Automatized self-supervised learning for skin lesion screening.

Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body screening (TBS), i.e., identifying suspicious lesions or ugly ducklings (UDs) by visual inspection, can be challenging and often requires sound expertise in pigmented lesions. To assist users of varying expertise levels, an artificial intelligence (AI) decision support tool was developed. Our solution identifies and characterizes UDs from real-world wide-field patient images. It employs a state-of-the-art object detection algorithm to locate and isolate all skin lesions present in a patient's total body images. These lesions are then sorted based on their level of suspiciousness using a self-supervised AI approach, tailored to the specific context of the patient under examination. A clinical validation study was conducted to evaluate the tool's performance. The results demonstrated an average sensitivity of 95% for the top-10 AI-identified UDs on skin lesions selected by the majority of experts in pigmented skin lesions. The study also found that the tool increased dermatologists' confidence when formulating a diagnosis, and the average majority agreement with the top-10 AI-identified UDs reached 100% when assisted by our tool. With the development of this AI-based decision support tool, we aim to address the shortage of specialists, enable faster consultation times for patients, and demonstrate the impact and usability of AI-assisted screening. Future developments will include expanding the dataset to include histologically confirmed melanoma and validating the tool for additional body regions.

GI.1 Norovirus Neutralizing Antibody Levels Are Correlated with GI.1 Histo-blood Group Antigen-Blocking Antibody Levels.

BACKGROUND: The in vitro cultivation of human noroviruses allows a comparison of antibody levels measured in neutralization and histoblood group antigen (HBGA)-blocking assays. METHODS: Serum samples collected during the evaluation of an investigational norovirus vaccine (HIL-214 [formerly TAK-214]) were assayed for neutralizing antibody levels against the vaccine's prototype Norwalk virus/GI.1 (P1) virus strain. Results were compared to those previously determined using HBGA-blocking assays. RESULTS: Neutralizing antibody seroresponses were observed in 83% of 24 vaccinated adults, and antibody levels were highly correlated (r=0.81, P<0.001) with those measured by HBGA-blocking. CONCLUSIONS: GI.1-specific HBGA-blocking antibodies are a surrogate for neutralization of GI.1 norovirus.

International Skin Imaging Collaboration-Designated Diagnoses (ISIC-DX): Consensus terminology for lesion diagnostic labeling.

BACKGROUND: A common terminology for diagnosis is critically important for clinical communication, education, research and artificial intelligence. Prevailing lexicons are limited in fully representing skin neoplasms. OBJECTIVES: To achieve expert consensus on diagnostic terms for skin neoplasms and their hierarchical mapping. METHODS: Diagnostic terms were extracted from textbooks, publications and extant diagnostic codes. Terms were hierarchically mapped to super-categories (e.g. 'benign') and cellular/tissue-differentiation categories (e.g. 'melanocytic'), and appended with pertinent-modifiers and synonyms. These terms were evaluated using a modified-Delphi consensus approach. Experts from the International-Skin-Imaging-Collaboration (ISIC) were surveyed on agreement with terms and their hierarchical mapping; they could suggest modifying, deleting or adding terms. Consensus threshold was >75% for the initial rounds and >50% for the final round. RESULTS: Eighteen experts completed all Delphi rounds. Of 379 terms, 356 (94%) reached consensus in round one. Eleven of 226 (5%) benign-category terms, 6/140 (4%) malignant-category terms and 6/13 (46%) indeterminate-category terms did not reach initial agreement. Following three rounds, final consensus consisted of 362 terms mapped to 3 super-categories and 41 cellular/tissue-differentiation categories. CONCLUSIONS: We have created, agreed upon, and made public a taxonomy for skin neoplasms and their hierarchical mapping. Further study will be needed to evaluate the utility and completeness of the lexicon.

Expert Agreement on the Presence and Spatial Localization of Melanocytic Features in Dermoscopy.

