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.

The Impact of Next-generation Sequencing on Interobserver Agreement and Diagnostic Accuracy of Desmoplastic Melanocytic Neoplasms.

Next-generation sequencing (NGS) is increasingly being utilized as an ancillary tool for diagnostically challenging melanocytic neoplasms. It is incumbent upon the pathology community to perform studies assessing the benefits and limitations of these tools in specific diagnostic scenarios. One of the most challenging diagnostic scenarios faced by skin pathologists involves accurate diagnosis of desmoplastic melanocytic neoplasms (DMNs). In this study, 20 expert melanoma pathologists rendered a diagnosis on 47 DMNs based on hematoxylin and eosin sections with demographic information. After submitting their diagnosis, the experts were given the same cases, but this time with comprehensive genomic sequencing results, and asked to render a diagnosis again. Identification of desmoplastic melanoma (DM) improved by 7%, and this difference was statistically significant ( P <0.05). In addition, among the 15 melanoma cases, in the pregenomic assessment, only 12 were favored to be DM by the experts, while after genomics, this improved to 14 of the cases being favored to be DM. In fact, some cases resulting in metastatic disease had a substantial increase in the number of experts recognizing them as DM after genomics. The impact of the genomic findings was less dramatic among benign and intermediate-grade desmoplastic tumors (BIDTs). Interobserver agreement also improved, with the Fleiss multirater Kappa being 0.36 before genomics to 0.4 after genomics. NGS has the potential to improve diagnostic accuracy in the assessment of desmoplastic melanocytic tumors. The degree of improvement will be most substantial among pathologists with some background and experience in bioinformatics and melanoma genetics.

BRAF Mutated and Morphologically Spitzoid Tumors, a Subgroup of Melanocytic Neoplasms Difficult to Distinguish From True Spitz Neoplasms.

Drivers of Spitz neoplasms include activating point mutations in HRAS and Spitz-associated genomic fusions. It has become evident that some BRAF -mutated melanocytic neoplasms can morphologically mimic Spitz tumors (STs). These have been termed BRAF mutated and morphologically spitzoid (BAMS). In this study, 17 experts from the International Melanoma Pathology Study Group assessed 54 cases which included 40 BAMS and 14 true STs. The participants reviewed the cases blinded to the genomic data and selected among several diagnostic options, including BAMS, ST, melanoma, and other. A total of 38% of all diagnostic selections in the BAMS cases were for BAMS, whereas 32% were for ST. In 22 of the BAMS cases, the favored diagnosis was BAMS, whereas in 17 of the BAMS cases, the favored diagnosis was ST. Among the 20 cases in the total group of 54 with the highest number of votes for ST, half were BAMS. Of BAMS, 75% had a number of votes for ST that was within the SD of votes for ST seen among true ST cases. There was poor interobserver agreement for the precise diagnosis of the BAMS (kappa = 0.16) but good agreement that these cases were not melanoma (kappa = 0.7). BAMS nevi/tumors can closely mimic Spitz neoplasms. Expert melanoma pathologists in this study favored a diagnosis of ST in nearly half of the BAMS cases. There are BAMS cases that even experts cannot morphologically distinguish from true Spitz neoplasms.

Immunohistochemistry for Diagnosing Melanoma in Older Adults.

