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Background: Lentigo maligna (LM) can mimic benign, flat, pigmented lesions and can be challenging to diagnose., Objective: To describe a new dermatoscopic feature termed "perifollicular linear projections (PLP)" as a diagnostic criterion for LM on the face., Methods: Retrospective study on reflectance confocal microscopy and dermatoscopy images of flat facial pigmented lesions originating from 2 databases. PLP were defined as short, linear, pigmented projections emanating from hair follicles. Dermatoscopy readers were blinded to the final histopathologic diagnosis., Results: From 83 consecutive LMs, 21/83 (25.3%) displayed "bulging of hair follicles" on reflectance confocal microscopy and 18 of these 21 (85.7%), displayed PLP on dermatoscopy. From a database of 2873 consecutively imaged and biopsied lesions, 252 flat-pigmented facial lesions were included. PLP was seen in 47/76 melanomas (61.8%), compared with 7/176 lesions (3.9%) with other diagnosis (P < .001). The sensitivity was 61.8% (95% CI, 49.9%-72.7%), specificity 96.0% (95% CI, 92.9%-98.4%). PLP was independently associated with LM diagnosis on multivariate analysis (OR 26.1 [95% CI, 9.6%-71.0])., Limitations: Retrospective study., Conclusion: PLP is a newly described dermatoscopic criterion that may add specificity and sensitivity to the early diagnosis of LM located on the face. We postulate that PLP constitutes an intermediary step in the LM progression model., Competing Interests: Conflicts of interest None disclosed., (Copyright © 2023 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Facial skin is characterized by high density of follicles. Facial neoplasms may present overlapping clinical and dermoscopic findings. Our goal was to evaluate and compare, via reflectance confocal microscopy (RCM), follicular involvement in facial neoplasms., Methods: We retrospectively searched our image database, between January 2008 and December 2020, for all facial lesions with (1) a standardized set of clinical, dermoscopic, and RCM images, and (2) a biopsy-proven diagnosis of lentigo maligna/lentigo maligna melanoma (LM/LMM, n = 39), basal cell carcinoma (BCC, n = 51), squamous cell carcinoma in situ (SCCIS, n = 5), actinic keratosis (AK, n = 11), and lichen-planus-like keratosis (LPLK, n = 18). Two readers jointly evaluated the RCM images for a set of predefined features of follicular involvement., Results: Diffuse obliteration of follicles was frequent in BCC (88%), while follicular infiltration by refractile dendritic cells and/or by bright round nucleated cells was common in melanoma (90% and 44%, respectively). Extension of atypical keratinocytes down follicles was more prominent among SCCIS than AK (80% vs. 45%, p = 0.01). In most LPLK (89%), there was follicular sparing., Conclusions: Evaluation of RCM criteria centering on the follicles can be useful in the differential diagnosis between common facial neoplasms., (© 2022 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: Patients with lesions suspicious for skin cancer often present to primary care physicians (PCPs), who may have limited training in skin cancer diagnosis., Objective: To measure the impact of an adjunctive handheld device for PCPs that employs elastic scattering spectroscopy (ESS) on the diagnosis and management of skin cancer., Methods: Fifty-seven PCPs evaluated 50 clinical images of skin lesions (25 malignant and 25 benign), first without and then with knowledge of the handheld ESS device output, and in each case indicated if a lesion was likely to be benign or malignant., Results: The diagnostic sensitivity of the PCPs with and without the use of the ESS device was 88% (95% CI, 84%-92%) and 67% (95% CI, 62%-72%), respectively ( P  < .0001). In contrast, no significant difference was observed in the diagnostic specificity. The management sensitivity of the physicians with and without the use of the ESS device was 94% (95% CI, 91%-96%) and 81% (95% CI, 77%-85%), respectively ( P  = .0009). Similarly, no significant difference was observed in the management specificity., Conclusion: The use of the ESS device may have the potential to help improve skin cancer diagnosis and confidence in management decision-making in a primary care setting., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Todd Thames and Thomaz de Campos Silva are advisors for DermaSensor, Inc. Laura Korb Ferris is a consultant for DermTech and an investigator for Castle Biosciences, SkinAnalytics, and DermTech.

