Determination of absorption changes from moments of distributions of times of flight of photons: optimization of measurement conditions for a two-layered tissue model

Depth-selective method for time-domain diffuse reflectance measurements: validation study of the dual subtraction technique

Research on the spatial distribution of sensitivity of time-domain near infrared diffuse reflectance measurement is reported in this paper. The main objective of the investigation is to validate theoretically calculated sensitivity profiles for a measurement geometry with two detectors and two sources in which sensitivity profiles of statistical moments of distributions of time of flight of photons (DTOFs) are spatially restricted to a region underneath the detectors. For this dual subtraction method, smaller sensitivities to changes appearing in the superficial layer of the medium were observed compared to the single distance and single subtraction methods. Experimental validation of this approach is based on evaluation of changes in the statistical moments of DTOFs measured on a liquid phantom with local absorption perturbations. The spatial distributions of sensitivities, depth-related sensitivity and depth selectivities were obtained from the dual subtraction method and compared with those from single distance and single subtraction approaches. Also, the contrast to noise ratio (CNR) was calculated for the dual subtraction technique and combined with depth selectivity in order to assess the overall performance (product of CNR and depth selectivity) of the method. Spatial sensitivity profiles from phantom experiments are in a good agreement with the results of theoretical studies and feature more locally restricted sensitivity volume with the point of maximal sensitivity located deeper. The highest value of overall performance was obtained experimentally for the second statistical moment in the dual subtraction method (∼10.8) surpassing that of the single distance method (∼8.7). This confirms the advantage of dual subtraction measurement geometries in the suppression of optical signals originated in the superficial layer of the medium.

Two-layered blood-lipid phantom and method to determine absorption and oxygenation employing changes in moments of DTOFs

Near-infrared spectroscopy (NIRS) is an established technique for measuring tissue oxygen saturation (StO₂), which is of high clinical value. For tissues that have layered structures, it is challenging but clinically relevant to obtain StO₂ of the different layers, e.g. brain and scalp. For this aim, we present a new method of data analysis for time-domain NIRS (TD-NIRS) and a new two-layered blood-lipid phantom. The new analysis method enables accurate determination of even large changes of the absorption coefficient (Δµ_a) in multiple layers. By adding Δµ_a to the baseline µ_a, this method provides absolute µ_a and hence StO₂ in multiple layers. The method utilizes (i) changes in statistical moments of the distributions of times of flight of photons (DTOFs), (ii) an analytical solution of the diffusion equation for an N-layered medium, (iii) and the Levenberg-Marquardt algorithm (LMA) to determine Δµ_a in multiple layers from the changes in moments. The method is suitable for NIRS tissue oximetry (relying on µ_a) as well as functional NIRS (fNIRS) applications (relying on Δµ_a). Experiments were conducted on a new phantom, which enabled us to simulate dynamic StO₂ changes in two layers for the first time. Two separate compartments, which mimic superficial and deep layers, hold blood-lipid mixtures that can be deoxygenated (using yeast) and oxygenated (by bubbling oxygen) independently. Simultaneous NIRS measurements can be performed on the two-layered medium (variable superficial layer thickness, L), the deep (homogeneous), and/or the superficial (homogeneous). In two experiments involving ink, we increased the nominal µ_a in one of two compartments from 0.05 to 0.25 cm^-1, L set to 14.5 mm. In three experiments involving blood (L set to 12, 15, or 17 mm), we used a protocol consisting of six deoxygenation cycles. A state-of-the-art multi-wavelength TD-NIRS system measured simultaneously on the two-layered medium, as well as on the deep compartment for a reference. The new method accurately determined µ_a (and hence StO₂) in both compartments. The method is a significant progress in overcoming the contamination from the superficial layer, which is beneficial for NIRS and fNIRS applications, and may improve the determination of StO₂ in the brain from measurements on the head. The advanced phantom may assist in the ongoing effort towards more realistic standardized performance tests in NIRS tissue oximetry. Data and MATLAB codes used in this study were made publicly available.

