Continuous correction of differential path length factor in near-infrared spectroscopy

Cerebral and muscle tissue oxygenation during exercise in healthy adults: A systematic review

BACKGROUND

Near-infrared spectroscopy (NIRS) technology has allowed for the measurement of cerebral and skeletal muscle oxygenation simultaneously during exercise. Since this technology has been growing and is now successfully used in laboratory and sports settings, this systematic review aimed to synthesize the evidence and enhance an integrative understanding of blood flow adjustments and oxygen (O2) changes (i.e., the balance between O2 delivery and O2 consumption) within the cerebral and muscle systems during exercise.

METHODS

A systematic review was conducted using PubMed, Embase, Scopus, and Web of Science databases to search for relevant studies that simultaneously investigated cerebral and muscle hemodynamic changes using the near-infrared spectroscopy system during exercise. This review considered manuscripts written in English and available before February 9, 2023. Each step of screening involved evaluation by 2 independent authors, with disagreements resolved by a third author. The Joanna Briggs Institute Critical Appraisal Checklist was used to assess the methodological quality of the studies.

RESULTS

Twenty studies were included, of which 80% had good methodological quality, and involved 290 young or middle-aged adults. Different types of exercises were used to assess cerebral and muscle hemodynamic changes, such as cycling (n = 11), treadmill (n = 1), knee extension (n = 5), isometric contraction of biceps brachii (n = 3), and duet swim routines (n = 1). The cerebral hemodynamics analysis was focused on the frontal cortex (n = 20), while in the muscle, the analysis involved vastus lateralis (n = 18), gastrocnemius (n = 3), biceps brachii (n = 5), deltoid (n = 1), and intercostal muscle (n = 1). Overall, muscle deoxygenation increases during exercise, reaching a plateau in voluntary exhaustion, while in the brain, oxyhemoglobin concentration increases with exercise intensity, reaching a plateau or declining at the exhaustion point.

CONCLUSION

Muscle and cerebral oxygenation respond differently to exercise, with muscle increasing O2 utilization and cerebral tissue increasing O2 delivery during exercise. However, at the exhaustion point, both muscle and cerebral oxygenation become compromised. This is characterized by a reduction in blood flow and a decrease in O2 extraction in the muscle, while in the brain, oxygenation reaches a plateau or decline, potentially resulting in motor failure during exercise.

Self-calibrated pulse oximetry algorithm based on photon pathlength change and the application in human freedivers

Significance

Pulse oximetry estimates the arterial oxygen saturation of hemoglobin (SaO 2 ) based on relative changes in light intensity at the cardiac frequency. Commercial pulse oximeters require empirical calibration on healthy volunteers, resulting in limited accuracy at low oxygen levels. An accurate, self-calibrated method for estimating SaO 2 is needed to improve patient monitoring and diagnosis.

Aim

Given the challenges of calibration at low SaO 2 levels, we pursued the creation of a self-calibrated algorithm that can effectively estimate SaO 2 across its full range. Our primary objective was to design and validate our calibration-free method using data collected from human subjects.

Approach

We developed an algorithm based on diffuse optical spectroscopy measurements of cardiac pulses and the modified Beer-Lambert law (mBLL). Recognizing that the photon mean pathlength (⟨ L ⟩ ) varies with SaO 2 related absorption changes, our algorithm aligns/fits the normalized ⟨ L ⟩ (across wavelengths) obtained from optical measurements with its analytical representation. We tested the algorithm with human freedivers performing breath-hold dives. A continuous-wave near-infrared spectroscopy probe was attached to their foreheads, and an arterial cannula was inserted in the radial artery to collect arterial blood samples at different stages of the dive. These samples provided ground-truth SaO 2 via a blood gas analyzer, enabling us to evaluate the accuracy of SaO 2 estimation derived from the NIRS measurement using our self-calibrated algorithm.

Results

The self-calibrated algorithm significantly outperformed the conventional method (mBLL with a constant ⟨ L ⟩ ratio) for SaO 2 estimation through the diving period. Analyzing 23 ground-truth SaO 2 data points ranging from 41% to 100%, the average absolute difference between the estimated SaO 2 and the ground truth SaO 2 is 4.23 % ± 5.16 % for our algorithm, significantly lower than the 11.25 % ± 13.74 % observed with the conventional approach.

Conclusions

By factoring in the variations in the spectral shape of ⟨ L ⟩ relative to SaO 2 , our self-calibrated algorithm enables accurate SaO 2 estimation, even in subjects with low SaO 2 levels.