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., (Copyright © 2020 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Background: Melanoma in situ and dysplastic nevi with severe atypia present overlapping histopathologic features. Reflectance confocal microscopy findings can be integrated with the dermatopathology report to improve differentiation between melanoma and dysplastic nevi with severe atypia., Objective: To compare prevalence of reflectance confocal microscopy findings between melanoma in situ and dysplastic nevi with severe atypia., Methods: This retrospective observational study compared reflectance confocal microscopy findings in dermatopathologically diagnosed dysplastic nevi with severe atypia and melanoma in situ, collected between 2007 and 2017 at a private pigmented-lesion clinic. Concordant pathologic diagnosis was defined as unanimous agreement between 3 dermatopathologists who independently reviewed all cases; all other cases were classified as discordant., Results: The study included 112 lesions, 62 concordant melanomas in situ, 28 concordant dysplastic nevi with severe atypia, and 22 discordant lesions. In comparing reflectance confocal microscopy findings in concordant cases, melanoma in situ showed more frequently than dysplastic nevi with severe atypia the presence of epidermal atypical melanocytes as round cells (19/62 vs 0/28; P < .001) and dendritic cells (50/62 vs 6/28; P < .001), as well as a diffuse distribution of epidermal atypical melanocytes (50/54 vs 3/6; P = .002). In contrast, dysplastic nevi with severe atypia showed the presence of dense melanocytic nests more frequently than melanoma in situ did (15/28 vs 14/62; P = .003)., Limitations: The study was based on a limited number of lesions originating from a single clinic., Conclusions: Reflectance confocal microscopy findings may help differentiate a subset of dysplastic nevi with severe atypia from melanoma in situ., (Copyright © 2020 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Although histopathology is the time-honored gold standard diagnostic measure in dermatology, several factors may detract from an accurate microscopic diagnosis. Limiting factors include: human error, suboptimal biopsy-site selection or biopsy technique, and inherent restrictions of vertical tissue sectioning that lead to incomplete microscopic evaluation of the lesion. Reflectance confocal microscopy (RCM) is a non-invasive imaging tool that allows for the cellular-level examination of the lesion, at a horizontal plane, which may complement the subsequent vertical histopathological tissue examination. Herein, we report a case series whereby prebiopsy RCM examination enhanced the accuracy of histopathological diagnosis or allowed for a critical appraisal of initial histopathological misdiagnosis., (© 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

This paper presents an approach that combines conventional image processing with deep learning by fusing the features from the individual techniques. We hypothesize that the two techniques, with different error profiles, are synergistic. The conventional image processing arm uses three handcrafted biologically inspired image processing modules and one clinical information module. The image processing modules detect lesion features comparable to clinical dermoscopy information-atypical pigment network, color distribution, and blood vessels. The clinical module includes information submitted to the pathologist-patient age, gender, lesion location, size, and patient history. The deep learning arm utilizes knowledge transfer via a ResNet-50 network that is repurposed to predict the probability of melanoma classification. The classification scores of each individual module from both processing arms are then ensembled utilizing logistic regression to predict an overall melanoma probability. Using cross-validated results of melanoma classification measured by area under the receiver operator characteristic curve (AUC), classification accuracy of 0.94 was obtained for the fusion technique. In comparison, the ResNet-50 deep learning based classifier alone yields an AUC of 0.87 and conventional image processing based classifier yields an AUC of 0.90. Further study of fusion of conventional image processing techniques and deep learning is warranted.

Background: Melanoma remains a challenge to diagnose, especially when appearing on the background of chronically sun-damaged skin (CSDS). Our goal was to identify and quantify the reflectance confocal microscopy (RCM) features of melanoma on non-facial CSDS., Methods: Included lesions were biopsy-proven melanomas, from anatomic sites other than the face, neck, scalp and acral skin, with histopathologic finding of solar elastosis in the underlying dermis. All included lesions underwent clinical, dermoscopic and RCM imaging, obtained in a standardized fashion, prior to biopsy. All images were retrospectively analyzed by four observers., Results: We identified 33 melanomas from 33 patients with 63.6% male patients and overall mean age of 72.8 years. The salient RCM features included an atypical honeycomb or disarranged epidermal pattern (81.8%), pagetoid infiltration of the epidermis by both round and/or dendritic melanocytes (100%), focal proliferation of predominantly dendritic melanocytes as sheets (78.8%), foci with non-edged papillae (84.8%), junctional thickening (60.6%), areas of irregular ring or meshwork pattern (78.8%), and underlying thickened collagen bundles (51.5%)., Conclusion: Non-facial CSDS melanomas share features similar to other melanoma types including pagetoid cells and non-edged papillae. The focal proliferation of dendritic pagetoid cells in sheets is similar to that seen in facial CSDS melanomas., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background: Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking., Methods: Google's Inception v4 CNN architecture was trained and validated using dermoscopic images and corresponding diagnoses. In a comparative cross-sectional reader study a 100-image test-set was used (level-I: dermoscopy only; level-II: dermoscopy plus clinical information and images). Main outcome measures were sensitivity, specificity and area under the curve (AUC) of receiver operating characteristics (ROC) for diagnostic classification (dichotomous) of lesions by the CNN versus an international group of 58 dermatologists during level-I or -II of the reader study. Secondary end points included the dermatologists' diagnostic performance in their management decisions and differences in the diagnostic performance of dermatologists during level-I and -II of the reader study. Additionally, the CNN's performance was compared with the top-five algorithms of the 2016 International Symposium on Biomedical Imaging (ISBI) challenge., Results: In level-I dermatologists achieved a mean (±standard deviation) sensitivity and specificity for lesion classification of 86.6% (±9.3%) and 71.3% (±11.2%), respectively. More clinical information (level-II) improved the sensitivity to 88.9% (±9.6%, P = 0.19) and specificity to 75.7% (±11.7%, P < 0.05). The CNN ROC curve revealed a higher specificity of 82.5% when compared with dermatologists in level-I (71.3%, P < 0.01) and level-II (75.7%, P < 0.01) at their sensitivities of 86.6% and 88.9%, respectively. The CNN ROC AUC was greater than the mean ROC area of dermatologists (0.86 versus 0.79, P < 0.01). The CNN scored results close to the top three algorithms of the ISBI 2016 challenge., Conclusions: For the first time we compared a CNN's diagnostic performance with a large international group of 58 dermatologists, including 30 experts. Most dermatologists were outperformed by the CNN. Irrespective of any physicians' experience, they may benefit from assistance by a CNN's image classification., Clinical Trial Number: This study was registered at the German Clinical Trial Register (DRKS-Study-ID: DRKS00013570; https://www.drks.de/drks&#95;web/).

