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pISSN 2950-9114 eISSN 2950-9122
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Original Article

Lab Med Qual Assur 2023; 45(1): 18-24

Published online March 31, 2023


Copyright © Korean Association of External Quality Assessment Service.

Quality Assessment of Wright-Giemsa Staining in Digital Cell Imaging

Chang-Hun Park1 and Heeyoung Kwon2

1Department of Laboratory Medicine and Genetics, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine; 2Clinical Research Support Center, Industry-Academy Cooperation Foundation, Masan University, Changwon, Korea

Correspondence to:Chang-Hun Park
Department of Laboratory Medicine and Genetics, Samsung Changwon Hospital, 158 Paryong-ro, Masanhoewon-gu, Changwon 51353, Korea
Tel +82-55-233-6097
E-mail ch.park@skku.edu

Received: November 25, 2022; Revised: December 27, 2022; Accepted: December 28, 2022

This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.


Background: With the introduction of digital cell image analyzer and artificial intelligence, automatic cell image identification and disease diagnosis has become possible. However, an inappropriately stained image can cause errors in cell recognition in digital cell imaging. In this study, we aimed to determine the quality index for the quality control of the staining method.
Methods: The differences (calculated values, VALCELL) in cell percentages (image counts [IMGCELL] and complete blood count with differential count [DIFFCELL]) between the image analyzer and the automatic hematology analyzer were calculated from the appropriately stained smears. Then, a Levey-Jennings control chart was plotted using the VALCELL and the inappropriately stained smears were evaluated against the Levey-Jennings control chart.
Results: The allowable ranges from the Levey-Jennings control charts for neutrophils and lymphocytes were –5.50 to 10.46 and –11.56 to 6.92, respectively. From the Levey-Jennings control charts, 33.3% (5/15) were outside the allowable ranges and considered inappropriately stained.
Conclusions: The differences in the cell percentages between the image analyzer and the automatic hematology analyzer may be used to detect inappropriately stained smears.

Keywords: Wright-Giemsa stain, Digital cell imaging analyzer, Quality assessment

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