Quantifying morphological heterogeneity: A study of more than 1 000 000 individual stored red blood cells

Vox Sanguinis

Volumn 109, Issue 3, 2015, Pages 221-230

  Piety, N Z ^a   Gifford, S C ^a   Yang, X ^a   Shevkoplyas, Sergey S ^a  

^a UNIVERSITY OF HOUSTON   (United States)

Author keywords

Microfluidic; Morphology; Storage

Indexed keywords

ACCURACY; ARTICLE; AUTOMATION; CELL SIZE; ECHINOCYTE; ERYTHROCYTE PRESERVATION; ERYTHROCYTE STRUCTURE; HUMAN; HUMAN CELL; MICROFLUIDICS; PRIORITY JOURNAL; QUANTITATIVE ANALYSIS; STOMATOCYTE; CLASSIFICATION; CYTOLOGY; DEVICES; ERYTHROCYTE; MICROFLUIDIC ANALYSIS; MICROSCOPY; PHYSIOLOGY; PROCEDURES;

AUTOMATION; ERYTHROCYTES; HUMANS; MICROFLUIDIC ANALYTICAL TECHNIQUES; MICROSCOPY;

EID: 84941601072     PISSN: 00429007     EISSN: 14230410     Source Type: Journal    
DOI: 10.1111/vox.12277     Document Type: Article

References (42)

