We present here a new technique called Frequency Domain Shortwave Infrared Spectroscopy (FD-SWIRS), which provides absolute broadband optical property extractions as well as tissue water and lipids concentrations using shortwave infrared light. Measurements from a custom digital FD system at 730, 852, 940, and 980 nm were combined with broadband continuous wave (CW) measurements (900 - 1310 nm). FD and CW measurements were integrated using model-based analysis to provide broadband absolute absorption and reduced scattering spectra. Intralipid and heavy water titrations, drift, SNR, a porcine desiccation experiment, and other key experiments were conducted to characterize the system.
KEYWORDS: Absorption, Chromophores, Calibration, Diffuse reflectance spectroscopy, Spectroscopy, In vivo imaging, Data modeling, Tissues, Scattering, Near infrared
We present a calibration-free instrument to measure absolute broadband absorption spectra of biological tissue. Initial measurements in skeletal muscle show that the fit to the data improves by introducing a spectrally flat absorption background.
We have recently introduced a Dual-Slope (DS) method implemented with Frequency-Domain (FD) NearInfraRed Spectroscopy (NIRS). Its chief advantages are a preferential sensitivity to deeper tissue and the suppression of instrumental artifacts. Thus-far, the work using the DS method has focused on local measurements of tissue hemodynamics. The next step in the development of DS is the measurement of spatially resolved absorption changes of tissue in vivo. To achieve this, we designed a DS imaging array for applications on human tissue. We utilized this array to measure maps of absolute optical properties in human skeletal muscle, and muscle hemodynamics during venous occlusion. In each case, spatial maps were created. The maps of baseline absolute optical properties showed higher scattering in connective tissue and higher absorption in muscle tissue. The analysis of hemodynamics found a greater blood accumulation during venous occlusion in muscle. Overall, muscle hemodynamics were shown to be spatially variable over a large area, suggesting the importance of imaging (as opposed to single-location) measurements. The preliminary data on human subjects with this new DS imaging array pave the way for applications in functional NIRS (fNIRS) for mapping brain activation.
One of the chief applications of diffuse optical spectroscopy is the measurement of chromophore concentrations in biological tissue, which requires measurements of tissue absorption. To achieve absolute absorption measurements, two chief confounds must be accounted for: instrumental contributions and tissue scattering. To account for instrumental contributions, a preliminary calibration on a phantom of known optical properties is typically done. The need for a calibration is eliminated by self-calibrating or dual-slope techniques using specially designed probe geometries. A technique that is capable of measuring tissue scattering is frequency domain near-infrared spectroscopy. However, it is typically not implemented for a spectrum of wavelengths due to instrumental complexity. Here we present a technique that combines self-calibrating frequency-domain at two wavelengths, to account for tissue scattering, and dual-slope continuous-wave broadband diffuse reflectance spectroscopy to achieve spectral measurements of absolute absorption between 600 nm and 1064 nm without any need for calibration. We apply this technique to two human tissues in vivo to determine concentrations of oxy-hemoglobin, deoxy-hemoglobin, lipids, and water. We found that the quality of the spectral fits may be significantly improved by the inclusion of a wavelength-independent background absorption. This leads to a discussion on the origin of this background absorption, and on the meaning of the chromophore concentrations that are recovered from spectral analysis. Current work is seeking to further understand and possibly correct for this apparent background absorption.
In a study on one patient during hemodialysis, we used near-infrared spectroscopy (NIRS) to measure coherent oscillations of cerebral concentrations of oxyhemoglobin ([HbO2]), deoxyhemoglobin ([Hb]), and total-hemoglobin ([HbT]) induced by systemic oscillations in mean arterial pressure (MAP) at a frequency of 0.07 Hz. During hemodialysis, we observed that the phase of [Hb] versus [HbO2] becomes less negative, whereas the phase of [HbT] versus MAP becomes more negative. By applying a quantitative hemodynamic model, we assign these phase changes to an increase in venous blood transit time and a less effective cerebral autoregulation during the hemodialysis process.
In this work we provide some examples of sensitivity of the dual slope method to localized absorption changes in the layered geometry. Reasonably, this model geometry better represents many types of tissue. The sensitivity is shown in a two- and three-layer geometry for alternating current (AC) and phase data for both point-like and layered-like absorption perturbations. Contrary to the homogeneous medium geometry, where the ratio of deep to superficial tissue sensitivity of phase is always greater than that of AC, this is not always the case in the layered geometry. Therefore, depending on the targeted tissue, subject and protocol, in some cases it might be preferable to use AC dual-slopes, whereas in other cases phase dual-slope may be a better choice.
The use of phase (Φ) data collected in Frequency-Domain Near-InfraRed Spectroscopy (FD-NIRS) has not been widespread in measurements of skeletal muscle and has mainly been applied to measure absolute optical properties. We show that single-distance (SD) Φ has a deeper sensitivity compared to SD intensity (I) and can be more sensitive to oxygen consumption in skeletal muscle underneath superficial adipose tissue. We also show the potential benefit of single-slope (SS) or dual-slope (DS) I or Φ in muscle studies.