The clinical diagnosis of tumors on the curved surfaces of the face, around the eyes, and on the mucosal surfaces can be difficult, while biopsies and excisions can have functional and aesthetic consequences. To avoid unnecessary surgery, clinicians have been aiming to attain accurate noninvasive diagnosis of lesions at these sites. However, acquisition of high-quality images with dermoscopy and with traditional wide-probe reflectance confocal microscopy (WP-RCM) have been hampered with technical difficulties. This article discusses the technical parameters of the handheld reflectance confocal microscope and discusses its advantages and limitations compared with the WP-RCM., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Importance: Reflectance confocal microscopy (RCM) studies have been performed to identify criteria for diagnosis of skin neoplasms. However, RCM-based diagnosis is operator dependent. Hence, reproducibility of RCM criteria needs to be tested., Objective: To test interobserver reproducibility of recognition of previously published RCM descriptors and accuracy of RCM-based skin cancer diagnosis., Design, Setting, and Participants: Observational retrospective web-based study of a set of RCM images collected at a tertiary academic medical center. Nine dermatologists (6 of whom had ≥3 years of RCM experience) from 6 countries evaluated an RCM study set from 100 biopsy-proven lesions, including 55 melanocytic nevi, 20 melanomas, 15 basal cell carcinomas, 7 solar lentigines or seborrheic keratoses, and 3 actinic keratoses. Between June 15, 2010, and October 21, 2010, participanting dermatologists, blinded to histopathological diagnosis, evaluated 3 RCM mosaic images per lesion for the presence of predefined RCM descriptors., Main Outcomes and Measures: The main outcome was identification of RCM descriptors with fair to good interrater agreement (κ statistic, ≥0.3) and independent correlation with malignant vs benign diagnosis on discriminant analysis. Additional measures included sensitivity and specificity for diagnosis of malignant vs benign for each evaluator, for majority diagnosis (rendered by ≥5 of 9 evaluators), and for experienced vs recent RCM users., Results: Eight RCM descriptors showed fair to good reproducibility and were independently associated with a specific diagnosis. Of these, the presence of pagetoid cells, atypical cells at the dermal-epidermal junction, and irregular epidermal architecture were associated with melanoma. Aspecific junctional pattern, basaloid cords, and ulceration were associated with basal cell carcinomas. Ringed junctional pattern and dermal nests were associated with nevi. The mean sensitivity for the group of evaluators was 88.9% (range, 82.9%-100%), and the mean specificity was 79.3% (range, 69.2%-90.8%). Majority diagnosis showed sensitivity of 100% and specificity of 80.0%. Sensitivity was higher for experienced vs recent RCM users (91.0% vs. 84.8%), but specificity was similar (80.0% vs. 77.9%)., Conclusions and Relevance: The study highlights key RCM diagnostic criteria for melanoma and basal cell carcinoma that are reproducibly recognized among RCM users. Diagnostic accuracy increases with experience. The higher accuracy of majority diagnosis suggests that there is intrinsically more diagnostic information in RCM images than is currently used by individual evaluators.

Reflectance confocal microscopy (RCM) offers high-resolution, noninvasive skin imaging and can help avoid obtaining unnecessary biopsy specimens. It can also increase efficiency in the surgical setting by helping to delineate tumor margins. Diagnostic criteria and several RCM algorithms have been published for the differentiation of benign and malignant neoplasms. We provide an overview of the basic principles of RCM, characteristic RCM features of normal skin and cutaneous neoplasms, and the limitations and future directions of RCM., (Copyright © 2015 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.)

