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Virtual Journal for Biomedical Optics

Virtual Journal for Biomedical Optics

| EXPLORING THE INTERFACE OF LIGHT AND BIOMEDICINE

  • Editor: Gregory W. Faris
  • Vol. 1, Iss. 7 — Jul. 17, 2006

Optics InfoBase > Virtual Journal for Biomedical Optics > Volume 1 > Issue 7 > Page 5418

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Multi-channel time-resolved system for functional near infrared spectroscopy

Davide Contini, Alessandro Torricelli, Antonio Pifferi, Lorenzo Spinelli, Floriano Paglia, and Rinaldo Cubeddu  »View Author Affiliations


Optics Express, Vol. 14, Issue 12, pp. 5418-5432 (2006)
http://dx.doi.org/10.1364/OE.14.005418


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Abstract

We have designed a compact dual wavelength multi-channel time-resolved system for functional near infrared spectroscopy. The system enables 16 sources and up to 64 collection points, with a minimum acquisition time of 5 ms per channel. Performances of the system have been tested on tissue phantoms in terms of linearity, noise, stability and reproducibility. Preliminary measurements on volunteers have been performed to validate the instrument capability to acquire in vivo maps of the hemodynamic parameters in the muscle during arterial occlusion and in the adult head during a finger tapping experiment.

© 2006 Optical Society of America

1. Introduction

Human brain mapping by functional near infrared spectroscopy (fNIRS) [1

Y. Hoshi and M. Tamura, “Detection of dynamic changes in cerebral oxygenation coupled to neuronal function during mental work in man,” Neurosci. Lett. 150, 5–8 (1993). [CrossRef] [PubMed]

–3

H. Obrig and A. Villringer, “Beyond the Visible—Imaging the Human Brain With Light,” J. Cereb. Blood Flow Metab. 23, 1–18 (2003). [CrossRef]

] is one of the most challenging and fascinating applications which employ red and near infrared light to non-invasively probe diffusive media like biological tissues [4

A. Yodh and B. Chance, “Spectroscopy and imaging with diffusing light”, Phys. Today 48, 34–40 (1995). [CrossRef]

]. Indeed the problem of mapping functional activation in the human brain by optical radiation is complicate. The diffusive nature of biological tissues prevents the discrimination of absorption and scattering contributions by simple continuous wave (CW) techniques. Therefore, CW techniques measure changes in the absorption coefficient and consequently derive changes, rather than absolute values, in the hemodynamics parameters (i.e. concentration of oxy-hemoglobin and deoxy-hemoglobin) [5

A. Villringer and B. Chance, “Noninvasive optical spectroscopy and imaging of human brain function,” Trends in Neurosci. 20, 435–442 (1997). [CrossRef]

]. For a majority of applications this approach is nonetheless interesting and efficient, thanks to the excellent signal-to-noise ratio and to the manageable configuration that CW systems normally exhibit.

However, the head is a strongly heterogeneous structure from an optical point of view. Light passes through the scalp, the skull and the cerebrospinal fluid (CSF) before reaching the brain and eventually probing cortical activation, typically a few centimeters below the head’s surface. To enhance depth sensitivity, CW systems use a large source detector distance, of the order of 4–5 cm, therefore increasing the sampled volume and worsening localization of the activated area. The use of multi-source and multi-detector tomographic or topographic arrangements could overcome this limitation at the expenses of increasing the overall complexity of the system [6

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23, S275–S288 (2004). [CrossRef] [PubMed]

].

In principle time- and frequency domain techniques provide a richer insight to the problem of non-invasively probing a diffusive medium. These approaches can discriminate between absorption and scattering contributions and derive absolute values for the hemodynamic parameters [7

M. S. Patterson, B. Chance, and B. C. Wilson, “Time resolved reflectance and transmittance for the noninvasive measurement of tissue optical properties,” Appl. Opt. 28, 2331–2336 (1989). [CrossRef] [PubMed]

, 8

M. S. Patterson, J. D. Moulton, B. C. Wilson, K. W. Berndt, and J. R. Lakowicz, “Frequency-domain reflectance for the determination of the scattering and absorption properties of tissue,” Appl. Opt. 30, 4474–4476 (1991). [CrossRef] [PubMed]

]. This however can be easily obtained in simple homogeneous models, while in a real heterogeneous medium like the human head it is easier to derive changes with respect to a baseline or effective average parameters rather than absolute values. For example, advanced time-resolved perturbation models for layered media have been recently derived [9

F. Martelli, S. Del Bianco, and G. Zaccanti, “Perturbation model for light propagation through diffusive layered media,” Phys. Med. Biol. 50, 2159–2166 (2005). [CrossRef] [PubMed]

], but they would require the use of a priori information (e.g., the anatomy of the head as provided by a MRI scan) for their practical and effective use with a simple, single source-detector, time-resolved set-up.

The actual potentiality of time-resolved techniques relies on an easier approach to the problem of depth sensitivity. Relevant studies have in fact shown either theoretically or experimentally, that in the time-domain depth sensitivity can be improved by simply exploiting the temporal information [10

J. Steinbrink, H. Wabnitz, H. Obrig, A. Villringer, and H. Rinneberg, “Determining changes in NIR absorption using a layered model of the human head,” Phys. Med. Biol. 46, 879–896 (2001). [CrossRef] [PubMed]

–12

J. Selb, J. J. Stott, M. A. Franceschini, A. G. Sorensen, and D. A. Boas, “Improved sensitivity to cerebral hemodynamics during brain activation with a time-gated optical system: analytical model and experimental validation,” J. Biomed Opt. 10, 11013 (2005). [CrossRef] [PubMed]

]. Further, we have recently shown that the use of a novel scheme for source-detector geometry in a time-resolved set-up would lead to increased contrast and spatial resolution [13

A. Torricelli, A. Pifferi, L. Spinelli, R. Cubeddu, F. Martelli, S. Del Bianco, and G. Zaccanti, “Timeresolved reflectance at null source-detector separation: improving contrast and resolution in diffuse optical imaging,” Phys. Rev. Lett. 95, 078101 (2005). [CrossRef] [PubMed]

].

Following these guiding principles, we have been developing and testing compact and portable multi-wavelengths multi-channel time-resolved systems for tissue oximetry and functional imaging studies. A first dual wavelength time-resolved system was built with a 4-channel detection stage [14

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “Compact tissue oximeter based on dual-wavelength multichannel time-resolved reflectance”, Appl. Opt. 38, 3670–3680 (1999). [CrossRef]

]. Then the performances were improved to an 8-channel set-up, which was effectively used for the noninvasive measurement of tissue oxygenation in the calf muscle [15

A. Torricelli, V. Quaresima, A. Pifferi, G. Biscotti, L. Spinelli, P. Taroni, M. Ferrari, and R. Cubeddu, “Mapping of calf muscle oxygenation and haemoglobin content during dynamic plantar flexion exercise by multi-channel time-resolved near infrared spectroscopy”, Phys. Med. Biol. 49, 685–699, (2004). [CrossRef] [PubMed]

] and in the frontal cortex [16

V. Quaresima, M. Ferrari, A. Torricelli, L. Spinelli, A. Pifferi, and R. Cubeddu, “Bilateral prefrontal cortex oxygenation responses to a verbal fluency task: a multichannel time-resolved near-infrared topography study,” J. Biomed. Opt. 10, 011012 (2005). [CrossRef]

]. Finally, we upgraded the system to a 9-source 12-detector configuration [17

D. Contini, A. Torricelli, A. Pifferi, L. Spinelli, P. Taroni, V. Quaresima, M. Ferrari, and R. Cubeddu, “Multi-channel time-resolved tissue oximeter for functional imaging of the brain,” IEEE Trans. Instrum. Meas. 55, 85–90 (2006). [CrossRef]

].

