Evaluation of dermoscopic algorithm for seborrhoeic keratosis: a prospective study in 412 patients

Can Artificial Intelligence "Hold" a Dermoscope?-The Evaluation of an Artificial Intelligence Chatbot to Translate the Dermoscopic Language

This survey represents the first endeavor to assess the clarity of the dermoscopic language by a chatbot, unveiling insights into the interplay between dermatologists and AI systems within the complexity of the dermoscopic language. Given the complex, descriptive, and metaphorical aspects of the dermoscopic language, subjective interpretations often emerge. The survey evaluated the completeness and diagnostic efficacy of chatbot-generated reports, focusing on their role in facilitating accurate diagnoses and educational opportunities for novice dermatologists. A total of 30 participants were presented with hypothetical dermoscopic descriptions of skin lesions, including dermoscopic descriptions of skin cancers such as BCC, SCC, and melanoma, skin cancer mimickers such as actinic and seborrheic keratosis, dermatofibroma, and atypical nevus, and inflammatory dermatosis such as psoriasis and alopecia areata. Each description was accompanied by specific clinical information, and the participants were tasked with assessing the differential diagnosis list generated by the AI chatbot in its initial response. In each scenario, the chatbot generated an extensive list of potential differential diagnoses, exhibiting lower performance in cases of SCC and inflammatory dermatoses, albeit without statistical significance, suggesting that the participants were equally satisfied with the responses provided. Scores decreased notably when practical descriptions of dermoscopic signs were provided. Answers to BCC scenario scores in the diagnosis category (2.9 ± 0.4) were higher than those with SCC (2.6 ± 0.66, p = 0.005) and inflammatory dermatoses (2.6 ± 0.67, p = 0). Similarly, in the teaching tool usefulness category, BCC-based chatbot differential diagnosis received higher scores (2.9 ± 0.4) compared to SCC (2.6 ± 0.67, p = 0.001) and inflammatory dermatoses (2.4 ± 0.81, p = 0). The abovementioned results underscore dermatologists' familiarity with BCC dermoscopic images while highlighting the challenges associated with interpreting rigorous dermoscopic images. Moreover, by incorporating patient characteristics such as age, phototype, or immune state, the differential diagnosis list in each case was customized to include lesion types appropriate for each category, illustrating the AI's flexibility in evaluating diagnoses and highlighting its value as a resource for dermatologists.

Correlation Among Serum Calcidiol, Sun Index, and Vitamin D Intake in Individuals With Seborrheic Keratoses Living in Coastal Area

INTRODUCTION

Seborrheic keratoses (SK) are benign epidermal tumors with high sun exposure as a major risk factor. Vitamin D deficiency is also thought to play a role in its pathogenesis. There has been no data regarding SK, calcidiol level, vitamin D intake, and sun index (SI) among people living in coastal areas in Indonesia.

OBJECTIVES

To assess the correlation between 1) serum calcidiol levels with SI and vitamin D intake and 2) lesion size with SI and serum calcidiol level among SK patients living in a coastal area.

METHODS

This is a cross-sectional study. We performed interviews using the sun index questionnaire and semiquantitative food frequency questionnaire for vitamin D; physical examination; dermoscopy to determine the largest SK lesion size; and measurement of serum calcidiol levels in participants with SK living in Cilincing District, North Jakarta. Spearman correlation test was used to assess the relationship between variables.

RESULTS

Thirty-nine participants with SK aged 19-59 years were analyzed. The median of the SK largest diameter, SI, serum calcidiol, and vitamin D intake was 2 (1-10) mm, 3.95 (1.1-23.52), 14.3 (5.25-35.30) ng/ml, and 4.3 (0.1-30.1) mcg/day, respectively. SI and vitamin D intake were not significantly correlated with calcidiol levels. Similarly, SI and calcidiol levels were not significantly correlated with the largest SK lesion size.

CONCLUSIONS

We found low calcidiol levels and vitamin D intake in this coastal population. The SI and vitamin D intake had no correlations with calcidiol levels. Furthermore, calcidiol levels and SI had no correlations with the lesion largest diameter.