1. Evans EA: New membrane concept applied to the analysis of fluid shear- and micropipette-deformed red blood cells. Biophys J 1973; 13:941-954
2. Bessis M: Red cell shapes. An illustrated classification and its rationale. Nouv Rev Fr Hematol 1972; 12:721-745
3. Fischer TM, Haest CW, Stohr-Liesen M, et al.: The stress-free shape of the red blood cell membrane. Biophys J 1981; 34:409-422
4. Gifford SC, Derganc J, Shevkoplyas SS, et al.: A detailed study of time-dependent changes in human red blood cells: from reticulocyte maturation to erythrocyte senescence. Br J Haematol 2006; 135:395-404
5. Deplaine G, Safeukui I, Jeddi F, et al.: The sensing of poorly deformable red blood cells by the human spleen can be mimicked in vitro. Blood 2011; 117:e88-e95
6. Greenwalt TJ: The how and why of exocytic vesicles. Transfusion 2006; 46:143-152
7. Hess JR: Red cell changes during storage. Transfus Apher Sci 2010; 43:51-59
8. Zimrin AB, Hess JR: Current issues relating to the transfusion of stored red blood cells. Vox Sang 2009; 96:93-103
9. Berezina TL, Zaets SB, Morgan C, et al.: Influence of storage on red blood cell rheological properties. J Surg Res 2002; 102:6-12
10. Park Y, Best CA, Badizadegan K, et al.: Measurement of red blood cell mechanics during morphological changes. Proc Natl Acad Sci USA 2010; 107:6731-6736
11. Yoshida T, Shevkoplyas SS: Anaerobic storage of red blood cells. Blood Transfus 2010; 8:220-236
12. Nagaprasad V, Singh M: Sequential analysis of the influence of blood storage on aggregation, deformability and shape parameters of erythrocytes. Clin Hemorheol Microcirc 1998; 18:273-284
13. Chin-Yee I, Arya N, d'Almeida MS: The red cell storage lesion and its implication for transfusion. Transfus Sci 1997; 18:447-458
14. Cooper RA, Jandl JH: The role of membrane lipids in the survival of red cells in hereditary spherocytosis. J Clin Invest 1969; 48:736-744
15. Bosman GJ, Werre JM, Willekens FL, et al.: Erythrocyte ageing in vivo and in vitro: structural aspects and implications for transfusion. Transfus Med 2008; 18:335-347
16. Hod EA, Spitalnik SL: Harmful effects of transfusion of older stored red blood cells: iron and inflammation. Transfusion 2011; 51:881-885
17. Hod EA, Brittenham GM, Billote GB, et al.: Transfusion of human volunteers with older, stored red blood cells produces extravascular hemolysis and circulating non-transferrin-bound iron. Blood 2011; 118:6675-6682
18. Albertini MC, Teodori L, Piatti E, et al.: Automated analysis of morphometric parameters for accurate definition of erythrocyte cell shape. Cytometry A 2003; 52:12-18
19. Berezina TL, Zaets SB, Machiedo GW: Alterations of red blood cell shape in patients with severe trauma. J Trauma 2004; 57:82-87
20. Hogman CF, Lof H, Meryman HT: Storage of red blood cells with improved maintenance of 2, 3-bisphosphoglycerate. Transfusion 2006; 46:1543-1552
21. de Korte D, Kleine M, Korsten HG, et al.: Prolonged maintenance of 2, 3-diphosphoglycerate acid and adenosine triphosphate in red blood cells during storage. Transfusion 2008; 48:1081-1089
22. Blasi B, D'Alessandro A, Ramundo N, et al.: Red blood cell storage and cell morphology. Transfus Med 2012; 22:90-96
23. Pierre RV: Red cell morphology and the peripheral blood film. Clin Lab Med 2002; 22:25-61, v-vi.
24. Xiong W, Ong SH, Lim JH, et al.: Automatic area classification in peripheral blood smears. IEEE Trans Biomed Eng 2010; 57:1982-1990
25. Anggraini D, Nugroho AS, Pratama C, et al.: Automated status identification of microscopic images obtained from malaria thin blood smears. Electrical Engineering and Informatics (ICEEI), 2011 International Conference on. IEEE, 2011:1-6
26. Whitesides GM, Ostuni E, Takayama S, et al.: Soft lithography in biology and biochemistry. Annu Rev Biomed Eng 2001; 3:335-373
27. Forouzan O, Burns JM, Robichaux JL, et al.: Passive recruitment of circulating leukocytes into capillary sprouts from existing capillaries in a microfluidic system. Lab Chip 2011; 11:1924-1932
28. Burns JM, Yang X, Forouzan O, et al.: Artificial microvascular network: a new tool for measuring rheologic properties of stored red blood cells. Transfusion 2012; 52:1010-1023
29. Shevkoplyas SS, Gifford SC, Yoshida T, et al.: Prototype of an in vitro model of the microcirculation. Microvasc Res 2003; 65:132-136
30. Shevkoplyas SS, Yoshida T, Munn LL, et al.: Biomimetic autoseparation of leukocytes from whole blood in a microfluidic device. Anal Chem 2005; 77:933-937
31. Shevkoplyas SS, Yoshida T, Gifford SC, et al.: Direct measurement of the impact of impaired erythrocyte deformability on microvascular network perfusion in a microfluidic device. Lab Chip 2006; 6:914-920
32. Gifford S: Methods of multivariate data cluster separation and visualization. United States Patent No. US 8, 423, 596 B2. Office USPaT. Issued April 16, 2013
33. Decre MM, Timmermans PH, van der Sluis O, et al.: Numerical and experimental study of critical roof collapse conditions in soft lithography. Langmuir 2005; 21:7971-7978
34. Hu Y, Osuna-Highley E, Hua J, et al.: Automated analysis of protein subcellular location in time series images. Bioinformatics 2010; 26:1630-1636
35. Sammut C, Webb GI: Encyclopedia of Machine Learning. New York, Springer, 2011
36. Hess JR: Measures of stored red blood cell quality. Vox Sang 2014; 107:1-9
37. Gifford SC, Spillane AM, Vignes SM, et al.: Controlled incremental filtration: a simplified approach to design and fabrication of high-throughput microfluidic devices for selective enrichment of particles. Lab Chip 2014; 14:4496-4505
38. Davis JA, Inglis DW, Morton KJ, et al.: Deterministic hydrodynamics: taking blood apart. Proc Natl Acad Sci USA 2006; 103:14779-14784
39. Huang S, Hou HW, Kanias T, et al.: Towards microfluidic-based depletion of stiff and fragile human red cells that accumulate during blood storage. Lab Chip 2015; 15:448-458
40. Di Ruberto C, Dempster A, Khan S, et al.: Analysis of infected blood cell images using morphological operators. Image Vis Comput 2002; 20:133-146
41. Angulo J, Klossa J, Flandrin G: Ontology-based lymphocyte population description using mathematical morphology on colour blood images. Cell Mol Biol (Noisy-le-Grand) 2006; 52:2-15
42. Huh S, Lee D, Murphy RF: Efficient framework for automated classification of subcellular patterns in budding yeast. Cytometry A 2009; 75:934-940