Due to limitations of the previous systems, in terms of signal-to-noise ratio and number of available channels, we have therefore pursued an advanced scheme to build a new multi-channel time-resolved system for functional NIR spectroscopy and diffuse optical imaging. In this work we describe the newest instrument which represents a breakthrough with respect to our previous systems for what concerns both sensitivity and imaging capability. In Section 2 we present the system set-up, while in Section 3 we report on system characterization. Preliminary in vivo measurements during cuff occlusion on the adult forearm muscle and on adult head during a finger tapping experiment are also presented in Section 4. Finally, Section 5 discusses similarity and differences of our set-up with respect to recently developed time-resolved systems.

2. System description

2.1 System set-up

Figure 1 reports the scheme of the novel system developed at the Department of Physics, Politecnico di Milano. A couple of pulsed diode lasers, operating at 690 nm and 820 nm, with 80 MHz repetition rate and 1 mW average power (PDL, Picoquant GmbH, Germany), are used as light sources. The laser heads are connected to multimode graded index fibers (50/125 µm) by means of a home-made coupler which combines a neutral density attenuator (J54-082, Edmund OptiK GmbH; Germany), with variable attenuation in the range 0–40 dB, and a standard FC fiber optics coupler. Multimode graded index optical fibers (50/125 µm) with different lengths and a 2×2 fused fiber optic splitter (VISNIR5050, OZ Optics, Canada) are used to time multiplexing the laser pulses at the different wavelengths, and to create two independent channels. In each channel a 1×9 fiber optic switch (F-SM19, PiezoJena GmbH, Germany) creates up to 9 independent sources or injection points, therefore 18 sources are available. To the purpose of recording the IRF and to acquire a reference signal, which takes into account any possible drift in the system, we could choose to sacrifice one output channel in each switch to reach a configuration with 16 injection points. The reference signal is split into four parallel signals by a 2×4 fused fiber optic splitter (VISNIR-25-25-25-25, OZOptics, Canada) which are then directed to the detectors after proper attenuation.

Fig. 1. Scheme of the system set-up (ND: neutral density attenuator; S1–S16: source fibers; R1–R4, reference fibers; F1–F16: collection bundles; PMT: photomultiplier; amp: amplifier; TCSPC: time-correlated single photon counting; sync: synchronization signal; µCHIP: microcontroller unit).

Four parallel detection chains accomplish acquisition of time-resolved reflectance curves. Each chain consists of a compact 4-channel photomultiplier (PMT) with a multialkali surface (R5900-20-M4, Hamamatsu Photonics, Japan), a routing electronics (HRT-41, Becker&Hickl, Germany), a fast amplifier (HFAC-26, Becker&Hickl, Germany) and a PC board (SPC130, Becker&Hickl, Germany) for time-correlated single photon counting (TCSPC). The parallel use of the four detection and acquisition lines enables a total of 16 independent detectors. Home-built fiber optic bundles, made by seven 1 mm core plastic fibers (ESKA CK-40, Mitsubishi Rayon Co., Japan), are used for light collection from tissue.

The system is controlled by a personal computer (Pentium IV 3.5 GHz, 2 Gb RAM), which hosts the acquisition boards and it is used for data storage. A home made software, written in C language in the LabWindows/CVI environment (National Instruments, TX), is used to control the instrument. The software is interfaced to a micro-controller unit (dsPIC30F6014, Microchip Technology Inc., AZ) which is used for the hardware control of the instrumentation. In particular, the micro-controller unit generates trigger signals for the synchronization of data acquisition by the TCSPC boards and of the fiber optic switches. Typically, by means of the micro-controller unit, the sources can be activated sequentially in any desired sequence.

Since fast measurements are needed for functional studies of brain hemodynamics and a large number of injection/collection points is required to perform imaging, there is a natural trade off between acquisition time, number of channels and signal-to-noise ratio. To obtain maximum flexibility, we have therefore designed the system so as it can operate with a minimum acquisition time of 2 ms in a single channel. When using multiple channel the 1x9 fiber optic switches set a constraint in the switching time to 5 ms, therefore a complete scan of all 16 sources can be performed in less than 50 ms.

The instrument response function (IRF) obtained by filling all the propagating modes of the bundle has a FWHM of approximately 500 ps. Figure 2 shows an example of the IRF and of a time-resolved reflectance (TRS) curve at 690 nm and at 820 nm.

Fig. 2. Example of instrument response function (IRF) and time-resolved reflectance curve (TRS) at 690 nm and 820 nm.

It is also possible to interface the instrument with dedicated software (Presentation, Neurobehavioral Systems, Inc, Albany, CA) for the management of functional studies.

2.2 Management of the multi-channel configuration

The system has been designed to operate like two parallel systems (e.g., for the left and right hemisphere in case of functional brain studies) with up to 9 injection points each. The maximum number of fiber bundles is 64. The external dimension of each fiber bundle, with protective jacket and fiber holder, is in fact 4 mm, while the area of a quadrant of the 4-channel PMT is approximately 9×9 mm2. Therefore we can couple 4 bundles to each quadrant, corresponding to a maximum of 16 bundles for each PMT, and a total of 64 bundles for the complete system. In the current configuration we have limited the number of fiber bundles to 16. This choice was made to simplify all test procedures both in vitro and in vivo. Work is in progress to build 48 other fiber bundles.

When using more than 16 fiber bundles, care should be taken to avoid cross talk. Cross talk between different PMTs might originate from the read-out electronics (mainly routers), and setting proper limits in the photon count rate can prevent it. At values lower than 2 MHz we did not experienced any reduction in the system performance due to cross talk. Optical cross talk between fiber bundles placed in different quadrant is negligible since each fiber bundle is in close contact with the PMT glass protective surface and shielded by a metallic holder. Finally, optical cross talk from fiber bundles placed in the same PMT quadrant is kept out by not collecting photons at the same time. For example, suppose to design two optical probes, with a hexagonal layout, working in parallel, each with 4 sources (S1–S4 and S5–S8, respectively) and 16 fiber bundles (F1–F16 and F17–F32, respectively), as shown in Fig. 3. Coupling between fiber bundles and PMTs is shown in Fig. 3 bottom row. Fiber bundles belonging to probe 1 (i.e., F1–F16) are connected to PMT-1 and PMT-2, while fiber bundles belonging to probe 2 (i.e., F17–F32) are connected to PMT-3 and PMT-4. Sources belonging to the same probe are sequentially activated and a complete frame is acquired after 4 time steps. On the other hand, sources in different probes can be operated in parallel. At step 1, source S1 (S5) is on and bundles F1, F2, F3, F4, F5, and F6 (F17, F18, F19, F20, F21, and F22) are used for probe 1 (probe 2). At step 2, source S2 (S6) and bundles F3, F4, F7, F8, F9, and F10 (F19, F20, F23, F24, F25, and F26) are activated and so on.

