Optical Coherence Tomography as Glucose Sensor in Blood

  • Hafeez UllahEmail author
  • Ejaz Ahmad
  • Fayyaz Hussain
Part of the Advanced Structured Materials book series (STRUCTMAT, volume 79)


Optical coherence tomography is a modern imaging modality that can visualize the biological tissues on micron levels. This chapter describes the use of OCT technique for measuring glucose in liquid phantoms, whole blood (in vitro and in vivo) based on temporal dynamics of light scattering. Whole blood smears imaged with microscope reveal the effect of red blood cells deformation and aggregation with white light microscope for animal and human blood. We found the changes in the shape of individual cells from biconcave discs to spherical shapes and eventually the lysis of the cells at optimum concentration of glucose. The increase of glucose in blood causes the changes in diffusion coefficients and shapes of the erythrocytes of glucose in stagnant and flowing fluids. The relative contributions of these competing effects have been studied by examining the motion dynamics of deformable asymmetrical RBCs and non deformable symmetrical PMS as flowing scattering particles. These systematic studies are aimed at eventual in vivo tissue imaging scenarios with speckle-variance OCT to visualize normal and malignant blood microvasculature in three and two dimensions and to monitor the glucose levels in blood by analyzing the Brownian motion of the red blood cells.


Optical coherence tomography Glucometry Blood rheology 2D and 3D imaging Blood vessels 



Our own contributions in this chapter were supported by Higher Education Commission Pakistan, Islamabad, Pakistan and Canadian Institutes of Health Research, Ottawa, Canada. We would like to acknowledge all those authors whose results are included/cited in this work. We specially pay our thanks to Dr. Prof. Alex Vitkin, Department of Medical Biophysics, University of Toronto, Canada, who allowed me to conduct the experiments and discussed the results about the quantification of glucose levels in blood in his OCT laboratory.


