Dermatopathological Correlation of Clinically Challenging Cutaneous Lesions: A Single Center Experience of 2184 cases

Author:

Ozcan Yunus,Özlü Emin,Karagün Ebru,Uyar Belkız,Gamsızkan Mehmet

Abstract

Introduction: Although textbooks provide the ideal clinical and histopathological findings, in practice we usually have fewer, and sometimes contradictory, findings to work with. Objectives: The primary goal of this study is to categorize the diagnoses of clinically challenging skin lesions, thereby identifying the most common diagnostic scenarios encountered by dermatopathologists in practice and the most perplexing differential diagnoses submitted by clinicians. Our secondary aim is to investigate how the case profile and clinician decision-making processes changed during the COVID-19 pandemic.Methods: We classified 2184 pathology reports into four major categories: inflammatory, neoplastic, non-diagnostic, and other. In each category, the three most frequently reported diagnoses were listed. For each listed diagnosis, the top 3 most frequently used differential diagnoses by the clinician prior to biopsy are listed. The period one year after and before the first nationally reported COVID-19 case was compared using the same classification.Results: The most common diagnoses and clinical differential diagnoses were listed for each category, with 45.4% being inflammatory and 27.4% being neoplastic diseases. Non-diagnostic reports accounted for 11.4% of all reports. The overall number of reports has decreased drastically since the pandemic, and the rates of keratinocytic and melanocytic neoplasms have increased, while the rates of other malignancies and spongiotic diseases have decreased.Conclusion: Although a trained eye can easily identify skin lesions when they are typical, even diseases we are familiar with can present atypically in real life. In these cases, histopathological examinations and clinicopathological correlation are critical in making an accurate diagnosis.

Publisher

Mattioli1885

Subject

Dermatology,Genetics,Oncology,Molecular Biology

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Skin Cancer Classification: A Comparison of CNN-Backbones for Feature-Extraction;Communications in Computer and Information Science;2024

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