Novel data types for frequency-domain diffuse optical spectroscopy and imaging of tissues: characterization of sensitivity and contrast-to-noise ratio for absorption perturbations

In frequency-domain (FD) diffuse optics it is known that the phase of photon-density waves (ϕ) has a stronger deep-to-superficial sensitivity ratio to absorption perturbations than the alternate current (AC) amplitude, or the direct current intensity (DC). This work is an attempt to find FD data types that feature similar or even better sensitivity and/or contrast-to-noise for deeper absorption perturbations than phase. One way is to start from the definition of characteristic function (Xt(ω)) of the photon's arrival time (t) and combining the real (ℜ ( X t ( ω ) ) = A C D C c o s ( ϕ ) ) and imaginary parts (ℑ [ X t ( ω ) ] = A C D C s i n ( ϕ ) ) with phase to yield new data types. These new data types enhance the role of higher order moments of the probability distribution of the photon's arrival time t. We study the contrast-to-noise and sensitivity features of these new data types not only in the single-distance arrangement (traditionally used in diffuse optics), but we also consider the spatial gradients, which we named dual-slope arrangements. We have identified six data types that for typical values of the optical properties of tissues and depths of interest, have better sensitivity or contrast-to-noise features than phase data and that can be used to enhance the limits of imaging of tissue in FD near infrared spectroscopy (NIRS). For example, one promising data type is ϕ - ℑ [ X t ( ω ) ] which shows, in the single-distance source-detector arrangement, an increase of deep-to-superficial sensitivity ratio with respect to phase by 41% and 27% at a source-detector separation of 25 and 35 mm, respectively. The same data type also shows an increase of contrast-to noise up to 35% with respect to phase when the spatial gradients of the data are considered.

How much do time-domain functional near-infrared spectroscopy (fNIRS) moments improve estimation of brain activity over traditional fNIRS?

SIGNIFICANCE

Advances in electronics have allowed the recent development of compact, high channel count time domain functional near-infrared spectroscopy (TD-fNIRS) systems. Temporal moment analysis has been proposed for increased brain sensitivity due to the depth selectivity of higher order temporal moments. We propose a general linear model (GLM) incorporating TD moment data and auxiliary physiological measurements, such as short separation channels, to improve the recovery of the HRF.

AIMS

We compare the performance of previously reported multi-distance TD moment techniques to commonly used techniques for continuous wave (CW) fNIRS hemodynamic response function (HRF) recovery, namely block averaging and CW GLM. Additionally, we compare the multi-distance TD moment technique to TD moment GLM.

APPROACH

We augmented resting TD-fNIRS moment data (six subjects) with known synthetic HRFs. We then employed block averaging and GLM techniques with "short-separation regression" designed both for CW and TD to recover the HRFs. We calculated the root mean square error (RMSE) and the correlation of the recovered HRF to the ground truth. We compared the performance of equivalent CW and TD techniques with paired t-tests.

RESULTS

We found that, on average, TD moment HRF recovery improves correlations by 98% and 48% for HbO and HbR respectively, over CW GLM. The improvement on the correlation for TD GLM over TD moment is 12% (HbO) and 27% (HbR). RMSE decreases 56% and 52% (HbO and HbR) for TD moment compared to CW GLM. We found no statistically significant improvement in the RMSE for TD GLM compared to TD moment.

CONCLUSIONS

Properly covariance-scaled TD moment techniques outperform their CW equivalents in both RMSE and correlation in the recovery of the synthetic HRFs. Furthermore, our proposed TD GLM based on moments outperforms regular TD moment analysis, while allowing the incorporation of auxiliary measurements of the confounding physiological signals from the scalp.

Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Reconstruction of optical coefficients in turbid media using time-resolved reflectance and calibration-free instrument response functions

Measurements of time-resolved reflectance from a homogenous turbid medium can be employed to retrieve the absolute values of its optical transport coefficients. However, the uncertainty in the temporal shift of the experimentally determined instrument response function (IRF) with respect to the real system response can lead to errors in optical property reconstructions. Instrument noise and measurement of the IRF in a reflectance geometry can exacerbate these errors. Here, we examine three reconstruction approaches that avoid requiring direct measurements of photon launch times. They work by (a) fitting relative shapes of the reflectance profile with a pre-determined constraint on the scattering coefficient, (b) calibrating launch-time differences via a reference sample, and (c) freely fitting for the launch-time difference within the inverse problem. Analysis methods that can place a tight bound on the scattering coefficient can produce errors within 5-15% for both absorption and scattering at source-detector separations of 10 and 15 mm. Including the time-shift in the fitting procedure also recovered optical coefficients to under 20% but showed large crosstalk between extracted scattering and absorption coefficients. We find that the uncertainty in the temporal shift greatly impacts the reconstructed reduced scattering coefficient compared to absorption.