  1. 1.
    C.A. Puliafito, M.R. Hee, J.S. Schuman, J.G. Fujimoto, Optical Coherence Tomography of Ocular Diseases, 2nd, illustrated ed. (SLACK Inc., New Jersey, 2004), p. 714Google Scholar
  2. 2.
    M.M.K.V. Larin, M.S. Eledrisi, R.O. Esenaliev, Noninvasive blood glucose monitoring with optical coherence tomography, a pilot study in human subjects. Diabetes Care 25, 2263–2267 (2002)CrossRefGoogle Scholar
  3. 3.
    P.A.M.W. Lindner, F. Kiesewetter, G. Häusler, Hand book of Optical Coherence Tomography, ed. by B. Bouma, E. Tearney (Marcel Dekker Inc., New York, 2002)Google Scholar
  4. 4.
    M. Atif, H. Ullah, M.Y. Hamza, M. Ikram, Catheters for optical coherence tomography. Laser Phys. Lett. 8(9), 629–646 (2011)Google Scholar
  5. 5.
    M.E. Brezinski, G.J. Tearney, N.J. Weissman, S.A. Boppart, B.E. Bouma, M.R. Hee, A.E. Weyman, E.A. Swanson, J.F. Southern, J.G. Fujimoto, Assessing atherosclerotic plaque morphology: comparison of optical coherence tomography and high frequency intravascular ultrasound. Heart 77(5), 397 (1997)CrossRefGoogle Scholar
  6. 6.
    G.J. Tearney, M.E. Brezinski, J.F. Southern, B.E. Bouma, S.A. Boppart, J.G. Fujimoto, Optical biopsy in human gastrointestinal tissue using optical coherence tomography. Am. J. Gastroenterol. 92(10), 1800–4 (1997)Google Scholar
  7. 7.
    C. Pitris, M.E. Brezinski, B.E. Bouma, G.J. Tearney, J.F. Southern, J.G. Fujimoton, High resolution imaging of the upper respiratory tract with optical coherence tomography. A feasibility study. Am. J. Respir. Crit. Care Med. 157(5), 1640 (1998)CrossRefGoogle Scholar
  8. 8.
    G.J. Tearney, M.E. Brezinski, J.F. Southern, B.E. Bouma, S.A. Boppart, J.G. Fujimoto, Optical biopsy in human urologic tissue using optical coherence tomography. J. Urol. 157(5), 1915 (1997)CrossRefGoogle Scholar
  9. 9.
    C.A. Jesser, S.A. Boppart, C. Pitris, D.L. Stamper, G.P. Nielsen, M.E. Brezinski, J.G. Fujimoto, High resolution imaging of transitional cell carcinoma with optical coherence tomography: Feasibility for the evaluation of bladder pathology. Br. J. Radiol. 72(864), 1170 (1999)CrossRefGoogle Scholar
  10. 10.
    C. Pitris, A.K. Goodman, S.A. Boppart, J.J. Libus, J.G. Fujimoto, M.E. Brezinski, High resolution imaging of cervical and uterine malignancies using optical coherence tomography. Obstect. Gyn. 93, 135 (1999)CrossRefGoogle Scholar
  11. 11.
    J.B.W. Colston, M.J. Everett, L.B. Da Silva, L.L. Otis, P. Stroeve, H. Nathel, Imaging of hard- and soft-tissue structure in the oral cavity by optical coherence tomography. Appl. Opt. 37(16), 3582 (1998)CrossRefGoogle Scholar
  12. 12.
    X.-J. Wang, T.E. Milner, J.F. de Boer, Y. Zhang, D.H. Pashley, J.S. Nelson, Characterization of Dentin and Enamel by use of Optical Coherence Tomography. Appl. Opt. 38(10), 2092 (1999)Google Scholar
  13. 13.
    P. Zakharov, M.S. Talary, I. Kolm, A. Caduff, Full-field optical coherence tomography for the rapid estimation of epidermal thickness: study of patients with diabetes mellitus type 1. Physiol. Meas. 31(2), 193 (2010)CrossRefGoogle Scholar
  14. 14.
    O.S. Khalil, Non-invasive glucose measurement technologies: an update from 1999 to the dawn of the new millennium. Diabetes Technology & Therapeutics 6(5), 660–697 (2004)MathSciNetCrossRefGoogle Scholar
  15. 15.
    C. Ok Kyung, Y.O. Kim, H. Mitsumaki, K. Kuwa, Noninvasive measurement of glucose by metabolic heat conformation method. Clin. Chem. 50, 1894–1898 (2004)CrossRefGoogle Scholar
  16. 16.
    E.-H. Yoo, S.-Y. Lee, Glucose biosensors: an overview of use in clinical practice. Sensors 10, 4558–4576 (2010)CrossRefGoogle Scholar
  17. 17.