Fig. 3. Example of fiber bundles displacement for two hexagonal probes, with 4 sources and 16 fiber bundles each (top). Strategy for avoiding cross talk among bundles for probe 1 (bottom). A similar scheme can be applied in parallel to PMT-3 and PMT4 for probe 2.

2.3 Data analysis

Simultaneous estimate of µs’ and µa may be achieved by best fitting of time-resolved reflectance curves with a standard model of diffusion theory [18

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. A 11, 2727–2741 (1994). [CrossRef]

]. To reduce dispersion of the fitted absorption coefficient values, we use the methods described by Nomura et al. [19

Y. Nomura, O. Hazeki, and M. Tamura, “Relationship between time-resolved and non-time-resolved Beer-Lambert law in turbid media,” Phys. Med. Biol. 42, 1009–1023 (1997). [CrossRef] [PubMed]

] and known as microscopic Lambert-Beer Law. First, for each wavelength λ a reference time-resolved reflectance curve R0(ρ, t, λ), at a inter-fiber distance ρ, is derived by averaging the curves corresponding to an initial resting period (typically 20 s). Fitting of R0(ρ, t, λ) yields the reference absorption value µa0(λ). Then Δµa(λ), the variation from the reference value, and the absorption coefficient µa(λ) are derived according to Eq.(1) and Eq.(2):

Δ μa(λ)=− 1 vtln ( R(ρ,t;λ) R0 (ρ,t;λ))
(1)
μa(λ) = μ a0(λ)+Δ μa(λ)
(2)

where v is the speed of light in the medium. Improvement over the standard methods is more effective when the number of collected photons is low. In this condition in fact standard fitting with the non-linear least square methods yields high dispersion in the fitted data [20

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “Experimental test of theoretical models for time-resolved reflectance,” Med. Phys. 23, 1625–1634 (1996). [CrossRef] [PubMed]

]. A fitting range from 80% of the peak of TRS curve in the leading edge and 1% in the trailing edge of the TRS curve was chosen for estimate of µa0(λ). For the estimation of Δµa(λ) from Eq.2, the fitting range was 70% to 1% both limits in the trailing edge, so as to enhance the contribution of late photons rather than early photons [16

V. Quaresima, M. Ferrari, A. Torricelli, L. Spinelli, A. Pifferi, and R. Cubeddu, “Bilateral prefrontal cortex oxygenation responses to a verbal fluency task: a multichannel time-resolved near-infrared topography study,” J. Biomed. Opt. 10, 011012 (2005). [CrossRef]

].

Taking the assumption that oxy- and deoxy-hemoglobin (O2Hb and HHb, respectively) are the main chromophores contributing to absorption, their concentrations are easily derived by using the knowledge of the extinction coefficient [21

S. Prahl, Oregon Medical Laser Center website (2001), http://omlc.ogi.edu/spectra.

]. Then, total hemoglobin content (tHb=HHb+O2Hb) and tissue oxygen saturation (SO2=O2Hb/tHb) are derived.

3. System characterization

A protocol for standardization of diffuse optical instrument performances, developed within the framework of the European Thematic Network “Medphot” [22

A. Pifferi, A. Torricelli, A. Bassi, P. Taroni, R. Cubeddu, H. Wabnitz, D. Grosenick, M. Möller, R. Macdonald, J. Swartling, T. Svensson, S. Andersson-Engels, R. L. P. van Veen, H. J. C. M. Sterenborg, J. M. Tualle, H. L. Nghiem, E. Tinet, S. Avrillier, M. Whelan, and H. Stamm, “Performance assessment of photon migration instruments: the Medphot protocol,” Appl. Opt. 11, 2104–2114 (2005). [CrossRef]

], was applied to determine linearity, noise, reproducibility and stability of the novel time-resolved instrument. Solid tissue phantoms made of Titanium dioxide particle (scattering agent) and toner powder (absorbing agent) embedded in an epoxy resin matrix were used for system characterization. A set of 32 phantoms with optical properties typical for biological tissue in the red and near infrared spectral range was measured. Phantoms labeled from 1 to 8, represent nominal absorption changes from 0 to 0.49 cm-1, in 0.07 cm-1 steps, while phantoms labeled from A to D, represent nominal reduced scattering changes from 5 to 20 cm-1, in 5 cm-1 steps.

3.1 Linearity for µa and µs’

A reflectance configuration with one source and 16 detection fiber bundles at the same distance of 2 cm was employed. Attenuation and acquisition times were varied so as to collect for each measurement time-resolved reflectance curves with about 105 counts per each wavelength. Results were similar at the two wavelengths, so only data at 690 nm are reported.

In Fig. 4(a) and 4(c) the measured absorption coefficients at 690 nm is plotted versus the conventional true absorption and reduced scattering coefficients, respectively. The conventional true values were obtained with an independent system [22

A. Pifferi, A. Torricelli, A. Bassi, P. Taroni, R. Cubeddu, H. Wabnitz, D. Grosenick, M. Möller, R. Macdonald, J. Swartling, T. Svensson, S. Andersson-Engels, R. L. P. van Veen, H. J. C. M. Sterenborg, J. M. Tualle, H. L. Nghiem, E. Tinet, S. Avrillier, M. Whelan, and H. Stamm, “Performance assessment of photon migration instruments: the Medphot protocol,” Appl. Opt. 11, 2104–2114 (2005). [CrossRef]

]. Good linearity over the range 0–0.4 cm-1 is obtained, while a small deviation is observed at the highest absorption. Minimal discrepancies among the four sets of scattering phantoms, as expected from the validity of the diffusion model [20

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “Experimental test of theoretical models for time-resolved reflectance,” Med. Phys. 23, 1625–1634 (1996). [CrossRef] [PubMed]

], are found. The horizontal lines in Fig. 4(c) represent the conventional true value for the absorption coefficient. In Fig. 4(b) and 4(d) the measured reduced scattering at 690 nm is plotted versus the conventional true absorption and reduced scattering coefficients, respectively. Again, a limited coupling between the optical parameters and good linearity are found. The horizontal lines in Fig. 4(b) represent the conventional true value for the reduced scattering coefficient.

Error bars in each plot represent inter-channel dispersion. A median value of 8% for both the measured absorption and the reduced scattering was observed.

Fig. 4. Linearity on absorption coefficient (top) and scattering coefficient (bottom) at 690 nm. Details on experimental set-up are shown in the inset in panel (a).

3.2 Noise

A test was performed to study the effect of the number of counts in the time-resolved reflectance curve on the measured absorption coefficient. Results are shown in Fig. 5(a) for one channel. The coefficient of variation (CV) for the absorption coefficient is found to be lower than 1% if more than 2 104 counts are collected, while 105 counts are needed for similar performance in the reduced scattering coefficient. In accordance to photon noise statistics [23

W. Louiselle, Quantum Statistical Properties of Radiation (Wiley, New York, 1974).

], best fit of CV as a function of photon counts N reveals square law dependence (i.e., CV ÷ Nn, coefficient n=-0.48 and -0.53 for the measured absorption and reduced scattering, respectively). Depending on the applications (i.e., on the expected signal-to-noise ratio) these results tailor the optimization of the set-up. For example, when the optical contrast is sufficient (e.g., during cuff occlusion on arm muscle) a very short acquisition time can be effectively used. For brain functional imaging experiments where the changes are dramatically smaller there is the need to improve data robustness either by increasing the acquisition time or by an off-line averaging during data analysis.

