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Photon Migration in NIRS Brain Imaging

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Book cover Application of Near Infrared Spectroscopy in Biomedicine

Part of the book series: Handbook of Modern Biophysics ((HBBT,volume 4))

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Abstract

Near-infrared spectroscopy (NIRS) is widely used to measure cerebral oxygenation and hemodynamics caused by brain activation. Blood volume and oxygenation are indicated by the absorption of tissue caused by oxygenated and deoxygenated hemoglobin/myoglobin. NIRS instruments can monitor temporal changes in blood volume and oxygenation in a single probing region. The desire to measure the spatial distribution of tissue absorption, which indicates the region of focal brain activation, has fostered development of NIRS imaging to localize the absorption change in the brain. There are two basic categories of NIRS imaging: tomography and topography. NIRS tomography provides the cross-sectional images of brain activation, whereas the two-dimensional distribution of brain activation in the cortex is obtained by NIRS topography.

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References

  1. Wyatt JS, Delpy DT, Cope M, Wray S, Reynolds EOR (1986) Quantification of cerebral oxygenation and haemodynamics in sick newborn infants by near infrared spectroscopy. Lancet 328(8515):1063–1066

    Article  Google Scholar 

  2. Chance B, Leigh JS, Miyake H, Smith DS, Nioka S, Greenfeld R, Finander M, Kaufmann K, Levy W, Young M (1988) Comparison of time-resolved and -unresolved measurements of deoxyhemoglobin in brain. Proc Natl Acad Sci U S A 85(14):4971–4975

    Article  PubMed  CAS  Google Scholar 

  3. Hoshi Y, Tamura M (1993) Detection of dynamic changes in cerebral oxygenation coupled to neural function during mental work in man. Neurosci Lett 150(1):5–8

    Article  PubMed  CAS  Google Scholar 

  4. Obrig H, Wenzel R, Kohl W, Horst S, Wobst P, Steinbrink J, Thomas F, Villringer A (2000) Near-infrared spectroscopy: does it function in functional activation studies of the adult brain. Int J Psychophysiol 35(2–3):125–142

    Article  PubMed  CAS  Google Scholar 

  5. Fujiwara N, Sakatani K, Katayama Y, Murata Y, Hoshino T, Fukaya C, Yamamoto T (2004) Evoked-cerebral blood oxygenation changes in false-negative activation in BOLD contrast functional MRI of patients with brain tumors. Neuroimage 14(4):1464–1471

    Article  Google Scholar 

  6. Gibson AP, Hebden JC, Arridge SR (2005) Recent advances in diffuse optical imaging. Phys Med Biol 50(4):R1–R43

    Article  PubMed  CAS  Google Scholar 

  7. Delpy DT, Cope M, van der Zee P, Arridge SR, Wray S, Watt JS (1988) Estimation of optical pathlength through tissue from direct time of flight measurement. Phys Med Biol 33(12):1433–1442

    Article  PubMed  CAS  Google Scholar 

  8. Hiraoka M, Firbank M, Essenpreis E, Cope M, Arridge SR, van der Zee P, Delpy DT (1993) A Monte Carlo investigation of optical pathlength in inhomogeneous tissue and its application to near-infrared spectroscopy. Phys Med Biol 38(12):1859–1876

    Article  PubMed  CAS  Google Scholar 

  9. Okada E, Firbank M, Delpy DT (1995) The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy. Phys Med Biol 40(12):2093–2108

    Article  PubMed  CAS  Google Scholar 

  10. Okada E, Schweiger M, Arridge SR, Firbank M, Delpy DT (1996) Experimental validation of Monte Carlo and finite-element methods for the estimation of the optical pathlength in inhomogeneous tissue. Appl Opt 35(19):3362–3371

    Article  PubMed  CAS  Google Scholar 

  11. Hielscher AH, Liu H, Chance B, Tittel FK, Jacques SL (1996) Time-resolved photon emission from layered turbid media. Appl Opt 35(4):719–728

    Article  PubMed  CAS  Google Scholar 

  12. Okada E, Firbank M, Schweiger M, Arridge SR, Cope M, Delpy DT (1997) Theoretical and experimental investigation of near-infrared light propagation in a model of the adult head. Appl Opt 36(1):21–31

    Article  PubMed  CAS  Google Scholar 

  13. Firbank M, Okada E, Delpy DT (1998) A theoretical study of the signal contribution of regions of the adult head to near-infrared spectroscopy studies of visual evoked responses. Neuroimage 8(1):69–78

