Scattering of Light by a Red Blood Cell

Borovoi, Anatoli G.; Naats, Edward I.; Oppel, Ulrich G.

doi:10.1117/1.429883

Cited by 75 publications

(46 citation statements)

References 4 publications

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“…The difference between the refractive indices of the erythrocyte cytoplasm and the blood plasma, as well as the specific size and structure of blood corpuscles explain the blood scattering properties [3,10,11]. The refractive index of the erythrocyte cytoplasm is determined mainly by the haemoglobin concentration [11,13,125].…”

Section: Immersion Clearingmentioning

confidence: 99%

“…The refractive index values of the connective tissue fibrils lie in the range 1.41-1.53 and depend upon the degree of hydration of their major component, the collagen [9]. The refractive index of the interstitial fluid and the blood plasma amounts to nearly 1.33-1.35 depending on the wavelength [3,10]. The main scatterers in the blood are the red blood cells (erythrocytes), which are acaryocytes, containing 70% of water, 25% of haemoglobin, and 5% of lipids, sugars, salts, enzymes, and proteins [11].…”

Section: Introduction: Fundamentals Of Optical Clearing Of Tissues Anmentioning

confidence: 99%

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Optical clearing of biological tissues: prospects of application in medical diagnostics and phototherapy

Genina

Bashkatov

Sinichkin

et al. 2015

JBPE

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Abstract.A review of specific features and methods of optical clearing and related interaction of light with tissues is presented. Physical and molecular mechanisms of immersion, compression, and photodynamic/photothermal optical clearing of some fibrous and cellular tissues are discussed. The possibility of efficient control of the tissue optical properties, particularly, the reduction of light scattering in tissues is demonstrated, which facilitates the increased efficiency of various optical visualisation methods (optical biopsy) used in medical purposes. © 2015 Samara State Aerospace University (SSAU).Keywords: tissue, optical clearing, optical diagnostics, imaging. 1, 404-413 (1997). 5. C. L. Smithpeter, A. K. Dunn, A. J. Welch, and R. Richards-Kortum, "Penetration depth limits of in vivo confocal reflectance imaging," Appl. Opt. 37, 2749Opt. 37, -2754Opt. 37, (1998. 6. V. V. Tuchin, L. V. Wang, and D. A. Zimnyakov, Optical Polarization in Biomedical Applications, SpringerVerlag, New York, NY, USA (2006). 7. R. Drezek, A. Dunn, and R. Richards-Kortum, "Light scattering from cells: finite-difference time-domain simulations and goniometric measurements," Appl. Opt. 38(16), 3651-3661 (1999). 8. K. Sokolov, R. Drezek, K. Gossagee, and R. Richards-Kortum, "Reflectance spectroscopy with polarized light:is it sensitive to cellular and nuclear morphology," Opt. Express 5, 302-317 (1999). 9. D. W. Leonard, and K. M. Meek, "Refractive indices of the collagen fibrils and extrafibrillar material of the corneal stroma," Biophysical J. 72, 1382-1387 (1997). 10. A. G. Borovoi, E. I. Naats, and U. G. Oppel, "Scattering of light by a red blood cell," J. Biomed. Opt. 3, 364-372 (1998). 11. A. N. Yaroslavsky, A. V. Priezzhev, J. Rodriguez, I. V. Yaroslavsky, and H. Battarbee, "Optics of blood,"Chap. 2 in Handbook of Optical Biomedical Diagnostics, V. V. Tuchin, Ed., pp. 169-216, PM107 SPIE Press, Bellingham, WA, USA (2002). 12. G. Mazarevica, T. Freivalds, and A. Jurka, "Properties of erythrocyte light refraction in diabetic patients," J.Biomed. Opt. 7, 244-247 (2002). 13. M. Friebel, and M. Meinke, "Model function to calculate the refractive index of native hemoglobin in the wavelength range of 250-1100 nm dependent on concentration," Appl. Opt. 45(12), 2838-2842 (2006). Appl. Opt. 35(19), 3413-3420 (1996). 34. D. Zhu, J. Wang, Z. Zhi, X. Wen, and Q. Luo, "Imaging dermal blood flow through the intact rat skin with an optical clearing method," J. Biomed. Opt. 15, 026008 (2010 241. K. König, G. Flemming, and R. Hibst, "Laser-induced autofluorescence spectroscopy of dental caries lesion," Cell. Mol. Biol. 44, 1293-1300. 242. E. G. Borisova, T. T. Uzunov, and L. A. Avramov, "Early differentiation between caries and tooth demineralization using laser-induced autofluorescence spectroscopy," Lasers Surg. Med. 34, 249-253 (2004 -20(12), 1512-1516 (1984). 245. K. Konig, H. Schneckenburger, and R. Hibst, "Time-gated in vivo autofluorescence imaging of dental caries,"Cell. Mol. Biol. 45, 233-239 (1999). 246. E. Borisova, P. Tr...

