Izvestiya of Saratov University.


ISSN 1817-3020 (Print)
ISSN 2542-193X (Online)

For citation:

Nikitin S. I., Ustinov V. D., Tsybrov E. G., Priezzhev A. V. Improved Data Processing Algorithm for Laser Ektacytometry of Red Blood Cells. Izvestiya of Saratov University. Physics , 2017, vol. 17, iss. 3, pp. 150-157. DOI: 10.18500/1817-3020-2017-17-3-150-157

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Full text:
(downloads: 113)

Improved Data Processing Algorithm for Laser Ektacytometry of Red Blood Cells

Nikitin Sergey Iur'evich, Lomonosov Moscow State University
Ustinov Vladislav Dmitrievich, Lomonosov Moscow State University
Tsybrov Evgeny Germanovich, Lomonosov Moscow State University
Priezzhev Alexander Vasil'evich, Lomonosov Moscow State University

Background and Objectives: Red blood cells deliver oxygen to organs and tissues. In case of tropical malaria, blood anemia, diabetes mellitus and many other diseases, the cells become corrupted. These pathologies lead in altering deformability of the cells, i.e ability to change their shape under external forces. Precise measurement of cell’s deformability gives important medical information which helps to cure and monitor the most wide spread diseases more effectively. Thus, to improve the accuracy of modern techniques measuring the deformability of red blood cells is a task of great importance. The goal of this study is to enhance precision of laser diffractometry which is one of the basic tools for analyzing the deformability of red blood cells. Materials and Methods: The problem of measuring the deformability of red blood cells by laser diffraction in a shear flow (ektacytometry) is considered. Improved theoretical analysis of the laser beam scattering by inhomogeneous ensemble of particles mimicking red blood cells in a shear flow is performed. Results: New diffractometric equations establishing relations between characteristics of red blood cells and parameters of the diffraction pattern were derived. New data processing algorithm is presented for measuring the average deformability, as well as width and asymmetry of the erythrocyte deformability distribution. The numerical simulation of a bimodal ensemble of red blood cells was used for the algorithm verification. Conclusion: It has been shown that the new algorithm provides higher cells’s deformability measurement accuracy compared to the algorithm developed earlier. 