Healing Process after High-Intensity Focused Ultrasound Treatment of Benign Skin Lesions: Dermoscopic Analysis and Treatment Guidelines

Background: High-Intensity Focused Ultrasound (HIFU) has emerged as a precise and non-invasive modality for tissue ablation and healing. This study presents a detailed dermoscopic analysis of skin healing post-High-Intensity Focused Ultrasound (HIFU) treatment, focusing on common benign skin lesions, such as seborrheic keratosis, sebaceous hyperplasia, vascular lesions, and sebaceous nevi. Methods: Prior to HIFU treatment, a comprehensive assessment was conducted, integrating ultrasound scanning and clinical evaluations. The TOOsonix System ONE-M was employed for HIFU treatments, with parameters tailored to each lesion type. Results: A common pattern observed across all lesions includes initial whitening post treatment, followed by scab formation and the development of a pink area with reparative vessels. This study, however, highlights distinct differences in fibrosis patterns and healing timelines across different lesion types. Each lesion type exhibited unique fibrosis patterns post treatment. Flatter variants of seborrheic keratosis healed within a month, displaying hypopigmentation and reparative vessels, alongside a distinct lattice fibrosis pattern in more verrucous forms, which took about two months to heal. Sebaceous hyperplasia, characterized by rapid healing within three weeks, demonstrated fibrosis with pink areas and perpendicular white lines, concluding with a slight depression. Vascular lesions varied in healing time based on depth, with superficial ones showing whitening and crust formation, while deeper lesions had vessel occlusion and size reduction accompanied by concentric fibrotic bands. Sebaceous nevi presented the longest healing duration of three months, characterized by amorphous white-gray structures, scab formation, and the emergence of pink areas with branching vessels, leading to clear skin with reduced white lines. Conclusions: in conclusion, this meticulous clinical evaluation highlights the unique healing characteristics and timelines for each skin lesion type treated with HIFU. These insights are invaluable for optimizing follow-up assessments, identifying potential complications, and refining treatment protocols. By providing detailed insights into the healing timelines and patterns for different types of lesions, patients can be better informed about their post-treatment journey.

Multiclass skin lesion localization and classification using deep learning based features fusion and selection framework for smart healthcare

BACKGROUND

The idea of smart healthcare has gradually gained attention as a result of the information technology industry's rapid development. Smart healthcare uses next-generation technologies i.e., artificial intelligence (AI) and Internet of Things (IoT), to intelligently transform current medical methods to make them more efficient, dependable and individualized. One of the most prominent uses of telemedicine and e-health in medical image analysis is teledermatology. Telecommunications technologies are used in this industry to send medical information to professionals. Teledermatology is a useful method for the identification of skin lesions, particularly in rural locations, because the skin is visually perceptible. One of the most recent tools for diagnosing skin cancer is dermoscopy. To classify skin malignancies, numerous computational approaches have been proposed in the literature. However, difficulties still exist i.e., lesions with low contrast, imbalanced datasets, high level of memory complexity, and the extraction of redundant features.

METHODS

In this work, a unified CAD model is proposed based on a deep learning framework for skin lesion segmentation and classification. In the proposed approach, the source dermoscopic images are initially pre-processed using a contrast enhancement based modified bio-inspired multiple exposure fusion approach. In the second stage, a custom 26-layered convolutional neural network (CNN) architecture is designed to segment the skin lesion regions. In the third stage, four pre-trained CNN models (Xception, ResNet-50, ResNet-101 and VGG16) are modified and trained using transfer learning on the segmented lesion images. In the fourth stage, the deep features vectors are extracted from all the CNN models and fused using the convolutional sparse image decomposition fusion approach. In the fifth stage, the univariate measurement and Poisson distribution feature selection approach is used for the best features selection for classification. Finally, the selected features are fed to the multi-class support vector machine (MC-SVM) for the final classification.

RESULTS

The proposed approach employed to the HAM10000, ISIC2018, ISIC2019, and PH2 datasets and achieved an accuracy of 98.57%, 98.62%, 93.47%, and 98.98% respectively which are better than previous works.