Dermoscopy aids in melanoma detection; however, agreement on dermoscopic features, including those of high clinical relevance, remains poor. In this study, we attempted to evaluate agreement among experts on exemplar images not only for the presence of melanocytic-specific features but also for spatial localization. This was a cross-sectional, multicenter, observational study. Dermoscopy images exhibiting at least 1 of 31 melanocytic-specific features were submitted by 25 world experts as exemplars. Using a web-based platform that allows for image markup of specific contrast-defined regions (superpixels), 20 expert readers annotated 248 dermoscopic images in collections of 62 images. Each collection was reviewed by five independent readers. A total of 4,507 feature observations were performed. Good-to-excellent agreement was found for 14 of 31 features (45.2%), with eight achieving excellent agreement (Gwet's AC >0.75) and seven of them being melanoma-specific features. These features were peppering/granularity (0.91), shiny white streaks (0.89), typical pigment network (0.83), blotch irregular (0.82), negative network (0.81), irregular globules (0.78), dotted vessels (0.77), and blue-whitish veil (0.76). By utilizing an exemplar dataset, a good-to-excellent agreement was found for 14 features that have previously been shown useful in discriminating nevi from melanoma. All images are public (www.isic-archive.com) and can be used for education, scientific communication, and machine learning experiments.

Position statement of the EADV Artificial Intelligence (AI) Task Force on AI-assisted smartphone apps and web-based services for skin disease.

BACKGROUND: As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer. OBJECTIVE: This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI-assisted smartphone applications (apps) and web-based services for skin diseases with emphasis on skin cancer detection. METHODS: An initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance. RESULTS: Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non-medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web-based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users. CONCLUSIONS: The utilisation of AI-assisted smartphone apps and web-based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of these apps into clinical practice.

A Bivalent Human Norovirus Vaccine Induces Homotypic and Heterotypic Neutralizing Antibodies.

A GII.2 outbreak in an efficacy study of a bivalent virus-like particle (VLP) norovirus vaccine, TAK-214, in healthy US adults provided an opportunity to examine GII.4 homotypic vs. GII.2 heterotypic responses to vaccination and infection. Three serological assays (VLP-binding, histoblood group antigen-blocking, and neutralizing) were performed for each genotype. Results were highly correlated within a genotype but not between genotypes. Although the vaccine provided protection from GII.2-associated disease, little GII.2-specific neutralization occurred after vaccination. Choice of antibody assay can affect assessments of human norovirus vaccine immunogenicity.

Saliency-Enhanced Content-Based Image Retrieval for Diagnosis Support in Dermatology Consultation: Reader Study.

BACKGROUND: Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users. OBJECTIVE: This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps. This approach provides better feature extraction, leading to better quantitative retrieval performance as well as providing interpretability for an eventual real-world implementation. METHODS: Content-based image retrieval (CBIR) algorithms rely on the comparison of image features embedded by convolutional neural network (CNN) against a labeled data set. Saliency maps are computer vision-interpretable methods that highlight the most relevant regions for the prediction made by a neural network. By introducing a fine-tuning stage that includes saliency maps to guide feature extraction, the accuracy of image retrieval is optimized. We refer to this approach as saliency-enhanced CBIR (SE-CBIR). A reader study was designed at the University Hospital Zurich Dermatology Clinic to evaluate SE-CBIR's retrieval accuracy as well as the impact of the participant's confidence on the diagnosis. RESULTS: SE-CBIR improved the retrieval accuracy by 7% (77% vs 84%) when doing single-lesion retrieval against traditional CBIR. The reader study showed an overall increase in classification accuracy of 22% (62% vs 84%) when the participant is provided with SE-CBIR retrieved images. In addition, the overall confidence in the lesion's diagnosis increased by 24%. Finally, the use of SE-CBIR as a support tool helped the participants reduce the number of nonmelanoma lesions previously diagnosed as melanoma (overdiagnosis) by 53%. CONCLUSIONS: SE-CBIR presents better retrieval accuracy compared to traditional CBIR CNN-based approaches. Furthermore, we have shown how these support tools can help dermatologists and residents improve diagnosis accuracy and confidence. Additionally, by introducing interpretable methods, we should expect increased acceptance and use of these tools in routine consultation.

Delphi Consensus Among International Experts on the Diagnosis, Management, and Surveillance for Lentigo Maligna.