Fuzzy logic image analysis techniques were used to analyze three shades of blue (lavender blue, light blue, and dark blue) in dermoscopic images for melanoma detection. A logistic regression model provided up to 82.7% accuracy for melanoma discrimination for 866 images. With a support vector machines (SVM) classifier, lower accuracy was obtained for individual shades (79.9-80.1%) compared with up to 81.4% accuracy with multiple shades. All fuzzy blue logic alpha cuts scored higher than the crisp case. Fuzzy logic techniques applied to multiple shades of blue can assist in melanoma detection. These vector-based fuzzy logic techniques can be extended to other image analysis problems involving multiple colors or color shades., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Importance: Nodular melanoma (NM) is a rapidly progressing potentially lethal skin tumor for which early diagnosis is critical., Objective: To determine the dermoscopy features of NM., Design: Eighty-three cases of NM, 134 of invasive non-NM, 115 of nodular benign melanocytic tumors, and 135 of nodular nonmelanocytic tumors were scored for dermoscopy features using modified and previously described methods. Lesions were separated into amelanotic/hypomelanotic or pigmented to assess outcomes., Setting: Predominantly hospital-based clinics from 5 continents., Main Outcome Measures: Sensitivity, specificity, and odds ratios for features/models for the diagnosis of melanoma., Results: Nodular melanoma occurred more frequently as amelanotic/hypomelanotic (37.3%) than did invasive non-NM (7.5%). Pigmented NM had a more frequent (compared with invasive non-NM; in descending order of odds ratio) symmetrical pigmentation pattern (5.8% vs 0.8%), large-diameter vessels, areas of homogeneous blue pigmentation, symmetrical shape, predominant peripheral vessels, blue-white veil, pink color, black color, and milky red/pink areas. Pigmented NM less frequently displayed an atypical broadened network, pigment network or pseudonetwork, multiple blue-gray dots, scarlike depigmentation, irregularly distributed and sized brown dots and globules, tan color, irregularly shaped depigmentation, and irregularly distributed and sized dots and globules of any color. The most important positive correlating features of pigmented NM vs nodular nonmelanoma were peripheral black dots/globules, multiple brown dots, irregular black dots/globules, blue-white veil, homogeneous blue pigmentation, 5 to 6 colors, and black color. A model to classify a lesion as melanocytic gave a high sensitivity (>98.0%) for both nodular pigmented and nonnodular pigmented melanoma but a lower sensitivity for amelanotic/hypomelanotic NM (84%). A method for diagnosing amelanotic/hypomelanotic malignant lesions (including basal cell carcinoma) gave a 93% sensitivity and 70% specificity for NM., Conclusions and Relevance: When a progressively growing, symmetrically patterned melanocytic nodule is identified, NM needs to be excluded.

Background: A series of studies has investigated epidemiological, clinical and genetic characteristics of patients with multiple primary melanoma (MPM). However, comparison of the clinical and dermoscopic features of MPM within a given individual has been described only in case reports., Objectives: To describe the dermoscopic features of MPM for each given patient, and to evaluate the characteristics eventually associated with similar or dissimilar appearance., Methods: From the databases of three skin-lesion clinics in the U.S.A., Italy and Spain we collected the dermoscopic images of melanomas in patients diagnosed with MPM., Results: Among 58 patients with MPM, we found that 53% of patients had dermoscopically similar melanomas and 47% of patients had dermoscopically different melanomas. In older patients 59% of melanomas were dermoscopically similar vs. 47% in younger patients (P=0·377). Similar thickness was associated with the occurrence of dermoscopically similar melanomas (19/30 cases, 63%; P=0·039). Most (65%) of the synchronous lesions were similar, compared with 36% of nonsynchronous lesions (P=0·029), and most (69%) of the melanomas on sun-damaged skin were similar, vs. 37% of melanomas on nonsun-damaged skin (P=0·015; odds ratio 3·88, 95% confidence interval 1·11-13·98). The percentage of dermoscopically different melanomas was higher in patients with a family history of melanoma (67% vs. 48%)., Conclusions: MPMs in a given patient have almost the same chance of looking dermoscopically similar or different. However, a subset of elderly patients with sun-damaged skin may present multiple, similar, thin melanomas characterized by pigment-network and regression structures., (© 2013 The Authors. BJD © 2013 British Association of Dermatologists.)

Background: The negative pigment network (NPN) is seen as a negative of the pigmented network and it is purported to be a melanoma-specific structure., Objectives: We sought to assess the frequency, sensitivity, specificity, and odds ratios (ORs) of NPN between melanoma cases and a group of control lesions., Methods: Digitalized images of skin lesions from 679 patients with histopathological diagnosis of dermatofibroma (115), melanocytic nevus (220), Spitz nevus (139), and melanoma (205) were retrospectively collected and blindly evaluated to assess the presence/absence of NPN., Results: The frequency of occurrence of NPN was higher in the melanoma group (34.6%) than in Spitz nevus (28.8%), melanocytic nevus (18.2%), and dermatofibroma (11.3%) groups. An OR of 1.8 emerged for the diagnosis of melanoma in the presence of NPN as compared with nonmelanoma diagnosis. Conversely, for melanocytic nevi and dermatofibromas the OR was very low (0.5 and 0.3, respectively). For Spitz nevi the OR of 1.1 was not statistically significant. When comparing melanoma with dermatofibroma, melanocytic nevus, and Spitz nevus, we observed a significantly higher frequency of multicomponent pattern (68.1%), asymmetric pigmentation (92.9%), irregularly distributed NPN (87.3%), and peripheral location of NPN (66.2%) in melanomas., Limitations: Further studies can provide the precise dermoscopic-histopathologic correlation of NPN in melanoma and other lesions., Conclusions: The overall morphologic pattern of NPN, such as the irregular distribution and the peripheral location of NPN, along with the multicomponent pattern and the asymmetric pigmentation could be used as additional features in distinguishing melanoma from Spitz nevus and other benign lesions., (Copyright © 2012 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.)