Chromophore reconstruction at depth in bilayered media: a method for quantification

We report a method for deriving the absolute value of absorption coefficients at depth in bilayered media. The method was simplified from that of time-resolved diffuse optical tomography (TR-DOT) into one dimension to validate and set up the main parameters with the help of simulations, and to test it in an easy preclinical model. The method was applied to buried flaps as used in reconstructive surgery, and absolute chromophore concentrations in the flap and in the upper (skin and fat) layer were derived. The encouraging results obtained lay a foundation for developing more complex multidimensional models.

Depth-selective data analysis for time-domain fNIRS: moments vs. time windows

Time-domain measurements facilitate the elimination of the influence of extracerebral, systemic effects, a key problem in functional near-infrared spectroscopy (fNIRS) of the adult human brain. The analysis of measured time-of-flight distributions of photons often relies on moments or time windows. However, a systematic and quantitative characterization of the performance of these measurands is still lacking. Based on perturbation simulations for small localized absorption changes, we compared spatial sensitivity profiles and depth selectivity for moments (integral, mean time of flight and variance), photon counts in time windows and their ratios for different time windows. The influence of the instrument response function (IRF) was investigated for all measurands and for various source-detector separations. Variance exhibits the highest depth selectivity among the moments. Ratios of photon counts in different late time windows can achieve even higher selectivity. An advantage of moments is their robustness against the shape of the IRF and instrumental drifts.

Performance of measurands in time-domain optical brain imaging: depth selectivity versus contrast-to-noise ratio

Time-domain optical brain imaging techniques introduce a number of different measurands for analyzing absorption changes located deep in the tissue, complicated by superficial absorption changes and noise. We implement a method that allows analysis, quantitative comparison and performance ranking of measurands under various conditions - including different values of reduced scattering coefficient, thickness of the superficial layer, and source-detector separation. Liquid phantom measurements and Monte Carlo simulations were carried out in two-layered geometry to acquire distributions of times of flight of photons and to calculate the total photon count, mean time of flight, variance, photon counts in time windows and ratios of photon counts in different time windows. Quantitative comparison of performance was based on objective metrics: relative contrast, contrast-to-noise ratio (CNR) and depth selectivity. Moreover, the product of CNR and depth selectivity was used to rank the overall performance and to determine the optimal source-detector separation for each measurand. Variance ranks the highest under all considered conditions.

Depth-resolved assessment of changes in concentration of chromophores using time-resolved near-infrared spectroscopy: estimation of cytochrome-c-oxidase uncertainty by Monte Carlo simulations

Time-resolved near-infrared spectroscopy (TR-NIRS) measurements can be used to recover changes in concentrations of tissue constituents ( Δ C ) by applying the moments method and the Beer-Lambert law. In this work we carried out the error propagation analysis allowing to calculate the standard deviations of uncertainty in estimation of the Δ C . Here, we show the process of choosing wavelengths for the evaluation of hemodynamic (oxy-, deoxyhemoglobin) and metabolic (cytochrome-c-oxidase (CCO)) responses within the brain tissue as measured with an in-house developed TR-NIRS multi-wavelength system, which measures at 16 consecutive wavelengths separated by 12.5 nm and placed between 650 and 950 nm. Data generated with Monte Carlo simulations on three-layered model (scalp, skull, brain) for wavelengths range from 650 to 950 nm were used to carry out the error propagation analysis for varying choices of wavelengths. For a detector with a spectrally uniform responsivity, the minimal standard deviation of the estimated changes in CCO within the brain layer, σ Δ C CCO brain  = 0.40 µM, was observed for the 16 consecutive wavelengths from 725 to 912.5 nm. For realistic a detector model, i.e. the spectral responsivity characteristic is considered, the minimum, σ Δ C CCO brain  = 0.47 µM, was observed at the 16 consecutive wavelengths from 688 to 875 nm. We introduce the method of applying the error propagation analysis to data as measured with spectral TR-NIRS systems to calculate uncertainty of recovery of tissue constituents concentrations.

