Histopathologic and Clinical Characterization of Brentuximab Vedotin-associated Rash.

Rash is one of the commonly observed adverse events with brentuximab vedotin (BV), a CD30-targeted antibody-drug conjugate used to treat cutaneous T-cell lymphoma (CTCL). However, clinical and histopathologic characterization of BV-associated rash (BVAR) is limited. Distinguishing BVAR from a patient's underlying CTCL can be challenging and can lead to treatment interruptions or even premature drug discontinuation. We performed a thorough clinical and histopathologic retrospective characterization of BVAR from a single institution. Utilizing polymerase chain reaction (PCR) and T-cell receptor high-throughput sequencing (TCR-HTS), we were able to isolate skin biopsy specimens from rash clinically suggestive of BVAR that also lacked a dominant TCR clone. A retrospective evaluation was performed of 26 biopsy specimens from 14 patients. Clinical features of BVAR included predominantly morbilliform or maculopapular morphology, delayed onset, and the trend toward moderate to severe classification, often requiring oral steroids. Most histopathologic specimens (25/26) showed spongiotic dermatitis as the primary reaction pattern. Many cases showed subtle findings to support a background interface or lichenoid eruption. Langerhans cell microabscesses were seen in one-fourth of specimens, and eosinophils were present in over one-half of the specimens. There were focal features mimicking CTCL, but these were not prominent. In 17 specimens with immunohistochemistry, the CD4:CD8 ratio in intraepidermal lymphocytes was relatively normal (1-6:1) in 65% (11/17) and 1:1 in 35% (6/17), demonstrating a trend toward increased CD8-positive cells compared with baseline CTCL. We have identified features that can help distinguish BVAR from a patient's CTCL, which can, in turn, help guide appropriate clinical management.

Cutaneous larva migrans in the northeastern US.

Cutaneous larva migrans (CLM) is a dermo-epidermal parasitic infection with a disproportionate incidence in developing countries, particularly in, and near tropical areas. It is characterized by erythematous, twisting, and linear plaques that can migrate to adjacent skin. Herein, we present an otherwise healthy 45-year-old woman who acquired a pruritic, erythematous, and serpiginous rash localized to her right medial ankle during a trip to New England. Oral ivermectin, the preferred first-line treatment for cutaneous larva migrans, was administered in combination with triamcinolone. This was followed by removal of the papular area via punch biopsy; treatment was successful with a one-week recovery. Although cutaneous larva migrans has traditionally been considered a tropical disease, clinicians should be cognizant of its expanding geographic spread.

Identification and confirmation via in situ hybridization of Merkel cell polyomavirus in rare cases of posttransplant cutaneous T-cell lymphoma.

BACKGROUND: Viral infection is an oncogenic factor in many hematolymphoid malignancies. We sought to determine the diagnostic yield of aligning off-target reads incidentally obtained during targeted hematolymphoid next-generation sequencing to a large database of viral genomes to screen for viral sequences within tumor specimens. METHODS: Alignment of off-target reads to viral genomes was performed using magicBLAST. Localization of Merkel cell polyomavirus (MCPyV) RNA was confirmed by RNAScope in situ hybridization. Integration analysis was performed using Virus-Clip. RESULTS: Four cases of post-cardiac-transplant folliculotropic mycosis fungoides (fMF) and one case of peripheral T-cell lymphoma (PTCL) were positive in off-target reads for MCPyV DNA. Two of the four cases of posttransplant fMF and the case of PTCL showed localization of MCPyV RNA to malignant lymphocytes, whereas the remaining two cases of posttransplant fMF showed MCPyV RNA in keratinocytes. CONCLUSIONS: Our findings raise the question of whether MCPyV may play a role in rare cases of T-lymphoproliferative disorders, particularly in the skin and in the heavily immunosuppressed posttransplant setting.

Best Practices for Clinical Skin Image Acquisition in Translational Artificial Intelligence Research.