INTRODUCTION: Melanoma of the lentigo maligna (LM) type is challenging. There is lack of consensus on the optimal diagnosis, treatment, and follow-up. OBJECTIVES: To obtain general consensus on the diagnosis, treatment, and follow-up for LM. METHODS: A modified Delphi method was used. The invited participants were either members of the International Dermoscopy Society, academic experts, or authors of published articles relating to skin cancer and melanoma. Participants were required to respond across three rounds using a 4-point Likert scale). Consensus was defined as >75% of participants agreeing/strongly agreeing or disagreeing/strongly disagreeing. RESULTS: Of the 31 experts invited to participate in this Delphi study, 29 participants completed Round 1 (89.9% response rate), 25/31 completed Round 2 (77.5% response rate), and 25/31 completed Round 3 (77.5% response rate). Experts agreed that LM diagnosis should be based on a clinical and dermatoscopic approach (92%) followed by a biopsy. The most appropriate primary treatment of LM was deemed to be margin-controlled surgery (83.3%), although non-surgical modalities, especially imiquimod, were commonly used either as alternative off-label primary treatment in selected patients or as adjuvant therapy following surgery; 62% participants responded life-long clinical follow-up was needed for LM. CONCLUSIONS: Clinical and histological diagnosis of LM is challenging and should be based on macroscopic, dermatoscopic, and RCM examination followed by a biopsy. Different treatment modalities and follow-up should be carefully discussed with the patient.

Expert Consensus Statement on Proficiency Standards for Dermoscopy Education in Primary Care.

BACKGROUND: Primary care providers (PCPs) frequently address dermatologic concerns and perform skin examinations during clinical encounters. For PCPs who evaluate concerning skin lesions, dermoscopy (a noninvasive skin visualization technique) has been shown to increase the sensitivity for skin cancer diagnosis compared with unassisted clinical examinations. Because no formal consensus existed on the fundamental knowledge and skills that PCPs should have with respect to dermoscopy for skin cancer detection, the objective of this study was to develop an expert consensus statement on proficiency standards for PCPs learning or using dermoscopy. METHODS: A 2-phase modified Delphi method was used to develop 2 proficiency standards. In the study's first phase, a focus group of PCPs and dermatologists generated a list of dermoscopic diagnoses and associated features. In the second phase, a larger panel evaluated the proposed list and determined whether each diagnosis was reflective of a foundational or intermediate proficiency or neither. RESULTS: Of the 35 initial panelists, 5 PCPs were lost to follow-up or withdrew; 30 completed the fifth and last round. The final consensus-based list contained 39 dermoscopic diagnoses and associated features. CONCLUSIONS: This consensus statement will inform the development of PCP-targeted dermoscopy training initiatives designed to support early cancer detection.

Agreement Between Experts and an Untrained Crowd for Identifying Dermoscopic Features Using a Gamified App: Reader Feasibility Study.

BACKGROUND: Dermoscopy is commonly used for the evaluation of pigmented lesions, but agreement between experts for identification of dermoscopic structures is known to be relatively poor. Expert labeling of medical data is a bottleneck in the development of machine learning (ML) tools, and crowdsourcing has been demonstrated as a cost- and time-efficient method for the annotation of medical images. OBJECTIVE: The aim of this study is to demonstrate that crowdsourcing can be used to label basic dermoscopic structures from images of pigmented lesions with similar reliability to a group of experts. METHODS: First, we obtained labels of 248 images of melanocytic lesions with 31 dermoscopic "subfeatures" labeled by 20 dermoscopy experts. These were then collapsed into 6 dermoscopic "superfeatures" based on structural similarity, due to low interrater reliability (IRR): dots, globules, lines, network structures, regression structures, and vessels. These images were then used as the gold standard for the crowd study. The commercial platform DiagnosUs was used to obtain annotations from a nonexpert crowd for the presence or absence of the 6 superfeatures in each of the 248 images. We replicated this methodology with a group of 7 dermatologists to allow direct comparison with the nonexpert crowd. The Cohen κ value was used to measure agreement across raters. RESULTS: In total, we obtained 139,731 ratings of the 6 dermoscopic superfeatures from the crowd. There was relatively lower agreement for the identification of dots and globules (the median κ values were 0.526 and 0.395, respectively), whereas network structures and vessels showed the highest agreement (the median κ values were 0.581 and 0.798, respectively). This pattern was also seen among the expert raters, who had median κ values of 0.483 and 0.517 for dots and globules, respectively, and 0.758 and 0.790 for network structures and vessels. The median κ values between nonexperts and thresholded average-expert readers were 0.709 for dots, 0.719 for globules, 0.714 for lines, 0.838 for network structures, 0.818 for regression structures, and 0.728 for vessels. CONCLUSIONS: This study confirmed that IRR for different dermoscopic features varied among a group of experts; a similar pattern was observed in a nonexpert crowd. There was good or excellent agreement for each of the 6 superfeatures between the crowd and the experts, highlighting the similar reliability of the crowd for labeling dermoscopic images. This confirms the feasibility and dependability of using crowdsourcing as a scalable solution to annotate large sets of dermoscopic images, with several potential clinical and educational applications, including the development of novel, explainable ML tools.