CONCLUSION

When compared to renowned state-of-the-art methods, experimental results show that the proposed skin lesion detection and classification approach achieved higher performance in terms of both visually and enhanced quantitative evaluation with enhanced accuracy.

Dermoscopy of inflamed seborrheic keratosis: A great mimic of malignancy

BACKGROUND

Clinical and dermoscopic recognition of seborrheic keratoses (SKs) is often straightforward, and biopsy might not be required. However, inflamed SKs (iSKs) can pose a diagnostic challenge. Dermoscopic features of iSKs have not yet been evaluated to date.

OBJECTIVES

To assess the diagnostic ability of a group of dermatologists to diagnose iSKs by dermoscopy. To evaluate the dermoscopic findings of a long series of inflamed seborrheic keratoses.

METHODS

Clinical and dermoscopic images of 100 difficult-to-diagnose skin tumours, including 29 iSKs, were presented to 33 clinicians (24 dermatologists and 9 dermatology residents), who were blinded to the diagnosis. The dermoscopic features of a series of 219 iSKs were retrospectively analysed.

RESULTS

iSKs were correctly identified in a 37.6% of cases. Classic dermoscopic criteria were present in only 47% of iSKs. The most frequent dermoscopic feature in iSKs was the presence of vascularization (91.3%), but only a 44.5% showed predominance of hairpin vessels. A bluish hue was observed in 18.3% of lesions. Seven dermoscopic patterns were identified, based on the dermoscopic similarity to other tumours: seborrheic keratosis-like (28.8%); squamous cell carcinoma-like (25.6%); melanoma-like (17.8%); keratoacanthoma-like (6.8%); basal cell carcinoma-like (5.9%); verruca vulgaris-like (5.9%); nevus-like (2.3%).

CONCLUSIONS

The diagnosis of iSKs can be challenging even with dermoscopy. They may behave as authentic mimics of other cutaneous tumours, including squamous cell carcinoma or melanoma. For this reason, histopathological examination should be mandatory in these cases.

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.

Usefulness of Dermoscopy to Provide Accurate Assessment of Skin Cancers

Seborrheic keratosis (SK) is the most common benign tumour of epidermal origin. In most cases, it is simple to recognize in the clinical examination. However, sometimes SK can be a problematic lesion. We present the cases of two patients with seborrheic keratosis in whom we diagnosed the skin cancer through dermoscopic and histopathological examinations. The article aims to draw attention to the need for dermoscopic examinations to be included for an accurate assessment of the nevi not only by dermatologists but also not-specialized doctors. We would like to underline that many skin cancers share the similar features of malignancy, and competence and capability to interpret the dermoscopic pictures correctly are important for early recognition of malignant lesion. Very often malignant skin cancers can be hidden among benign lesions like seborrheic keratosis or they can be imitators of benign lesions. Amongst all cases of imposing SK, basal cell carcinoma, squamous cell carcinoma, melanoma is the most important differential diagnosis, of which their dermoscopic features will be discussed in this article.

Differential Diagnosis and Management on Seborrheic Keratosis in Elderly Patients

Seborrheic keratoses are exceedingly common in the elderly and usually are easy to diagnose and do not require treatment. However, given their great variety of clinical presentation, they may give rise to false-positive cases, meaning that they may at times mimic melanoma, squamous cell carcinoma and basal cell carcinoma. On the other hand, melanoma may mimic seborrheic keratosis, leading to incorrect patient management. With this review, we would like to summarize the current knowledge about epidemiology, clinical, dermoscopic and reflectance confocal microscopy imaging of this common entity, and we also summarize the currently available treatment options.