    Article  PubMed  CAS  Google Scholar 

  14. Wolf M, Keel M, Dietz V, von Siebenthal K, Bucher HU, Baenziger O (1999) The influence of a clear layer on near-infrared spectrophotometry measurements using a liquid neonatal head phantom. Phys Med Biol 44(7):1743–1754

    Article  PubMed  CAS  Google Scholar 

  15. Okada E (2000) The effect of superficial tissue of the head on spatial sensitivity profiles for near-infrared spectroscopy and imaging. Opt Rev 7(5):375–382

    Article  CAS  Google Scholar 

  16. Okada E, Delpy DT (2003) Near-infrared light propagation in an adult head model, I: modeling of low-level scattering in the cerebrospinal fluid layer. Appl Opt 42(16):2906–2914

    Article  PubMed  Google Scholar 

  17. Boas DA, Culver JP, Stott JJ, Dunn AK (2002) Three-dimensional Monte Carlo code for photon migration through complex heterogeneous media including the adult human head. Opt Express 10(3):159–170

    Article  PubMed  Google Scholar 

  18. Fukui Y, Ajichi Y, Okada E (2003) Monte Carlo prediction of near-infrared light propagation in realistic adult and neonatal head models. Appl Opt 42(16):2881–2887

    Article  PubMed  Google Scholar 

  19. Fukui Y, Yamamoto T, Kato T, Okada E (2003) Analysis of light propagation in a three-dimensional realistic head model for topographic imaging by finite-difference method. Opt Rev 10(5):470–473

    Article  Google Scholar 

  20. Kawaguchi H, Koyama T, Okada E (2007) Effect of probe arrangement on reproducibility of images by near-infrared topography evaluated by a virtual head phantom. Appl Opt 46(10):1658–1668

    Article  PubMed  Google Scholar 

  21. Heiskala J, Hiltunen P, Nissilä I (2009) Significance of background optical properties, time-resolved information and optode arrangement in diffuse optical imaging of term neonates. Phys Med Biol 54(3):535–554

    Article  PubMed  CAS  Google Scholar 

  22. Wilson BC, Adam G (1983) A Monte Carlo model for the absorption and flux distributions of light in tissue. Med Phys 10(6):824–830

    Article  PubMed  CAS  Google Scholar 

  23. van der Zee P, Delpy DT (1987) Simulation of the point spread function for light in tissue by a Monte Carlo technique. Adv Exp Med Biol 215:179–191

    Article  PubMed  Google Scholar 

  24. Wang L, Jacques SL, Zheng L (1995) MCML – Monte Carlo modeling of light transport in multi-layered tissues. Comput Methods Programs Biomed 47(2):131–146

    Article  PubMed  CAS  Google Scholar 

  25. Patterson MS, Chance B, Wilson BC (1989) Time-resolved reflectance and transmittance for the noninvasive measurement of tissue optical properties. Appl Opt 28(12):2331–2336

    Article  PubMed  CAS  Google Scholar 

  26. Farrell TJ, Patterson MS, Wilson B (1992) A diffusion theory model of spatially resolved, steady-state diffuse reflectance for the noninvasive determination of tissue optical properties in vivo. Med Phys 19(4):879–888

    Article  PubMed  CAS  Google Scholar 

  27. Arridge SR, Cope M, Delpy DT (1992) Theoretical basis for the determination of optical pathlengths in tissue: temporal and frequency analysis. Phys Med Biol 37(7):1531–1560

    Article  PubMed  CAS  Google Scholar 

  28. Arridge SR, Schweiger M, Hiraoka M, Delpy DT (1993) A finite-element approach for modeling photon transport in tissue. Med Phys 20(2):299–309

    Article  PubMed  CAS  Google Scholar 

  29. Yamada Y, Hasegawa Y (1993) Time-resolved FEM analysis of photon migration in random media. Proc SPIE 1888:167–178

    Article  Google Scholar 

  30. Firbank M, Arridge SR, Schweiger M, Delpy DT (1996) An investigation of light transport through scattering bodies with non-scattering regions. Phys Med Biol 41(4):767–783

    Article  PubMed  CAS  Google Scholar 

  31. Dehghani H, Arridge SR, Schweiger M, Delpy DT (2000) Optical tomography in the presence of void regions. J Opt Soc Am A 17(9):1659–1670

    Article  Google Scholar 

  32. Hayashi T, Kashio Y, Okada E (2003) Hybrid Monte Carlo diffusion method for light propagation in tissue with a low-scattering region. Appl Opt 42(16):2888–2896

    Article  PubMed  Google Scholar 

  33. Koyama T, Iwasaki A, Ogoshi Y, Okada E (2005) Practical and adequate approach to modeling light propagation in an adult head with low-scattering regions by use of diffusion theory. Appl Opt 44(11):2094–2103

