Abstract

Laser Doppler flowmetry with a large source-detector spacing has been applied to measure blood perfusion in the deeper regions of tissue. The influence of the depth of perfusion on the Doppler spectrum for the large source-detector spacing is likely to be different from that for the conventional laser Doppler instruments with small source-detector spacing. In this study, the light propagation in a tissue model with a blood perfusion layer is predicted by the Monte Carlo simulation to discuss the influence of the depth of perfusion, blood volume, and source-detector spacing on the spectrum of the Doppler signal detected with large source-detector spacing. The influence of the depth of perfusion on the Doppler spectrum for the large source-detector spacing is different from that for the conventional laser Doppler instruments with small source-detector spacing, although the influence of source-detector spacing and blood volume on the Doppler spectrum for large source-detector spacing is almost the same as that for the conventional laser Doppler instruments. The influence of the depth of the perfusion on the Doppler spectrum depends on the path length that the detected light travels at different depths.

© 2003 Optical Society of America

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References

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  1. L. Duteil, J. C. Bernengo, W. Schalla, “A double wavelength laser Doppler system to investigate skin microcirculation,” IEEE. Trans. Biomed. Eng. BME-32, 439–447 (1985).
    [CrossRef]
  2. R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
    [CrossRef] [PubMed]
  3. R. Bonner, R. Nossal, “Model for laser Doppler measurements of perfusion in tissue,” Appl. Opt. 20, 2097–2107 (1981).
    [CrossRef] [PubMed]
  4. H. W. Jentink, F. F. de Mul, R. Graaff, H. E. Suichies, J. G. Aarnoudse, J. Greve, “Laser Doppler flowmetry: measurements in a layered perfusion model and Monte Carlo simulations of measurements,” Appl. Opt. 30, 2592–2597 (1991).
    [CrossRef] [PubMed]
  5. M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Laser Doppler blood flowmetry using two wavelengths: Monte Carlo simulations and measurements,” Appl. Opt. 33, 3549–3558 (1994).
    [CrossRef] [PubMed]
  6. H. W. Jentink, F. F. M. de Mul, R. G. A. M. Hermsen, R. Graaff, J. Greve, “Monte Carlo simulations of laser Doppler blood flow measurement using different lasers,” Appl. Opt. 29, 2371–2381 (1990).
    [CrossRef] [PubMed]
  7. M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Monte Carlo simulations and measurements of signals in laser Doppler flowmetry on human skin,” in Time-Resolved Spectroscopy and Imaging of Tissues, B. Chance, A. Katzir, eds., Proc. SPIE1431, 63–72 (1991).
    [CrossRef]
  8. M. Larsson, W. Steenbergen, T. Stromberg, “Influence of optical properties and fiber separation on laser doppler flownetry,” J. Biomed. Opt. 7, 236–243 (2002).
    [CrossRef] [PubMed]
  9. R. Lohwasser, G. Soelkner, “Experimental and theoretical laser-Doppler frequency spectra of a tissuelike model of a human head with capillaries,” Appl. Opt. 38, 2128–2137 (1999).
    [CrossRef]
  10. C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
    [CrossRef] [PubMed]
  11. S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
    [CrossRef] [PubMed]
  12. B. C. Wilson, G. Adam, “A Monte Carlo model for the absorption and flux distributions of light in tissue,” Med. Phys. 10, 824–830 (1983).
    [CrossRef] [PubMed]
  13. F. F. M. de Mul, M. H. Koelink, M. L. Kok, P. J. Harmsma, J. Greve, R. Graaff, J. G. Aarnoudse, “Laser Doppler velocimetry and Monte Carlo simulations on models for blood perfusion in tissue,” Appl. Opt. 34, 6595–6611 (1995).
    [CrossRef] [PubMed]
  14. M. K. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, G. Aarnoudse, “Analytical calculations and Monte Carlo simulations of laser Doppler flowmetry using a cubic lattice model,” Appl. Opt. 31, 3061–3067 (1992).
    [CrossRef] [PubMed]
  15. E. Okada, M. Firbank, D. T. Delpy, “The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy,” Phys. Med. Biol. 40, 2093–2108 (1995).
    [CrossRef] [PubMed]

2002

R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
[CrossRef] [PubMed]

M. Larsson, W. Steenbergen, T. Stromberg, “Influence of optical properties and fiber separation on laser doppler flownetry,” J. Biomed. Opt. 7, 236–243 (2002).
[CrossRef] [PubMed]

1999

1998

C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
[CrossRef] [PubMed]

