Model function to calculate the refractive index of native hemoglobin in the wavelength range of 250-1100 nm dependent on concentration

Friebel, M.F.; Meinke, Martina C.

doi:10.1364/ao.45.002838

Cited by 152 publications

(169 citation statements)

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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]. The volume and the shape of an individual erythrocyte are determined by the osmolality of the blood plasma [125,126].…”

Section: Immersion Clearingmentioning

confidence: 99%

“…The refractive index values of dehydrated erythrocytes at the wavelength of 550 nm fall within the range 1.61-1.66 [12]. The refractive index of the haemoglobin solution with the concentration of 32 g/dL, which is a typical concentration of haemoglobin in the erythrocyte, amounts to nearly 1.42 [13]. For the human blood the refractive index is 1.36-1.40 depending on the wavelength [3].…”

Section: Introduction: Fundamentals Of Optical Clearing Of Tissues Anmentioning

confidence: 98%

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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: 98%

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

Genina

Bashkatov

Sinichkin

et al. 2015

JBPE

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“…In the context of RBCs, these two features make DPM an excellent candidate for measuring rapid thermal fluctuations of the red cell membrane. It must be noted that RI of the Hb is related to the concentration of the Hb and could be calculated as follows: n c = n w (1 + βc), where n w is the RI of water, c is the concentration of the Hb, and β is the wavelength-dependent RI increment (55). Using the Hb concentration, the average RI has been calculated for each density category to provide a more accurate account of the red cell morphology.…”

Section: Methodsmentioning

confidence: 99%

Cellular normoxic biophysical markers of hydroxyurea treatment in sickle cell disease

Hosseini

Abidi

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Hydroxyurea (HU) has been used clinically to reduce the frequency of painful crisis and the need for blood transfusion in sickle cell disease (SCD) patients. However, the mechanisms underlying such beneficial effects of HU treatment are still not fully understood. Studies have indicated a weak correlation between clinical outcome and molecular markers, and the scientific quest to develop companion biophysical markers have mostly targeted studies of blood properties under hypoxia. Using a common-path interferometric technique, we measure biomechanical and morphological properties of individual red blood cells in SCD patients as a function of cell density, and investigate the correlation of these biophysical properties with drug intake as well as other clinically measured parameters. Our results show that patient-specific HU effects on the cellular biophysical properties are detectable at normoxia, and that these properties are strongly correlated with the clinically measured mean cellular volume rather than fetal hemoglobin level.

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“…The second method as expressed by Eq. (2) is based on a long held and reasonably validated view assuming a linear relation for a type of biomolecules between its density and specific contribution to RI beyond n w [26][27][28][29]. Once RI values assigned to all voxels, an OCM was obtained and its morphology and/or RI can be modified to generate a series of OCMs derived from the same cell imaged by a confocal microscope.…”

Section: Establishment Of Ocm and Simulation Of Light Scatteringmentioning

confidence: 99%

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus

Zhang¹,

Feng²,

Jiang³

et al. 2016

Opt. Express

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Coherent light scattering presents complex spatial patterns that depend on morphological and molecular features of biological cells. We present a numerical approach to establish realistic optical cell models for generating virtual cells and accurate simulation of diffraction images that are comparable to measured data of prostate cells. With a contourlet transform algorithm, it has been shown that the simulated images and extracted parameters can be used to distinguish virtual cells of different nuclear volumes and refractive indices against the orientation variation. These results demonstrate significance of the new approach for development of rapid cell assay methods through diffraction imaging. References and links 1.D. Zink, A. H. Fischer, and J. A. Nickerson, "Nuclear structure in cancer cells," Nat. Rev. Cancer 4, 677-687 (2004 IntroductionNucleus is one of the largest organelles inside eukaryotic cells, provides the site for DNA and RNA synthesis, plays critical roles in cell development. Hence it serves as one of major targets for cell assay by morphology and is especially important for detection of abnormal conditions and cancer diagnosis [1]. Optical detection through coherent light scattering offers a much valued platform for its label-free nature and capacities to extract both morphology and molecular information. Characterization of nucleus by scattered light signals thus attracts active research efforts [2][3][4][5][6][7]. Determination of cellular and nuclear morphology is fundamentally a challenging inverse problem for their complex 3D structures. For example, structural reconstruction requires large amount of measured data per cell and often expensive computation that is too long for rapid assay [8,9]. If one aims at only to distinguish cell types such as cancer from normal or apoptotic from viable cells, however, the goal may be achieved empirically with moderate amount of measured data per cell and powerful algorithms of pattern recognition. In either case, it is very useful to develop realistic optical cell models (OCMs) and accurate simulation tools for forward calculations of measured signals of scattered light. They can be employed, for example, to generate training data for algorithm development in search of the correlations between morphological features of cells and diffraction patterns of coherent light scatter.In this report, we present a numerical approach based on previous studies for establishing realistic OCMs for generating virtual cells and accurate simulation of polarized diffraction image (p-DI) data [9][10][11][12][13]. The new approach takes the advantage of 3D cell morphology and molecular information acquired from the fluorescent confocal images to produce simulated p-DI data that are comparable to the measured ones acquired with a polarization diffraction imaging flow cytometry (p-DIFC) system [14][15][16][17][18][19][20]. To demonstrate the utility of the realistic OCMs, we have investigated the effects of nuclear morphology and refractive index (RI) on di...

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Model function to calculate the refractive index of native hemoglobin in the wavelength range of 250-1100 nm dependent on concentration

Cited by 152 publications

References 11 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

Cellular normoxic biophysical markers of hydroxyurea treatment in sickle cell disease

Realistic optical cell modeling and diffraction imaging simulation for study of optical and morphological parameters of nucleus

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