KEYWORDS: Matrices, Data modeling, Signal detection, Detection and tracking algorithms, Tissues, Sensors, Motion measurement, Brain, Linear filtering, Filtering (signal processing)
Significance: We demonstrated the potential of using domain adaptation on functional near-infrared spectroscopy (fNIRS) data to classify different levels of n-back tasks that involve working memory.
Aim: Domain shift in fNIRS data is a challenge in the workload level alignment across different experiment sessions and subjects. To address this problem, two domain adaptation approaches—Gromov–Wasserstein (G-W) and fused Gromov–Wasserstein (FG-W) were used.
Approach: Specifically, we used labeled data from one session or one subject to classify trials in another session (within the same subject) or another subject. We applied G-W for session-by-session alignment and FG-W for subject-by-subject alignment to fNIRS data acquired during different n-back task levels. We compared these approaches with three supervised methods: multiclass support vector machine (SVM), convolutional neural network (CNN), and recurrent neural network (RNN).
Results: In a sample of six subjects, G-W resulted in an alignment accuracy of 68 % ± 4 % (weighted mean ± standard error) for session-by-session alignment, FG-W resulted in an alignment accuracy of 55 % ± 2 % for subject-by-subject alignment. In each of these cases, 25% accuracy represents chance. Alignment accuracy results from both G-W and FG-W are significantly greater than those from SVM, CNN, and RNN. We also showed that removal of motion artifacts from the fNIRS data plays an important role in improving alignment performance.
Conclusions: Domain adaptation has potential for session-by-session and subject-by-subject alignment of mental workload by using fNIRS data.
We introduce a novel method to enhance the sensitivity of near-infrared spectroscopy (NIRS) to deep tissue (i.e. brain cortex, skeletal muscle, etc.) in non-invasive diffuse optical measurements. Our method relies on the collection of the phase of photon-density waves, launched by intensity-modulated light in frequency-domain NIRS, from two paired sets of multi-distance data. The two sets of data are combined into a phase dual-slope, which features a stronger sensitivity to deeper vs. superficial tissue. For typical conditions of functional NIRS, the maximum sensitivity of phase dual-slopes is at a depth of ~11 mm, which approaches the depth of cortical tissue.
Near-infrared spectroscopy (NIRS) is a non-invasive optical technique that is sensitive to blood volume, blood flow, and oxygen consumption in biological tissue. In particular, a NIRS-measured quantity that has been previously considered as a surrogate for blood flow measurements is the difference of oxy- and deoxy-hemoglobin concentrations ([HbD] = [HbO2] – [Hb]). We propose a new NIRS method for measurements of cerebral blood flow (CBF), which improves on the [HbD] surrogate by accounting for blood volume contributions and for temporal delays due to the blood transit time in the microvasculature. This new NIRS method relies on concepts of coherent hemodynamics spectroscopy (CHS), and we identify it with the acronym NIRS-CHS. We report a comparison of CBF transient dynamics measured on human subjects with NIRS-CHS, with the [HbD] surrogate and with diffuse correlation spectroscopy (DCS). We found a good agreement between the CBF dynamics measured with NIRS-CHS and with DCS, while the [HbD] dynamics lag because of the delayed effect of CBF on [HbD] due to the capillary and venous blood transit times. The NIRS-CHS method also affords absolute measurements of baseline CBF, for which we found a value of 69 ± 6 ml/100g/min (mean ± standard error) in a group of six healthy volunteers. Further studies to characterize and validate CBF measurements with NIRS-CHS are currently ongoing, with an emphasis on the assessment of accuracy, precision, and reproducibility.
Oscillations in the tissue concentrations of deoxyHemoglobin ([Hb]) and OxyHemoglobin ([HbO]) can be measured in the human brain using Near InfraRed Spectroscopy (NIRS). These oscillations may be driven by temporal dynamics of Arterial Blood Pressure (ABP). Coherent Hemodynamics Spectroscopy (CHS) is a technique that measures oscillations of [Hb] and [HbO] that are coherent with ABP. These oscillations, at a frequency of 0.1 Hz in this work, can then be interpreted with CHS to get physiologically relevant parameters to monitor cerebral AutoRegulation (AR) and microvascular integrity. Systemic oscillations in ABP can be induced with cyclic inflation and deflation of pneumatic thigh cuffs or by paced breathing. ABP oscillations may also occur spontaneously during resting conditions. Here, these three types of ABP oscillations (induced with thigh cuffs, induced with paced breathing, and spontaneously occurring) are considered, and the phase between coherent [Hb] and [HbO] oscillations is interpreted in terms of AR. In two healthy human subjects, it was found that paced breathing may be subjective, either improving or impairing AR depending on the individual paced breathing amplitude. Cuff cyclic inflations and spontaneous hemodynamics resulted in no significant difference in the relative phase of cerebral [Hb] and [HbO] oscillations at 0.1 Hz. These initial results suggest that spontaneous hemodynamics may be used for CHS in place of induced ABP oscillations, with the advantage of not relying on subject’s actions (like paced breathing) or special equipment (like pneumatic thigh cuffs).
