Journal of cutaneous pathology · 2024
Dermatopathologist accuracy in classifying angioinvasive fungal infections using virtual microscopy.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Harrison Iris, Patel Basil, Kunzler Elaine, Walker Addie, Missall Tricia, Motaparthi Kiran
Аннотация
BACKGROUND: Due to perceived difficulty in the categorization of angioinvasive fungal infections based on histopathology, variation exists in dermatopathology reporting.
METHODS: This study characterized the diagnosis of angioinvasive fungal infections by light microscopy at a single academic institution over an 11-year period. Subsequently, the accuracy of blinded reclassification by virtual microscopy was measured.
RESULTS: Seventy-six specimens with hematoxylin-eosin slides were obtained from 33 patients. The mean diagnostic accuracy of dermatopathologists in differentiating mucormycosis, hyalohyphomycosis, and phaeohyphomycosis based on blinded reclassification via virtual microscopy was 74%, with a range of 65%-91%.
CONCLUSIONS: While there was a range in diagnostic accuracy, the highest score of 91% and the identification of common sources of error suggest that histopathologic categorization of angioinvasive fungal infections can frequently be performed. However, accurate identification is not always possible given common pitfalls in diagnosis. In addition, standardized and clinically useful reporting should be considered.
METHODS: This study characterized the diagnosis of angioinvasive fungal infections by light microscopy at a single academic institution over an 11-year period. Subsequently, the accuracy of blinded reclassification by virtual microscopy was measured.
RESULTS: Seventy-six specimens with hematoxylin-eosin slides were obtained from 33 patients. The mean diagnostic accuracy of dermatopathologists in differentiating mucormycosis, hyalohyphomycosis, and phaeohyphomycosis based on blinded reclassification via virtual microscopy was 74%, with a range of 65%-91%.
CONCLUSIONS: While there was a range in diagnostic accuracy, the highest score of 91% and the identification of common sources of error suggest that histopathologic categorization of angioinvasive fungal infections can frequently be performed. However, accurate identification is not always possible given common pitfalls in diagnosis. In addition, standardized and clinically useful reporting should be considered.