Fig. 5. (a) Coefficient of variation (CV) for the measured absorption and reduced scattering coefficient at 690 nm. The line in the log-log plot is a best fit to the data (excluding the last three points) to a square law: CV ÷ Nn. (b) Stability test: plot of the error with respect to the mean value over the last 30 min for the measured absorption coefficient at 690 nm. The green (red) lines correspond to ±3% (±10%).

3.3 Stability

A stability test for the novel instrument was performed in the reflectance configuration with one source and 16 detection fiber bundles at a relative distance of 2 cm on the phantom B3. Immediately after switch on of the instruments and for a total of 2 h, time-resolved reflectance curves at 690 and 820 nm were acquired with an acquisition time of 1 s. Results at 690 nm for the measured absorption coefficient are presented in Fig. 5(b) where the error with respect to the mean value over the last 30 min is shown. Similar results hold for the other wavelength and for the reduced scattering coefficient. A warm-up time of 45 min is sufficient to reach a less than 1% stability while 1h is typically needed if less than 0.5% is required. The main cause of this behaviour is the warm-up of the laser sources.

3.4 Reproducibility

Measurements were performed over 4 days in the same experimental conditions of the stability test. The relative displacement of the measured optical coefficients obtained at each measurement day with respect to the average value calculated over the 4 days was less than 2.5% for µa, and less than 1.8% for µs’.

4. In vivo experiments

Preliminary in vivo experiments were performed to test the performance of the system. A standard cuff occlusion on the muscle was chosen as first experiment. The relatively big changes in hemodynamics associated with this type of protocol allowed checking the basic system functioning. Then, a finger-tapping experiment was performed to check system sensitivity in functional studies of the brain.

4.1 Muscle - Cuff occlusion

One adult volunteer (male, 37 years) was recruited from the lab and informed consent was obtained. Measurements were performed simultaneously on the medial aspect of the left and of the right arm, away from any palpable bone. On each arm, 4 sources and 8 detectors, arranged in the configuration shown in Fig. 6 made the probe. The injection and collection fibers were held normally to the skin and at a relative distance ρ=2.0 cm by a black rubber pad connected to brand fasteners (ONE-WRAP®, Velcro Italia Srl, I). The fibers were firmly positioned so that they provided no pressure to the skin, but no movement was allowed. Measurements were performed in a dimmed room to decrease the amount of background light. The arms laid in a comfortable resting position on a flat surface. A pneumatic cuff was placed loosely around the right arm.

Fig. 6. Muscle experiment: geometry of the position of sources and detectors (panel (a)) and photo during measurements (panel(b))

A standard protocol was followed. After an initial period (2 min) in resting position, the cuff was rapidly inflated to a pressure of 250 mmHg to provide an abrupt vascular (venous and arterial) occlusion. The cuff occlusion was maintained for 2 min with the muscle resting. The cuff was then released and the recovery phase followed for 2 min. Time-resolved reflectance measurements were simultaneously performed at two wavelengths with an acquisition time of 250 ms per channel, resulting in 1 s per frame.

Figure 7 reports the time courses for HHb, O2Hb, SO2 and tHb in one channel for the left (thin line) and right arm (thick line), respectively. No significant changes occur in the hemodynamic parameters of the left arm during the whole experiment, while as expected an increase in HHb (about 10%) and a corresponding decrease of O2Hb and SO2 are found during occlusion. Since occlusion initially closes vein and later artery, we observe an 4% increase in tHb. When cuff is released we observe a return to the baseline values.

Fig. 7. Time course of hemodynamic parameters in one channel of the left (thin line) and right (thick line) forearm muscle.

To better show the heterogeneity of the muscle response, Fig. 8 reports the spatial map for changes in SO2 and tHb in the left and right forearm. While during baseline we observe a rather uniform distribution in both arms, during cuff occlusion in the right arm there is a significant increase of tHb (more pronounced in the upper part of the arm, close to the occlusion) and a corresponding decrease of SO2. At the same time, in the left arm minor increase is observed in tHb (consistent with an increased blood flow in the not occluded arm), while SO2 is not significantly altered with respect to the baseline. After cuff release in the right arm we note a reduction of tHB with respect to the occlusion situation and an overshoot of SO2. Again as expected small changes are found in the left arm.

Fig. 8. Spatial maps of hemodynamic changes during baseline (top), task (middle) and recovery (bottom) in the right (left column) and left (right column) forearm.

4.2 Brain - Finger tapping

Preliminary in vivo measurements were performed on one adult volunteer (male, 37 years) to monitor the optical response to motor stimuli. 30 s of baseline, 30 s of motor task (finger opposition at a frequency rate of 3Hz), and 30 s of recovery composed the measurement protocol. The protocol was repeated 4 times with the right (R) hand. The optical probe was placed over the head in order to cover the underlying motor cortex and it was centered (according to the international 10–20 system for the EEG electrode placement) at the C3 point. The injection and collection fibers were held normally to the skin and at a relative distance ρ=2.0 cm by a black rubber pad connected to brand fasteners (ONE-WRAP®, Velcro Italia Srl, I). The fibers were firmly positioned so that they provided no pressure to the skin, but no movement was allowed. Measurements were performed in a dimmed room to decrease the amount of background light. Time-resolved reflectance measurements were simultaneously performed at two wavelengths with an acquisition time of 250 ms per channel, resulting in 1 s per frame.

Fig. 9. Brain experiment: geometry of the position of sources and detectors (panel (a)) and photo during measurements (panel(b))

During data analysis, a folding average over the 4 intervals was applied to improve the signal to noise ratio. Also, to better compare results with literature data, changes in O2Hb (ΔO2Hb) and HHb (ΔHHb) were calculated by making the difference with the average values during the baseline period (0–30 s).

Figure 10 reports the time courses for HHb, O2Hb, SO2 and tHb in one channel for the right (thin line) and left hemisphere (thick line), respectively. No significant changes occur in the hemodynamic parameters of the right hemisphere channel during the whole experiment, while as expected an increase in O2Hb and SO2 together with a corresponding decrease of HHb are found during the task. Amplitude and time-course of the changes are on the whole consistent with standard hemodynamic response following brain activation [6

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23, S275–S288 (2004). [CrossRef] [PubMed]

].

Fig. 10. Time course of hemodynamic changes in one channel of the left (thin line) and right (thick line) hemisphere.

Figure 11 reports the spatial map for changes in SO2 and tHb in the left and right hemisphere.

Fig. 11. Spatial maps of hemodynamic changes in the brain during baseline (top), task (middle) and recovery (bottom) for the contralateral (left column) and ipsilateral (right column) hemisphere.

While during baseline we observe a rather uniform distribution in both hemispheres, during finger tapping there is a focal increase of SO2and a corresponding increase of tHb. At the same time, in the right (i.e., ipsilateral) hemisphere minor changes are observed in tHb and SO2 is not significantly altered with respect to the baseline. In the recovery period in both hemispheres we note an overall return to the baseline values, with a limited increase in SO2 for the right hemisphere.

