Abstract

Simulations based on diffusion theory that use a finite-element method and rely on an magnetic resonance imaging head model suggest that time-resolved diffuse optical techniques could provide information about the depth at which variations in perfusion take place and improve the detection of cortical activation. Experimental investigations were performed with sequentially driven picosecond laser diodes and an eight-channel time-correlated single-photon-counting detection system. The experimental results obtained for activation in the motor cortex, and for the Valsalva maneuver, confirm our assumptions and are in good agreement with the simulated data.

© 2005 Optical Society of America

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  1. B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).
  2. Y. Fukui, Y. Ajichi, E. Okada, “Monte Carlo prediction of near-infrared light propagation in realistic adult and neonatal head models,” Appl. Opt. 42, 2881–2887 (2003).
    [CrossRef] [PubMed]
  3. S. R. Arridge, M. Schweiger, M. Hiraoka, D. T. Delpy, “A finite element approach for modelling photon transport in tissue,” Med. Phys. 20, 299–309 (1993).
    [CrossRef] [PubMed]
  4. M. Schweiger, S. R. Arridge, “Comparison of two- and three-dimensional reconstruction methods in optical tomography,” Appl. Opt. 37, 7419–7428 (1998).
    [CrossRef]
  5. S. R. Arridge, M. Schweiger, “Photon-measurement density functions. Part 2: Finite-element-method calculations,” Appl. Opt. 34, 8026–8037 (1995).
    [CrossRef] [PubMed]
  6. P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
    [CrossRef]
  7. D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
    [CrossRef] [PubMed]
  8. F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
    [CrossRef] [PubMed]
  9. J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
    [CrossRef] [PubMed]

2004 (2)

F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
[CrossRef] [PubMed]

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

2003 (1)

1998 (1)

1995 (1)

1993 (2)

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

S. R. Arridge, M. Schweiger, M. Hiraoka, D. T. Delpy, “A finite element approach for modelling photon transport in tissue,” Med. Phys. 20, 299–309 (1993).
[CrossRef] [PubMed]

1988 (1)

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Ajichi, Y.

Alter, C.

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

Arridge, S.

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Arridge, S. R.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

M. Schweiger, S. R. Arridge, “Comparison of two- and three-dimensional reconstruction methods in optical tomography,” Appl. Opt. 37, 7419–7428 (1998).
[CrossRef]

S. R. Arridge, M. Schweiger, “Photon-measurement density functions. Part 2: Finite-element-method calculations,” Appl. Opt. 34, 8026–8037 (1995).
[CrossRef] [PubMed]

S. R. Arridge, M. Schweiger, M. Hiraoka, D. T. Delpy, “A finite element approach for modelling photon transport in tissue,” Med. Phys. 20, 299–309 (1993).
[CrossRef] [PubMed]

Austin, T.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Chance, B.

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

Cope, M.

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Cunin, B.

P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
[CrossRef]

Delpy, D. T.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

S. R. Arridge, M. Schweiger, M. Hiraoka, D. T. Delpy, “A finite element approach for modelling photon transport in tissue,” Med. Phys. 20, 299–309 (1993).
[CrossRef] [PubMed]

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Everdell, N.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Fukui, Y.

Gao, F.

F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
[CrossRef] [PubMed]

Gibson, A.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Hebden, J. C.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Hiraoka, M.

S. R. Arridge, M. Schweiger, M. Hiraoka, D. T. Delpy, “A finite element approach for modelling photon transport in tissue,” Med. Phys. 20, 299–309 (1993).
[CrossRef] [PubMed]

Lipton, L.

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

Meek, J. H.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Okada, E.

Poulet, P.

P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
[CrossRef]

Schweiger, M.

Tanikawa, Y.

F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
[CrossRef] [PubMed]

Torregrossa, M.

P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
[CrossRef]

Uhring, W.

P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
[CrossRef]

Unah, C.

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

Van der Zee, P.

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Wray, S.

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Wyatt, J.

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

Wyatt, J. S.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Yamada, Y.

F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
[CrossRef] [PubMed]

Yusof, R.

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Zhao, H.

F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
[CrossRef] [PubMed]

Zhuang, Z.

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

Zint, C. V.