Recent advances in artificial intelligence research have led to an increase in the development of algorithms for detecting malignancies from clinical and dermoscopic images of skin diseases. These methods are dependent on the collection of training and testing data. There are important considerations when acquiring skin images and data for translational artificial intelligence research. In this paper, we discuss the best practices and challenges for light photography image data collection, covering ethics, image acquisition, labeling, curation, and storage. The purpose of this work is to improve artificial intelligence for malignancy detection by supporting intentional data collection and collaboration between subject matter experts, such as dermatologists and data scientists.

Development and Clinical Evaluation of an Artificial Intelligence Support Tool for Improving Telemedicine Photo Quality.

Importance: Telemedicine use accelerated during the COVID-19 pandemic, and skin conditions were a common use case. However, many images submitted may be of insufficient quality for making a clinical determination. Objective: To determine whether an artificial intelligence (AI) decision support tool, a machine learning algorithm, could improve the quality of images submitted for telemedicine by providing real-time feedback and explanations to patients. Design, Setting, and Participants: This quality improvement study with an AI performance component and single-arm clinical pilot study component was conducted from March 2020 to October 2021. After training, the AI decision support tool was tested on 357 retrospectively collected telemedicine images from Stanford telemedicine from March 2020 to June 2021. Subsequently, a single-arm clinical pilot study was conducted to assess feasibility with 98 patients in the Stanford Department of Dermatology across 2 clinical sites from July 2021 to October 2021. For the clinical pilot study, inclusion criteria for patients included being adults (aged ≥18 years), presenting to clinic for a skin condition, and being able to photograph their own skin with a smartphone. Interventions: During the clinical pilot study, patients were given a handheld smartphone device with a machine learning algorithm interface loaded and were asked to take images of any lesions of concern. Patients were able to review and retake photos prior to submitting, so each submitted photo met the patient's assumed standard of clinical acceptability. A machine learning algorithm then gave the patient feedback on whether the image was acceptable. If the image was rejected, the patient was provided a reason by the AI decision support tool and allowed to retake the photos. Main Outcomes and Measures: The main outcome of the retrospective image analysis was the receiver operator curve area under the curve (ROC-AUC). The main outcome of the clinical pilot study was the image quality difference between the baseline images and the images approved by AI decision support. Results: Of the 98 patients included, the mean (SD) age was 49.8 (17.6) years, and 50 (51%) of the patients were male. On retrospective telemedicine images, the machine learning algorithm effectively identified poor-quality images (ROC-AUC of 0.78) and the reason for poor quality (blurry ROC-AUC of 0.84; lighting issues ROC-AUC of 0.70). The performance was consistent across age and sex. In the clinical pilot study, patient use of the machine learning algorithm was associated with improved image quality. An AI algorithm was associated with reduction in the number of patients with a poor-quality image by 68.0%. Conclusions and Relevance: In this quality improvement study, patients use of the AI decision support with a machine learning algorithm was associated with improved quality of skin disease photographs submitted for telemedicine use.

Incidence Trends of Primary Cutaneous T-Cell Lymphoma in the US From 2000 to 2018: A SEER Population Data Analysis.

Using SEER database data, this cohort study analyzed cutaneous T-cell lymphoma incidence by tumor subtype, sex, age, race and ethnicity, socioeconomic status, and geography.

Disparities in dermatology AI performance on a diverse, curated clinical image set.

An estimated 3 billion people lack access to dermatological care globally. Artificial intelligence (AI) may aid in triaging skin diseases and identifying malignancies. However, most AI models have not been assessed on images of diverse skin tones or uncommon diseases. Thus, we created the Diverse Dermatology Images (DDI) dataset-the first publicly available, expertly curated, and pathologically confirmed image dataset with diverse skin tones. We show that state-of-the-art dermatology AI models exhibit substantial limitations on the DDI dataset, particularly on dark skin tones and uncommon diseases. We find that dermatologists, who often label AI datasets, also perform worse on images of dark skin tones and uncommon diseases. Fine-tuning AI models on the DDI images closes the performance gap between light and dark skin tones. These findings identify important weaknesses and biases in dermatology AI that should be addressed for reliable application to diverse patients and diseases.