Finally, to show the depth sensitivity of the time-resolved approach, we have calculated the contrast for different time-gate values in the 0–2500 ps range, in steps of 250 ps, at 690 nm and 820 nm (see Fig. 12). If the time-gate steps forward from 500 to 2500 ps, there is a four time increase in the contrast. When the time-gate delay is increased, the contribution of late photons is enhanced, therefore a deeper region is sampled.

Fig. 12. Plot of the contrast for different time-gate values in the 0–2500 ps range in steps of 250 ps at 690 nm and 820 nm.

5. Discussion

A comprehensive review on technological advantages/disadvantages of CW, frequency-domain, and time-resolved technique in fNIRS studies has been reported previously [2

G. Strangman, D. A. Boas, and J. P. Sutton, “Non-invasive neuroimaging using near-infrared light,” Biol. Psychiatry 52, 679–693 (2002). [CrossRef] [PubMed]

]. In Ref. [15

A. Torricelli, V. Quaresima, A. Pifferi, G. Biscotti, L. Spinelli, P. Taroni, M. Ferrari, and R. Cubeddu, “Mapping of calf muscle oxygenation and haemoglobin content during dynamic plantar flexion exercise by multi-channel time-resolved near infrared spectroscopy”, Phys. Med. Biol. 49, 685–699, (2004). [CrossRef] [PubMed]

] and [17

D. Contini, A. Torricelli, A. Pifferi, L. Spinelli, P. Taroni, V. Quaresima, M. Ferrari, and R. Cubeddu, “Multi-channel time-resolved tissue oximeter for functional imaging of the brain,” IEEE Trans. Instrum. Meas. 55, 85–90 (2006). [CrossRef]

] we have already discussed performances of the time-resolved systems presented in the 1999–2003 photon migration literature. Here we focus the discussion on the time-resolved systems that have been recently developed for functional brain studies.

Thanks to unrivaled temporal resolution and to the possibility to easily perform broadband multi-wavelength measurements, streak camera based set-ups have currently being used for characterization of diffusive media [24

C. Zint, W. Uhring, M. Torregrossa, B. Cunin, and P. Poulet, “Streak Camera: A Multidetector for Diffuse Optical Tomography,” Appl. Opt. 42, 3313–3320 (2003). [CrossRef] [PubMed]

–26

R. Esposito, S. De Nicola, M. Lepore, I. Delfino, and P. L. Indovina, “A perturbation approach to characterize absorptive inclusions in diffusing media by time-resolved contrast measurements,” J. Opt. A: Pure Appl. Opt. 6, 736–741 (2004). [CrossRef]

]. However, it has to be considered that high costs would definitely limit the use of streak camera for clinical applications. The same reason might reduce the impact of time-gated intensified charge-coupled camera (ICCD) [27

C. D’Andrea, D. Comelli, A. Pifferi, A. Torricelli, G. Valentini, and R. Cubeddu, “Time-resolved optical imaging through turbid media using a fast data acquisition system based on a gated CCD camera,” J. Phys. D: Appl. Phys. 36, 1675–1681 (2003). [CrossRef]

, 28

G. M. Turner, G. Zacharakis, A. Soubret, J. Ripoll, and V. Ntziachristos, “Complete-angle projection diffuse optical tomography by use of early photons,” Opt. Lett. 15, 409–411 (2005). [CrossRef]

]. Nonetheless, in a recent work [12

J. Selb, J. J. Stott, M. A. Franceschini, A. G. Sorensen, and D. A. Boas, “Improved sensitivity to cerebral hemodynamics during brain activation with a time-gated optical system: analytical model and experimental validation,” J. Biomed Opt. 10, 11013 (2005). [CrossRef] [PubMed]

] an ICCD system was used for one-wavelength point measurements of cerebral hemodynamics and demonstrated sufficient sensitivity and resolution.

Nowadays, the majority of time-resolved systems for multi-wavelength functional studies employ the time-correlated single photon counting (TCSPC) technique [29

W. Becker, Advance time-correlated single-photon counting (Springer Verlag, Berlin, 2005). [CrossRef]

]. Key issues for the choice of TCSPC are availability of relatively low cost laser sources, detectors and acquisition electronics. Moreover, portable and compact systems can be built.

The research group at Physikalisch-Technische Bundesanstalt in Berlin, Germany, has developed a three-wavelength four-detection-channel TCSPC instrument [30

A. Liebert, H. Wabnitz, J. Steinbrink, H. Obrig, M. Moller, R. Macdonald, A. Villringer, and H. Rinneberg, “Time-resolved multidistance near-infrared spectroscopy of the adult head: intracerebral and extracerebral absorption changes from moments of distribution of times of flight of photons,” Appl Opt. 43, 3037–47 (2004). [CrossRef] [PubMed]

] that was effectively used for bedside assessment of cerebral perfusion in stroke patients [31

A. Liebert, H. Wabnitz, J. Steinbrink, M. Moller, R. Macdonald, H. Rinneberg, A. Villringer, and H. Obrig, “Bed-side assessment of cerebral perfusion in stroke patients based on optical monitoring of a dye bolus by time-resolved diffuse reflectance,” Neuroimage 24, 426–435 (2005). [CrossRef] [PubMed]

]. This system has been recently upgraded to a 16-channel configuration by inserting a 1×9 fiber optic switch [32

H. Wabnitz, M. Moeller, A. Liebert, A. Walter, R. Erdmann, O. Raitza, C. Drenckhan, J. P. Dreier, H. Obrig, J. Steinbrink, and R. MacDonald K. Licha and R. Cubeddu, “A time-domain NIR brain imager applied in functional simulation experiments,” in Photon Migration and Diffuse-Light Imaging II, Proceedings of SPIE Volume: 5859 Editor(s): (2005). [CrossRef]

]. Starting from that scheme, a 32-channel configuration has been assembled by doubling the switching and detection elements at the Institute of Biocybernetics and Biomedical Engineering in Warsaw, Poland [33

M. Kacprzak, A. Liebert, and R. Maniewski, “A time-resolved NIR topography system for two hemispheres of the brain,” presented at the European Conferences on Biomedical Optics, Munich, Germany, 13–16 June 2005.

].

Although the basic elements are the same, in the development of the system described in this work we have followed a different scheme. The main difference is the use of a larger number of detection channels (16 instead of 8), while the number of sources is similar (16 vs. 18). This would allow us to build an optical probe with a more densely spacing of fiber bundles for a better head coverage, or to perform measurement with an increased duty cycle per each fiber bundles.

The research group in Strasbourg has used an eight-channel system based on picosecond laser sources and a multi-anode micro-channel plate (MCP) PMT together with 2D finite-element model (FEM) simulations to perform a single point measurement during a finger tapping experiment [34

B. Montcel, R. Chabrier, and P. Poulet, “Detection of cortical activation with time-resolved diffuse optical methods,” Appl Opt. 44, 1942–1947 (2005). [CrossRef] [PubMed]

, 35

B. Montcel, R. Chabrier, and P. Poulet K. Licha and R. Cubeddu, “Improvements in brain activation using time-resolved diffuse optical means,”,” in Photon Migration and Diffuse-Light Imaging II, Proceedings of SPIE Volume: 5859 Editor(s): (2005). [CrossRef]

]. The use of MCP-PMTs yielded good temporal resolution of about 260 ps, where most of the broadening is due to dispersion in the fiber bundles. The limited number of channel however prevents this system to be effectively used for imaging studies.