Antibodies Produced in Response to a Live-Attenuated Dengue Vaccine Are Functional in Activating the Complement System.

BACKGROUND: Antibody-driven complement system (CS) activation has been associated with protection against symptomatic dengue virus (DENV) infection. Aggregation, opsonization, lysis, and phagocytosis are mechanisms triggered by antibody-antigen immunocomplexes following fixation of the component 1q (C1q) and activation of the classical pathway. As a result, DENV neutralization and clearance are facilitated, whereas antibody-dependent enhancement of infection is inhibited. We investigated the ability of antibodies produced in response to Takeda's dengue vaccine candidate, TAK-003, to fix C1q and activate CS. METHODS: Serum samples were collected from seronegative and seropositive participants in a phase 2 clinical trial (DEN-203), pre- and postvaccination. Samples were evaluated for the presence of complement-fixing antibodies (CFAs) against DENV using a Luminex multiplex-based immunoassay. RESULTS: TAK-003 elicited production of CFAs against all 4 DENV serotypes, which persisted for 1 year postvaccination, irrespective of baseline serostatus. CFA levels were correlated with neutralizing antibody titers and virus-binding total IgG and IgG1 concentrations. Furthermore, efficiency of CFA fixation was greater in samples with higher polyclonal IgG avidity. CONCLUSIONS: These results indicate that antibodies produced after TAK-003 vaccination are functional in both activating CS and neutralizing virus infection by all DENV serotypes, which may contribute to efficacy of TAK-003. CLINICAL TRIALS REGISTRATION: NCT01511250.

Theory-Based Approaches to Support Dermoscopic Image Interpretation Education: A Review of the Literature.

Introduction: Efficient interpretation of dermoscopic images relies on pattern recognition, and the development of expert-level proficiency typically requires extensive training and years of practice. While traditional methods of transferring knowledge have proven effective, technological advances may significantly improve upon these strategies and better equip dermoscopy learners with the pattern recognition skills required for real-world practice. Objectives: A narrative review of the literature was performed to explore emerging directions in medical image interpretation education that may enhance dermoscopy education. This article represents the first of a two-part review series on this topic. Methods: To promote innovation in dermoscopy education, the International Skin Imaging Collaborative (ISIC) assembled a 12-member Education Working Group that comprises international dermoscopy experts and educational scientists. Based on a preliminary literature review and their experiences as educators, the group developed and refined a list of innovative approaches through multiple rounds of discussion and feedback. For each approach, literature searches were performed for relevant articles. Results: Through a consensus-based approach, the group identified a number of emerging directions in image interpretation education. The following theory-based approaches will be discussed in this first part: whole-task learning, microlearning, perceptual learning, and adaptive learning. Conclusions: Compared to traditional methods, these theory-based approaches may enhance dermoscopy education by making learning more engaging and interactive and reducing the amount of time required to develop expert-level pattern recognition skills. Further exploration is needed to determine how these approaches can be seamlessly and successfully integrated to optimize dermoscopy education.

Indications for Digital Monitoring of Patients With Multiple Nevi: Recommendations from the International Dermoscopy Society.

Introduction: In patients with multiple nevi, sequential imaging using total body skin photography (TBSP) coupled with digital dermoscopy (DD) documentation reduces unnecessary excisions and improves the early detection of melanoma. Correct patient selection is essential for optimizing the efficacy of this diagnostic approach. Objectives: The purpose of the study was to identify, via expert consensus, the best indications for TBSP and DD follow-up. Methods: This study was performed on behalf of the International Dermoscopy Society (IDS). We attained consensus by using an e-Delphi methodology. The panel of participants included international experts in dermoscopy. In each Delphi round, experts were asked to select from a list of indications for TBSP and DD. Results: Expert consensus was attained after 3 rounds of Delphi. Participants considered a total nevus count of 60 or more nevi or the presence of a CDKN2A mutation sufficient to refer the patient for digital monitoring. Patients with more than 40 nevi were only considered an indication in case of personal history of melanoma or red hair and/or a MC1R mutation or history of organ transplantation. Conclusions: Our recommendations support clinicians in choosing appropriate follow-up regimens for patients with multiple nevi and in applying the time-consuming procedure of sequential imaging more efficiently. Further studies and real-life data are needed to confirm the usefulness of this list of indications in clinical practice.

