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XN-1000 Hematology Analyzer as an Alternative to Flow Cytometry for Measuring Residual Cells in Blood Components

  • Anita Siller (Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH) ;
  • Lisa Seekircher (Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck) ;
  • Daniela Schmidt (Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH) ;
  • Lena Tschiderer (Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck) ;
  • Peter Willeit (Institute of Clinical Epidemiology, Public Health, Health Economics, Medical Statistics and Informatics, Medical University of Innsbruck) ;
  • Harald Schennach (Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH) ;
  • Marco Amato (Central Institute for Blood Transfusion and Immunology, University Hospital of Innsbruck, Tirol Kliniken GmbH)
  • Received : 2024.08.18
  • Accepted : 2025.01.07
  • Published : 2025.07.01

Abstract

Background: Measuring residual cells in blood products is legally required for monitoring the manufacturing process and ensuring recipient safety. We compared the accuracy and performance of the two methodologies. Methods: Residual white blood cells (rWBCs), red blood cells (rRBCs), and platelets (rPLTs) were measured in RBC concentrates (rWBCs), fresh frozen plasma (rWBCs, rRBCs, and rPLTs), and PLT concentrates (rWBCs and rRBCs) using the Sysmex XN-1000 hematology analyzer (Sysmex, Kobe, Japan) equipped with Blood Bank mode and standard flow cytometry (fluorescence-activated cell sorting; FACS). Results: rWBC counts in RBC concentrates and plasma were similar between XN-1000 and FACS. In pooled pathogen-inactivated PLT concentrates, XN-1000 yielded higher rWBC counts. Correlations between XN-1000 and FACS were moderate for rWBCs (0.42, 95% confidence interval: 0.15-0.69) in RBC inline-filtrated WBC-depleted RBC concentrates. In plasma, correlations were high for rWBC, rRBC, and rPLT counts, with Spearman correlation coefficients of 0.82-0.97. In pathogen-inactivated PLT concentrates, correlations were moderate for rWBCs (0.58, 0.33-0.84) and rRBCs (0.61, 0.35-0.87) in pooled samples but not significant in apheresis-derived samples. Median differences between FACS and XN-1000 were generally low, but XN-1000 overestimated residual cell counts in a subset of measurements. Residual cell cut-off values were surpassed in >90% of RBC concentrates, plasma, and apheresis pathogen-inactivated PLT concentrates using both methods. In pooled pathogen-inactivated PLT concentrates, 91.2% and 70.6% surpassed the cut-off using FACS and XN-1000, respectively. Conclusions: Sysmex XN-1000 is suitable for residual cell measurements in RBC concentrates and plasma, with some limitations for PLT concentrates.

Keywords

Acknowledgement

We thank all employees of the manufacturing department of the Central Institute for Blood Transfusion and Immunology.