Background: Most studies on dermoscopy of acral lesions were conducted in Asian populations. In this study, we analyzed these features in a predominantly Caucasian population., Objective: Estimate the prevalence of dermoscopic features in acral lesions, and assess their level of agreement between observers., Methods: In this retrospective multicenter study, 167 acral lesions (66 melanomas) were evaluated for 13 dermoscopic patterns by 26 physicians, via a secured Internet platform., Results: Parallel furrow pattern, bizarre pattern, and diffuse pigmentation with variable shades of brown had the highest prevalence. The agreement for lesion patterns between physicians was variable. Agreement was dependent on the level of diagnostic difficulty., Conclusion: Lesions with a diameter >1 cm were more likely to be melanoma. We found as well that a benign pattern can be seen in parts of melanomas. For this reason one should evaluate an acral lesion for the presence of malignant patterns first.

Background: Studies have shown that the incidence of melanoma in situ (MIS) is increasing significantly., Objective: This study analyzes selected clinical and demographic characteristics of MIS cases observed in private dermatology practices in the United States., Methods: This study collected 257 MIS cases from 4 private dermatology practices in the United States from January 2005 through December 2009, recording age, gender, anatomic location, lesion size, patient-reported change in lesion, and concern about lesion. Case totals for invasive melanoma during the same period were recorded., Results: The data collected showed a higher incidence of MIS in sun-exposed areas of older patients, especially men. The median age of patients at the time of MIS detection was 69 years. The most common site for MIS was the head-neck region. The number of MIS cases collected exceeded the number of invasive malignant melanoma cases during the study period, with an observed ratio of 1.35:1., Limitations: For 136 patients, data were collected retrospectively for lesion size, location, gender, and age. For these patients, patient-reported change in lesion and concern about lesion were not collected. Patients often did not consent to a full body examination, therefore, it is possible that MIS lesions may have been missed in double-clothed areas., Conclusion: Careful attention to pigmented lesions, even lesions less than 4 mm, on sun-exposed areas, including scalp, trunk, and feet, will facilitate earlier diagnosis of MIS. As only 30.4% of male patients and 50% of female patients had concern about these lesions, it still falls to the dermatologist to discover MIS., (Copyright © 2011 American Academy of Dermatology, Inc. All rights reserved.)

Background: The 'gold standard' for the diagnosis of melanocytic lesions is dermatopathology. Although most of the diagnostic criteria are clearly defined, the interpretation of histopathology slides may be subject to interobserver variability., Objectives: The aim of this study was to determine the variability among dermatopathologists in the interpretation of clinically difficult melanocytic lesions., Methods: This study used the database of MelaFind®, a computer-vision system for the diagnosis of melanoma. All lesions were surgically removed and sent for independent evaluation by four dermatopathologists. Agreement was calculated using kappa statistics., Results: A total of 1,249 pigmented melanocytic lesions were included. There was a substantial agreement among expert dermatopathologists: two-category kappa was 0.80 (melanoma vs. non-melanoma) and three-category kappa was 0.62 (malignant vs. borderline vs. benign melanocytic lesions). The agreement was significantly greater for patients ≥40 years (three-category kappa = 0.67) than for younger patients (kappa = 0.49). In addition, the agreement was significantly lower for patients with atypical mole syndrome (AMS) (kappa = 0.31) than for patients without AMS (kappa = 0.76)., Limitations: The data were limited by the inclusion/exclusion criteria of the MelaFind® study. This might represent a selection bias. The agreement was evaluated using kappa statistics. This is a standard method for evaluating agreement among pathologists, but might be considered controversial by some statisticians., Conclusions: Expert dermatopathologists have a high level of agreement when diagnosing clinically difficult melanocytic lesions. However, even among expert dermatopathologists, the current 'gold standard' is not perfect. Our results indicate that lesions from younger patients and patients with AMS may be more problematic for the dermatopathologists, suggesting that improved diagnostic criteria are needed for such patients., (Copyright © 2012 S. Karger AG, Basel.)

Background: Seborrheic keratoses are the most common skin lesions known to contain small white or yellow structures called milia-like cysts (MLCs). Varied appearances can sometimes make it difficult to differentiate benign lesions from malignant lesions such as melanoma, the deadliest form of skin cancer found in humans., Objective: The purpose of this study was to determine the statistical occurrence of MLCs in benign vs. malignant lesions., Methods: A medical student with 10 months experience in examining approximately 1000 dermoscopy images and a dermoscopy-naïve observer analysed contact non-polarized dermoscopy images of 221 malignant melanomas and 175 seborrheic keratoses for presence of MLCs., Results: The observers found two different types of MLCs present: large ones described as cloudy and smaller ones described as starry. Starry MLCs were found to be prevalent in both seborrheic keratoses and melanomas. Cloudy MLCs, however, were found to have 99.1% specificity for seborrheic keratoses among this group of seborrheic keratoses and melanomas., Conclusion: Cloudy MLCs can be a useful tool for differentiating between seborrheic keratoses and melanomas., (© 2010 The Authors. Journal of the European Academy of Dermatology and Venereology © 2010 European Academy of Dermatology and Venereology.)