    Article  PubMed  Google Scholar 

  34. Custo A, Wells WM III, Barnett AH, Hillman EMC, Boas DA (2006) Effective scattering coefficient of the cerebral spinal fluid in adult head models for diffuse optical imaging. Appl Opt 45(19):4747–4755

    Article  PubMed  Google Scholar 

  35. Oki Y, Kawaguchi H, Okada E (2009) Validation of practical diffusion approximation for virtual near infrared spectroscopy using a digital head phantom. Opt Rev 16(2):153–159

    Article  CAS  Google Scholar 

  36. Schotland JC, Haselgrove JC, Leigh JS (1993) Photon hitting density. Appl Opt 32(4):448–453

    Article  PubMed  CAS  Google Scholar 

  37. Arridge SR (1995) Photon-measurement density functions, 1: analytical forms. Appl Opt 34(31):7395–7409

    Article  PubMed  CAS  Google Scholar 

  38. Eda H, Oda I, Ito Y, Wada Y, Oikawa Y, Tsunazawa Y, Takada M (1999) Multichannel time-resolved optical tomographic imaging system. Rev Sci Instrum 70(9):3595–3602

    Article  CAS  Google Scholar 

  39. Schmidt FEW, Fry ME, Hillman EMC, Hebden JC, Delpy DT (2000) A 32-channel time-resolved instrument for medical optical tomography. Rev Sci Instrum 71(1):256–265

    Article  CAS  Google Scholar 

  40. Wabnitz H, Moeller M, Liebert A, Obrig H, Steinbrink J, Macdonald R (2010) Time-resolved near-infrared spectroscopy and imaging of the adult human brain. Adv Exp Med Biol 662:143–148

    Article  PubMed  CAS  Google Scholar 

  41. Arridge SR (1993) The forward and inverse problems in time-resolved infrared imaging. In: Müller G et al (eds) Medical optical tomography: functional imaging and monitoring. SPIE Press, Bellingham, pp 35–64

    Google Scholar 

  42. Schweiger M, Arridge SR, Delpy DT (1993) Application of the finite-element method for the forward and inverse models in optical tomography. J Math Imaging Vis 3(3):263–283

    Article  Google Scholar 

  43. Arridge SR, Schweiger M (1995) Photon-measurement density functions, 2: finite-element-method calculations. Appl Opt 34(34):8026–8037

    Article  PubMed  CAS  Google Scholar 

  44. Arridge SR, Hebden JC (1997) Optical imaging in medicine, II: modelling and reconstruction. Phys Med Biol 42(5):841–853

    Article  PubMed  CAS  Google Scholar 

  45. Arridge SR (1999) Optical tomography in medical imaging. Inverse Probl 15(2):R41–R93

    Article  Google Scholar 

  46. Gibson AP, Hebden JC, Riley J, Everdell N, Schweiger M, Arridge SR, Delpy DT (2005) Linear and nonlinear reconstruction for optical tomography of phantoms with nonscattering regions. Appl Opt 44(19):3925–3936

    Article  PubMed  Google Scholar 

  47. Gibson AP, Austin T, Everdell NL, Schweiger M, Arridge SR, Meek JH, Wyatt JS, Delpy DT, Hebden JC (2006) Three-dimensional whole-head optical tomography of passive motor evoked responses in the neonate. Neuroimage 30(2):521–528

    Article  PubMed  CAS  Google Scholar 

  48. Austin T, Gibson AP, Branco G, Yusof R, Arridge SR, Meek JH, Wyatt JS, Delpy DT, Hebden JC (2006) Three-dimensional optical imaging of blood volume and oxygenation in the preterm brain. Neuroimage 31(4):1426–1433

    Article  PubMed  CAS  Google Scholar 

  49. Maki A, Yamashita Y, Ito Y, Watanabe E, Mayanagi Y, Koizumi H (1995) Spatial and temporal analysis of human motor activity using noninvasive NIR topography. Med Phys 22(12):1997–2005

    Article  PubMed  CAS  Google Scholar 

  50. Koizumi H, Yamamoto T, Maki A, Yamashita Y, Sato H, Kawaguchi H, Ichikawa N (2003) Optical topography: practical problems and new applications. Appl Opt 42(16):3054–3062

    Article  PubMed  Google Scholar 

  51. Watanabe E, Maki A, Kawaguchi F, Takashiro K, Yamashita Y, Koizumi H, Mayanagi Y (1998) Noninvasive assessment of language dominance with near-infrared spectroscopic mapping. Neurosci Lett 256(1):49–52

