Authors
Hongkyung Kim, Oh Joo Kweon, Sumi Yoon, Yong Kwan Lim, Bohyun Kim
Published in
Annals of laboratory medicine. Aug 19, 2026. Epub Aug 19, 2026.
Abstract
Digital morphology (DM) analyzers are increasingly used for white blood cell (WBC) differential counting in routine hematology laboratories, necessitating tailored external quality assessment (EQA) schemes. We evaluated EQA-relevant practical considerations for DM analyzer-based WBC differentials.
Fifteen clinical laboratories participated in a multicenter EQA simulation using five centrally prepared, unstained peripheral blood smear samples. Institution-level post-classification results were analyzed as the primary outcomes. Exploratory analyses were performed using pre-classification and manual microscopic differentials. Examiner-level variability within institutions was evaluated, along with the distributions of WBC-classified and unclassified images following examiner verification.
Most participating laboratories used DM analyzers primarily for screening WBC differentials, with predefined criteria for manual microscopic reviews, particularly when abnormal cell populations were noted. Inter-institutional and examiner-level variability were most pronounced for morphologically similar cell classes. Post-classification results were generally comparable with those of manual differentials across most cell classes. The proportion of unclassified images (including artifacts) increased, suggesting that operational and sample-related factors influenced the interpretation of the EQA results.
We identified key practical considerations for the EQA of DM analyzer-based WBC differential counting. An appropriate EQA design should incorporate clinically relevant abnormal cell populations and challenging sample types; data interpretation should extend beyond standard deviation index-based metrics to address abnormal cell detection. The overall concordance between post-classification results and manual differentials supports the importance of periodic verification, and slide quality should be considered when implementing DM analyzer-based EQA programs.
PMID:
42613184
Bibliographic data and abstract were imported from PubMed on 19 Aug 2026.
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