Granularity, also called peppering and multiple blue-grey dots, is defined as an accumulation of tiny, blue-grey granules in dermoscopy images. Granularity is most closely associated with a diagnosis of malignant melanoma. This study analyzes areas of granularity with color and texture measures to discriminate granularity in melanoma from similar areas in non-melanoma skin lesions. The granular areas in dermoscopy images of 74 melanomas and 14 melanomas in situ were identified and manually selected. For 200 non-melanoma dermoscopy images, those areas which most closely resembled granularity in color and texture were similarly selected. Ten texture and twenty-two color measures were studied. The texture measures consisted of the average and range of energy, inertia, correlation, inverse difference, and entropy. The color measures consisted of absolute and relative RGB averages, absolute and relative RGB chromaticity averages, absolute and relative G/B averages, CIE X, Y, Z, X/Y, X/Z and Y/Z averages, R variance, and luminance. These measures were calculated for each granular area of the melanomas and the comparable areas in the non-melanoma images. Receiver operating characteristic (ROC) curve analysis showed that the best separation of melanoma images from non-melanoma images by granular area features was obtained with a combination of color and texture measures. Comparison of ROC results showed greater separation of melanoma from benign lesions using relative color than using absolute color. Statistical analysis showed that the four most significant measures of granularity in melanoma are two color measures and two texture measures averaged over the spots: relative blue, relative green, texture correlation, and texture energy range. The best feature set, utilizing texture and relative color measures, achieved an accuracy of 96.4% based on area under the receiver operating characteristic curve., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

Objective: To identify and analyze subtypes of globules based on size, shape, network connectedness, pigmentation, and distribution to determine which globule types and globule distributions are most frequently associated with a diagnosis of malignant melanoma., Design: Retrospective case series of dermoscopy images with globules., Setting: Private dermatology practices., Participants: Patients in dermatology practices. Intervention Observation only. Main Outcome Measure Association of globule types with malignant melanoma., Results: The presence of large globules (odds ratio [OR], 5.25) and globules varying in size (4.72) or shape (5.37) had the highest ORs for malignant melanoma among all globule types and combinations studied. Classical globules (dark, discrete, convex, and 0.10-0.20 mm) had a higher risk (OR, 4.20) than irregularly shaped globules (dark, discrete, and not generally convex) (2.89). Globules connected to other structures were not significant in the diagnosis of malignant melanoma. Of the different configurations studied, asymmetric clusters have the highest risk (OR, 3.02)., Conclusions: The presence of globules of varying size or shape seems to be more associated with a diagnosis of malignant melanoma than any other globule type or distribution in this study. Large globules are of particular importance in the diagnosis of malignant melanoma.

Reflectance confocal microscopy (RCM) allows noninvasive imaging of the epidermis and superficial dermis. Like dermoscopy, RCM acquires images in the horizontal plane (en face), allowing assessment of tissue pathology underlying dermoscopic structures of interest at a cellular-level resolution. Thus, clinicians using dermoscopy may find RCM to be particularly useful. Our aim was to show the value of RCM for diagnosis and management decisions related to pigmented and nonpigmented skin neoplasms seen in daily practice. Six cases of clinically and dermoscopically equivocal skin lesions, for which RCM facilitated making the correct diagnosis, are presented. Final diagnoses were made based on histopathologic analysis. Three flat pigmented skin lesions with dermoscopic signs of regression showed distinct RCM features that allowed their correct classification as pigmented basal cell carcinoma, pigmented actinic keratosis, and melanoma on sun-damaged skin. A flat nonpigmented skin lesion on the face, which did not show distinct clinical or dermoscopic features, was correctly diagnosed as basal cell carcinoma based on RCM findings. In addition, the response of a pigmented actinic keratosis and a melanoma in situ on sun-damaged skin to noninvasive topical treatment was monitored using RCM. RCM is a promising and practical imaging tool for the diagnosis and follow-up of pigmented and nonpigmented skin lesions.

Dermoscopy has been described as a useful tool for the early diagnosis of melanoma and the differential diagnosis of pigmented lesions of the skin. This has been proven by three independent meta analyses of the literature. Dermoscopy is a fast evolving field with a high number of new publications every year. Initially, the use of dermoscopy was limited to pigmented lesions, but it is used more and more in other situations. It has become an important tool for the diagnosis of nail pigmentations, hair and scalp disorders, and so forth. In this article we try to provide an update on recent trends and developments in dermoscopy.

Objective: To determine the predictive dermoscopic features of amelanotic and hypomelanotic melanoma., Design: A total of 105 melanomas (median Breslow thickness, 0.76 mm), 170 benign melanocytic lesions, and 222 nonmelanocytic lesions lacking significant pigment (amelanotic, partially pigmented, and light colored) were imaged using glass-plate dermoscopy devices and scored for 99 dermoscopic features. Diagnostic models were derived from and tested on independent randomly selected lesions., Setting: Predominantly hospital-based clinics from 5 continents., Main Outcome Measures: Sensitivity, specificity, and odds ratios for individual features and models for the diagnosis of melanoma and malignancy., Results: The most significant negative predictors of melanoma were having multiple (>3) milialike cysts (odds ratio, 0.09; 95% confidence interval, 0.01-0.64), comma vessels with a regular distribution (0.10; 0.01-0.70), comma vessels as the predominant vessel type (0.16; 0.05-0.52), symmetrical pigmentation pattern (0.18; 0.09-0.39), irregular blue-gray globules (0.20; 0.05-0.87), and multiple blue-gray globules (0.28; 0.10-0.81). The most significant positive predictors were having a blue-white veil (odds ratio,13; 95% confidence interval, 3.9-40.0), scarlike depigmentation (4.4; 2.4-8.0), multiple blue-gray dots (3.5; 1.9-6.4), irregularly shaped depigmentation (3.3; 2.0-5.3), irregular brown dots/globules (3.2; 1.8-5.6), 5 to 6 colors (3.2; 1.6-6.3), and predominant central vessels (3.1; 1.6-6.0). A simple model distinguishing melanomas from all nonmelanomas had a sensitivity of 70% and a specificity of 56% in the test set. A model distinguishing all malignant lesions from benign lesions had a sensitivity of 96% and a specificity of 37%. Conclusion Although the diagnostic accuracy of dermoscopy for melanoma lacking significant pigment is inferior to that of more pigmented lesions, features distinguishing the former from benign lesions can be visualized on dermoscopic evaluation.