We used coherent hemodynamics spectroscopy (CHS) and near-infrared spectroscopy (NIRS) for dynamic measurements of absolute cerebral blood flow (CBF) in one healthy subject over the prefrontal cortex. Temporal transients in mean arterial pressure (MAP) and CBF were induced by rapid deflation of pneumatic thigh cuffs following a sustained 2-minute occlusion at a super-systolic pressure. We studied the sensitivity of relative and absolute measurements of CBF with NIRS-CHS (CBFNIRS-CHS) to the physiological parameters in the CHS model. The temporal dynamics of CBFNIRS-CHS were compared with co-localized NIRS measurements of hemoglobin difference ([HbD] = [HbO2]−[Hb]), and with diffuse correlation spectroscopy (DCS) measurements of relative CBF. We demonstrated that NIRS-CHS provides quantitative measurements of absolute baseline CBF, and corrects [HbD] estimations of CBF dynamics for blood volume contributions and for blood transit times in the microvasculature resulting in a better agreement with CBF dynamics measured by DCS.
We have compared different methods for analyzing dynamic changes of oxy- and deoxyhemoglobin concentrations oscillations, measured by near infrared spectroscopy (NIRS), during cyclic pneumatic thigh cuff occlusion and release at the frequency of 0.1 Hz. This protocol is usually adopted in coherence hemodynamics spectroscopy (CHS) to induce controlled arterial blood pressure perturbations which drive hemodynamic changes in the brain. It is a general problem of NIRS to differentiate hemodynamic signals originated in the brain from those in the extracerebral tissue layer. The purpose of this study is to gain some understanding about the spatial origin of the oscillating optical signals according to these five different methods of data analysis during the thigh cuff occlusion and release protocol. The results obtained on six human subjects show that similar qualitative behavior of oxy- and deoxyhemoglobin dynamic changes are found by using: (1) modified Beer-Lambert law at far source detector separations (d > 25 mm); (2) DC intensity slope method at d > 25 mm; (3) multi-distance method at d >25 mm; (4) Two-layer modified Beer-Lambert law (using d > 25 mm) when we consider dynamic changes in the second (deeper) layer. At short source-detector separations (d < 15 mm), the hemoglobin concentration changes obtained with the modified Beer-Lambert law are consistent with those obtained for the first (superficial) layer with the two-layer modified Beer-Lambert law. For more quantitative assessment of cerebral dynamic changes, we argue that DC slope or two-layer modified Beer-Lambert law should provide better estimates. We support this claim by comparing the sensitivity to layered absorption perturbations obtained by using the modified BeerLambert law and the DC slope methods.
We report a near-infrared spectroscopy (NIRS) study of coherent hemodynamic oscillations measured on the human forehead at multiple source–detector distances (1 to 4 cm). The physiological source of the coherent hemodynamics is arterial blood pressure oscillations at a frequency of 0.1 Hz, induced by cyclic inflation (to a pressure of 200 mmHg) and deflation of two thigh cuffs wrapped around the subject’s thighs. To interpret our results, we use a recently developed hemodynamic model and a phasor representation of the oscillations of oxyhemoglobin, deoxyhemoglobin, and total hemoglobin concentrations in the tissue (phasors O, D, and T, respectively). The increase in the phase angle between D and O at larger source–detector separations is assigned to greater flow versus volume contributions and to a stronger blood flow autoregulation in deeper tissue (brain cortex) with respect to superficial tissue (scalp and skull). The relatively constant phase lag of T versus arterial blood pressure oscillations at all source–detector distances was assigned to competing effects from stronger autoregulation and smaller arterial-to-venous contributions in deeper tissue with respect to superficial tissue. We demonstrate the application of a hemodynamic model to interpret coherent hemodynamics measured with NIRS and to assess the different nature of shallow (extracerebral) versus deep (cerebral) tissue hemodynamics.
Hemodynamic-based neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and near-infrared spectroscopy (NIRS) sense hemoglobin concentration in cerebral tissue. The local concentration of hemoglobin, which is differentiated into oxy- and deoxy-hemoglobin by NIRS, features spontaneous oscillations over time scales of 10-100 s in response to a number of local and systemic physiological processes. If one of such processes becomes the dominant source of cerebral hemodynamics, there is a high coherence between this process and the associated hemodynamics. In this work, we report a method to identify such conditions of coherent hemodynamics, which may be exploited to study and quantify microvasculature and microcirculation properties. We discuss how a critical value of significant coherence may depend on the specific data collection scheme (for example, the total acquisition time) and the nature of the hemodynamic data (in particular, oxy- and deoxy-hemoglobin concentrations measured with NIRS show an intrinsic level of correlation that must be taken into account). A frequency-resolved study of coherent hemodynamics is the basis for the new technique of coherent hemodynamics spectroscopy (CHS), which aims to provide measures of cerebral blood flow and cerebral autoregulation. While these concepts apply in principle to both fMRI and NIRS data, in this article we focus on NIRS data.
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