Continuous non-invasive optical monitoring of cerebral blood flow and oxidative metabolism after acute brain injury

Rapid detection of ischemic conditions at the bedside can improve treatment of acute brain injury. In this observational study of 11 critically ill brain-injured adults, we employed a monitoring approach that interleaves time-resolved near-infrared spectroscopy (TR-NIRS) measurements of cerebral oxygen saturation and oxygen extraction fraction (OEF) with diffuse correlation spectroscopy (DCS) measurement of cerebral blood flow (CBF). Using this approach, we demonstrate the clinical promise of non-invasive, continuous optical monitoring of changes in CBF and cerebral metabolic rate of oxygen (CMRO₂). In addition, the optical CBF and CMRO₂ measures were compared to invasive brain tissue oxygen tension (PbtO₂), thermal diffusion flowmetry CBF, and cerebral microdialysis measures obtained concurrently. The optical CBF and CMRO₂ information successfully distinguished between ischemic, hypermetabolic, and hyperemic conditions that arose spontaneously during patient care. Moreover, CBF monitoring during pressor-induced changes of mean arterial blood pressure enabled assessment of cerebral autoregulation. In total, the findings suggest that this hybrid non-invasive neurometabolic optical monitor (NNOM) can facilitate clinical detection of adverse physiological changes in brain injured patients that are otherwise difficult to measure with conventional bedside monitoring techniques.

Influence of intra-abdominal pressure on the amplitude of fluctuations of cerebral hemoglobin concentration in the respiratory band

An intra-abdominal pressure (IAP) is correlated with cerebral perfusion, in a mechanism of reducing venous outflow. The elevated intra-abdominal pressure leads to an increase in the intracranial pressure and a decrease in the cerebral perfusion pressure. We studied the relationship between the IAP and the cerebral oxygenation with the use of the near infrared spectroscopy technique during a gynecological surgery. The changes in hemoglobin concentrations were analyzed in the time-frequency domain in the frequency band related to respiration. The measurements were carried out in 15 subjects who underwent laparoscopic surgery. During the laparoscopy, the intra-abdominal cavity was insufflated with CO₂, which caused a controlled increase in the IAP. It was observed that the amplitudes of respiration-related waves present in hemoglobin concentration signals show an increase of 1.5 to 8.5 times during elevation of the IAP by 15 mmHg.

Multiwavelength time-resolved near-infrared spectroscopy of the adult head: assessment of intracerebral and extracerebral absorption changes

An optical technique based on diffuse reflectance measurement combined with indocyanine green (ICG) bolus tracking is extensively tested as a method for the clinical assessment of brain perfusion at the bedside. We report on multiwavelength time-resolved diffuse reflectance spectroscopy measurements carried out on the head of a healthy adult during the intravenous administration of a bolus of ICG. Intracerebral and extracerebral changes in absorption were estimated from an analysis of changes in statistical moments (total number of photons, mean time of flight and variance) of the distributions of times of flight (DTOF) of photons recorded simultaneously at 16 wavelengths from the range of 650-850 nm using sensitivity factors estimated by diffusion approximation based on a layered model of the studied medium. We validated the proposed method in a series of phantom experiments and in-vivo measurements. The results obtained show that changes in the concentration of the ICG can be assessed as a function of time of the experiment and depth in the tissue. Thus, the separation of changes in ICG concentration appearing in intra- and extracerebral tissues can be estimated from optical data acquired at a single source-detector pair of fibers/fiber bundles positioned on the surface of the head.

Time-resolved near infrared light propagation using frequency domain superposition

Time-resolved temporal point spread function (TPSF) measurement of near infrared spectroscopic (NIRS) data allows the estimation of absorption and reduced scattering properties of biological tissues. Such analysis requires an iterative calculation of the theoretical TPSF curve using mathematical and computational models of the domain being imaged which are computationally complex and expensive. In this work, an efficient methodology for representing the TPSF data using a superposition of cosines calculated in frequency domain is presented. The proposed method is outlined and tested on finite element realistic models of the human neck and head. Using an adult head model containing ~140k nodes, the TPSF calculation at each node for one source is accelerated from 3.11 s to 1.29 s within an error limit of ± 5% related to the time domain calculation method.