Objective: To evaluate the performance of dermoscopists in diagnosing small pigmented skin lesions (diameter

Background: The presence of multiple blue-grey dots (MBGD) is widely used by clinicians to decide if a pigmented lesion should be removed, but only little is known about their significance., Objectives: To evaluate the significance of MBGD for the dermoscopic diagnosis of melanoma., Methods: In part 1 we retrospectively evaluated 340 pigmented lesions for the presence and morphological appearance of granularity. One hundred and seventy melanomas were included and matched with 170 benign and dysplastic naevi which were randomly chosen from our collection. In part 2, 3773 lesions were examined prospectively in at-risk patients: all lesions with granularity were recorded, surgically removed and subjected to histopathological examination., Results: In part 1, granularity was found in 26.5% of the benign lesions and 93.5% of melanomas. The presence of granularity, granularity at the periphery, irregularly distributed granularity and granularity in association with red and white colour were statistically highly significant for the diagnosis of melanoma (P < 0.001). In part 2, granularity was found in 1.08% of the 3773 lesions and more frequently in sun-damaged skin. Sensitivity for the diagnosis of melanoma was 85% and specificity 99%., Conclusions: After the revision of many lesions with MBGD, we concluded that the term 'granularity' better describes this entity. Lesions with irregular granularity (periphery, irregularly distributed) should be removed especially if they are associated with red, blue or white colour. Lesions with a benign dermoscopy pattern which have granularity with a regular appearance and involving only a small portion of the lesion do not require surgical excision.

Objective: To describe the diagnostic performance of SolarScan (Polartechnics Ltd, Sydney, Australia), an automated instrument for the diagnosis of primary melanoma., Design: Images from a data set of 2430 lesions (382 were melanomas; median Breslow thickness, 0.36 mm) were divided into a training set and an independent test set at a ratio of approximately 2:1. A diagnostic algorithm (absolute diagnosis of melanoma vs benign lesion and estimated probability of melanoma) was developed and its performance described on the test set. High-quality clinical and dermoscopy images with a detailed patient history for 78 lesions (13 of which were melanomas) from the test set were given to various clinicians to compare their diagnostic accuracy with that of SolarScan., Setting: Seven specialist referral centers and 2 general practice skin cancer clinics from 3 continents. Comparison between clinician diagnosis and SolarScan diagnosis was by 3 dermoscopy experts, 4 dermatologists, 3 trainee dermatologists, and 3 general practitioners., Patients: Images of the melanocytic lesions were obtained from patients who required either excision or digital monitoring to exclude malignancy., Main Outcome Measures: Sensitivity, specificity, the area under the receiver operator characteristic curve, median probability for the diagnosis of melanoma, a direct comparison of SolarScan with diagnoses performed by humans, and interinstrument and intrainstrument reproducibility., Results: The melanocytic-only diagnostic model was highly reproducible in the test set and gave a sensitivity of 91% (95% confidence interval [CI], 86%-96%) and specificity of 68% (95% CI, 64%-72%) for melanoma. SolarScan had comparable or superior sensitivity and specificity (85% vs 65%) compared with those of experts (90% vs 59%), dermatologists (81% vs 60%), trainees (85% vs 36%; P =.06), and general practitioners (62% vs 63%). The intraclass correlation coefficient of intrainstrument repeatability was 0.86 (95% CI, 0.83-0.88), indicating an excellent repeatability. There was no significant interinstrument variation (P = .80)., Conclusions: SolarScan is a robust diagnostic instrument for pigmented or partially pigmented melanocytic lesions of the skin. Preliminary data suggest that its performance is comparable or superior to that of a range of clinician groups. However, these findings should be confirmed in a formal clinical trial.

The rising incidence of cutaneous malignant melanoma has been observed in the past decades. Currently, there is no cure for metastatic melanoma; only early diagnosis followed by prompt excision of cutaneous lesions ensures a good prognosis. The clinical ABCD rule is created as a framework for differentiating melanomas from benign pigmented skin lesions, and it serves as the basis for current clinical diagnosis. The ABCD rule relies on four simple clinical morphologies of melanoma: 1) Asymmetry, 2) Border irregularity, 3) Color variegation, and 4) Diameter greater than 6 mm. Although it is valuable, it has its limitations. Currently, the diagnostic accuracy for physicians is about 65%. This statistic implies that 1) melanomas with subtle signs are missed as benign lesions, and 2) benign lesions are over diagnosed as melanomas, which lead to unnecessary biopsies.