A hierarchical three-step superpixels and deep learning framework for skin lesion classification

Skin cancer is one of the most common and dangerous cancer that exists worldwide. Malignant melanoma is one of the most dangerous skin cancer types has a high mortality rate. An estimated 196,060 melanoma cases will be diagnosed in 2020 in the USA. Many computerized techniques are presented in the past to diagnose skin lesions, but they are still failing to achieve significant accuracy. To improve the existing accuracy, we proposed a hierarchical framework based on two-dimensional superpixels and deep learning. First, we enhance the contrast of original dermoscopy images by fusing local and global enhanced images. The entire enhanced images are utilized in the next step to segmentation skin lesions using three-step superpixel lesion segmentation. The segmented lesions are mapped over the whole enhanced dermoscopy images and obtained only segmented color images. Then, a deep learning model (ResNet-50) is applied to these mapped images and learned features through transfer learning. The extracted features are further optimized using an improved grasshopper optimization algorithm, which is later classified through the Naïve Bayes classifier. The proposed hierarchical method has been evaluated on three datasets (Ph2, ISBI2016, and HAM1000), consisting of three, two, and seven skin cancer classes. On these datasets, our method achieved an accuracy of 95.40%, 91.1%, and 85.50%, respectively. The results show that this method can be helpful for the classification of skin cancer with improved accuracy.

Dermoscopy in China: current status and future prospective

OBJECTIVE

Dermoscopy is a useful technique for improving the diagnostic accuracy of various types of skin disorders. In China, dermoscopy has been widely accepted, and domestic researchers have made tremendous progress in the field of dermoscopy. The main purpose of this review is to summarize the current status of dermoscopy in China and identify its future directions.

DATA SOURCES

Articles included in this review were obtained by searching the following databases: Wanfang, China National Knowledge Infrastructure, PubMed, and the Web of Science. We focused on research published before 2019 with keywords including dermoscopy, dermoscopic, dermoscope and trichoscopy.

STUDY SELECTION

A total of 50 studies were selected. Of these studies, 20 studies were in Chinese and 30 in English, research samples of all the studies were collected from Chinese populations.

RESULTS

Since 2000, more than 380 articles about dermoscopy have been published in domestic or foreign journals. Dermoscopy can improve the diagnostic accuracy of neoplastic diseases, evaluating the therapeutic effect of treatment, and determining the treatment endpoint, and it can also assist in the differential diagnosis of inflammatory diseases and in the assessment of the severity of the disease. In addition, researches about the applications of dermoscopy during surgical treatment have been published. Training courses aiming to improve the diagnostic ability of dermatologists, either face-to-face or online, have been offered. The Chinese Skin Image Database, launched in 2017 as a work platform for dermatologists, has promoted the development of dermoscopy in China. Computer-aided diagnostic systems based on the Chinese population are ready for use. In the future, cooperation, resource sharing, talent development, image management, and computer-aided diagnosis will be important directions for the development of dermoscopy in China.

CONCLUSION

Dermoscopy has been widely used and developed in China, however, it still needs to address more challenges in the future.

Evaluation of dermoscopic criteria for seborrheic keratosis on non-polarized versus polarized dermoscopy

BACKGROUND

The two dermoscopic methods, polarized dermoscopy (PD) and non-polarized dermoscopy (NPD), use different types of light sources. Here, we aimed to explore the differences between these two methods in the diagnosis of seborrheic keratosis (SK).

MATERIALS AND METHODS

The images of 121 cases of SK taken by a digital camera equipped with NPD and PD were evaluated against 14 dermoscopic criteria of SK.

RESULTS

The agreement levels between NPD and PD were fair to perfect against the dermoscopic criteria of SK. Perfect agreement was observed in fingerprint-like structures (κ = 0.812) and linear irregular vessels (κ = 0.807). Substantial agreement was determined in comedo-like openings (κ = 0.640), hairpin vessels (κ = 0.609), a moth-eaten border (κ = 0.642), sharp demarcation (κ = 0.637), network-like structures (κ = 0.662), and a mica-like pattern (κ = 0.639). Moderate agreement was found in milia-like cysts (κ = 0.550), fissures and ridges (κ = 0.554), dotted vessels (κ = 0.496), and color variability (κ = 0.438). Fair agreement was obtained only in comma vessels (κ = 0.340).

CONCLUSION

Based on our results, we cannot recommend an absolute dermoscopic method for the diagnosis of SK; rather, we suggest that the methods are complementary.