    M.G. Ghosn, V.V. Tuchin, K.V. Larin, Depth-resolved monitoring of glucose diffusion in tissues by using optical coherence tomography. Opt. Lett. 31(15), 2314–2316 (2006)CrossRefGoogle Scholar
  18. 18.
    G.L. Cote, M.D. Fox, R.B. Northrop, Noninvasive optical polarimetric glucose sensing using a true phase measurement technique. IEEE Trans.Biomed. Eng. 39(7), 752–756 (1992)CrossRefGoogle Scholar
  19. 19.
    M.R. Prausnitz, J.S. Noonan, Permeability of cornea, sclera, and conjunctiva: a literature analysis for drug delivery to the eye. J. Pharm. Sci. 87(12), 1479–1488 (1998)CrossRefGoogle Scholar
  20. 20.
    R.A. Gabbay, S. Sivarajah, Optical coherence tomography-based continuous noninvasive glucose monitoring in patients with diabetes. Diabet. Technol. Ther. 10(3), 188–193 (2008)CrossRefGoogle Scholar
  21. 21.
    H. Xiong, Z. Guo, C. Zeng, L. Wang, Y. He, S. Liu, Application of hyperosmotic agent to determine gastric cancer with optical coherence tomography ex vivo in mice. J. Biomed. Opt. 14(2), 024029 (2009)CrossRefGoogle Scholar
  22. 22.
    M. Kohl, M. Cope, M. Essenpreis, D. Böcker, Influence of glucose concentration on light scattering in tissue-simulating phantoms. Opt. Lett. 19(24), 2170–2172 (1994)CrossRefGoogle Scholar
  23. 23.
    M. Brezinski, Optical Coherence Tomography: Principles and Applications. (Academic Press, Cambridge, 2009)Google Scholar
  24. 24.
    U. Hafeez, Imaging of Biological Tissues using Diffuse Reflectance and Optical Coherence Tomography. (Department of Physics, Pakistan Institute of Engineering and Applied Sciences, Islamabad, 2012), p. 152Google Scholar
  25. 25.
    H. Ullah, M. Ikram, Optical Coherence Tomography for Glucose Monitoring in Blood. (LAP Lambert Academic Publishing, Saarbrücken, 2012)Google Scholar
  26. 26.
    K.V. Larin, M.G. Ghosn, S.N. Ivers, A. Tellez, J.F. Granada, Quantification of glucose diffusion in arterial tissues by using optical coherence tomography. Laser Phys. Lett. 4(4), 312–317 (2007)CrossRefGoogle Scholar
  27. 27.
    H. Ullah, M. Atif, S. Firdous, M.S. Mehmood, M. Ikram, C. Kurachi, C. Grecco, G. Nicolodelli, V.S. Bagnato, Femtosecond light distribution at skin and liver of rats: analysis for use in optical diagnostics. Laser Phys. Lett. 7(12), 889–898 (2010)CrossRefGoogle Scholar
  28. 28.
    K.V. Larin, M.G. Ghosn, S.N. Ivers, A. Tellez, J.F. Granada, Quantification of glucose diffusion in arterial tissues by using optical coherence tomography. Laser Phys. Lett. 4(4), 312 (2007)CrossRefGoogle Scholar
  29. 29.
    K.V. Larin, V.V. Tuchin, Functional imaging and assessment of the glucose diffusion rate in epithelial tissues in optical coherence tomography. Quantum Electron. 38(6), 551 (2008)CrossRefGoogle Scholar
  30. 30.
    H. Ullah, G. Gilanie, M. Attique, M. Hamza, M. Ikram, M-mode swept source optical coherence tomography for quantification of salt concentration in blood: an in vitro study. Laser Phys. 22(5), 1002–1010 (2012)Google Scholar
  31. 31.
    H. Ullah, A. Mariampillai, M. Ikram, I. Vitkin, Can temporal analysis of optical coherence tomography statistics report on dextrorotatory-glucose levels in blood? Laser Phys. 21(11), 1962–1971 (2011)CrossRefGoogle Scholar
  32. 32.
    S. Prahl. Mie Scattering Calculator (2011), (cited 11 Apr 2011), Available from:
  33. 33.
    X. Guo, Z.Y. Guo, H.J. Wei, H.Q. Yang, Y.H. He, S.S. Xie, G.Y. Wu, H.Q. Zhong, L.Q. Li, Q.L. Zhao, In vivo quantification of propylene glycol, glucose and glycerol diffusion in human dkin with optical coherence tomography. Laser Phys. 20, 1849–1855 (2010)CrossRefGoogle Scholar
  34. 34.