Background: There is a need for better standardization of the dermoscopic terminology in assessing pigmented skin lesions., Objective: The virtual Consensus Net Meeting on Dermoscopy was organized to investigate reproducibility and validity of the various features and diagnostic algorithms., Methods: Dermoscopic images of 108 lesions were evaluated via the Internet by 40 experienced dermoscopists using a 2-step diagnostic procedure. The first-step algorithm distinguished melanocytic versus nonmelanocytic lesions. The second step in the diagnostic procedure used 4 algorithms (pattern analysis, ABCD rule, Menzies method, and 7-point checklist) to distinguish melanoma versus benign melanocytic lesions. kappa Values, log odds ratios, sensitivity, specificity, and positive likelihood ratios were estimated for all diagnostic algorithms and dermoscopic features., Results: Interobserver agreement was fair to good for all diagnostic methods, but it was poor for the majority of dermoscopic criteria. Intraobserver agreement was good to excellent for all algorithms and features considered. Pattern analysis allowed the best diagnostic performance (positive likelihood ratio: 5.1), whereas alternative algorithms revealed comparable sensitivity but less specificity. Interobserver agreement on management decisions made by dermoscopy was fairly good (mean kappa value: 0.53)., Conclusion: The virtual Consensus Net Meeting on Dermoscopy represents a valid tool for better standardization of the dermoscopic terminology and, moreover, opens up a new territory for diagnosing and managing pigmented skin lesions.

Objectives: To describe morphological features of seborrheic keratosis as seen by dermoscopy and to investigate their prevalence., Design: Prospective cohort study using macrophotography and dermoscopy for the documentation of seborrheic keratosis., Settings: Seborrheic keratoses were prospectively collected in 2 sites: a private practice in Plantation, Fla (site 1), and the Department of Dermatology at the University Hospital Geneva in Switzerland (site 2)., Patients: A total of 203 pigmented seborrheic keratoses (from 192 patients) with complete documentation were collected (111 from site 1 and 93 from site 2)., Interventions: Screening for new morphological features of seborrheic keratosis and evaluation of all lesions for the prevalence of these criteria., Main Outcome Measures: Identification of new morphological criteria and evaluation of frequency., Results: A total of 15 morphological dermoscopic criteria were identified. Standard criteria such as milialike cysts and comedolike openings were found in a high number of cases (135 and 144, respectively). We found network and networklike structures to be present in 94 lesions (46%). Using standard diagnostic criteria for seborrheic keratosis, 30 lesions would not have been diagnosed as such., Conclusions: The classic dermoscopic criteria for seborrheic keratosis (milialike cysts and comedolike openings) have a high prevalence but the use of additional dermoscopic criteria such as fissures, hairpin blood vessels, sharp demarcation, and moth-eaten borders improves the diagnostic accuracy. The proper identification of pigment network and networklike structures is important for the correct diagnosis.

Dermoscopy is a simple to use in vivo method for the early diagnosis of malignant melanoma and the differential diagnosis of pigmented skin lesions. It has been shown to increase diagnostic accuracy over clinical visual inspection in the hands of an experienced physician. This paper is a review of the principles of Dermoscopy as well as recent technological developments.

Background: Differentiation of melanoma from melanocytic nevi is difficult even for skin cancer specialists. This motivates interest in computer-assisted analysis of lesion images., Objective: Our purpose was to offer fully automatic differentiation of melanoma from dysplastic and other melanocytic nevi through multispectral digital dermoscopy., Method: At 4 clinical centers, images were taken of pigmented lesions suspected of being melanoma before biopsy. Ten gray-level (MelaFind) images of each lesion were acquired, each in a different portion of the visible and near-infrared spectrum. The images of 63 melanomas (33 invasive, 30 in situ) and 183 melanocytic nevi (of which 111 were dysplastic) were processed automatically through a computer expert system to separate melanomas from nevi. The expert system used either a linear or a nonlinear classifier. The "gold standard" for training and testing these classifiers was concordant diagnosis by two dermatopathologists., Results: On resubstitution, 100% sensitivity was achieved at 85% specificity with a 13-parameter linear classifier and 100%/73% with a 12-parameter nonlinear classifier. Under leave-one-out cross-validation, the linear classifier gave 100%/84% (sensitivity/specificity), whereas the nonlinear classifier gave 95%/68%. Infrared image features were significant, as were features based on wavelet analysis., Conclusion: Automatic differentiation of invasive and in situ melanomas from melanocytic nevi is feasible, through multispectral digital dermoscopy.

This is the first reported case of a melanoma in a psoriatic plaque. The clinical, dermoscopic, and histologic features of this case are detailed. A review of the risk of melanoma among patients treated with psoralen-ultraviolet A is presented.

The article discusses a study which investigated patient concern as a predictor of a potentially cutaneous malignant lesion. Topics discussed include historical information obtained from patients in dermatology clinics including history of melanoma, age and location of the lesion, factors that could be contributing to lack of awareness among older patients, and the integration of patient concern in other information to improve melanoma sensitivity detection.