Differentiation of seborrheic keratosis from basal cell carcinoma, nevi and melanoma by RGB autofluorescence imaging

A clinical trial on the autofluorescence imaging of skin lesions comprising 16 dermatologically confirmed pigmented nevi, 15 seborrheic keratosis, 2 dysplastic nevi, histologically confirmed 17 basal cell carcinomas and 1 melanoma was performed. The autofluorescence spatial properties of the skin lesions were acquired by smartphone RGB camera under 405 nm LED excitation. The diagnostic criterion is based on the calculation of the mean autofluorescence intensity of the examined lesion in the spectral range of 515 nm-700 nm. The proposed methodology is able to differentiate seborrheic keratosis from basal cell carcinoma, pigmented nevi and melanoma. The sensitivity and specificity of the proposed method was estimated as being close to 100%. The proposed methodology and potential clinical applications are discussed in this article.

Seborrheic keratoses mimicking melanoma unveiled by in vivo reflectance confocal microscopy

BACKGROUND

Seborrheic keratoses (SebK) with atypical dermoscopy presentation are increasingly reported. These lesions do not exhibit typical dermoscopy features of SebK and sometimes mimic melanoma, thus complicating the differential diagnosis. Reflectance confocal microscopy (RCM) is a non-invasive tool, which allows an in vivo imaging of the skin. The study objectives were to evaluate the agreement between RCM classification and histological diagnoses, and the reliability of well-known RCM criteria for SebK in the identification of SebK with atypical dermoscopy presentation.

MATERIALS AND METHODS

We retrospectively analysed at RCM excised lesions presenting in dermoscopy ≥1 score at revisited 7-point checklist. The study population consisted of cases showing no melanocytic RCM findings. Lesions were investigated for distinct non-melanocytic RCM features, blinded from histopathology diagnoses. Histopathology matching was then performed before statistical analysis.

RESULTS

The study consisted of 117 cases, classified at RCM as SebK (71 cases), dermatofibroma (18 cases), basal cell carcinoma (13 cases), squamous cell carcinoma (2 cases), and "non-specific" (13 cases). Overall K strength of agreement at histopathology matching proved 0.76. Of the 71 cases classified at RCM with SebK, agreement was achieved in 97%.

CONCLUSION

Reflectance confocal microscopy classification proved high agreement with histopathology for SebK with atypical dermoscopy presentations, allowing an early differential diagnosis. RCM features in this group of lesions were similar to those described for typical cases of SebK, and may assist clinician therapy decision making, whilst avoiding unnecessary excisions.

The limitations of dermoscopy: false-positive and false-negative tumours

Dermoscopy has been documented to increase the diagnostic accuracy of clinicians evaluating skin tumours, improving their ability to detect skin cancer and better recognize benign moles. However, dermoscopically 'false-positive' and 'false-negative' tumours do exist. False-positive diagnosis usually leads to unnecessary excisions. False-negative diagnosis is much more dangerous, as it might result in overlooking a cancer, with severe undesirable consequences for the patient and the physician. Therefore, management strategies should mainly focus on addressing the risk of dermoscopically false-negative tumours. The most frequent benign tumours that might acquire dermatoscopic characteristics suggestive of malignancy are seborrhoeic keratosis (SK), including solar lentigo, melanoacanthoma, irritated, clonal and regressive SK, angioma (mainly thrombosed angioma and angiokeratoma), dermatofibroma, benign adnexal tumours and naevi (Clark, Spitz, recurrent, combined, sclerosing). The most useful clues to recognize these tumours are the following: solar lentigo - broad network; melanoacanthoma - sharp border; irritated SK - regularly distributed white perivascular halos; clonal SK - classic SK criteria; regressive SK - remnants of SK; targetoid haemosiderotic haemangioma - dark centre and reddish periphery; thrombosed angioma - sharp demarcation; angiokeratoma - dark lacunae; atypical dermatofibromas - palpation; follicular tumours - white colour; sebaceous tumours - yellow colour; Clark naevi - clinical context; Spitz/Reed naevi - age; combined naevi - blue central area; recurrent naevi - pigmentation within the scar; sclerosing naevi - age and location on the upper back; blue naevi - history. Malignant tumours that might mimic benign ones and escape detection are melanoma (in situ, nevoid, spitzoid, verrucous, regressive, amelanotic), squamous cell carcinoma (mainly well-differentiated variants) and rarely basal cell carcinoma (non-pigmented variants). The most useful clues to recognize the peculiar melanoma subtypes are as follows: melanoma in situ - irregular hyperpigmented areas; nevoid melanoma - history of growth; spitzoid melanoma - age; verrucous melanoma - blue-black sign; regressive melanoma - peppering or scar-like depigmentation; amelanotic melanoma - pink colour, linear irregular vessels, dotted vessels. In this article, we summarized the most frequent dermoscopic variations of common skin tumours that are often misinterpreted, aiming to assist clinicians to reduce the number of false diagnoses.