Researchers from Hamamatsu Photonics K. K., Japan, reported the use of a 16-channel time-domain system for human brain mapping by means of diffuse optical tomography [36

Y. Ueda, T. Yamanaka, D. Yamashita, T. Suzuki, E. Ohmae, M. Oda, and Y. Yamashita, “Reflectance diffuse optical tomography:its application to hunam brain mapping,” Jap. J. Appl. Phys. 44, L1203–L1206 (2005). [CrossRef]

], while a single channel device have been used for research studies on piglets [37

S. Ijichi, T. Kusaka, K. Isobe, F. Islam, K. Okubo, H. Okada, M. Namba, K. Kawada, T. Imai, and S. Itoh, “Quantification of cerebral hemoglobin as a function of oxygenation using near-infrared time-resolved spectroscopy in a piglet model of hypoxia,” J. Biomed. Opt. 10, 024026 (2005). [CrossRef] [PubMed]

] or newborn babies [38

S. Ijichi, T. Kusaka, K. Isobe, K. Okubo, K. Kawada, M. Namba, H. Okada, T. Nishida, T. Imai, and S. Itoh, “Developmental Changes of Optical Properties in Neonates Determined by Near-Infrared Time-Resolved Spectroscopy,” Ped. Res. 58, 568–573 (2005). [CrossRef]

]. However, commercial devices for functional studies by time-domain measurement seem not to be currently available outside Japan.

Presently, our system is designed for topography or multi-point imaging. We have not tested yet the performance of our system for a tomographic approach involving simultaneous collection of light signals from different fiber bundles at different distances from the source. This approach would require a longer acquisition time, and it is more suited to quasi-static rather than functional imaging. Nonetheless, there are no technical limitations to such approach.

A current limitation of the system could be the use of a simple data analysis procedure. As described in Section 2.3 we are currently employing the microscopic Lambert-Beer Law to assess changes in the absorption coefficient. We also focus on late photons in the tail of the temporal point spread function to enhance contribution from deeper layers, where haemodynamic changes related to metabolic (e.g., muscle) or functional (e.g., brain) activation are located. This model is in fact rigorous in a homogeneous medium (as demonstrated in the calibration on tissue phantoms), while in complex geometry it yields an overall average. However, the system is also able to work in a multi-distance configuration, so as to acquire data which could be interpreted with advanced algorithms based on a layered modeling of the sampled tissue [9

F. Martelli, S. Del Bianco, and G. Zaccanti, “Perturbation model for light propagation through diffusive layered media,” Phys. Med. Biol. 50, 2159–2166 (2005). [CrossRef] [PubMed]

]. Nonetheless, work is currently in progress to develop innovative and robust analytical and semi-empirical algorithms for depth discrimination based on the information encoded in time-domain data.

6. Conclusion

A novel time-resolved multi-channel system for functional studies has been described and characterized on tissue phantoms. Preliminary measurements on volunteers have been performed to validate the system performances in vivo during cuff occlusion of the muscle and during motor task experiment for human brain mapping. Discussion on recently developed time-domain systems for functional studies has been reported. Future work will focus on the construction of an efficient probe for fast and stable positioning of source and detection fibers and on the integration of sensors for monitoring physiological signals (e.g. frequency of the heart beat and breathing). Measurement campaigns will be conducted to explore the advantages and limitations of time-domain functional near infrared spectroscopy for human brain mapping and for applied physiology studies.

Acknowledgments

The work was partially supported by MIUR under the project PRIN2005 (prot. 2005025333).

References and Links

1.

Y. Hoshi and M. Tamura, “Detection of dynamic changes in cerebral oxygenation coupled to neuronal function during mental work in man,” Neurosci. Lett. 150, 5–8 (1993). [CrossRef] [PubMed]

2.

G. Strangman, D. A. Boas, and J. P. Sutton, “Non-invasive neuroimaging using near-infrared light,” Biol. Psychiatry 52, 679–693 (2002). [CrossRef] [PubMed]

3.

H. Obrig and A. Villringer, “Beyond the Visible—Imaging the Human Brain With Light,” J. Cereb. Blood Flow Metab. 23, 1–18 (2003). [CrossRef]

4.

A. Yodh and B. Chance, “Spectroscopy and imaging with diffusing light”, Phys. Today 48, 34–40 (1995). [CrossRef]

5.

A. Villringer and B. Chance, “Noninvasive optical spectroscopy and imaging of human brain function,” Trends in Neurosci. 20, 435–442 (1997). [CrossRef]

6.

D. A. Boas, A. M. Dale, and M. A. Franceschini, “Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy,” Neuroimage 23, S275–S288 (2004). [CrossRef] [PubMed]

7.

M. S. Patterson, B. Chance, and B. C. Wilson, “Time resolved reflectance and transmittance for the noninvasive measurement of tissue optical properties,” Appl. Opt. 28, 2331–2336 (1989). [CrossRef] [PubMed]

8.

M. S. Patterson, J. D. Moulton, B. C. Wilson, K. W. Berndt, and J. R. Lakowicz, “Frequency-domain reflectance for the determination of the scattering and absorption properties of tissue,” Appl. Opt. 30, 4474–4476 (1991). [CrossRef] [PubMed]

9.

F. Martelli, S. Del Bianco, and G. Zaccanti, “Perturbation model for light propagation through diffusive layered media,” Phys. Med. Biol. 50, 2159–2166 (2005). [CrossRef] [PubMed]

10.

J. Steinbrink, H. Wabnitz, H. Obrig, A. Villringer, and H. Rinneberg, “Determining changes in NIR absorption using a layered model of the human head,” Phys. Med. Biol. 46, 879–896 (2001). [CrossRef] [PubMed]

11.

S. Del Bianco, F. Martelli, and G. Zaccanti “Penetration depth of light re-emitted by a diffusive medium: theoretical and experimental investigation,” Phys. Med. Biol. 47, 4131–44 (2002). [CrossRef] [PubMed]

12.

J. Selb, J. J. Stott, M. A. Franceschini, A. G. Sorensen, and D. A. Boas, “Improved sensitivity to cerebral hemodynamics during brain activation with a time-gated optical system: analytical model and experimental validation,” J. Biomed Opt. 10, 11013 (2005). [CrossRef] [PubMed]

13.

A. Torricelli, A. Pifferi, L. Spinelli, R. Cubeddu, F. Martelli, S. Del Bianco, and G. Zaccanti, “Timeresolved reflectance at null source-detector separation: improving contrast and resolution in diffuse optical imaging,” Phys. Rev. Lett. 95, 078101 (2005). [CrossRef] [PubMed]

14.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “Compact tissue oximeter based on dual-wavelength multichannel time-resolved reflectance”, Appl. Opt. 38, 3670–3680 (1999). [CrossRef]

15.

A. Torricelli, V. Quaresima, A. Pifferi, G. Biscotti, L. Spinelli, P. Taroni, M. Ferrari, and R. Cubeddu, “Mapping of calf muscle oxygenation and haemoglobin content during dynamic plantar flexion exercise by multi-channel time-resolved near infrared spectroscopy”, Phys. Med. Biol. 49, 685–699, (2004). [CrossRef] [PubMed]

16.

V. Quaresima, M. Ferrari, A. Torricelli, L. Spinelli, A. Pifferi, and R. Cubeddu, “Bilateral prefrontal cortex oxygenation responses to a verbal fluency task: a multichannel time-resolved near-infrared topography study,” J. Biomed. Opt. 10, 011012 (2005). [CrossRef]

17.