1995

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

E. Okada, M. Firbank, D. T. Delpy, “The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy,” Phys. Med. Biol. 40, 2093–2108 (1995).
[CrossRef] [PubMed]

F. F. M. de Mul, M. H. Koelink, M. L. Kok, P. J. Harmsma, J. Greve, R. Graaff, J. G. Aarnoudse, “Laser Doppler velocimetry and Monte Carlo simulations on models for blood perfusion in tissue,” Appl. Opt. 34, 6595–6611 (1995).
[CrossRef] [PubMed]

1994

1992

1991

1990

1985

L. Duteil, J. C. Bernengo, W. Schalla, “A double wavelength laser Doppler system to investigate skin microcirculation,” IEEE. Trans. Biomed. Eng. BME-32, 439–447 (1985).
[CrossRef]

1983

B. C. Wilson, G. Adam, “A Monte Carlo model for the absorption and flux distributions of light in tissue,” Med. Phys. 10, 824–830 (1983).
[CrossRef] [PubMed]

1981

Aarnoudse, G.

Aarnoudse, J. G.

Adam, G.

B. C. Wilson, G. Adam, “A Monte Carlo model for the absorption and flux distributions of light in tissue,” Med. Phys. 10, 824–830 (1983).
[CrossRef] [PubMed]

Bauhuf, C.

R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
[CrossRef] [PubMed]

Bernengo, J. C.

L. Duteil, J. C. Bernengo, W. Schalla, “A double wavelength laser Doppler system to investigate skin microcirculation,” IEEE. Trans. Biomed. Eng. BME-32, 439–447 (1985).
[CrossRef]

Bondar, I.

R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
[CrossRef] [PubMed]

Bonner, R.

Cooper, C. E.

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

Cope, M.

C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
[CrossRef] [PubMed]

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

Dassel, A. C. M.

de Mul, F. F.

de Mul, F. F. M.

Delpy, D. T.

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

E. Okada, M. Firbank, D. T. Delpy, “The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy,” Phys. Med. Biol. 40, 2093–2108 (1995).
[CrossRef] [PubMed]

Duteil, L.

L. Duteil, J. C. Bernengo, W. Schalla, “A double wavelength laser Doppler system to investigate skin microcirculation,” IEEE. Trans. Biomed. Eng. BME-32, 439–447 (1985).
[CrossRef]

Essenpreis, M.

C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
[CrossRef] [PubMed]

Ewell, C. E.

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

Fahlbusch, R.

R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
[CrossRef] [PubMed]

Firbank, M.

E. Okada, M. Firbank, D. T. Delpy, “The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy,” Phys. Med. Biol. 40, 2093–2108 (1995).
[CrossRef] [PubMed]

Graaff, R.

F. F. M. de Mul, M. H. Koelink, M. L. Kok, P. J. Harmsma, J. Greve, R. Graaff, J. G. Aarnoudse, “Laser Doppler velocimetry and Monte Carlo simulations on models for blood perfusion in tissue,” Appl. Opt. 34, 6595–6611 (1995).
[CrossRef] [PubMed]

M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Laser Doppler blood flowmetry using two wavelengths: Monte Carlo simulations and measurements,” Appl. Opt. 33, 3549–3558 (1994).
[CrossRef] [PubMed]

M. K. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, G. Aarnoudse, “Analytical calculations and Monte Carlo simulations of laser Doppler flowmetry using a cubic lattice model,” Appl. Opt. 31, 3061–3067 (1992).
[CrossRef] [PubMed]

H. W. Jentink, F. F. de Mul, R. Graaff, H. E. Suichies, J. G. Aarnoudse, J. Greve, “Laser Doppler flowmetry: measurements in a layered perfusion model and Monte Carlo simulations of measurements,” Appl. Opt. 30, 2592–2597 (1991).
[CrossRef] [PubMed]

H. W. Jentink, F. F. M. de Mul, R. G. A. M. Hermsen, R. Graaff, J. Greve, “Monte Carlo simulations of laser Doppler blood flow measurement using different lasers,” Appl. Opt. 29, 2371–2381 (1990).
[CrossRef] [PubMed]

M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Monte Carlo simulations and measurements of signals in laser Doppler flowmetry on human skin,” in Time-Resolved Spectroscopy and Imaging of Tissues, B. Chance, A. Katzir, eds., Proc. SPIE1431, 63–72 (1991).
[CrossRef]

Greve, J.