What's new in dermoscopy of Bowen's disease: two new dermoscopic signs and its differential diagnosis

BACKGROUND

Clinical and dermoscopic features of Bowen's disease (BD) show great diversity. Some lesions of BD are often difficult to be differentiated from seborrheic keratosis, actinic keratosis, lichen planus-like keratosis, etc. It is necessary to fully describe the dermoscopic features of the disease, considering differential diagnosis.

OBJECTIVE

To describe the dermoscopic feautres of Bowen's disease and summarize the dermoscopic differential diagnosis of the disease.

PATIENTS AND METHODS

Altogether 146 lesions with a histopathological diagnosis of Bowen's disease were consecutively included in this study. All the lesions were imaged with dermoscopy and analyzed for dermoscopic features.

RESULTS

A total of 146 lesions were analyzed. The dermoscopic features most frequently observed in our series of lesions were scales (78.8%), glomerular vessels (69.2%), yellow crusts (56.8%), focal hemorrhage (55.5%), focal/multifocal hypopigmentation (44.5%), and linear irregular vessels (42.5%). Besides, we found two new dermoscopic signs in BD: the double-edge sign (30.1%) and the clusters of brown structureless areas (38.4%).

CONCLUSION

Bowen's disease presents a variety of dermoscopic features. The recognition of two new dermoscopic signs of BD and fully understanding its dermoscopic features will help us in differential diagnosis.

Dermoscopic Clues for Diagnosing Melanomas That Resemble Seborrheic Keratosis

Importance

Melanomas that clinically mimic seborrheic keratosis (SK) can delay diagnosis and adequate treatment. However, little is known about the value of dermoscopy in recognizing these difficult-to-diagnose melanomas.

Objective

To describe the dermoscopic features of SK-like melanomas to understand their clinical morphology.

Design, Setting, and Participants

This observational retrospective study used 134 clinical and dermoscopic images of histopathologically proven melanomas in 134 patients treated in 9 skin cancer centers in Spain, France, Italy, and Austria. Without knowledge that the definite diagnosis for all the lesions was melanoma, 2 dermoscopy-trained observers evaluated the clinical descriptions and 48 dermoscopic features (including all melanocytic and nonmelanocytic criteria) of all 134 images and classified each dermoscopically as SK or not SK. The total dermoscopy score and the 7-point checklist score were assessed. Images of the lesions and patient data were collected from July 15, 2013, through July 31, 2014.

Main Outcomes and Measures

Frequencies of specific morphologic patterns of (clinically and dermoscopically) SK-like melanomas, patient demographics, and interobserver agreement of criteria were evaluated.

Results

Of the 134 cases collected from 72 men and 61 women, all of whom were white and who had a mean (SD) age of 55.6 (17.5) years, 110 (82.1%) revealed dermoscopic features suggestive of melanoma, including pigment network (74 [55.2%]), blue-white veil (72 [53.7%]), globules and dots (68 [50.7%]), pseudopods or streaks (47 [35.1%]), and blue-black sign (43 [32.3%]). The remaining 24 cases (17.9%) were considered likely SKs, even by dermoscopy. Overall, lesions showed a scaly and hyperkeratotic surface (45 [33.6%]), yellowish keratin (42 [31.3%]), comedo-like openings (41 [30.5%]), and milia-like cysts (30 [22.4%]). The entire sample achieved a mean (SD) total dermoscopy score of 4.7 (1.6) and a 7-point checklist score of 4.4 (2.3), while dermoscopically SK-like melanomas achieved a total dermoscopy score of only 4.2 (1.3) and a 7-point checklist score of 2.0 (1.9), both in the range of benignity. The most helpful criteria in correctly diagnosing SK-like melanomas were the presence of blue-white veil, pseudopods or streaks, and pigment network. Multivariate analysis found only the blue-black sign to be significantly associated with a correct diagnosis, while hyperkeratosis and fissures and ridges were independent risk markers of dermoscopically SK-like melanomas.