Spitz nevus with EHBP1-ALK fusion and distinctive membranous localization of ALK.

ALK rearrangements define a histopathologically distinctive yet diverse subset of Spitz tumors characterized by fusiform to epithelioid melanocytes with frequent fascicular growth and ALK overexpression. Molecularly, these tumors are characterized by fusions between ALK and a variety of gene partners, most commonly TPM3 and DCTN1. We describe an unusual case of a Spitz nevus occurring in a 13-year-old female that manifested ALK immunopositivity with cell membrane localization. The proliferation was polypoid and composed of elongated nests of epithelioid melanocytes with enlarged nuclei, prominent nucleoli, and abundant cytoplasm without significant atypia and lacking mitotic figures. The nevus exhibited strong and diffuse expression of p16. Targeted next-generation RNA sequencing revealed an in-frame EHBP1-ALK fusion, which has been reported only once in the literature. EHBP1 encodes an adaptor protein with plasma membrane targeting potential. Together, these findings suggest that the 5' ALK fusion partner in Spitz tumors may dictate the subcellular localization of the ALK chimeric oncoprotein. In summary, this case highlights a rare ALK fusion associated with a distinct immunohistochemical staining pattern and further expands the spectrum of ALK-rearranged melanocytic tumors.

Artificial intelligence for dermatopathology: Current trends and the road ahead.

Artificial intelligence (AI), including deep learning methods that leverage neural network-based algorithms, hold significant promise for dermatopathology and other areas of diagnostic pathology in research and clinical practice. There has been significant progress over past several years in applying AI to analyzing digital histopathology images for diagnosis. While much work in AI analysis of histopathology data remains investigational, recent regulatory agency approval in Europe and United States of AI-assisted tools for clinical use in histopathologic diagnosis of prostate and breast cancer herald broader movement of AI into the clinical diagnostic realm of anatomic pathology, including dermatopathology. However, significant challenges remain in translating AI from research into clinical practice, including algorithmic real-world performance, robustness to variation in data sets and practice settings, effective integration into clinical workflows, and cost effectiveness. This review introduces core concepts and terminology in AI, and assesses current progress and challenges in applying AI to dermatopathology.

High prevalence of Leishmania spp. in dogs from Central West Colombia.

Leishmaniasis is a widespread disease caused by species of the genus Leishmania. In Colombia, this zoonosis is endemic in rural areas with a high prevalence in the departments of Antioquia, Santander, Meta, Tolima and Nariño. Dogs are the most important domestic reservoirs of the pathogen, given the epidemiological importance of dogs in the control of leishmaniasis is needed to determine the prevalence of Leishmania spp. in canine population of the rural area of Ibagué and to identify potential risk factors related to the presence of this parasite. A cross-sectional study was carried out in 173 dogs from the rural area of Ibagué. Leishmania spp. was detected by amplifying the Internal Transcribed Spacer (ITS-1) and two regions of the hsp70 gene through PCR. Factor associations were calculated through the Chisquare and odds ratio. Prevalence of Leishmania spp. infection in dogs was of 91.33% (158/173), where 36.71% (58/158) of the Leishmania spp. positive dogs showed one or more clinical signs of canine leishmaniasis and 63.29% (100/158) of the dogs were asymptomatic. Factors associated with the presence of the parasite did not show significance. In addition, hsp70D-PCR was proved to be highly efficient for the detection of Leishmania spp.

Next-generation sequencing confirms T-cell clonality in a subset of pediatric pityriasis lichenoides.

