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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

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1437-4331
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Volume 56, Issue 1

Issues

Performance of automated digital cell imaging analyzer Sysmex DI-60

Hyeong Nyeon Kim
  • Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Republic of Korea
  • Other articles by this author:
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/ Mina Hur
  • Corresponding author
  • Department of Laboratory Medicine, Konkuk University School of Medicine, Konkuk University Medical Center, 120-1, Neungdong-ro, Hwayang-dong, Gwangjin-gu, Seoul 05030, Republic of Korea, Phone: +82-2-2030-5581, Fax: +82-2-2636-6764
  • Email
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/ Hanah Kim
  • Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Republic of Korea
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/ Seung Wan Kim
  • Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Republic of Korea
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/ Hee-Won Moon
  • Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Republic of Korea
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/ Yeo-Min Yun
  • Department of Laboratory Medicine, Konkuk University School of Medicine, Seoul, Republic of Korea
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Published Online: 2017-06-16 | DOI: https://doi.org/10.1515/cclm-2017-0132

Abstract

Background:

The Sysmex DI-60 system (DI-60, Sysmex, Kobe, Japan) is a new automated digital cell imaging analyzer. We explored the performance of DI-60 in comparison with Sysmex XN analyzer (XN, Sysmex) and manual count.

Methods:

In a total of 276 samples (176 abnormal and 100 normal samples), white blood cell (WBC) differentials, red blood cell (RBC) classification and platelet (PLT) estimation by DI-60 were compared with the results by XN and/or manual count. RBC morphology between pre-classification and verification was compared according to the ICSH grading criteria. The manual count was performed according to the Clinical and Laboratory Standards Institute guidelines (H20-A2).

Results:

The overall concordance between DI-60 and manual count for WBCs was 86.0%. The agreement between DI-60 pre-classification and verification was excellent (weighted κ=0.963) for WBC five-part differentials. The correlation with manual count was very strong for neutrophils (r=0.955), lymphocytes (r=0.871), immature granulocytes (r=0.820), and blasts (r=0.879). RBC grading showed notable differences between DI-60 and manual counting on the basis of the ICSH grading criteria. Platelet count by DI-60 highly correlated with that by XN (r=0.945). However, DI-60 underestimated platelet counts in samples with marked thrombocytosis.

Conclusions:

The performance of DI-60 for WBC differential, RBC classification, and platelet estimation seems to be acceptable even in abnormal samples with improvement after verification. DI-60 would help optimize the workflow in hematology laboratory with reduced manual workload.

Keywords: comparison; manual count; performance; Sysmex DI-60; Sysmex XN

References

  • 1.

    Hur M, Cho JH, Kim H, Hong MH, Moon HW, Yun YM, et al. Optimization of laboratory workflow in clinical hematology laboratory with reduced manual slide review: comparison between Sysmex XE-2100 and ABX Pentra DX120. Int J Lab Hematol 2011;33:434–40.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 2.

    Clinical and Laboratory Standards Institute (CLSI). Reference leukocytes (WBC) differential count (proportional) and evaluation of instrumental methods: approval standard, 2nd ed. CLSI Document H20-A2. Wayne, PA: CLSI, 2007.Google Scholar

  • 3.

    Rumke CL. Imprecision of ratio-derived differential leukocyte counts. Blood Cells 1985;11:311–5.PubMedGoogle Scholar

  • 4.

    Da Costa L. Digital image analysis of blood cells. Clin Lab Med 2015;35:105–22.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 5.

    Perel ID, Herrmann NR, Watson LJ. Automated differential leucocyte counting by the Geometric Data Hematrak system: eighteen months experience in a private pathology laboratory. Pathology 1980;12:449–60.CrossrefGoogle Scholar

  • 6.

    Kratz A, Bengtsson HI, Case JE, Keefe JM, Beatrice GH, Grzybek DY, et al. Performance evaluation of the CellaVision DM96 system: WBC differentials by automated digital image analysis supported by an artificial neural network. Am J Clin Pathol 2005;127:770–81.Google Scholar

  • 7.

    Smits SM, Leyte A. Clinical performance evaluation of the CellaVision Image Capture System in the white blood cell differential on peripheral blood smears. J Clin Pathol 2014;67:168–72.PubMedCrossrefWeb of ScienceGoogle Scholar

  • 8.

    VanVranken SJ, Patterson ES, Rudmann SV, Waller KV. A survey study of benefits and limitations of using CellaVision DM96 for peripheral blood differentials. Clin Lab Sci 2014;27:32–9.PubMedGoogle Scholar

  • 9.

    Tabe Y, Yamamoto T, Maenou L, Nakai R, Idei M, Horii T, et al. Performance evaluation of the digital cell imaging analyzer DI-60 integrated into the fully automated Sysmex XN hamatology analyzer system. Clin Chem Lab Med 2015;53:281–9.Google Scholar

  • 10.

    Briggs C, Longair I, Slavik M, Thwaite K, Mills R, Thavaraja V, et al. Can automated blood film analysis replace the manaul differential? An evaluation of the CellaVision DM96 autoamted image analysis system. Int J Lab Hematol 2009;31:48–60.PubMedCrossrefGoogle Scholar

  • 11.

