Abstract

Frequency-domain near-infrared spectro-imaging offers significant advantages over the continuous-wave method in human brain applications. However, the drawback of existing instruments is a low signal-to-noise ratio for measured phase and modulation depth changes caused by cerebral activation. In this paper we show that in the case of the geometry specific for the activated area in the human brain, the SNR can be significantly improved by increasing the modulation frequency. We present the results of two studies: one performed experimentally using a sub-nanosecond pulsed light source and a spherical absorbing inhomo geneity immersed in a highly scattering solution, and the other performed numerically using Monte Carlo simulations of light transport in an MRI-based digital phantom of the adult human head. We show that changes caused by the absorbing inhomogeneity in both phase and modulation depth increase with frequency and reach maximum values at frequencies between 400 and 1400 MHz, depending on the particular source-detector distance. We also show that for the human head geometry an increase of the modulation frequency from 100 to 500 MHz can increase the phase SNR 2–3 times, and the modulation depth SNR up to 10 times.

© 2003 Optical Society of America

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References

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Appl. Opt. (2)

J. Biomed. Opt. (1)

J. H. Choi, M. Wolf, V. Toronov, U. Wolf, C. Polzonetti, D. Hueber, L. Safonova, R. Gupta, A. Michalos, W. Mantulin, E. Gratton, �??Noninvasive determination of absolute optical properties of adult human brain: near infrared spectroscopy approach,�?? J. Biomed. Opt. (in press)

Med. Phys. (1)

I.G. Zubal, C.R. Harrell, E.O. Smith, Z. Rattner, G. Gindi, P.B.Hoffer, �??Computerized 3-Dimensional Segmented Human Anatomy," Med. Phys. 21, 299-302 (1994), <a href="http://noodle.med.yale.edu/zubal/">http://noodle.med.yale.edu/zubal/</a>.
[CrossRef] [PubMed]

Neuroimage (2)

V. Toronov , A. Webb, S. Walker, R. Gupta, J. H. Choi, E. Gratton, D. Hueber, �??The Roles of Changes in Deoxyhemoglobin Concentration and Blood Volume in the fMRI BOLD Signal,�?? Neuroimage 19, 1521-31 (2003).
[CrossRef] [PubMed]

M. Firbank, E. Okada, D.T. Delpy, �??A theoretical study of the signal contribution of regions of the adult head to near infrared spectroscopy studies of visual evoked responses,�?? Neuroimage 8, 69-78 (1998).
[CrossRef] [PubMed]

Neurosci. Lett. (1)

A. Villringer, J. Planck, C. Hock, L. Schleinkofer, U. Dirnagl, "Near infrared spectroscopy (NIRS): a new tool to study hemodynamic changes during activation of brain function in human adults,�?? Neurosci. Lett. 154, 101-104 (1993).
[CrossRef] [PubMed]

Opt. Express (2)

Optics Express (1)

V. Toronov, A. Webb, J. H. Choi, M. Wolf, L. Safonova, U. Wolf, E. Gratton. �??Study of Local Cerebral Hemodynamic Fluctuations by Simultaneous Frequency-Domain near-infrared spectroscopy and fMRI,�?? Optics Express 9, 417-427 (2001), <a href="http://www.opticsexpress.org/abstract.cfm?URI=OPEX-9-8-417">.http://www.opticsexpress.org/abstract.cfm?URI=OPEX-9-8-417</a>
[CrossRef] [PubMed]

Photochem Photobiol. (1)

R.M. Danen, Y.Wang, X.D. Li, W.S.Thayer, A.G. Yodh, �??Regional imager for low-resolution functional imaging of the brain with diffusing near-infrared light,�?? Photochem Photobiol. 67, 33-40 (1998).
[CrossRef] [PubMed]

Phys. Med. Biol. (1)

C.D. Kurth and W.S. Thayer, �??A multiwavelength frequency-domain near-infrared cerebral oximeters,�?? Phys. Med. Biol. 44, 727-740 (1999).
[CrossRef] [PubMed]

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Figures (7)

Fig. 1.
Fig. 1.

Fluctuations in the frequency domain parameters acquired in -vivo using the 110 MHz ISS Oximeter. (a) Standard deviation of the phase. (b) Standard deviation of AC.

Fig. 2.
Fig. 2.

Schematic of the setup for the pulsed-laser experiment

Fig. 3.
Fig. 3.

Position of the object relative to the source and detector in the pulsed-laser experiment.

Fig. 4.
Fig. 4.

Experimental data from the pulsed-laser experiment: (a) normalized source, 15 mm, and 30 mm pulses (b) Fourier power spectra of pulses shown in Fig 4(a); (c) changes in phase caused by the absorbing inhomogeneity, (d) changes in modulation depth (AC/DC ratio); (e) phase SNR as function of modulation frequency; (f) MD SNR as function of frequency. In Figs. 4(e) and (f) the SNR values are computed using the analytical noise model. Values corresponding to each curve are normalized to the value for the same curve at 100 MHz

Fig. 5.
Fig. 5.

Changes in AC SNR caused by the absorbing object. Data is normalized to the DC SNR at 15 mm.

Fig. 6.
Fig. 6.

MRI -based digital phantom of the adult head used in Monte Carlo simulations

Fig. 7.
Fig. 7.

Monte Carlo simulated Data: ): (a) changes in phase caused by the absorbing inhomogeneity, (b) changes in modulation depth; (c) phase SNR as function of modulation frequency normalized to the 100 MHz value for the same distance; (d) MD SNR as function of frequency normalized to the 100 MHz value for the same distance; (e) phase SNR as function of modulation frequency normalized to the 100 MHz value for the 15 mm curve; (f) MD SNR as function of frequency normalized to the 100 MHz value for the 15 mm curve.

Equations (19)

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I ( t ) = a cos ( ωt + ϕ ) + b
i ( t ) = q Δ fg ( t ) N pe
i ( t ) = i ( t ) + ξ ( t ) ,
N pe ( t ) = ηS Δ f I ( t ) ,
i ( t ) = G ( t ) I ( t ) ,
i ( t ) = ( A cos ( ωt + ϕ ) + B ) ( 1 + m cos ( ω t ) ) ,
X = 4 T T 2 T 2 i ( t ) e i Ω t dt = A e + ψ ,
σ AC 2 = cos 2 ( ϕ ) ψ ' 2 + sin 2 ( ϕ ) ψ " 2 + 2 sin ( 2 ϕ ) ψ ' ψ "
σ Φ 2 = sin 2 ( ϕ ) ψ ' 2 + cos 2 ( ϕ ) ψ " 2 2 sin ( 2 ϕ ) ψ ' ψ " A 2 ,
DC = 4 T T 2 T 2 i ( t ) dt = DC + ζ ,
4 T T 2 T 2 ξ ( t ) dt .
ξ ( t ' ) ξ ( t " ) = σ i 2 ( t ' ) δ ( t ' t " ) ,
σ i 2 ( t ) = q Δ fg ( t ) i ( t ) = α ( A cos ( ωt + ϕ ) + B ) ( 1 + m cos ( ω ' t ) ) 2 ,
ψ ' 2 = ψ " 2 = α 4 ( 2 + m ) T B = α ( 2 + m ) T DC ,
ψ ' ψ " = 0 ,
σ DC = ζ 2 = γ DC ,
σ AC = β DC ,
σ Φ = β DC AC ,
σ AC DC = AC DC σ AC 2 + σ DC 2 DC 2 ,

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