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Performance of digital morphology analyzer CellaVision DC-1

Gun-Hyuk Lee, Sumi Yoon, Minjeong Nam, Hanah Kim, Mina Hur

2022Clinical Chemistry and Laboratory Medicine (CCLM)19 citationsDOIOpen Access PDF

Abstract

OBJECTIVES: CellaVision DC-1 (DC-1, Sysmex, Kobe, Japan) is a newly launched digital morphology analyzer that was developed mainly for small to medium-volume laboratories. We evaluated the precision, qualitative performance, comparison of cell counts between DC-1 and manual counting, and turnaround time (TAT) of DC-1. METHODS: Using five peripheral blood smear (PBS) slides spanning normal white blood cell (WBC) range, precision and qualitative performance of DC-1 were evaluated according to the Clinical and Laboratory Standards Institute (CLSI) EP15-A3, EP15-Ed3-IG1, and EP12-A2 guidelines. Cell counts of DC-1 and manual counting were compared according to the CLSI EP 09C-ED3 guidelines, and TAT of DC-1 was also compared with TAT of manual counting. RESULTS: DC-1 showed excellent precision (%CV, 0.0-3.5%), high specificity (98.9-100.0%), and high negative predictive value (98.4-100.0%) in 18 cell classes (12 WBC classes and six non-WBC classes). However, DC-1 showed 0% of positive predictive value in seven cell classes (metamyelocytes, myelocytes, promyelocytes, blasts, plasma cells, nucleated red blood cells, and unidentified). The largest absolute mean differences (%) of DC-1 vs. manual counting was 2.74. Total TAT (min:s) was comparable between DC-1 (8:55) and manual counting (8:55). CONCLUSIONS: This is the first study that comprehensively evaluated the performance of DC-1 including its TAT. DC-1 has a reliable performance that can be used in small to medium-volume laboratories for assisting PBS review. However, DC-1 may make unnecessary workload for cell verification in some cell classes.

Topics & Concepts

Cell countingPredictive valueNuclear medicinePeripheral bloodMedicineTurnaround timeBiomedical engineeringInternal medicineComputer scienceCancerOperating systemCell cycleClinical Laboratory Practices and Quality ControlDigital Imaging for Blood DiseasesCell Image Analysis Techniques
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