Instructional Strategies to Enhance Dermoscopic Image Interpretation Education: a Review of the Literature.

Introduction: In image interpretation education, many educators have shifted away from traditional methods that involve passive instruction and fragmented learning to interactive ones that promote active engagement and integrated knowledge. By training pattern recognition skills in an effective manner, these interactive approaches provide a promising direction for dermoscopy education. Objectives: A narrative review of the literature was performed to probe emerging directions in medical image interpretation education that may support dermoscopy education. This article represents the second of a two-part review series. Methods: To promote innovation in dermoscopy education, the International Skin Imaging Collaborative (ISIC) assembled an Education Working Group that comprises international dermoscopy experts and educational scientists. Based on a preliminary literature review and their experiences as educators, the group developed and refined a list of innovative approaches through multiple rounds of discussion and feedback. For each approach, literature searches were performed for relevant articles. Results: Through a consensus-based approach, the group identified a number of theory-based approaches, as discussed in the first part of this series. The group also acknowledged the role of motivation, metacognition, and early failures in optimizing the learning process. Other promising teaching tools included gamification, social media, and perceptual and adaptive learning modules (PALMs). Conclusions: Over the years, many dermoscopy educators may have intuitively adopted these instructional strategies in response to learner feedback, personal observations, and changes in the learning environment. For dermoscopy training, PALMs may be especially valuable in that they provide immediate feedback and adapt the training schedule to the individual's performance.

Suspicious Skin Lesion Detection in Wide-Field Body Images using Deep Learning Outlier Detection.

During consultation dermatologists have to address hundreds of lesions in a limited amount of time. They will not only evaluate the single lesion of interest but more importantly the context of it. Visually comparing the similarity of the majority of lesions within the same patient provides a strong indication for lesions with significantly differing aspects. Deep learning algorithms are capable to identify such outliers, i.e. images that differ considerably from the expected appearance on a larger cohort, and highlight the main differences in those cases. In the present study we evaluate the use of autoencoders as unsupervised tools to detect suspicious skin lesions based on evaluation of real world data acquired during consultation at the USZ Dermatology Clinic. Clinical Relevance- Deep learning algorithms are showing many promising results in dermatology lesion classification. However the context of the lesion is normally not considered in the analysis which prevents these tools to transition into routine practice. An outlier detector based on real world data would allow a dermatologist or general practitioner to detect the suspicious lesions for further examination. The algorithm would additionally provide useful insights by highlighting the feature differences between the original outlier (malignant lesion) and the lesion reconstructed by the autoencoder.

Breadth and Dynamics of Human Norovirus-Specific Antibodies in the First Year of Life.

We measured antibody binding to diverse norovirus virus-like particles over 12 months in 16 children. All had maternal antibodies at 2 months, with estimated lowest levels at 5 months of age. Antibody increases after 3 months suggested natural infections. This information could guide the timing of future norovirus vaccines.

International Dermoscopy Society criteria for non-neoplastic dermatoses (general dermatology): validation for skin of color through a Delphi expert consensus.

BACKGROUND: The International Dermoscopy Society (IDS) recently released a set of five basic dermoscopic parameters (vessels, scales, follicular findings, "other structures," and specific clues) encompassing a total of 31 subitems to standardize the use of dermoscopy in non-neoplastic dermatoses, yet they have been developed taking into account Caucasian/Asian skin, with consequent possible limitations if used in dark skin. OBJECTIVES: To validate the abovementioned criteria for the use in dark-skinned patients (phototypes IV-VI) through an expert consensus. METHODS: The two-round Delphi method was adopted, with an iterative process consisting of two rounds of email questionnaires. Potential panelists were recruited via e-mail from all over the world based on their expertise on dermoscopy of non-neoplastic dermatoses in skin of color. RESULTS: Twenty-two panelists took part in the validation process. All of the five originally proposed parameters and subitems reached agreement during the first round, aside from "follicular red dots." Additionally, during round 1, five new subitems were proposed (perifollicular scales distribution, follicular openings obliteration, broken hairs, eccrine pigmentation, and eccrine ostia obliteration), along with the possibility to change the denomination of parameter 3 (from "follicular findings" to "follicular/eccrine findings") and split it into two subparameters ("follicular findings" and "eccrine findings"). All such proposals reached agreement during the second round and therefore were included in the final list, for a total of 37 items. CONCLUSIONS: Although nearly all the dermoscopic criteria originally proposed by the IDS are applicable even to darker phototypes, several additional variables need to be assessed.