References

  1. Hervig TA, Doughty HA, Cardigan RA, Apelseth TO, Hess JR, Noorman F et al., Re-introducing whole blood for transfusion: considerations for blood providers. Vox Sang 2021;116:167–74. https://doi.org/10.1111/vox.12998
  2. Pietersz RN, van der Meer PF, Seghatchian MJ. Update on leucocyte depletion of blood components by filtration. Transfus Sci 1998;19:321–8. https://doi.org/10.1016/S0955-3886(98)00056-3
  3. Mack S and Vassallo RR. Component residual white blood cell counting made easy? Transfusion 2020;60:4–6. https://doi.org/10.1111/trf.15642
  4. Elmakki EE, Madkhali MA, Oraibi O, Alqassimi S, Saleh E. Transfusionassociated graft-versus-host disease in adults. Cureus 2023;15: e44148. https://doi.org/10.7759/cureus.44148
  5. Santana JM and Dumont LJ. A flow cytometric method for detection and enumeration of low-level, residual red blood cells in platelets and mononuclear cell products. Transfusion 2006;46:966–72. https://doi.org/10.1111/j.1537-2995.2006.00829.x
  6. Cavagnetto C, Alejo Blanco R, McKenna H, Willmott L, Aydogdu E, Akinyemi N, et al. Residual red cells in blood components: a multisite study of fully automated enumeration using a hematology analyzer. Transfusion 2021;61:568–78. https://doi.org/10.1111/trf.16196
  7. Lippi G, Rossi R, Ippolito L, Zobbi V, Azzi D, Pipitone S, et al. Influence of residual platelet count on routine coagulation, factor VIII, and factor IX testing in postfreeze-thaw samples. Semin Thromb Hemost 2013;39: 834–9. https://doi.org/10.1055/s-0033-1356572
  8. European Directorate for the Quality of Medicines and Healthcare of the Council of Europe. Guide to the preparation, use and quality assurance of blood components. 2023. https://www.edqm.eu/en/blood-guide (Updated on Aug 2024).
  9. Dzik S. Principles of counting low numbers of leukocytes in leukoreduced blood components. Transfus Med Rev 1997;11:44–55. https://doi.org/10.1016/S0887-7963(97)80009-0
  10. Masse M, Naegelen C, Pellegrini N, Segier JM, Marpaux N, Beaujean F. Validation of a simple method to count very low white cell concentrations in filtered red cells or platelets. Transfusion 1992;32:565–71. https://doi.org/10.1046/j.1537-2995.1992.32692367203.x
  11. Blanco RA, Cavagnetto C, Willmott L, Aydogdu E, Akinyemi N, Standring H, et al. The use of a hematology analyzer with a new generation of software as an alternative to flow cytometry for enumerating residual white blood cells in blood components. Transfusion 2020;60:155–64. https://doi.org/10.1111/trf.15606
  12. Petersson A and Ekblom K. Methods for counting residual leukocytes in leukocyte-depleted plasma-a comparison between a routine hematology instrument, the Nageotte chamber, flow cytometry, and a fluorescent microscopy analyzer. Transfusion 2017;57:1192–8. https://doi.org/10.1111/trf.14007
  13. Dzik S, Moroff G, Dumont L. A multicenter study evaluating three methods for counting residual WBCs in WBC-reduced blood components: Nageotte hemocytometry, flow cytometry, and microfluorometry. Transfusion 2000;40:513–20. https://doi.org/10.1046/j.1537-2995.2000.40050513.x
  14. Frey ME, Petersen HC, Gerke O. Nonparametric limits of agreement for small to moderate sample sizes: a simulation study. Stats 2020;3:343–55. https://doi.org/10.3390/stats3030022
  15. Twomey PJ. How to use difference plots in quantitative method comparison studies. Ann Clin Biochem 2006;43:124–9. https://doi.org/10.1258/000456306776021616
  16. Lagerberg JW and de Korte D. Improved accuracy in counting residual white blood cells in red cell concentrates using new blood bank mode software of SYSMEX XN-1000 hematology analyzer. Transfusion 2020; 60:2456–7. https://doi.org/10.1111/trf.15985
  17. Valina O, Vankova I, Mintzas K, Knappova K, Gasova Z. Validation of the Sysmex XN analyser and Blood Bank mode for the quality and safety of donor blood and transfusion products. Transfus Med 2024;34:30–8. https://doi.org/10.1111/tme.13028
  18. Arisawa F, Wakamoto S, Akino M, Ikuta K, Kino S. Evaluation of the Blood Bank mode software of Sysmex XN-1000TM hematology analyzer for counting residual red blood cells and platelets in platelet concentrates, and residual white blood cells in leukocyte-reduced whole blood. Sysmex J Int 2021;31:18–27.
  19. Genicco A, Rychlicki C, Da Lio L, Montanari M, Moretti M. Verification of leukocyte contamination in leucodepleted blood components using the Blood Bank mode of the Sysmex XN-1000 hematology analyzer. Riv Ital Med Lab 2023;19:30–40.