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Section: Immersion Clearingmentioning

confidence: 99%

Section: Introduction: Fundamentals Of Optical Clearing Of Tissues Anmentioning

confidence: 99%

Optical clearing of biological tissues: prospects of application in medical diagnostics and phototherapy

Genina

Bashkatov

Sinichkin

et al. 2015

JBPE

View full text Add to dashboard Cite

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“…To alleviate this complexity we use an analytical approximation for the shape profile. To find the latter, which is both convenient and accurate, we considered the following popular parametric equations: Cassini ovals [22], equation of Borovoy et al [15], model of Fung et al [6], and proposed an extended Fung model of variable order N:…”

Section: Optical Model Of Red Blood Cellmentioning

confidence: 99%

“…Extension of this approach to the RBCs requires knowledge of their precise shape. There exist a number of simple empiric parametric shape equations, which has been used in optical studies of RBCs [6,15,16]. While most of them has been to some extent verified by fitting to the experimental data, they cannot be used to reliably describe the whole range of mature RBC shapes, since the underlying data is limited to a few hundred cells [6,8].…”

Section: Introductionmentioning

confidence: 99%

Mature red blood cells: from optical model to inverse light-scattering problem

Gilev¹,

Yurkin²,

Chernyshova³

et al. 2016

Biomed. Opt. Express

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Abstract:We propose a method for characterization of mature red blood cells (RBCs) morphology, based on measurement of light-scattering patterns (LSPs) of individual RBCs with the scanning flow cytometer and on solution of the inverse light-scattering (ILS) problem for each LSP. We considered a RBC shape model, corresponding to the minimal bending energy of the membrane with isotropic elasticity, and constructed an analytical approximation, which allows rapid simulation of the shape, given the diameter and minimal and maximal thicknesses. The ILS problem was solved by the nearest-neighbor interpolation using a preliminary calculated database of 250,000 theoretical LSPs. For each RBC in blood sample we determined three abovementioned shape characteristics and refractive index, which also allows us to calculate volume, surface area, sphericity index, spontaneous curvature, hemoglobin concentration and content. ©2016 Optical Society of America

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“…Examples of such simplifications include the spherical 2,7 and spheroidal 8 approximations of the RBCs' morphology made because of the ease with which the optical properties can be obtained from either the Lorenz-Mie theory or the extended boundary condition method (EBCM). Other examples of the simplifications are the use of approximate or semi-empirical scattering computational methods to compute the optical properties of more realistic RBC shapes, such as the Born approximation, 9 anomalous diffraction theory, 10,11 Wentzel-Kramers-Brillouin approximation, 12 and physical-geometric-optics approximation method. 13 As the numerical methods have gradually developed to solve Maxwell's equations, numerous publications are available on light scattering by RBCs using numerically rigorous methods including the discrete-dipole approximation (DDA), 14,15 finitedifference time-domain (FDTD) method, 16 boundary element method, 17 multilevel fast multipole algorithm (MLFMA), 18 and discrete sources method (DSM).…”

Section: Introductionmentioning

confidence: 99%

Modeling of light scattering by biconcave and deformed red blood cells with the invariant imbedding T-matrix method

Yang

2013

J. Biomed. Opt

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Abstract. The invariant imbedding T-matrix method (II-TM) is employed to simulate the optical properties of normal biconcave and deformed red blood cells (RBCs). The phase matrix elements of a RBC model computed with the II-TM are compared with their counterparts computed with the discrete-dipole approximation (DDA) method. As expected, the DDA results approach the II-TM results with an increase in the number of dipoles per incident wavelength. Computationally, the II-TM is faster than the DDA when multiple RBC orientations are considered. For a single orientation, the DDA is comparable with or even faster than the II-TM because the DDA efficiently converges for optically soft particles; however, the DDA method demands significantly more computer memory than the II-TM. After the applicability of the II-TM is numerically confirmed, a comparison is conducted of the optical properties of oxygenated and deoxygenated RBCs and of normal and deformed RBCs. The spectral variations of RBCs' optical properties are investigated in the wavelength range from 0.25 to 1.0 μm. Furthermore, the statistically averaged phase matrix of spheres and biconcave RBCs are compared. Conducted numerical simulations suggest the applicability of the II-TM for the inverse light scattering analysis and radiative transfer simulations in blood. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Scattering of Light by a Red Blood Cell

Cited by 75 publications

References 4 publications

Optical clearing of biological tissues: prospects of application in medical diagnostics and phototherapy

Optical clearing of biological tissues: prospects of application in medical diagnostics and phototherapy

Mature red blood cells: from optical model to inverse light-scattering problem

Modeling of light scattering by biconcave and deformed red blood cells with the invariant imbedding T-matrix method

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