F. F. M. de Mul, M. H. Koelink, M. L. Kok, P. J. Harmsma, J. Greve, R. Graaff, J. G. Aarnoudse, “Laser Doppler velocimetry and Monte Carlo simulations on models for blood perfusion in tissue,” Appl. Opt. 34, 6595–6611 (1995).
[CrossRef] [PubMed]

M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Laser Doppler blood flowmetry using two wavelengths: Monte Carlo simulations and measurements,” Appl. Opt. 33, 3549–3558 (1994).
[CrossRef] [PubMed]

M. K. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, G. Aarnoudse, “Analytical calculations and Monte Carlo simulations of laser Doppler flowmetry using a cubic lattice model,” Appl. Opt. 31, 3061–3067 (1992).
[CrossRef] [PubMed]

H. W. Jentink, F. F. de Mul, R. Graaff, H. E. Suichies, J. G. Aarnoudse, J. Greve, “Laser Doppler flowmetry: measurements in a layered perfusion model and Monte Carlo simulations of measurements,” Appl. Opt. 30, 2592–2597 (1991).
[CrossRef] [PubMed]

H. W. Jentink, F. F. M. de Mul, R. G. A. M. Hermsen, R. Graaff, J. Greve, “Monte Carlo simulations of laser Doppler blood flow measurement using different lasers,” Appl. Opt. 29, 2371–2381 (1990).
[CrossRef] [PubMed]

M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Monte Carlo simulations and measurements of signals in laser Doppler flowmetry on human skin,” in Time-Resolved Spectroscopy and Imaging of Tissues, B. Chance, A. Katzir, eds., Proc. SPIE1431, 63–72 (1991).
[CrossRef]

Harmsma, P. J.

Hermsen, R. G. A. M.

Jentink, H. W.

Koelink, M. H.

Koelink, M. K.

Kohl, M.

C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
[CrossRef] [PubMed]

Kok, M. L.

Larsson, M.

M. Larsson, W. Steenbergen, T. Stromberg, “Influence of optical properties and fiber separation on laser doppler flownetry,” J. Biomed. Opt. 7, 236–243 (2002).
[CrossRef] [PubMed]

Lohwasser, R.

Matcher, S. J.

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

Nossal, R.

Okada, E.

E. Okada, M. Firbank, D. T. Delpy, “The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy,” Phys. Med. Biol. 40, 2093–2108 (1995).
[CrossRef] [PubMed]

Schalla, W.

L. Duteil, J. C. Bernengo, W. Schalla, “A double wavelength laser Doppler system to investigate skin microcirculation,” IEEE. Trans. Biomed. Eng. BME-32, 439–447 (1985).
[CrossRef]

Simpson, C. R.

C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
[CrossRef] [PubMed]

Soelkner, G.

Steenbergen, W.

M. Larsson, W. Steenbergen, T. Stromberg, “Influence of optical properties and fiber separation on laser doppler flownetry,” J. Biomed. Opt. 7, 236–243 (2002).
[CrossRef] [PubMed]

Steinmeier, R.

R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
[CrossRef] [PubMed]

Stromberg, T.

M. Larsson, W. Steenbergen, T. Stromberg, “Influence of optical properties and fiber separation on laser doppler flownetry,” J. Biomed. Opt. 7, 236–243 (2002).
[CrossRef] [PubMed]

Suichies, H. E.

Wilson, B. C.

B. C. Wilson, G. Adam, “A Monte Carlo model for the absorption and flux distributions of light in tissue,” Med. Phys. 10, 824–830 (1983).
[CrossRef] [PubMed]

Anal. Biochem.

S. J. Matcher, C. E. Ewell, C. E. Cooper, M. Cope, D. T. Delpy, “Performance comparison of several publish tissue near-infrared spectroscopy algorithms,” Anal. Biochem. 227, 54–68 (1995).
[CrossRef] [PubMed]

Appl. Opt.

R. Bonner, R. Nossal, “Model for laser Doppler measurements of perfusion in tissue,” Appl. Opt. 20, 2097–2107 (1981).
[CrossRef] [PubMed]

H. W. Jentink, F. F. M. de Mul, R. G. A. M. Hermsen, R. Graaff, J. Greve, “Monte Carlo simulations of laser Doppler blood flow measurement using different lasers,” Appl. Opt. 29, 2371–2381 (1990).
[CrossRef] [PubMed]

H. W. Jentink, F. F. de Mul, R. Graaff, H. E. Suichies, J. G. Aarnoudse, J. Greve, “Laser Doppler flowmetry: measurements in a layered perfusion model and Monte Carlo simulations of measurements,” Appl. Opt. 30, 2592–2597 (1991).
[CrossRef] [PubMed]

