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논문 기본 정보

자료유형
학술저널
저자정보
Park Seong Jun (Department of Laboratory Medicine Korea University Guro Hospital Seoul Korea) Yoon Jung (Department of Laboratory Medicine Korea University Guro Hospital Seoul Korea) 권정아 (Department of Laboratory Medicine Korea University Guro Hospital Seoul Korea) Yoon Soo-Young (Department of Laboratory Medicine Korea University Guro Hospital Seoul Korea)
저널정보
대한진단검사의학회 Annals of Laboratory Medicine Annals of Laboratory Medicine 제41권 제1호
발행연도
2021.1
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44 - 50 (7page)

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Background: The Advanced RBC Application of the CellaVision DM9600 system (CellaVision AB, Lund, Sweden) automatically characterizes and classifies red blood cells (RBCs) into 21 morphological categories based on their size, color, shape, and inclusions. We evaluated the diagnostic performance of the CellaVision Advanced RBC Application with respect to the classification and grading of RBC morphological abnormalities in accordance with the 2015 International Council for Standardization in Haematology (ICSH) guidelines. Methods: A total of 223 samples, including 123 with RBC morphological abnormalities and 100 from healthy controls, were included. Seven RBC morphological abnormalities and their grading obtained with CellaVision DM9600 pre- and post-classification were compared with the results obtained using manual microscopic examination. The grading cut-off percentages were determined in accordance with the 2015 ICSH guidelines. The sensitivity and specificity of the CellaVision DM9600 system were evaluated using the manual microscopic examination results as a true positive. Results: In pre-classification, >90% sensitivity was observed for target cells, tear drop cells, and schistocytes, while >90% specificity was observed for acanthocytes, spherocytes, target cells, and tear drop cells. In post-classification, the detection sensitivity and specificity of most RBC morphological abnormalities increased, except for schistocytes (sensitivity) and acanthocytes (specificity). The grade agreement rates ranged from 35.9% (echinocytes) to 89.7% (spherocytes) in pre-classification and from 46.2% (echinocytes) to 90.1% (spherocytes) in post-classification. The agreement rate of samples with within-one grade difference exceeded 90% in most categories, except for schistocytes and echinocytes. Conclusions: The Advanced RBC Application of CellaVision DM9600 is a valuable screening tool for detecting RBC morphological abnormalities.
#Red blood cell #Morphology #Advanced RBC Application #CellaVision DM9600 #International Council for Standardization in Haematology guidelines

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참고문헌 (15)

참고문헌 신청
Stouten K / 2015 / Examination of peripheral blood smears: performance evaluation of a digital microscope system using a large-scale leukocyte database / Int J Lab Hematol 37:e137~e140 google schola Lee LH / 2013 / Performance of CellaVision DM96 in leukocyte classification / J Pathol Inform 4:14 google schola Cornet E / 2008 / Performance evaluation and relevance of the CellaVision DM96 system in routine analysis and in patients with malignant hematological diseases / Int J Lab Hematol 30:536~542 google schola Kratz A / 2005 / Performance evaluation of the CellaVision DM96 system: WBC differentials by automated digital image analysis supported by an artificial neural network / Am J Clin Pathol 124:770~781 google schola Criel M / 2016 / Evaluation of the red blood cell advanced software application on the CellaVision DM96 / Int J Lab Hematol 38:366~374 google schola

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