    Article  PubMed  CAS  Google Scholar 

  52. Taga G, Konishi Y, Maki A, Tachibana T, Fujiwara M, Koizumi H (2000) Spontaneous oscillation of oxy- and deoxy-hemoglobin changes with a phase difference throughout the occipital cortex of newborn infants observed using noninvasive optical topography. Neurosci Lett 282(1–2):101–104

    Article  PubMed  CAS  Google Scholar 

  53. Miyai I, Tanabe HC, Sase I, Eda H, Oda I, Konishi I, Tsunazawa Y, Suzuki T, Yanagida T, Kubota K (2001) Cortical mapping of gait in humans: a near-infrared spectroscopic topography study. Neuroimage 14(5):1186–1192

    Article  PubMed  CAS  Google Scholar 

  54. Suto T, Fukuda M, Ito M, Uehara T, Mikuni M (2004) Multichannel near-infrared spectroscopy in depression and schizophrenia: cognitive brain activation study. Biol Psychiatry 55(5):501–511

    Article  PubMed  Google Scholar 

  55. Yamamoto T, Maki A, Kadoya A, Tanikawa Y, Yamada Y, Okada E, Koizumi H (2002) Arranging optical fibres for the spatial resolution improvement of topographic images. Phys Med Biol 47(18):3429–3440

    Article  PubMed  Google Scholar 

  56. Kawaguchi H, Hayashi T, Kato T, Okada E (2004) Theoretical evaluation of accuracy in position and size of brain activity obtained by near-infrared topography. Phys Med Biol 49(12):2753–2765

    Article  PubMed  Google Scholar 

  57. Tian F, Alexandrakis G, Liu H (2009) Optimization of probe geometry for diffuse optical brain imaging based on measurement density and distribution. Appl Opt 48(13):2496–2504

    Article  PubMed  Google Scholar 

  58. Boas DA, Dale AM, Franceschini MA (2004) Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy. Neuroimage 23(S1):S275–S288

    Article  PubMed  Google Scholar 

  59. Schweiger M, Arridge SR (1999) Optical tomographic reconstruction in a complex head model using a priori region boundary information. Phys Med Biol 44(11):2703–2721

    Article  PubMed  CAS  Google Scholar 

  60. Hielscher AH, Bluestone AY, Abdoulaev GS, Klose AD, Lasker J, Stewart M, Netz U, Beuthan J (2002) Near-infrared diffuse optical tomography. Dis Markers 18(5–6):313–337

    Article  PubMed  CAS  Google Scholar 

  61. Cheong WF, Prahl SA, Welch AJ (1990) A review of the optical properties of biological tissues. IEEE J Quantum Electron 26(12):2166–2185

    Article  Google Scholar 

  62. Firbank M, Hiraoka M, Essenpreis M, Delpy DT (1993) Measurement of the optical properties of the skull in the wavelength range 650–950 nm. Phys Med Biol 38(4):503–510

    Article  PubMed  CAS  Google Scholar 

  63. van der Zee P, Essenpreis M, Delpy DT (1993) Optical properties of brain tissue. Proc SPIE 1888:454–465

    Article  Google Scholar 

  64. Simpson CR, Kohl M, Essenpreis M, Cope M (1998) Near-infrared optical properties of ex vivo human skin subcutaneous tissue measured using the Monte Carlo inversion technique. Phys Med Biol 43(9):2465–2478

    Article  PubMed  CAS  Google Scholar 

  65. Kienle A, Glanzmann T (1999) In vivo determination of the optical properties of muscle with time-resolved reflectance using a layered model. Phys Med Biol 44(11):2689–2702

    Article  PubMed  CAS  Google Scholar 

  66. Meinke M, Müller G, Helfmann J, Friebel M (2007) Empirical model functions to calculate hematocrit-dependent optical properties of human blood. Appl Opt 46(10):1742–1753

    Article  PubMed  CAS  Google Scholar 

  67. Okada E, Delpy DT (2003) Near-infrared light propagation in an adult head model, II: effect of superficial tissue thickness on the sensitivity of the near-infrared spectroscopy signal. Appl Opt 42(16):2915–2922

    Article  PubMed  Google Scholar 

  68. Henyey LG, Greenstein JL (1941) Diffuse radiation in the galaxy. Astrophys J 93(1):70–83

    Article  Google Scholar 

  69. Patterson MS, Wilson BC, Wyman DR (1991) The propagation of optical radiation in tissue, I: models of radiation transport and their application. Lasers Med Sci 6(2):155–168