Development and Characterization of a Multiplex Assay to Quantify Complement-Fixing Antibodies against Dengue Virus.

Antibodies capable of activating the complement system (CS) when bound with antigen are referred to as "complement-fixing antibodies" and are involved in protection against Flaviviruses. A complement-fixing antibody test has been used in the past to measure the ability of dengue virus (DENV)-specific serum antibodies to activate the CS. As originally developed, the test is time-consuming, cumbersome, and has limited sensitivity for DENV diagnosis. Here, we developed and characterized a novel multiplex anti-DENV complement-fixing assay based on the Luminex platform to quantitate serum antibodies against all four serotypes (DENV1-4) that activate the CS based on their ability to fix the complement component 1q (C1q). The assay demonstrated good reproducibility and showed equivalent performance to a DENV microneutralization assay that has been used to determine DENV serostatus. In non-human primates, antibodies produced in response to primary DENV1-4 infection induced C1q fixation on homologous and heterologous serotypes. Inter-serotype cross-reactivity was associated with homology of the envelope protein. Interestingly, the antibodies produced following vaccination against Zika virus fixed C1q on DENV. The anti-DENV complement fixing antibody assay represents an alternative approach to determine the quality of functional antibodies produced following DENV natural infection or vaccination and a biomarker for dengue serostatus, while providing insights about immunological cross-reactivity among different Flaviviruses.

Clinical and Dermoscopic Features of Melanocytic Lesions on the Face Versus the External Ear.

INTRODUCTION: Melanoma of the external ear is a rare condition accounting for 7-20% of all melanomas of the head and neck region. They present classical features of extra-facial melanomas clinically and dermoscopically. In contrast, facial melanomas show peculiar patterns in dermoscopy. OBJECTIVES: To evaluate whether there are clinical and/or dermoscopic differences in melanocytic lesions located either at the external ear or on the face. METHODS: In this retrospective study we reviewed an image database for clinical and dermoscopic images of melanomas and nevi located either on the face or at the level of the external ear. RESULTS: 65 patients (37 men; 63.8%) with 65 lesions were included. We found no significant differences in comparing face melanomas with melanomas at the level of the external ear, neither clinically nor dermoscopically. However, we provided evidence for differences in some clinical and dermoscopic features of melanomas and nevi of the external ear. CONCLUSIONS: In this study, we reported no significant differences in comparing melanomas on the face with melanomas of the external ear, both clinically and dermoscopically. Furthermore, we provided data on clinical and dermoscopic differences comparing nevi and melanoma of the external ear.

Dermoscopy Proficiency Expectations for US Dermatology Resident Physicians: Results of a Modified Delphi Survey of Pigmented Lesion Experts.

Importance: Dermoscopy education in US dermatology residency programs varies widely, and there is currently no existing expert consensus identifying what is most important for resident physicians to know. Objectives: To identify consensus-based learning constructs representing an appropriate foundational proficiency in dermoscopic image interpretation for dermatology resident physicians, including dermoscopic diagnoses, associated features, and representative teaching images. Defining these foundational proficiency learning constructs will facilitate further skill development in dermoscopic image interpretation to help residents achieve clinical proficiency. Design, Setting, and Participants: A 2-phase modified Delphi surveying technique was used to identify resident learning constructs in 3 sequential sets of surveys-diagnoses, features, and images. Expert panelists were recruited through an email distributed to the 32 members of the Pigmented Lesion Subcommittee of the Melanoma Prevention Working Group. Twenty-six (81%) opted to participate. Surveys were distributed using RedCAP software. Main Outcomes and Measures: Consensus on diagnoses, associated dermoscopic features, and representative teaching images reflective of a foundational proficiency in dermoscopic image interpretation for US dermatology resident physicians. Results: Twenty-six pigmented lesion and dermoscopy specialists completed 8 rounds of surveys, with 100% (26/26) response rate in all rounds. A final list of 32 diagnoses and 116 associated dermoscopic features was generated. Three hundred seventy-eight representative teaching images reached consensus with panelists. Conclusions and Relevance: Consensus achieved in this modified Delphi process identified common dermoscopic diagnoses, associated features, and representative teaching images reflective of a foundational proficiency in dermoscopic image interpretation for dermatology residency training. This list of validated objectives provides a consensus-based foundation of key learning points in dermoscopy to help resident physicians achieve clinical proficiency in dermoscopic image interpretation.