    Kim H, Hur M, Choi SG, Oh KM, Moon HW, Yun YM. Comparison of white blood cell counts by WNR, WDF, and WPC channels in Sysmex XN hematology analyzer. Int J Lab Hematol 2015;37:869–75.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 12.

    Palmer L, Briggs C, Mcfadden S, Zini G, Burthem J, Rozenberg G, et al. ICSH recommendations for the standardization of nomenclature and grading of peripheral blood cell morphological features. Int J Lab Hematol 2015;37:287–303.Web of ScienceCrossrefPubMedGoogle Scholar

  • 13.

    Maedel LB, Doig K. Examination of the peripheral blood film and correlation with the complete blood count. In: Rodak’s hematology: Clinical principles and application, 5th ed. St. Louis, MO: Saunders, 2015:242.Google Scholar

  • 14.

    McHugh ML. Interrater reliability: the kappa statistic. Biochem Med 2012;22:276–82.Google Scholar

  • 15.

    Mukaka MM. A guide to appropriate use of correlation coefficient in medical research. Malawi Med J 2012;24:69–71.PubMedGoogle Scholar

  • 16.

    Billard M, Lainey E, Armoogum P, Alberti C, Fenneteau O, Da Costa L. Evaluation of the CellaVision DM automated microscope in pediatrics. Int J Lab Hematol 2010;32:530–8.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 17.

    Cornet E, Perol JP, Troussard X. Performance evaluation and relevance of the CellaVision DM96 system in routine analysis and in patients with malignant hematological diseases. Int J Lab Hematol 2008;30:536–42.Web of SciencePubMedGoogle Scholar

  • 18.

    Park SH, Park CJ, Choi MO, Kim MJ, Cho YU, Jang S, et al. Automated digital cell morphology identification system (CellaVision DM96) is very useful for leukocyte differentials in specimens with qualitative or quantitative abnormalities. Int J Lab Hematol 2013;35:517–27.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 19.

    International Council for Standardization in Haematology, Writing Group, Briggs C, Culp N, Davis B, D’onofrio G, Zini G, Machin SJ, et al. ICSH guidelines for the evaluation of blood cell analysers including those used for differential leucocyte and reticulocyte counting. Int J Lab Hematol 2014;36:613–27.CrossrefPubMedWeb of ScienceGoogle Scholar

  • 20.

    Eilertsen H, Henriksson CE, Hagve TA. The use of CellsVision DM96 in the verification of the presence of blasts in samples flagged by the sysmex XE-5000. Int J Lab Hematol 2017 Mar 23. doi: 10.1111/ijlh.12648. [Epub ahead of print]Google Scholar

  • 21.

    Horn CL, Mansoor A, Wood B, Nelson H, Higa D, Lee LH, et al. Performance of the CellaVision DM96 system for detecting red blood cell morphologic abnormalities. J Pathol Inform 2015;6:11.PubMedCrossrefGoogle Scholar

  • 22.

    Hervent AS, Godefroid M, Cauwelier B, Billiet J, Emmerechts J. Evaluation of schistocyte analysis by a novel automated digital cell morphology application. Int J Lab Hematol 2015;37:588–96.PubMedCrossrefWeb of ScienceGoogle Scholar

  • 23.

    Egelé A, Gelder WV, Riedl J. Automated detection and classification of schistocytes by a novel red blood cell module using digital imaging/microscopy. J Hematol 2015;4:184–6.CrossrefGoogle Scholar

  • 24.

    Criel M, Godefroid M, Deckers B, Devos H, Cauwelier B, Emmerechts J. Evaluation of the red blood cell adavanced software application on the CellaVision DM96. Int J Lab Hematol 2016;38:366–74.CrossrefGoogle Scholar

  • 25.

    Egelé A, Stouten K, van der Heul-Nieuwenhuijsen L, de Bruin L, Teuns R, van Gelder W et al. Classification of several morphological red blood cell abnormalities by DM96 digital imaging. Int J Lab Hematol 2016;38:e98–101.PubMedCrossrefWeb of ScienceGoogle Scholar

  • 26.

    Gao Y, Mansoor A, Wood B, Nelson H, Higa D, Naugler C. Platelet count estimation using the CellaVision DM96 system. J Pathol Inform 2013;4:16.CrossrefPubMedGoogle Scholar

About the article

Corresponding author: Mina Hur, MD, PhD, Department of Laboratory Medicine, Konkuk University School of Medicine, Konkuk University Medical Center, 120-1, Neungdong-ro, Hwayang-dong, Gwangjin-gu, Seoul 05030, Republic of Korea, Phone: +82-2-2030-5581, Fax: +82-2-2636-6764


Received: 2017-02-16

Accepted: 2017-05-01

Published Online: 2017-06-16

Published in Print: 2017-11-27


Author contributions: Kim HN collected the samples, analyzed the data, and wrote the draft; Kim H analyzed the data; Hur M conceived the study, analyzed the data, and finalized the draft; Kim SW collected the samples; Moon HW and Yun YM discussed the data and reviewed the manuscript. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

Research funding: This work was supported by Konkuk University Medical Center Research Grant 2017.

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.


Citation Information: Clinical Chemistry and Laboratory Medicine (CCLM), Volume 56, Issue 1, Pages 94–102, ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: https://doi.org/10.1515/cclm-2017-0132.

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