P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
[CrossRef]

Appl. Opt. (3)

Med. Phys. (1)

S. R. Arridge, M. Schweiger, M. Hiraoka, D. T. Delpy, “A finite element approach for modelling photon transport in tissue,” Med. Phys. 20, 299–309 (1993).
[CrossRef] [PubMed]

Phys. Med. Biol. (3)

D. T. Delpy, M. Cope, P. Van der Zee, S. Arridge, S. Wray, J. Wyatt, “Estimation of optical pathlength through tissue from direct time of flight measurement,” Phys. Med. Biol. 33, 1433–1442 (1988).
[CrossRef] [PubMed]

F. Gao, H. Zhao, Y. Tanikawa, Y. Yamada, “Optical tomographic mapping of cerebral haemodynamics by means of time-domain detection: methodology and phantom validation,” Phys. Med. Biol. 49, 1055–1078 (2004).
[CrossRef] [PubMed]

J. C. Hebden, A. Gibson, T. Austin, R. Yusof, N. Everdell, D. T. Delpy, S. R. Arridge, J. H. Meek, J. S. Wyatt, “Imaging changes in blood volume and oxygenation in the newborn infant brain using three-dimensional optical tomography,” Phys. Med. Biol. 49, 1117–1130 (2004).
[CrossRef] [PubMed]

Proc. Natl. Acad. Sci. (1)

B. Chance, Z. Zhuang, C. Unah, C. Alter, L. Lipton, “Cognition-activated low-frequency modulation of light absorption in human brain,” Proc. Natl. Acad. Sci. 90, 3770–3774 (1993).

Other (1)

P. Poulet, C. V. Zint, M. Torregrossa, W. Uhring, B. Cunin, “Comparison of two time-resolved detectors for diffuse optical tomography: photomultiplier tube–time-correlated single photon counting and multichannel streak camera,” in Optical Tomography and Spectroscopy of Tissue V, B. Chance, R. Alfano, B. Tromberg, M. Tamura, E. Sevick-Muraca, eds., Proc. SPIE4955, 154–163 (2003).
[CrossRef]

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Figures (9)

Fig. 1
Fig. 1

Segmented image of the head with a model of activation in the cortex. The gray scale represents the inverse of the absorption coefficient. The source and detector positions used for computations are shown.

Fig. 2
Fig. 2

FEM solution to the diffusion equation at four consecutive times superimposed on the coronal MRI slice of the head used for the optical model. White lines represent places where the photon density is 10%, 1%, 0.1%, and 0.01% of the maximum.

Fig. 3
Fig. 3

The μa PMDFs for four source–detector distances superimposed on the coronal MRI slice of the head used for the optical model. White lines represent places where the sensitivity is 10%, 1%, and 0.1% of the maximum.

Fig. 4
Fig. 4

The μa PMDFs for three different photon arrival times superimposed on the coronal MRI slice of the head used for the optical model, as well as the TPSF corresponding to this configuration. The distance between the source and the detector is 30 mm. White lines represent places where the sensitivity is 10%, 1%, and 0.1% of the maximum.

Fig. 5
Fig. 5

Experimental setup of the system used for the detection of activation in the motor cortex.

Fig. 6
Fig. 6

TPSF at rest (thin, solid curve). Differences between the TPSFs during activation and at rest: simulated (dashed curve), experimental (dotted curve), and filtered experimental (thick, solid curve). The integral intensities of the TPSF and of the simulated differences were normalized to the integral intensity of the filtered experimental difference: (a) Valsalva maneuver and (b) cortical activation. Measurements were taken at 830 nm and 30 mm.

Fig. 7
Fig. 7

Experimental (dotted curve) and filtered experimental (solid curve) differences (Valsalva maneuver minus motor cortex activation) between the two curves shown in Figs. 6(a) and 6(b).

Fig. 8
Fig. 8

(a) Temporal strips of the TPSF from 1 to 8. (b) Intensity variation curves relative to the mean intensity along the first rest period (graph 8 has a different scale). Contrast and CNR were computed as explained in the text. Measurements were taken at 830 nm and 30 mm.

Fig. 9
Fig. 9

Mean variation in oxyhemoglobin (ΔHbO2) (thin solid curve) and deoxyhemoglobin (ΔHb) (thick solid curve) concentrations in the analyzed area during activation of the motor cortex. Four stimulation periods (bold zones) of 32 s each were conducted with rest periods between them.

Tables (1)

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Table 1 Optical Properties of Tissues for a Wavelength of 800 nm

Equations (2)

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Attenuation ( OD ) = - log ( I I 0 ) = ɛ C L B + G ,
LB = c n t ,

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