    Y.L. Jin, J.Y. Chen, L. Xu, P.N. Wang, Refractive index measurement for biomaterial samples by total internal reflection. Phys. Med. Biol. 51(20), N371 (2006)CrossRefGoogle Scholar
  35. 35.
    M. Brezinski, Optical coherence tomography principles and applications (Elsevier, San Diego, USA, 2006)Google Scholar
  36. 36.
    B.J. Berne, R. Pecora, dynamic light scattering with applications to chemistry, biology, and physics (Dover Publications, Inc., Mineola, New York, 2000)Google Scholar
  37. 37.
    website. Physical characteristics of water (at the atmospheric pressure). (2011) (cited 22 Feb 2011), Available from:
  38. 38.
    Telisa, J. Telis-Romeroa, H.B. Mazzottia, A.L. Gabasb, Viscosity of aqueous carbohydrate solutions at different temperatures and concentrations. Int. J. Food Prop. 10(1), 185–195 (2007)CrossRefGoogle Scholar
  39. 39.
    S. Kim, S. Yang, D. Lim, Effect of dextran on rheological properties of rat blood. J. Mech. Sci. Technol. 23(3), 868–873 (2009)CrossRefGoogle Scholar
  40. 40.
    N. Dobrovol’skii, Y. Lopukhin, A. Parfenov, A. Peshkov, A blood viscosity analyzer. Biomed. Eng. 31(3), 140–143 (1997)CrossRefGoogle Scholar
  41. 41.
    (2011) (cited 2011 28th January), Available from:
  42. 42.
    O.S. Zhernovaya, V.V. Tuchin, I.V. Meglinski, Monitoring of blood proteins glycation by refractive index and spectral measurements. Laser Phys. Lett. 5(6), 460–464 (2008)CrossRefGoogle Scholar
  43. 43.
    G. Barshtein, I. Tamir, S. Yedgar, Red blood cell rouleaux formation in dextran solution: dependence on polymer conformation. Eur. Biophys. J. 27(2), 177–181 (1998)CrossRefGoogle Scholar
  44. 44.
    A.A. Bednov, E.V. Savateeva, A.A. Oraevsky. Opto-acoustic monitoring of blood optical properties as a function of glucose concentration (2003)Google Scholar
  45. 45.
    T.W. Secomb, B. Styp-Rekowska, A.R. Pries, Two-dimensional simulation of red blood cell deformation and lateral migration in microvessels. Ann. Biomed. Eng. 35, 755–765 (2007)CrossRefGoogle Scholar
  46. 46.
    R. Skalak, P.R. Zarda, K.M. Jan, S. Chien, Mechanics of Rouleau formation. Biophys. J. 35(3), 771–781 (1981)CrossRefGoogle Scholar
  47. 47.
    H. Ullah, F. Hussain, M.A. Abdul, J. Malik, M.A. Sial, E. Ahmed, Durr-e-Sabeeh, Qualitative monitoring of glucose, salt and distilled water in whole blood: an in vitro study. Unpublished data (2015)Google Scholar
  48. 48.
    A.I. Joseph, S. Yazdanfar, V. Westphal, S. Radhakrishan, A.M. Rollins, Real-time and functional optical coherence tomography. In IEEE, p. 110 (2002)Google Scholar
  49. 49.
    H. Ullah, A. Mariampillai, M. Ikram, I.A. Vitkin, Can temporal analysis of optical coherence tomography statistics report on dextrorotatory-glucose levels in blood? Laser Phys. 21(11), 1962–1971 (2011)CrossRefGoogle Scholar
  50. 50.
    A.A. Bednov, A.A. Karabutov, E.V. Savateeva, W.F. March, A.A. Oraevsky. Monitoring glucose in vivo by measuring laser-induced acoustic profiles (2000)Google Scholar
  51. 51.
    H. Ullah, B. Davoudi, A. Mariampillai, G. Hussain, M. Ikram, I.A. Vitkin, Quantification of glucose levels in flowing blood using M-mode swept source optical coherence tomography. Laser Phys. 22(4), 797–804 (2012)CrossRefGoogle Scholar
  52. 52.
    V.V. Tuchin, Laser Fiber Optics in Biomedical Research. (Saratov State Univ. Publ., Russia, 1998), 383pGoogle Scholar
  53. 53.
    J.A. Jacquez, Red blood cell as glucose carrier: significance for placental and cerebral glucose transfer. Am. J. Physiol. Regul. Integr. Comparative Physiol. 246(3), R289–R298 (1984)Google Scholar
  54. 54.
    J.D. Ramshaw, Brownian motion in flowing fluids. Phys. Fluids 22, 1595–1601 (1979)CrossRefzbMATHGoogle Scholar
  55. 55.
