Quantitative Determination of Surface Morphology of Red Blood Cell

Abstract

In this study, the determination of the surface morphology of red blood cell (RBC) from interferogram image obtained by quantitative phase imaging (QPI) method is presented. QPI, is an optical measurement method frequently used in recent years, allows to obtain quantitative data for different samples (cell, thin film surface, etc.). Many measurement setups at the micrometer level and with nanometer precision have been designed for quantitative surface determination. Among these, white light diffraction phase microscopy (WDPM) is a design that combines the advantages of off-axis holography-specific speed and phase sensitivity associated with common path interferometry. Interferogram image of RBCs have been formed by the WDPM setup. Analysis of this image has been carried out by Fourier transform. As a result of this analysis, three-dimensional (3D), dynamic (observable from all angles) and height-known profiles of RBCs have been created. From the height profiles, the parameters related to the morphology of RBCs as the projected surface area (PSA), diameter (D), mean corpuscular volume (MCV) and total surface area occupied by the cell (SA), have been determined quantitatively. In addition, two-dimensional images, obtained by examining blood samples with light microscopy and scanning electron microscopy (SEM), have been compared with the data achieved by WDPM. The advantages and disadvantages of WDPM and light microscopy and SEM, which are commonly used in biomedical measurements, are discussed through the results. In this way, it was possible to see the difference between QPI and traditional methods used to imaging the cell surface.

Keywords

• quantitative phase imaging
• interferogram
• Fourier transform
• light microscope
• SEM

Supporting Institution

Turkish Scientific and Technical Research Council (TÜBİTAK)

Project Number

122E201

References

1. Ahmadzadeh, E., Jaferzadeh, K., Lee, J., & Moon, I. (2017). Automated three-dimensional morphology-based clustering of human erythrocytes with regular shapes: stomatocytes, discocytes, and echinocytes. Journal of Biomedical Optics, 22(7), 076015. https://doi.org/10.1117/1.jbo.22.7.076015
2. Bhaduri, B., Pham, H., Mir, M., & Popescu, G. (2012). Diffraction phase microscopy with white light. Optics Letters, 37(6), 1094–1096. http://www.ncbi.nlm.nih.gov/pubmed/23292428
3. Buys, A. V, Van Rooy, M.-J., Soma, P., Van Papendorp, D., Lipinski, B., & Pretorius, E. (2013). Changes in red blood cell membrane structure in type 2 diabetes: a scanning electron and atomic force microscopy study. Cardiovascular Diabetology, 12(1), 25. https://doi.org/10.1186/1475-2840-12-25
4. Cacace, T., Bianco, V., & Ferraro, P. (2020). Quantitative phase imaging trends in biomedical applications. Optics and Lasers in Engineering, 135(February), 106188. https://doi.org/10.1016/j.optlaseng.2020.106188
5. Curl, C. L., Bellair, C. J., Harris, T., Allman, B. E., Harris, P. J., Stewart, A. G., Roberts, A., Nugent, K. a., & Delbridge, L. M. D. (2005). Refractive index measurement in viable cells using quantitative phase-amplitude microscopy and confocal microscopy. Cytometry Part A, 65(1), 88–92. https://doi.org/10.1002/cyto.a.20I34
6. Dursun, A., Özder, S., & Ecevit, F. N. (2004). Continuous wavelet transform analysis of projected fringe patterns. Measurement Science and Technology, 15(9), 1768–1772. https://doi.org/10.1088/0957-0233/15/9/013
7. Edwards, C., Zhou, R., Hwang, S., McKeown, S. J., Wang, K., Bhaduri, B., Ganti, R., Yunker, P. J., Yodh, A. G., Rogers, J. A., Goddard, L. L., & Popescu, G. (2014). Diffraction phase microscopy: monitoring nanoscale dynamics in materials science [Invited]. Applied Optics, 53(27), G33. https://doi.org/10.1364/AO.53.000G33
8. Endo, T., Yasuno, Y., Makita, S., Itoh, M., & Yatagai, T. (2005). Profilometry with line-field Fourier-domain interferometry. Optics Express, 13(3), 695–701. https://doi.org/org/10.1364/OPEX.13.000695