Quantification of cytochrome c oxidase and tissue oxygenation using CW-NIRS in a mouse cerebral cortex

We provide a protocol for measuring the absolute concentration of the oxidized and reduced state of cytochrome c oxidase (CCO) in the cerebral cortex of mice, using broadband continuous-wave NIRS. The algorithm (NIR-AQUA) allows for absolute quantification of CCO and deoxyhemoglobin. Combined with an anoxia pulse, this also allows for quantification of total hemoglobin, and tissue oxygen saturation. CCO in the cortex was 4.9 ± 0.1 μM (mean ± SD, n=6). In normoxia, 84% of CCO was oxidized. We include hypoxia and cyanide validation studies to show CCO can be quantified independently to hemoglobin. This can be applied to study oxidative metabolism in the many rodent models of neurological disease.

Multi-modal diffuse optical spectroscopy for high-speed monitoring and wide-area mapping of tissue optical properties and hemodynamics

SIGNIFICANCE

Diffuse optical spectroscopic imaging (DOSI) is a versatile technology sensitive to changes in tissue composition and hemodynamics and has been used for a wide variety of clinical applications. Specific applications have prompted the development of versions of the DOSI technology to fit specific clinical needs. This work describes the development and characterization of a multi-modal DOSI (MM-DOSI) system that can acquire metabolic, compositional, and pulsatile information at multiple penetration depths in a single hardware platform. Additionally, a 3D tracking system is integrated with MM-DOSI, which enables registration of the acquired data to the physical imaging area.

AIM

We demonstrate imaging, layered compositional analysis, and metabolism tracking capabilities using a single MM-DOSI system on optical phantoms as well as in vivo human tissue.

APPROACH

We characterize system performance with a silicone phantom containing an embedded object. To demonstrate multi-layer sensitivity, we imaged human calf tissue with a 4.8-mm skin-adipose thickness. Human thenar tissue was also measured using a combined broadband DOSI and continuous-wave near-infrared spectroscopy method (∼15  Hz acquisition rate).

RESULTS

High-resolution optical property maps of absorption (μa) and reduced scattering (μs  '  ) were recovered on the phantom by capturing over 1000 measurement points in under 5 minutes. On human calf tissue, we show two probing depth layers have significantly different (p  <  0.001) total-hemo/myoglobin and μs  '   composition. On thenar tissue, we calculate tissue arterial oxygen saturation, venous oxygen saturation, and tissue metabolic rate of oxygen consumption during baseline and after release of an arterial occlusion.

CONCLUSIONS

The MM-DOSI can switch between collection of broadband spectra, high-resolution images, or multi-depth hemodynamics without any hardware reconfiguration. We conclude that MM-DOSI enables acquisition of high resolution, multi-modal data consolidated in a single platform, which can provide a more comprehensive understanding of tissue hemodynamics and composition for a wide range of clinical applications.

Near Infrared Spectroscopy for Muscle Specific Analysis of Intensity and Fatigue during Cross-Country Skiing Competition-A Case Report

The aims of the study were to assess the robustness and non-reactiveness of wearable near-infrared spectroscopy (NIRS) technology to monitor exercise intensity during a real race scenario, and to compare oxygenation between muscle groups important for cross-country skiing (XCS). In a single-case study, one former elite XCS (age: 39 years, peak oxygen uptake: 65.6 mL/kg/min) was equipped with four NIRS devices, a high-precision global navigation satellite system (GNSS), and a heart rate (HR) monitor during the Vasaloppet long-distance XCS race. All data were normalized to peak values measured during incremental laboratory roller skiing tests two weeks before the race. HR reflected changes in terrain and intensity, but showed a constant decrease of 0.098 beats per minute from start to finish. Triceps brachii (TRI) muscle oxygen saturation (SmO2) showed an interchangeable pattern with HR and seems to be less affected by drift across the competition (0.027% drop per minute). Additionally, TRI and vastus lateralis (VL) SmO2 revealed specific loading and unloading pattern of XCS in uphill and downhill sections, while rectus abdominus (RA) SmO2 (0.111% drop per minute) reflected fatigue patterns occurring during the race. In conclusion, the present preliminary study shows that NIRS provides a robust and non-reactive method to monitor exercise intensity and fatigue mechanisms when applied in an outdoor real race scenario. As local exercise intensity differed between muscle groups and central exercise intensity (i.e., HR) during whole-body endurance exercise such as XCS, NIRS data measured at various major muscle groups may be used for a more detailed analysis of kinetics of muscle activation and compare involvement of upper body and leg muscles. As TRI SmO2 seemed to be unaffected by central fatigue mechanisms, it may provide an alternative method to HR and GNSS data to monitor exercise intensity.