    D.B. Kunimasa Miyazaki, Brownian motion in a fluid in simple shear flow. Phys. A 217, 53–74 (1995)CrossRefGoogle Scholar
  56. 56.
    M. Ninck, M. Untenberger, T. Gisler, Diffusing-wave spectroscopy with dynamic contrast variation: disentangling the effects of blood flow and extravascular tissue shearing on signals from deep tissue. Biomed. Opt. Express 1(5), 1502–1513 (2010)CrossRefGoogle Scholar
  57. 57.
    B.D.H. Ullah, A. Mariampillai, G. Hussain, M. Ikram, I.A. Vitkin, Quantification of glucose levels in flowing blood using M-mode swept source optical coherence tomography. Laser Phy. (2011, article in press)Google Scholar
  58. 58.
    H. Ullah, B. Davoudi, A. Mariampillai, G. Hussain, M. Ikram, I. Vitkin, Quantification of glucose levels in flowing blood using M-mode swept source optical coherence tomography. Laser Phys. 22(4), 797–804 (2012)Google Scholar
  59. 59.
    M. Kinnunen, R. Myllyla, S. Vainio, Detecting glucose-induced changes in in vitro and in vivo experiments with optical coherence tomography. J. Biomed. Opt. 13(2), 021111–021117 (2008)CrossRefGoogle Scholar
  60. 60.
    J. Moger, S.J. Matcher, C.P. Winlove, A. Shore, Measuring red blood cell flow dynamics in a glass capillary using Doppler optical coherence tomography and Doppler amplitude optical coherence tomography. J. Biomed. Opt. 9(5), 982–994 (2004)CrossRefGoogle Scholar
  61. 61.
    R. Darby, Chemical Engineering Fluid Mechanics. (Marcel Dekker, Inc., New York, NY 2001), p. 10016Google Scholar
  62. 62.
    D. Rusu, D. Genoe, P. van Puyvelde, E. Peuvrel-Disdier, P. Navard, G.G. Fuller, Dynamic light scattering during shear: measurements of diffusion coefficients. Polymer 40(6), 1353–1357 (1999)CrossRefGoogle Scholar
  63. 63.
    Z. Li, H. Li, J. Li, X. Lin, Feasibility of glucose monitoring based on Brownian dynamics in time-domain optical coherence tomography. Laser Phys. 21(11), 1995–1998 (2011)CrossRefGoogle Scholar
  64. 64.
    H. Ullah, E. Ahmed, M. Ikram, Human cervical carcinoma detection and glucose monitoring in blood micro vasculatures with swept source OCT. JETP Lett. 97(12), 690–696 (2013)CrossRefGoogle Scholar
  65. 65.
    M.L. Hans-Anton Lehr, Michael D. Menger, Dirk Nolte, Konrad Messmer, Dorsal Skinfold Chamber Technique for Intravital Microscopy in Nude Mice. Am. J. Pathol. 143(4), 1055–1062 (1993)Google Scholar
  66. 66.
    S.J. Md Menger, P. Walter, F. Hammersen, K. Messmer, A novel technique for studies on the microvasculature of transplanted islets of Langerhans in vivo. Int. J. Microcirc. Clin. Exp. 9, 109–117 (1990)Google Scholar
  67. 67.
    A. Mariampillai, B.A. Standish, E.H. Moriyama, M. Khurana, N.R. Munce, M.K.K. Leung, J. Jiang, A. Cable, B.C. Wilson, I.A. Vitkin, V.X.D. Yang, Speckle variance detection of microvasculature using swept-source optical coherence tomography. Opt. Lett. 33(13), 1530–1532 (2008)CrossRefGoogle Scholar
  68. 68.
    N. Sudheendran, S.H. Syed, M.E. Dickinson, I.V. Larina, K.V. Larin, Speckle variance OCT imaging of the vasculature in live mammalian embryos. Laser Phys. Lett. 8(3), 247–252 (2011)CrossRefGoogle Scholar
  69. 69.
    G. Hüttmann, Optical coherence tomography (OCT) for early diagnosis of tumors and online-control of photodynamic therapy (PDT). Photodiagn. Photodyn. Ther. 8(2), 152 (2011)CrossRefGoogle Scholar

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© Springer India 2016

Authors and Affiliations

  1. 1.Laser and Optronics Laboratory, Department of PhysicsBahauddin Zakariya UniversityMultanPakistan
  2. 2.Material Simulation Research Laboratory (MSRL), Department of PhysicsBahauddin Zakariya UniversityMultanPakistan

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