9. Goldstein, J. I., Newbury, D. E., Michael, J. R., Ritchie, N. W. M., Scott, J. H. J., & Joy, D. C. (2018). Scanning Electron Microscopy and X-Ray Microanalysis. In Physicochemical Methods of Mineral Analysis. Springer New York. https://doi.org/10.1007/978-1-4939-6676-9
10. Jaferzadeh, K., & Moon, I. (2016). Human red blood cell recognition enhancement with three-dimensional morphological features obtained by digital holographic imaging. Journal of Biomedical Optics, 21(12), 126015. https://doi.org/10.1117/1.jbo.21.12.126015
11. Jaferzadeh, K., Sim, M. W., Kim, N. G., & Moon, I. K. (2019). Quantitative analysis of three-dimensional morphology and membrane dynamics of red blood cells during temperature elevation. Scientific Reports, 9(1), 1–9. https://doi.org/10.1038/s41598-019-50640-z
12. Lee, K., Kim, K., Jung, J., Heo, J., Cho, S., Lee, S., Chang, G., Jo, Y., Park, H., & Park, Y. (2013). Quantitative Phase Imaging Techniques for the Study of Cell Pathophysiology: From Principles to Applications. Sensors, 13(4), 4170–4191. https://doi.org/10.3390/s130404170
13. Leonhardt, K. (2005). Optical topometry of surfaces with locally changing materials, layers and contaminations Part 2: Fringe projection topometry. Journal of Modern Optics, 52(10), 1367–1384. https://doi.org/10.1080/09500340512331309057
14. Majeed, H., Ma, L., Lee, Y. J., Kandel, M., Min, E., Jung, W., Best-Popescu, C., & Popescu, G. (2018). Magnified Image Spatial Spectrum (MISS) microscopy for nanometer and millisecond scale label-free imaging. Optics Express, 26(5), 5423. https://doi.org/10.1364/OE.26.005423
15. Majeed, H., Sridharan, S., Mir, M., Ma, L., Min, E., Jung, W., & Popescu, G. (2017). Quantitative phase imaging for medical diagnosis. Journal of Biophotonics, 10(2), 177–205. https://doi.org/10.1002/jbio.201600113
16. Mir, M., Ding, H., Wang, Z., Reedy, J., Tangella, K., & Popescu, G. (2010). Blood screening using diffraction phase cytometry. Journal of Biomedical Optics, 15(2), 027016. https://doi.org/10.1117/1.3369965
17. Moon, I., Yi, F., Lee, Y. H., Javidi, B., Boss, D., & Marquet, P. (2013). Automated quantitative analysis of 3D morphology and mean corpuscular hemoglobin in human red blood cells stored in different periods. Optics Express, 21(25), 30947. https://doi.org/10.1364/oe.21.030947
18. Mukherjee, R., Saha, M., Routray, A., & Chakraborty, C. (2015). Nanoscale Surface Characterization of Human Erythrocytes by Atomic Force Microscopy: A Critical Review. IEEE Transactions on Nanobioscience, 14(6), 625–633. https://doi.org/10.1109/TNB.2015.2424674
19. Oprisan, B., Stoica, I., & Avadanei, M. I. (2017). Morphological changes induced in erythrocyte membrane by the antiepileptic treatment: An atomic force microscopy study. Microscopy Research and Technique, 80(4), 364–373. https://doi.org/10.1002/jemt.22804 Park, H., Lee, S., Ji, M., Kim, K., Son, Y., Jang, S., & Park, Y. (2016). Measuring cell surface area and deformability of individual human red blood cells over blood storage using quantitative phase imaging. Scientific Reports, 6(June), 1–10. https://doi.org/10.1038/srep34257
20. Pham, H. V, Edwards, C., Goddard, L. L., & Popescu, G. (2013). Fast phase reconstruction in white light diffraction phase microscopy. Applied Optics, 52(1), A97. https://doi.org/10.1364/AO.52.000A97
21. Popescu, G. (2011). Quantitative Phase Imaging of Cells and Tissues. The McGraw-Hill Companies, Inc. https://www.accessengineeringlibrary.com/browse/quantitative-phase-imaging-of-cells-and-tissues Popescu, G., Ikeda, T., Dasari, R. R., & Feld, M. S. (2006). Diffraction phase microscopy for quantifying cell structure and dynamics. Optics Letters, 31(6), 775. https://doi.org/10.1364/OL.31.000775
22. Popescu, G., Park, Y. K., Choi, W., Dasari, R. R., Feld, M. S., & Badizadegan, K. (2008). Imaging red blood cell dynamics by quantitative phase microscopy. Blood Cells, Molecules, and Diseases, 41(1), 10–16. https://doi.org/10.1016/j.bcmd.2008.01.010
23. Quan, C., He, X. Y., Wang, C. F., Tay, C. J., & Shang, H. M. (2001). Shape measurement of small objects using LCD fringe projection with phase shifting. Optics Communications, 189(1–3), 21–29. https://doi.org/10.1016/S0030-4018(01)01038-0 Reolon, D., Jacquot, M., Verrier, I., Brun, G., & Veillas, C. (2006). Broadband supercontinuum interferometer for high-resolution profilometry. Optics Express, 14(1), 128–137. https://doi.org/org/10.1364/OPEX.14.000128
24. Singh, V., Srivastava, V., & Mehta, D. S. (2020). Machine learning-based screening of red blood cells using quantitative phase imaging with micro-spectrocolorimetry. Optics and Laser Technology, 124(December 2019). https://doi.org/10.1016/j.optlastec.2019.105980
25. Takeda, M., & Mutoh, K. (1983). Fourier transform profilometry for the automatic measurement of 3-D object shapes. Applied Optics, 22(24), 3977. https://doi.org/10.1364/ao.22.003977
26. Ünal, A., Kocahan, Ö., Altunan, B., Aksoy Gündoğdu, A., Uyanık, M., & Özder, S. (2020). Quantitative phase imaging of erythrocyte in epilepsy patients. Microscopy Research and Technique, December, 1–9. https://doi.org/10.1002/jemt.23676
27. Zhou, W., & Wang, Z. L. (2007). Scanning Microscopy for Nanotechnology. In W. Zhou & Z. L. Wang (Eds.), Scanning Microscopy for Nanotechnology: Techniques and Applications. Springer New York. https://doi.org/10.1007/978-0-387-39620-0