M. K. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, G. Aarnoudse, “Analytical calculations and Monte Carlo simulations of laser Doppler flowmetry using a cubic lattice model,” Appl. Opt. 31, 3061–3067 (1992).
[CrossRef] [PubMed]

M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Laser Doppler blood flowmetry using two wavelengths: Monte Carlo simulations and measurements,” Appl. Opt. 33, 3549–3558 (1994).
[CrossRef] [PubMed]

R. Lohwasser, G. Soelkner, “Experimental and theoretical laser-Doppler frequency spectra of a tissuelike model of a human head with capillaries,” Appl. Opt. 38, 2128–2137 (1999).
[CrossRef]

F. F. M. de Mul, M. H. Koelink, M. L. Kok, P. J. Harmsma, J. Greve, R. Graaff, J. G. Aarnoudse, “Laser Doppler velocimetry and Monte Carlo simulations on models for blood perfusion in tissue,” Appl. Opt. 34, 6595–6611 (1995).
[CrossRef] [PubMed]

IEEE. Trans. Biomed. Eng.

L. Duteil, J. C. Bernengo, W. Schalla, “A double wavelength laser Doppler system to investigate skin microcirculation,” IEEE. Trans. Biomed. Eng. BME-32, 439–447 (1985).
[CrossRef]

J. Biomed. Opt.

M. Larsson, W. Steenbergen, T. Stromberg, “Influence of optical properties and fiber separation on laser doppler flownetry,” J. Biomed. Opt. 7, 236–243 (2002).
[CrossRef] [PubMed]

Med. Phys.

B. C. Wilson, G. Adam, “A Monte Carlo model for the absorption and flux distributions of light in tissue,” Med. Phys. 10, 824–830 (1983).
[CrossRef] [PubMed]

NeuroImage

R. Steinmeier, I. Bondar, C. Bauhuf, R. Fahlbusch, “Laser Doppler flowmetry mapping of cerebrocortical microflow: characteristics and limitations,” NeuroImage 15, 107–119 (2002).
[CrossRef] [PubMed]

Phys. Med. Biol.

C. R. Simpson, M. Kohl, M. Essenpreis, M. Cope, “Near-infrared optical properties of ex vivo human skin and subcutaneous tissues measured using the Monte Carlo inversion technique,” Phys. Med. Biol. 43, 2465–2478 (1998).
[CrossRef] [PubMed]

E. Okada, M. Firbank, D. T. Delpy, “The effect of overlying tissue on the spatial sensitivity profile of near-infrared spectroscopy,” Phys. Med. Biol. 40, 2093–2108 (1995).
[CrossRef] [PubMed]

Other

M. H. Koelink, F. F. M. de Mul, J. Greve, R. Graaff, A. C. M. Dassel, J. G. Aarnoudse, “Monte Carlo simulations and measurements of signals in laser Doppler flowmetry on human skin,” in Time-Resolved Spectroscopy and Imaging of Tissues, B. Chance, A. Katzir, eds., Proc. SPIE1431, 63–72 (1991).
[CrossRef]

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Figures (9)

Fig. 1
Fig. 1

Tissue model for the Monte Carlo simulation.

Fig. 2
Fig. 2

Doppler power spectra at a blood velocity of 10 mm/s for source-detector spacings (a) of 10 mm and (b) of 20 mm.

Fig. 3
Fig. 3

Calculated average Doppler frequency as a function of the depth of perfusion.

Fig. 4
Fig. 4

Average Doppler frequency as a function of the blood volume in the perfusion layer at a velocity of perfusion of 10 mm/s for a source-detector spacing of 20 mm.

Fig. 5
Fig. 5

Average number of Doppler scattering events as a function of the depth of the perfusion layer.

Fig. 6
Fig. 6

Average number of Doppler scattering events as a function of the blood volume in the perfusion layer for a source-detector spacing of 20 mm.

Fig. 7
Fig. 7

Accumulated trajectories of the detected photons for source-detector spacings (a) of 10 mm, (b) of 20 mm, (c) of 30 mm.

Fig. 8
Fig. 8

Normalized path length of detected photons at different depths. Gray bars at the bottom represent the depth of perfusion layers used to calculate the results shown in Figs. 2, 3, and 5.

Fig. 9
Fig. 9

Relation between the average Doppler frequency and the average number of Doppler scattering events.

Equations (6)

Equations on this page are rendered with MathJax. Learn more.

li=-lnP/μs,
Δfs=12πks-kiv,
Wn=W0 exp-μaL,
Sf=Sm · Δfr=c i=0N-m WiWi+m,
f=0 f Sfdf0 Sfdf,
Nave=i=0MAXDop ci ii=0MAXDop ci,

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