    Article  Google Scholar 

  70. Ishimaru A (1978) Wave propagation and scattering in random media. Academic, New York

    Google Scholar 

  71. Furutsu K, Yamada Y (1994) Diffusion approximation for a dissipative random medium and the applications. Phys Rev E 50(5):3634–3640

    Article  CAS  Google Scholar 

  72. Martelli F, Sassaroli A, Yamada Y, Zaccanti G (2002) Analytical approximate solutions of the time-domain diffusion equation in layered slab. J Opt Soc Am A 19(1):71–80

    Article  Google Scholar 

  73. Wang S, Shibahara N, Kuramashi D, Okawa S, Kakuta N, Okada E, Maki A, Yamada Y (2010) Effect of spatial variation of skull and cerebrospinal fluid layers on optical mapping of brain activity. Opt Rev 17(4):410–420

    Article  Google Scholar 

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Acknowledgments

I would like to acknowledge funding support from the Japan Society for the Promotion of Science, Grant-in-Aid for Scientific Research (B) (19360035), and invaluable scientific discussions with Drs. Hiroshi Kawaguchi and Tsuyoshi Yamamoto.

Author information

Authors and Affiliations

  1. Department of Electronics and Electrical Engineering, Keio University, Yokohama, 223-8522, Japan

    Eiji Okada Ph.D.

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  1. Eiji Okada Ph.D.
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Correspondence to Eiji Okada Ph.D. .

Editor information

Editors and Affiliations

  1. BIOCHEMISTRY & MOLECULAR MEDICINE, University of California Davis BIOCHEMISTRY & MOLECULAR MEDICINE, Davis, California, USA

    Thomas Jue

  2. Kanazawa University, Kanazawa, Japan

    Kazumi Masuda

Appendices

Problems

  1. 3.1.

    Assume that the concentration of hemoglobin is changed from 0.1 to 0.11 mM and the oxygen saturation of the blood is changed from 65% to 70% in the activated region of the brain. The extinction coefficients of oxygenated hemoglobin and deoxygenated hemoglobin at 780-nm wavelength are 0.16 and 0.25 mM−1 mm−1, respectively. The partial optical pathlength in the activated region for a probe pair is 5 mm.

    1. (a)

      Find the absorption change in the activated region.

    2. (b)

      Find the change in optical density (NIRS signal) caused by absorption change in the activated region.

  2. 3.2.

    Derive the equations that calculate the concentration change in oxygenated and deoxygenated hemoglobins from change in optical density (NIRS signal) at two wavelengths, λ 1 and λ 2. The extinction coefficient of oxygenated hemoglobin and deoxygenated hemoglobin is εoxy−Hb and εdeoxy−Hb, respectively. Assume that the wavelength dependence of the partial optical pathlength in the activated region <L act> can be ignored.

  3. 3.3.

    Draw polar plots of the probability distribution of deflection angle p(θ) described by the Henyey-Greenstein phase function for g = 0.1, g = 0.5, and g = 0.9.

  4. 3.4.

    A pencil beam of short pulse is incident onto tissues, and diffusely reflected light is detected at 20 mm from the incident point. Analyze light propagation in the tissues by analytical solution of the diffusion equation described in [25]. The optical properties of the tissues: (1) μ s  = 10 mm−1, g = 0.9, μ a  = 0.01 mm−1. (2) μ s  = 10 mm−1, g = 0.85, μ a  = 0.01 mm−1. (3) μ s  = 5 mm−1, g = 0.8, μ a  = 0.02 mm−1. Although the diffusion coefficient is defined as \( \kappa =1/3\{({{\mu^{\prime}}_s}+{\mu_a})\} \) in [25], \( \kappa =1/(3{{\mu^{\prime}}_s}) \) can be used for the calculations. The speed of light in the medium is 0.2 mm/ps, and refractive index mismatch at the tissue boundary can be ignored.

    1. (a)

      Determine the transport scattering coefficient of each tissue.

    2. (b)

      Determine the depth of the isotropic point source created by the incident beam.

    3. (c)

      Draw the temporal distribution of reflectance.

Further Reading

Frostig RD (ed) (2002) In vivo optical imaging of brain function. CRC Press, New York/Washington, DC

Potter RF (ed) (1993) Medical optical tomography: functional imaging and monitoring. SPIE Press, Washington, DC

Tuchin V (2000) Tissue optics. SPIE Press, Washington, DC

Wang LV, Wu H (2007) Biomedical optics. Wiley, New York

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Okada, E. (2013). Photon Migration in NIRS Brain Imaging. In: Jue, T., Masuda, K. (eds) Application of Near Infrared Spectroscopy in Biomedicine. Handbook of Modern Biophysics, vol 4. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-6252-1_3

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