Related Experiment Video
Updated: Aug 20, 2026
Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
Published on: March 22, 2022
Digital Morphology Analyzer-Based White Blood Cell Differentials: Practical Considerations for External Quality
Hongkyung Kim1, Oh Joo Kweon2, Sumi Yoon2
1Department of Laboratory Medicine, Chung-Ang University Hospital, Chung-Ang University College of Medicine, Seoul, Korea.
Background:
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.
Methods:
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.
Results:
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.
Conclusions:
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.