  1. Mokken F. C., Kedaria M., Henny C. P., Hardeman M. R., Gelb A. W. The clinical importance of erythrocyte deformability, a hemorheological parameter. Annals of Hematology, 1992, vol. 64, no. 3, pp. 113–122.
  2. Renoux C., Parrow N., Faes C., Joly P., Hardeman M., Tisdale J., Levine M., Garnier N., Bertrand Y., Kebaili K., Cuzzubbo D., Cannas G., Martin C., Connes P. Importance of methodological standardization for the ektacytometric measures of red blood cell deformability in sickle cell anemia. Clinical Hemorheology and Microcirculation, 2016, vol. 62, pp. 173–179. DOI: https://doi.org/10.3233/CH-151979
  3. Azhermacheva M. N., Plotnikov D. M., Aliev O. I., Alifi rova V. M., Plotnikov M. B., Burkova K. I. Reologicheskie svoistva krovi v ostreishii period ishemicheskogo insul’ta i ikh vzaimosviaz’ so stepen’iu tiazhesti nevrologicheskikh narushenii [The rheological properties of blood in the most acute stage of ischemic stroke and their relation to the severity of neurological impairment]. Biulleten’ Sibirskoi Meditsiny, 2013, vol. 12, no. 5, pp. 5–12 (in Russian).
  4. Musielak M. Red blood cell-deformability measurement: Review of techniques. Clinical Hemorheology and Microcirculation, 2009, vol. 42, pp. 47–64. DOI: https://doi.org/10.3233/CH-2009-1187
  5. Kim Yo., Kim K., Park Y. Measurement Techniques for Red Blood Cell Deformability: Recent Advances. Chapter 10. In: Blood Cell – An Overview of Studies in Hematology. Ed. Terry E. Moschandreou. 2012, pp. 167–194. DOI: https://doi.org/10.5772/50698
  6. Kim J., Lee H., Shin S. Advances in the measurement of red blood cell deformability: A brief review. Journal of Cellular Biotechnology, 2015, vol. 1, pp. 63–79. DOI: https://doi.org/10.3233/JCB-15007
  7. Baskurt O. K., Boynard M., Cokelet G. C., Connes Ph., Cooke B. M., Forconi S., Liao F., Hardeman M. R., Jung F., Meiselman H. J., Nash G., Nemeth N., Neu B., Sandhagen B., Shin S., Thurston G., Wautier J. New guidelines for hemorheological laboratory techniques. Clinical Hemorheology and Microcirculation, 2009, vol. 42, pp. 75–97.
  8. Firsov N. N., Priezzhev A. V., Klimova N. V., Tyurina A. Yu. Fundamental laws of the deformational behavior of erythrocytes in shear flow. Journal of Engineering Physics and Thermophysics, 2006, vol. 79, no. 1, pp. 118–124.
  9. Vialiat A., Abkarian M. Red blood cell: from its mechanics to its motion in shear fl ow. International Journal of Laboratory Hematology, 2014, vol. 36, pp. 237–243.
  10. Bessis M., Mohandas N. A diffractometric method for the measurement of cellular deformability. Blood Cells, 1975, vol. 1, pp. 307–313.
  11. Hardeman M. R., Goedhart P. T., Dobbe J. G. G., Lettinga K. P. Laser-assisted optical rotational cell analyzer (LORCA). A new instrument for measurement of various structural hemorheological parameters. Clinical Hemorheology and Microcirculation, 1994, vol. 14, pp. 605–618.
  12. Firsov N. N., Dzhanashiya P. Kh. Vvedeniye v eksperimental’nuyu i klinicheskuyu gemoreologiyu [Introduction to clinical experimental hemorheology]. Moscow, Izd-vo GOU VPO «RGMU» [Russian State Medical University], 2004. 280 p. (in Russian).
  13. Shin S., Ku Yu., Park M., Jang J., Suh J. Rapid celldeformability sensing system based on slit-fl ow laser diffractometry with decreasing pressure differential. Biosensors and Bioelectronics, 2005, vol. 20, pp. 1291–1297.
  14. RHEOSCAN. Available at: http://www.rheoscan.com/main/main.html (accessed 15 January 2017).
  15. Baskurt O. K., Hardeman M. R., Uyuklu M., Ulker P., Cengiz M., Nemeth N., Shin S., Alexy T., Meiselman H. J. Comparison of three commercially available ektacytometers with different shearing geometries. Biorheology, 2009, vol. 46, pp. 251–264. DOI: https://doi.org/10.3233/BIR-2009-0536
  16. Dobbe J. G. G., Hardeman M. R., Streekstra G. J., Starckee J., Ince C., Grimbergen C. A. Analyzing red blood cell-deformability distributions. Blood Cells, Molecules, and Diseases, 2002, vol. 28, p. 373.
  17. Nikitin S. Y., Priezzhev A. V., Lugovtsov A. E., Ustinov V. D. Measuring skewness of red blood cell deformability distribution by laser ektacytometry. Quantum Electronics, 2014, vol. 44, no. 8, pp. 774–778.
  18. Nikitin S. Yu., Priezzhev A. V., Lugovtsov A. E., Ustinov V. D., Razgulin A. V. Laser ektacytometry and evaluation of statistical characteristics of inhomogeneous ensembles of red blood cells. JQSRT, 2014, vol. 146, pp. 365–375.
  19. Nikitin S. Yu., Lugovtsov A. E., Ustinov V. D., Lin M. D., Priezzhev A. V. Study of laser beam scattering by inhomogeneous ensemble of red blood cells in a shear fl ow. JIOHS, 2015, vol. 8, pp. 1550031. DOI: https://doi.org/10.1142/S1793545815500315
  20. Nikitin S. Yu., Ustinov V. D., Yurchuk Yu. S., Lugovtsov A. E., Lin M. D., Priezzhev A. V. New diffractometric equations and data processing algorithm for laser ektacytometry of red blood cells. JQSRT, 2016, vol. 178, pp. 315–324.
  21. Nikitin S. Yu., Priezzhev A. V., Lugovtsov A. E. Analysis of laser beam scattering by an ensemble of particles modeling red blood cells in ektacytometer. JQSRT, 2013, vol. 121, pp. 1–8.
Краткое содержание:
(downloads: 98)
На сайте журнала 05.04.2023 запланированы технические работы. В это время сайт может быть недоступен. С уважением, администрация сайта.