (100% sBCCs) was characterized by the presence of cords connected to the epidermis (90%, p < 0.001), tumor islands located in the epidermis (100%, p < 0.001), smaller vascular diameter (100%, p < 0.001) and solar elastosis (90%, p = 0.017), and cluster 2 (nsBCCs 85%) was defined by the dermic location of tumor islands (87.5%, p < 0.001) with branch-like structures (70.8%, p = 0.007) and surrounding collagen (83.3%, p = 0.012), peripheral palisading (83.3%, p = 0.012) and coiled vascular morphology (79.2%, p < 0.001) with a larger vascular diameter (50%, p < 0.001). Conclusions: RCM is able to diagnose BCCs mimicking melanoma at dermoscopy and seems able to identify sBCCs and nsBCCs.

Unusual Clinical Presentations of Malignant Melanoma: A Review of Clinical and Histologic Features with Special Emphasis on Dermatoscopic Findings

This review presents the main challenges encountered when diagnosing unusual variants of malignant melanoma with the aim of raising awareness to allow application of the most appropriate treatment strategies. Although these melanomas are often rare, their misdiagnosis potentially jeopardizes patients' health and survival, and has medicolegal implications. The clinical and histologic presentations of melanoma vary greatly, and assessment of uncommon melanomas can be difficult for practitioners because of their scarcity and resemblance to other dermatologic entities. The most problematic melanoma types are desmoplastic melanoma, polypoid melanoma, primary dermal melanoma, verrucous malignant melanoma, pigmented epithelioid melanocytoma, mucosal melanoma, follicular melanoma and melanoma with non-melanocytic differentiation. The two most difficult-to-diagnose subtypes of melanoma are the nevoid and the amelanotic melanomas. Some specific attributes of these variants can be more easily recognized with digital dermatoscopy, facilitating early detection and possibly avoiding invasive procedures. Key cases with the most notable clinical, dermatoscopic, and histopathologic features are presented, highlighting the practical issues of making an accurate diagnosis and choosing the best therapy.