BACKGROUND: Pityriasis lichenoides (PL) is a papulosquamous disease that affects both adults and children. Previous studies have shown a subset of this entity to have clonal T-cell populations via PCR-based assays. In this study, we sought to implement next-generation sequencing (NGS) as a more sensitive and specific test to examine for T-cell clonality within the pediatric population. METHODS: We identified 18 biopsy specimens from 12 pediatric patients with clinical and histopathologic findings compatible with PL. Patient demographics, clinical features, management, and histopathologic findings were reviewed. All specimens were analyzed for clonality with NGS of T-cell receptor beta (TRB) and gamma (TRG) genes. RESULTS: Of the 12 patients, 9 (75%) had complete resolution of lesions at the time of data collection (mean follow-up 31 months). The remaining three patients significantly improved with methotrexate (with or without acitretin). Interestingly, 7 of 12 patients (58%) and 9 of 17 biopsy specimens (53%) showed evidence of T-cell clonality. Two patients showed matching TRB clones from different anatomic sites. CONCLUSIONS: T-cell clonality is a common finding in PL, probably representing a "reactive clonality" rather than a true lymphoproliferative disorder. Clonality alone cannot be used as a means to distinguish PL from lymphomatoid papulosis or cutaneous lymphoma.

Appropriate use criteria for ancillary diagnostic testing in dermatopathology: New recommendations for 11 tests and 220 clinical scenarios from the American Society of Dermatopathology Appropriate Use Criteria Committee.

BACKGROUND: Appropriate use criteria (AUC) provide patient-centered physician guidance in test selection. An initial set of AUC was reported by the American Society of Dermatopathology (ASDP) in 2018. AUC reflect evidence collected at single timepoints and may be affected by evolving evidence and experience. The objective of this study was to update and expand AUC for selected tests. METHODS: RAND/UCLA (RAND Corporation [Santa Monica, CA]/University of California Los Angeles) methodology used includes the following: (a) literature review; (b) review of previously rated tests and previously employed clinical scenarios; (c) selection of previously rated tests for new ratings; (d) development of new clinical scenarios; (e) selection of additional tests; (f) three rating rounds with feedback and group discussion after rounds 1 and 2. RESULTS: For 220 clinical scenarios comprising lymphoproliferative (light chain clonality), melanocytic (comparative genomic hybridization, fluorescence in situ hybridization, reverse transcription polymerase chain reaction, telomerase reverse transcriptase promoter), vascular disorders (MYC), and inflammatory dermatoses (periodic acid-Schiff, Gömöri methenamine silver), consensus by panel raters was reached in 172 of 220 (78%) scenarios, with 103 of 148 (70%) rated "usually appropriate" or "rarely appropriate" and 45 of 148 (30%), "appropriateness uncertain." LIMITATIONS: The study design only measures appropriateness. Cost, availability, test comparison, and additional clinical considerations are not measured. The possibility that the findings of this study may be influenced by the inherent biases of the dermatopathologists involved in the study cannot be excluded. CONCLUSIONS: AUC are reported for selected diagnostic tests in clinical scenarios that occur in dermatopathology practice. Adhering to AUC may reduce inappropriate test utilization and improve healthcare delivery.

Immunohistochemical ALK Expression in Granular Cell Atypical Fibroxanthoma: A Diagnostic Pitfall for ALK-Rearranged Non-neural Granular Cell Tumor.

ABSTRACT: Atypical fibroxanthoma (AFX) is a neoplasm that most commonly occurs on sun-damaged skin of the head and neck in elderly patients and that usually exhibits indolent clinical behavior with complete excision. The granular cell variant of AFX demonstrates overlapping histopathologic features with dermal non-neural granular cell tumor (NNGCT), which typically arises on the extremities of young to middle aged adults with rare reports of regional metastasis. A subset of NNGCT harbors ALK rearrangements and expresses ALK by immunohistochemistry. Here, we present 2 cases of granular cell AFX occurring on the scalp of males aged 73 and 87 with ALK expression by immunohistochemistry and no evidence of an ALK rearrangement on fluorescence in situ hybridization, representing a diagnostic pitfall for NNGCT.