Performance evaluation of digital morphology analyzer CellaVision DM1200

Introduction: For white blood cell (WBC) differentials, manual counting is the standard method, but blood smears can now be automatically analyzed thanks to advancements in digital imaging technologies. In this study, we aimed to evaluate the performance of CellaVision DM1200 on white blood cell differentials and erythrocyte abnormalities, using blood smears from normal and abnormal samples. The pre-classification and reclassification of WBCs by CellaVision were compared to the reference manual count. Methods: Our evaluation for CELLAVISION DM1200 took several steps initiating by precision which includes repeatability and reproducibility. The accuracy was determined by comparison of results between the optical microscope and CELLAVISION DM1200, using Passing Bablok regression analysis. We also studied the ability of the CellaVision DM1200 system to identify clinically important abnormalities compared with manual microscopic differential counting by calculating sensitivity and specificity. Red blood cells were also evaluated by studying sensitivity and specificity. Results: Repeatability and reproducibility showed acceptable results. Regarding the comparability between the optical microscope and CELLAVISION DM1200, post-classification showed good results compared to pre-classification. Evaluation of color, size, and morphology abnormalities of RBCs showed good results. Conclusion: After verification, the CELLAVISION DM1200's performance for WBC differential and detection of abnormalities of RBCs appears to be satisfactory, even in abnormal samples. However, CELLAVISION DM1200 cannot fully replace manual WBC differential counting, reclassification and slide review are still required in abnormal samples.

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Publication Details

Journal
GSC Advanced Research and Reviews
Published
2025-04-15
DOI
https://doi.org/10.30574/gscarr.2025.23.1.0108
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
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article

Performance evaluation of digital morphology analyzer CellaVision DM1200

Salma Rouhi, Sanae Sayagh, Wafa Quiddi, Ouijdane Kajjoune et al.
GSC Advanced Research and Reviews
Industrial Vision Systems and Defect Detection
article

Performance evaluation of digital morphology analyzer CellaVision DM1200

Salma Rouhi, Sanae Sayagh, Wafa Quiddi, Ouijdane Kajjoune, Hajiba Azza
article en

Abstract

Introduction: For white blood cell (WBC) differentials, manual counting is the standard method, but blood smears can now be automatically analyzed thanks to advancements in digital imaging technologies. In this study, we aimed to evaluate the performance of CellaVision DM1200 on white blood cell differentials and erythrocyte abnormalities, using blood smears from normal and abnormal samples. The pre-classification and reclassification of WBCs by CellaVision were compared to the reference manual count. Methods: Our evaluation for CELLAVISION DM1200 took several steps initiating by precision which includes repeatability and reproducibility. The accuracy was determined by comparison of results between the optical microscope and CELLAVISION DM1200, using Passing Bablok regression analysis. We also studied the ability of the CellaVision DM1200 system to identify clinically important abnormalities compared with manual microscopic differential counting by calculating sensitivity and specificity. Red blood cells were also evaluated by studying sensitivity and specificity. Results: Repeatability and reproducibility showed acceptable results. Regarding the comparability between the optical microscope and CELLAVISION DM1200, post-classification showed good results compared to pre-classification. Evaluation of color, size, and morphology abnormalities of RBCs showed good results. Conclusion: After verification, the CELLAVISION DM1200's performance for WBC differential and detection of abnormalities of RBCs appears to be satisfactory, even in abnormal samples. However, CELLAVISION DM1200 cannot fully replace manual WBC differential counting, reclassification and slide review are still required in abnormal samples.

GSC Advanced Research and ReviewsVol. 23(1)
Centre Hospitalier Universitaire Mohammed VI (MA)
Openalex Percentile: Top 90%
Industrial Vision Systems and Defect Detection
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