D. Contini, A. Torricelli, A. Pifferi, L. Spinelli, P. Taroni, V. Quaresima, M. Ferrari, and R. Cubeddu, “Multi-channel time-resolved tissue oximeter for functional imaging of the brain,” IEEE Trans. Instrum. Meas. 55, 85–90 (2006). [CrossRef]

18.

R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams, and B. J. Tromberg, “Boundary conditions for the diffusion equation in radiative transfer,” J. Opt. Soc. Am. A 11, 2727–2741 (1994). [CrossRef]

19.

Y. Nomura, O. Hazeki, and M. Tamura, “Relationship between time-resolved and non-time-resolved Beer-Lambert law in turbid media,” Phys. Med. Biol. 42, 1009–1023 (1997). [CrossRef] [PubMed]

20.

R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli, and G. Valentini, “Experimental test of theoretical models for time-resolved reflectance,” Med. Phys. 23, 1625–1634 (1996). [CrossRef] [PubMed]

21.

S. Prahl, Oregon Medical Laser Center website (2001), http://omlc.ogi.edu/spectra.

22.

A. Pifferi, A. Torricelli, A. Bassi, P. Taroni, R. Cubeddu, H. Wabnitz, D. Grosenick, M. Möller, R. Macdonald, J. Swartling, T. Svensson, S. Andersson-Engels, R. L. P. van Veen, H. J. C. M. Sterenborg, J. M. Tualle, H. L. Nghiem, E. Tinet, S. Avrillier, M. Whelan, and H. Stamm, “Performance assessment of photon migration instruments: the Medphot protocol,” Appl. Opt. 11, 2104–2114 (2005). [CrossRef]

23.

W. Louiselle, Quantum Statistical Properties of Radiation (Wiley, New York, 1974).

24.

C. Zint, W. Uhring, M. Torregrossa, B. Cunin, and P. Poulet, “Streak Camera: A Multidetector for Diffuse Optical Tomography,” Appl. Opt. 42, 3313–3320 (2003). [CrossRef] [PubMed]

25.

C. Abrahamsson, T. Svensson, S. Svanberg, and S. Andersson-Engels, “Time and wavelength resolved spectroscopy of turbid media using light continuum generated in a crystal fiber,” Opt. Express 12, 4103–4112 (2004). [CrossRef] [PubMed]

26.

R. Esposito, S. De Nicola, M. Lepore, I. Delfino, and P. L. Indovina, “A perturbation approach to characterize absorptive inclusions in diffusing media by time-resolved contrast measurements,” J. Opt. A: Pure Appl. Opt. 6, 736–741 (2004). [CrossRef]

27.

C. D’Andrea, D. Comelli, A. Pifferi, A. Torricelli, G. Valentini, and R. Cubeddu, “Time-resolved optical imaging through turbid media using a fast data acquisition system based on a gated CCD camera,” J. Phys. D: Appl. Phys. 36, 1675–1681 (2003). [CrossRef]

28.

G. M. Turner, G. Zacharakis, A. Soubret, J. Ripoll, and V. Ntziachristos, “Complete-angle projection diffuse optical tomography by use of early photons,” Opt. Lett. 15, 409–411 (2005). [CrossRef]

29.

W. Becker, Advance time-correlated single-photon counting (Springer Verlag, Berlin, 2005). [CrossRef]

30.

A. Liebert, H. Wabnitz, J. Steinbrink, H. Obrig, M. Moller, R. Macdonald, A. Villringer, and H. Rinneberg, “Time-resolved multidistance near-infrared spectroscopy of the adult head: intracerebral and extracerebral absorption changes from moments of distribution of times of flight of photons,” Appl Opt. 43, 3037–47 (2004). [CrossRef] [PubMed]

31.

A. Liebert, H. Wabnitz, J. Steinbrink, M. Moller, R. Macdonald, H. Rinneberg, A. Villringer, and H. Obrig, “Bed-side assessment of cerebral perfusion in stroke patients based on optical monitoring of a dye bolus by time-resolved diffuse reflectance,” Neuroimage 24, 426–435 (2005). [CrossRef] [PubMed]

32.

H. Wabnitz, M. Moeller, A. Liebert, A. Walter, R. Erdmann, O. Raitza, C. Drenckhan, J. P. Dreier, H. Obrig, J. Steinbrink, and R. MacDonald K. Licha and R. Cubeddu, “A time-domain NIR brain imager applied in functional simulation experiments,” in Photon Migration and Diffuse-Light Imaging II, Proceedings of SPIE Volume: 5859 Editor(s): (2005). [CrossRef]

33.

M. Kacprzak, A. Liebert, and R. Maniewski, “A time-resolved NIR topography system for two hemispheres of the brain,” presented at the European Conferences on Biomedical Optics, Munich, Germany, 13–16 June 2005.

34.

B. Montcel, R. Chabrier, and P. Poulet, “Detection of cortical activation with time-resolved diffuse optical methods,” Appl Opt. 44, 1942–1947 (2005). [CrossRef] [PubMed]

35.

B. Montcel, R. Chabrier, and P. Poulet K. Licha and R. Cubeddu, “Improvements in brain activation using time-resolved diffuse optical means,”,” in Photon Migration and Diffuse-Light Imaging II, Proceedings of SPIE Volume: 5859 Editor(s): (2005). [CrossRef]

36.

Y. Ueda, T. Yamanaka, D. Yamashita, T. Suzuki, E. Ohmae, M. Oda, and Y. Yamashita, “Reflectance diffuse optical tomography:its application to hunam brain mapping,” Jap. J. Appl. Phys. 44, L1203–L1206 (2005). [CrossRef]

37.

S. Ijichi, T. Kusaka, K. Isobe, F. Islam, K. Okubo, H. Okada, M. Namba, K. Kawada, T. Imai, and S. Itoh, “Quantification of cerebral hemoglobin as a function of oxygenation using near-infrared time-resolved spectroscopy in a piglet model of hypoxia,” J. Biomed. Opt. 10, 024026 (2005). [CrossRef] [PubMed]

38.

S. Ijichi, T. Kusaka, K. Isobe, K. Okubo, K. Kawada, M. Namba, H. Okada, T. Nishida, T. Imai, and S. Itoh, “Developmental Changes of Optical Properties in Neonates Determined by Near-Infrared Time-Resolved Spectroscopy,” Ped. Res. 58, 568–573 (2005). [CrossRef]

OCIS Codes
(170.1470) Medical optics and biotechnology : Blood or tissue constituent monitoring
(170.3890) Medical optics and biotechnology : Medical optics instrumentation
(170.5280) Medical optics and biotechnology : Photon migration
(170.6920) Medical optics and biotechnology : Time-resolved imaging

ToC Category:
Medical Optics and Biotechnology

History
Original Manuscript: February 27, 2006
Revised Manuscript: May 23, 2006
Manuscript Accepted: May 27, 2006
Published: June 12, 2006

Virtual Issues
Vol. 1, Iss. 7 Virtual Journal for Biomedical Optics

Citation
Davide Contini, Alessandro Torricelli, Antonio Pifferi, Lorenzo Spinelli, Floriano Paglia, and Rinaldo Cubeddu, "Multi-channel time-resolved system for functional near infrared spectroscopy," Opt. Express 14, 5418-5432 (2006)
http://www.opticsinfobase.org/vjbo/abstract.cfm?URI=oe-14-12-5418