Lawrence K. Subtraction-based approach for enhancing the depth sensitivity of time-resolved NIRS

The aim of this study was to evaluate enhancing of the depth sensitivity of time-resolved near-infrared spectroscopy with a subtraction-based approach. Due to the complexity of light propagation in a heterogeneous media, and to prove the validity of the proposed method in a heterogeneous turbid media we conducted a broad analysis taking into account a number of parameters related to the method as well as various parameters of this media. The results of these experiments confirm that the depth sensitivity of the subtraction-based approach is better than classical approaches using continuous-wave or time-resolved methods. Furthermore, the results showed that the subtraction-based approach has a unique, selective sensitivity to a layer at a specific depth. In vivo application of the proposed method resulted in a greater magnitude of the hemodynamic changes during functional activation than with the standard approach.

Optimal estimation reconstruction of the optical properties of a two-layered tissue phantom from time-resolved single-distance measurements

In this work, we have tested the optimal estimation (OE) algorithm for the reconstruction of the optical properties of a two-layered liquid tissue phantom from time-resolved single-distance measurements. The OE allows a priori information, in particular on the range of variation of fit parameters, to be included. The purpose of the present investigations was to compare the performance of OE with the Levenberg–Marquardt method for a geometry and real experimental conditions typically used to reconstruct the optical properties of biological tissues such as muscle and brain. The absorption coefficient of the layers was varied in a range of values typical for biological tissues. The reconstructions performed demonstrate the substantial improvements achievable with the OE provided a priori information is available. We note the extreme reliability, robustness, and accuracy of the retrieved absorption coefficient of the second layer obtained with the OE that was found for up to six fit parameters, with an error in the retrieved values of less than 10%. A priori information on fit parameters and fixed forward model parameters clearly improves robustness and accuracy of the inversion procedure.

Optimization of the method for assessment of brain perfusion in humans using contrast-enhanced reflectometry: multidistance time-resolved measurements

The aim of the study was to determine optimal measurement conditions for assessment of brain perfusion with the use of optical contrast agent and time-resolved diffuse reflectometry in the near-infrared wavelength range. The source-detector separation at which the distribution of time of flights (DTOF) of photons provided useful information on the inflow of the contrast agent to the intracerebral brain tissue compartments was determined. Series of Monte Carlo simulations was performed in which the inflow and washout of the dye in extra- and intracerebral tissue compartments was modeled and the DTOFs were obtained at different source-detector separations. Furthermore, tests on diffuse phantoms were carried out using a time-resolved setup allowing the measurement of DTOFs at 16 source-detector separations. Finally, the setup was applied in experiments carried out on the heads of adult volunteers during intravenous injection of indocyanine green. Analysis of statistical moments of the measured DTOFs showed that the source-detector separation of 6 cm is recommended for monitoring of inflow of optical contrast to the intracerebral brain tissue compartments with the use of continuous wave reflectometry, whereas the separation of 4 cm is enough when the higher-order moments of DTOFs are available.

Separation of superficial and cerebral hemodynamics using a single distance time-domain NIRS measurement

In functional near-infrared spectroscopy (fNIRS) superficial hemodynamics can mask optical signals related to brain activity. We present a method to separate superficial and cerebral absorption changes based on the analysis of changes in moments of time-of-flight distributions and a two-layered model. The related sensitivity factors were calculated from individual optical properties. The method was validated on a two-layer liquid phantom. Absorption changes in the lower layer were retrieved with an accuracy better than 20%. The method was successfully applied to in vivo data and compared to the reconstruction of homogeneous absorption changes.

Identifying and quantifying main components of physiological noise in functional near infrared spectroscopy on the prefrontal cortex

Functional Near-Infrared Spectroscopy (fNIRS) is a promising method to study functional organization of the prefrontal cortex. However, in order to realize the high potential of fNIRS, effective discrimination between physiological noise originating from forehead skin haemodynamic and cerebral signals is required. Main sources of physiological noise are global and local blood flow regulation processes on multiple time scales. The goal of the present study was to identify the main physiological noise contributions in fNIRS forehead signals and to develop a method for physiological de-noising of fNIRS data. To achieve this goal we combined concurrent time-domain fNIRS and peripheral physiology recordings with wavelet coherence analysis (WCA). Depth selectivity was achieved by analyzing moments of photon time-of-flight distributions provided by time-domain fNIRS. Simultaneously, mean arterial blood pressure (MAP), heart rate (HR), and skin blood flow (SBF) on the forehead were recorded. WCA was employed to quantify the impact of physiological processes on fNIRS signals separately for different time scales. We identified three main processes contributing to physiological noise in fNIRS signals on the forehead. The first process with the period of about 3 s is induced by respiration. The second process is highly correlated with time lagged MAP and HR fluctuations with a period of about 10 s often referred as Mayer waves. The third process is local regulation of the facial SBF time locked to the task-evoked fNIRS signals. All processes affect oxygenated haemoglobin concentration more strongly than that of deoxygenated haemoglobin. Based on these results we developed a set of physiological regressors, which were used for physiological de-noising of fNIRS signals. Our results demonstrate that proposed de-noising method can significantly improve the sensitivity of fNIRS to cerebral signals.