Importance: Pathologic assessment to diagnose skin biopsies, especially for cutaneous melanoma, can be challenging, and immunohistochemistry (IHC) staining has the potential to aid decision-making. Currently, the temporal trends regarding the use of IHC for the examination of skin biopsies on a national level have not been described. Objective: To illustrate trends in the use of IHC for the examination of skin biopsies in melanoma diagnoses. Design, Setting, and Participants: A retrospective cross-sectional study was conducted to examine incident cases of melanoma diagnosed between January 2000 and December 2017. The analysis used the SEER-Medicare linked database, incorporating data from 17 population-based registries. The study focused on incident cases of in situ or malignant melanoma of the skin diagnosed in patients 65 years or older. Data were analyzed between August 2022 and November 2023. Main Outcomes and Measures: The main outcomes encompassed the identification of claims for IHC within the month of melanoma diagnoses and extending up to 14 days into the month following diagnosis. The SEER data on patients with melanoma comprised demographic, tumor, and area-level characteristics. Results: The final sample comprised 132 547 melanoma tumors in 116 117 distinct patients. Of the 132 547 melanoma diagnoses meeting inclusion criteria from 2000 to 2017, 43 396 cases had accompanying IHC claims (33%). Among these cases, 28 298 (65%) were diagnosed in male patients, 19 019 (44%) were diagnosed in patients aged 65 years to 74 years, 16 444 (38%) in patients aged 75 years to 84 years, and 7933 (18%) in patients aged 85 years and older. In 2000, 11% of melanoma cases had claims for IHC at or near the time of diagnosis. This proportion increased yearly, with 51% of melanoma cases having associated IHC claims in 2017. Increasing IHC use is observed for all stages of melanoma, including in situ melanoma. Claims for IHC in melanomas increased in all 17 SEER registries but at different rates. In 2017, the use of IHC for melanoma diagnosis ranged from 39% to 68% across registries. Conclusions and Relevance: Considering the dramatically rising and variable use of IHC in diagnosing melanoma by pathologists demonstrated in this retrospective cross-sectional study, further investigation is warranted to understand the clinical utility and discern when IHC most improves diagnostic accuracy or helps patients.

Is Primary Poorly Differentiated Sarcomatoid Malignancy of the Parotid Gland Sarcomatoid Undifferentiated/Dedifferentiated Melanoma? Report of Three Unusual Cases Diagnosed by Fine-Needle Aspiration Combined with Histological, Immunohistochemical, and Molecular Analyses.

INTRODUCTION: Poorly differentiated primary sarcomatoid parotid malignancies are extremely rare. These tumors have not been consistently studied by morphology, immunohistochemistry, or molecular techniques. CASE PRESENTATION: We report three unusual cases of parotid gland poorly-differentiated sarcomatoid malignancy investigated by fine-needle aspiration and studied histologically, by immunohistochemistry and molecular investigations. Aspirates showed poorly specific polymorphous sarcomatoid malignancy in all cases. Histologically, all cases were polymorphous high-grade malignancies, and additionally, one case showed epithelial structures and was finally classified as salivary carcinosarcoma. Immunohistochemistry showed classical melanocytic markers negativity but positivity for PRAME, CD10, and WT1 in all three tumors and for CD56 in two tumors, which can potentially be supportive of melanocytic origin. Although not entirely specific, molecular characterization also suggested the melanocytic lineage of these tumors. CONCLUSION: Although rare, primary malignant melanoma of salivary gland was already described, but undifferentiated/dedifferentiated amelanotic forms are unknown in this localization up today. Further case reports of similar presentations are required to confirm the unequivocal primary origin of these obscure neoplasms in the parotid gland.

Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma.

Artificial intelligence (AI) systems have been shown to help dermatologists diagnose melanoma more accurately, however they lack transparency, hindering user acceptance. Explainable AI (XAI) methods can help to increase transparency, yet often lack precise, domain-specific explanations. Moreover, the impact of XAI methods on dermatologists' decisions has not yet been evaluated. Building upon previous research, we introduce an XAI system that provides precise and domain-specific explanations alongside its differential diagnoses of melanomas and nevi. Through a three-phase study, we assess its impact on dermatologists' diagnostic accuracy, diagnostic confidence, and trust in the XAI-support. Our results show strong alignment between XAI and dermatologist explanations. We also show that dermatologists' confidence in their diagnoses, and their trust in the support system significantly increase with XAI compared to conventional AI. This study highlights dermatologists' willingness to adopt such XAI systems, promoting future use in the clinic.