Conclusions and Relevance

Seborrheic keratosis-like melanomas can be dermoscopically challenging, but the presence of the blue-black sign, pigment network, pseudopods or streaks, and/or blue-white veil, despite the presence of other SK features, allows the correct diagnosis of most of the difficult melanoma cases.

Dermatofibroma simulating seborrheic keratosis dermoscopically

Dermatofibroma is a frequent benign tumor of easy clinical diagnosis in most cases, but that can mimic other dermatoses. Dermoscopy may help to define the diagnosis and its classical pattern is a central white area, similar to a scar, surrounded by a discrete pigment network. However, dermoscopic findings are not always typical. We describe here a case of dermatofibroma exhibiting ridges, furrows and pseudocomedos, a pattern which is typical of seborrheic keratosis, in dermoscopy.

Standardization of terminology in dermoscopy/dermatoscopy: Results of the third consensus conference of the International Society of Dermoscopy

BACKGROUND

Evolving dermoscopic terminology motivated us to initiate a new consensus.

OBJECTIVE

We sought to establish a dictionary of standardized terms.

METHODS

We reviewed the medical literature, conducted a survey, and convened a discussion among experts.

RESULTS

Two competitive terminologies exist, a more metaphoric terminology that includes numerous terms and a descriptive terminology based on 5 basic terms. In a survey among members of the International Society of Dermoscopy (IDS) 23.5% (n = 201) participants preferentially use descriptive terminology, 20.1% (n = 172) use metaphoric terminology, and 484 (56.5%) use both. More participants who had been initially trained by metaphoric terminology prefer using descriptive terminology than vice versa (9.7% vs 2.6%, P < .001). Most new terms that were published since the last consensus conference in 2003 were unknown to the majority of the participants. There was uniform consensus that both terminologies are suitable, that metaphoric terms need definitions, that synonyms should be avoided, and that the creation of new metaphoric terms should be discouraged. The expert panel proposed a dictionary of standardized terms taking account of metaphoric and descriptive terms.

LIMITATIONS

A consensus seeks a workable compromise but does not guarantee its implementation.

CONCLUSION

The new consensus provides a revised framework of standardized terms to enhance the consistent use of dermoscopic terminology.

Unusual Dermoscopic Patterns of Seborrheic Keratosis

BACKGROUND

Seborrheic keratoses (SKs) may sometimes mimic benign and malignant skin tumors, and a biopsy can be necessary in order to rule out malignancy.

METHODS

From the database of our pigmented lesion clinic, we evaluated the dermoscopic features of difficult-to-diagnose SKs that were biopsied between January 2010 and December 2014.

RESULTS

SKs represented 3.8% of all excised lesions (161/ 4,182). Specifically, 91 (56.5%) were excised to rule out melanoma, 63 (39.1%) to rule out squamous cell carcinoma and 7 (4.4%) to rule out basal cell carcinoma. The following 10 global dermoscopic patterns were identified: multicomponent (32; 19.9%); reticular (24; 14.9%), characterized by an irregular pigment network; bowenoid (21; 13.0%); hairpin (19; 11.8%); keratoacanthoma-like (16; 9.9%); blue-nevus-like (15; 9.3%); lichenoid (6; 3.7%); hyperkeratotic (6; 3.7%); clonal (5; 3.1%); spitzoid (5; 3.1%). Furthermore, 12 SKs (7.5%) were not included in any of such patterns (not classified).

CONCLUSION

Our results are in line with previous studies highlighting the dermoscopic variability of SKs. Although excised SKs may be classified into 1 of 10 repetitive dermoscopic patterns, a biopsy remains mandatory for those that cannot be clearly differentiated from common skin malignancies.