Assessment of cerebral perfusion in post-traumatic brain injury patients with the use of ICG-bolus tracking method

The aim of this study was to verify the usefulness of the time-resolved optical method utilizing diffusely reflected photons and fluorescence signals combined with intravenous injection of indocyanine green (ICG) in the assessment of brain perfusion in post-traumatic brain injury patients. The distributions of times of flight (DTOFs) of diffusely reflected photons were acquired together with the distributions of times of arrival (DTAs) of fluorescence photons. The data analysis methodology was based on the observation of delays between the signals of statistical moments (number of photons, mean time of flight and variance) of DTOFs and DTAs related to the inflow of ICG to the extra- and intracerebral tissue compartments. Eleven patients with brain hematoma, 15 patients with brain edema and a group of 9 healthy subjects were included in this study. Statistically significant differences between parameters obtained in healthy subjects and patients with brain hematoma and brain edema were observed. The best optical parameter to differentiate patients and control group was variance of the DTOFs or DTAs. Results of the study suggest that time-resolved optical monitoring of inflow of the ICG seems to be a promising tool for detecting cerebral perfusion insufficiencies in critically ill patients.

Quantitative evaluation of deep and shallow tissue layers' contribution to fNIRS signal using multi-distance optodes and independent component analysis

To quantify the effect of absorption changes in the deep tissue (cerebral) and shallow tissue (scalp, skin) layers on functional near-infrared spectroscopy (fNIRS) signals, a method using multi-distance (MD) optodes and independent component analysis (ICA), referred to as the MD-ICA method, is proposed. In previous studies, when the signal from the shallow tissue layer (shallow signal) needs to be eliminated, it was often assumed that the shallow signal had no correlation with the signal from the deep tissue layer (deep signal). In this study, no relationship between the waveforms of deep and shallow signals is assumed, and instead, it is assumed that both signals are linear combinations of multiple signal sources, which allows the inclusion of a "shared component" (such as systemic signals) that is contained in both layers. The method also assumes that the partial optical path length of the shallow layer does not change, whereas that of the deep layer linearly increases along with the increase of the source-detector (S-D) distance. Deep- and shallow-layer contribution ratios of each independent component (IC) are calculated using the dependence of the weight of each IC on the S-D distance. Reconstruction of deep- and shallow-layer signals are performed by the sum of ICs weighted by the deep and shallow contribution ratio. Experimental validation of the principle of this technique was conducted using a dynamic phantom with two absorbing layers. Results showed that our method is effective for evaluating deep-layer contributions even if there are high correlations between deep and shallow signals. Next, we applied the method to fNIRS signals obtained on a human head with 5-, 15-, and 30-mm S-D distances during a verbal fluency task, a verbal working memory task (prefrontal area), a finger tapping task (motor area), and a tetrametric visual checker-board task (occipital area) and then estimated the deep-layer contribution ratio. To evaluate the signal separation performance of our method, we used the correlation coefficients of a laser-Doppler flowmetry (LDF) signal and a nearest 5-mm S-D distance channel signal with the shallow signal. We demonstrated that the shallow signals have a higher temporal correlation with the LDF signals and with the 5-mm S-D distance channel than the deep signals. These results show the MD-ICA method can discriminate between deep and shallow signals.

Method for the discrimination of superficial and deep absorption variations by time domain fNIRS

A method for the discrimination of superficial and deep absorption variations by time domain functional near infrared spectroscopy is presented. The method exploits the estimate of the photon time-dependent pathlength in different domains of the sampled medium and makes use of an approach based on time-gating of the photon distribution of time-of-flights. Validation of the method is performed in the two-layer geometry to focus on muscle and head applications. Numerical simulations varied the thickness of the upper layer, the interfiber distance, the shape of the instrument response function and the photon counts. Preliminary results from in vivo data are also shown.