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References

  1. Y. Hoshi and M. Tamura, "Detection of dynamic changes in cerebral oxygenation coupled to neuronal function during mental work in man," Neurosci. Lett. 150, 5-8 (1993). [CrossRef] [PubMed]
  2. G. Strangman, D. A. Boas, and J. P. Sutton, "Non-invasive neuroimaging using near-infrared light," Biol. Psychiatry 52, 679-693 (2002). [CrossRef] [PubMed]
  3. H. Obrig and A. Villringer, "Beyond the Visible—Imaging the Human Brain With Light," J. Cereb. Blood Flow Metab. 23, 1-18 (2003). [CrossRef]
  4. A. Yodh and B. Chance, "Spectroscopy and imaging with diffusing light", Phys. Today 48, 34-40 (1995). [CrossRef]
  5. A. Villringer and B. Chance, "Noninvasive optical spectroscopy and imaging of human brain function," Trends in Neurosci. 20, 435-442 (1997). [CrossRef]
  6. D. A. Boas, A. M. Dale, and M. A. Franceschini, "Diffuse optical imaging of brain activation: approaches to optimizing image sensitivity, resolution, and accuracy," Neuroimage 23, S275-S288 (2004). [CrossRef] [PubMed]
  7. M. S. Patterson, B. Chance, and B. C. Wilson, "Time resolved reflectance and transmittance for the non-invasive measurement of tissue optical properties," Appl. Opt. 28, 2331-2336 (1989). [CrossRef] [PubMed]
  8. M. S. Patterson, J. D. Moulton, B. C. Wilson, K. W. Berndt, and J. R. Lakowicz, "Frequency-domain reflectance for the determination of the scattering and absorption properties of tissue," Appl. Opt. 30, 4474-4476 (1991). [CrossRef] [PubMed]
  9. F. Martelli, S. Del Bianco and G. Zaccanti, "Perturbation model for light propagation through diffusive layered media," Phys. Med. Biol. 50, 2159-2166 (2005). [CrossRef] [PubMed]
  10. J. Steinbrink, H. Wabnitz, H. Obrig, A. Villringer and H. Rinneberg, "Determining changes in NIR absorption using a layered model of the human head," Phys. Med. Biol. 46, 879-896 (2001). [CrossRef] [PubMed]
  11. S. Del Bianco, F. Martelli and G. Zaccanti "Penetration depth of light re-emitted by a diffusive medium: theoretical and experimental investigation," Phys. Med. Biol. 47, 4131-44 (2002). [CrossRef] [PubMed]
  12. J. Selb, J. J. Stott, M. A. Franceschini, A. G. Sorensen, and D. A. Boas, "Improved sensitivity to cerebral hemodynamics during brain activation with a time-gated optical system: analytical model and experimental validation," J. Biomed Opt. 10, 11013 (2005). [CrossRef] [PubMed]
  13. A. Torricelli, A. Pifferi, L. Spinelli, R. Cubeddu, F. Martelli, S. Del Bianco and G. Zaccanti, "Time-resolved reflectance at null source-detector separation: improving contrast and resolution in diffuse optical imaging," Phys. Rev. Lett. 95, 078101 (2005). [CrossRef] [PubMed]
  14. R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli and G. Valentini, "Compact tissue oximeter based on dual-wavelength multichannel time-resolved reflectance", Appl. Opt. 38, 3670-3680 (1999). [CrossRef]
  15. A. Torricelli, V. Quaresima, A. Pifferi, G. Biscotti, L. Spinelli, P. Taroni, M. Ferrari and R. Cubeddu, "Mapping of calf muscle oxygenation and haemoglobin content during dynamic plantar flexion exercise by multi-channel time-resolved near infrared spectroscopy", Phys. Med. Biol. 49, 685-699, (2004). [CrossRef] [PubMed]
  16. V. Quaresima, M. Ferrari, A. Torricelli, L. Spinelli, A. Pifferi, and R. Cubeddu, "Bilateral prefrontal cortex oxygenation responses to a verbal fluency task: a multichannel time-resolved near-infrared topography study," J. Biomed. Opt. 10, 011012 (2005). [CrossRef]
  17. D. Contini, A. Torricelli, A. Pifferi, L. Spinelli, P. Taroni, V. Quaresima, M. Ferrari and R. Cubeddu, "Multi-channel time-resolved tissue oximeter for functional imaging of the brain," IEEE Trans. Instrum. Meas. 55, 85-90 (2006). [CrossRef]
  18. R. C. Haskell, L. O. Svaasand, T. T. Tsay, T. C. Feng, M. S. McAdams and B. J. Tromberg, "Boundary conditions for the diffusion equation in radiative transfer," J. Opt. Soc. Am. A 11, 2727-2741 (1994). [CrossRef]
  19. Y. Nomura, O. Hazeki and M. Tamura, "Relationship between time-resolved and non-time-resolved Beer-Lambert law in turbid media," Phys. Med. Biol. 42, 1009-1023 (1997). [CrossRef] [PubMed]
  20. R. Cubeddu, A. Pifferi, P. Taroni, A. Torricelli and G. Valentini, "Experimental test of theoretical models for time-resolved reflectance," Med. Phys. 23, 1625-1634 (1996). [CrossRef] [PubMed]
  21. S. Prahl, Oregon Medical Laser Center website (2001), http://omlc.ogi.edu/spectra.
  22. A. Pifferi, A. Torricelli, A. Bassi, P. Taroni, R. Cubeddu, H. Wabnitz, D. Grosenick, M. Möller, R. Macdonald, J. Swartling, T. Svensson, S. Andersson-Engels, R. L. P. van Veen, H. J. C. M. Sterenborg, J. M. Tualle, H. L. Nghiem, E. Tinet, S. Avrillier, M. Whelan, and H. Stamm, "Performance assessment of photon migration instruments: the Medphot protocol," Appl. Opt. 11, 2104-2114 (2005). [CrossRef]
  23. W. Louiselle, Quantum Statistical Properties of Radiation (Wiley, New York, 1974).
  24. C. Zint, W. Uhring, M. Torregrossa, B. Cunin, and P. Poulet, "Streak Camera: A Multidetector for Diffuse Optical Tomography, " Appl. Opt. 42, 3313-3320 (2003). [CrossRef] [PubMed]
  25. C. Abrahamsson, T. Svensson, S. Svanberg, and S. Andersson-Engels,"Time and wavelength resolved spectroscopy of turbid media using light continuum generated in a crystal fiber," Opt. Express 12, 4103-4112 (2004). [CrossRef] [PubMed]
  26. R. Esposito, S. De Nicola, M. Lepore, I. Delfino and P. L. Indovina, "A perturbation approach to characterize absorptive inclusions in diffusing media by time-resolved contrast measurements," J. Opt. A: Pure Appl. Opt. 6, 736-741 (2004). [CrossRef]
  27. C. D'Andrea, D. Comelli, A. Pifferi, A. Torricelli, G. Valentini and R. Cubeddu, "Time-resolved optical imaging through turbid media using a fast data acquisition system based on a gated CCD camera," J. Phys. D: Appl. Phys. 36, 1675-1681 (2003). [CrossRef]
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