A consensus guide to using functional near-infrared spectroscopy in posture and gait research

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is increasingly used in the field of posture and gait to investigate patterns of cortical brain activation while people move freely. fNIRS methods, analysis and reporting of data vary greatly across studies which in turn can limit the replication of research, interpretation of findings and comparison across works.

RESEARCH QUESTION AND METHODS

Considering these issues, we propose a set of practical recommendations for the conduct and reporting of fNIRS studies in posture and gait, acknowledging specific challenges related to clinical groups with posture and gait disorders.

RESULTS

Our paper is organized around three main sections: 1) hardware set up and study protocols, 2) artefact removal and data processing and, 3) outcome measures, validity and reliability; it is supplemented with a detailed checklist.

SIGNIFICANCE

This paper was written by a core group of members of the International Society for Posture and Gait Research and posture and gait researchers, all experienced in fNIRS research, with the intent of assisting the research community to lead innovative and impactful fNIRS studies in the field of posture and gait, whilst ensuring standardization of research.

Implementation of a six-around-one optical probe based on diffuse light spectroscopy for study of cerebral properties in a murine mouse model of autism spectrum disorder

Light reflectance spectroscopy (LRS) is a multispectral technique, sensitive to the absorption and scattering properties of biological molecules in tissues. It is used as a noninvasive tool to extract quantitative physiological information from human tissues and organs. A near-infrared LRS based on a single optical probe was used to monitor changes in optical and hemodynamic parameters in a mouse model of autism. A murine model of autism induced by developmental exposure to valproic acid (VPA) was used. Since autism could be attributed to neuroanatomical changes, we hypothesize that these changes can be detected using the LRS because spectral properties depend on both molecular composition and structural changes. The fiber-optic probe in the setup consisted of seven small optical fibers: six fibers for illumination placed in a circular manner around a central single collection fiber. Overall, measurements demonstrate changes in diffused reflectance spectra, cerebral optical tissue properties (absorption and scattering), and chromophore levels. Furthermore, we were able to identify differences between male and female groups. Finally, the effectiveness of S-Adenosylmethionine as a drug therapy was studied and found to improve the hemodynamic outcome. For the first time, to the best of our knowledge, the LRS is utilized to study variations in brain parameters in the VPA autism model mice through an intact scalp.

Comparison of Broadband and Discrete Wavelength Near-Infrared Spectroscopy Algorithms for the Detection of Cytochrome aa3 Reduction

BACKGROUND

Cytochrome aa3, the terminal component of the electron transport chain, absorbs near-infrared radiation (NIR) differentially depending on its oxidation state (Cytox), which can in theory be measured using near-infrared spectroscopy (NIRS) by relating light absorption at specific wavelengths to chromophore concentrations. Some NIRS algorithms use discrete wavelengths, while others analyze a band of NIR (broadband NIRS). The purpose of this study was to test the ability of discrete wavelength and broadband algorithms to measure changes in Cytox (primary outcome), and to determine whether or not a discreet wavelength NIRS algorithm could perform similarly to a broadband NIRS algorithm for the measurement of Cytox in a staged hypoxia-cyanide model (hypoxia and cyanide have oppositional effects on tissue saturation, but both cause cytochrome reduction).

METHODS

Twenty Sprague-Dawley rats were anesthetized with isoflurane, intubated, and instrumented. Blood pressure, end-tidal carbon dioxide, and arterial oxygen saturation were measured. A halogen light source transmitted NIR transcranially. NIR from the light source and the skull was transmitted to 2 cooled charge-coupled device spectrometers. Rats were subjected to anoxia (fraction of inspired oxygen, 0.0) until arterial oxygen saturation decreased to 70%. After recovery, 5 mg/kg sodium cyanide was injected intravenously. The cycle was repeated until cardiac arrest occurred. Relative concentrations of hemoglobin and cytochrome aa3 were calculated using discreet wavelength and broadband NIRS algorithms.

RESULTS

Hypoxia led to an increase in calculated deoxyhemoglobin (0.20 arbitrary units [AUs]; 95% confidence interval [CI], 0.17-0.22; P < .0001), a decrease in calculated oxyhemoglobin (-0.16 AUs; 95% CI, -0.19 to -0.14; P < .0001), and a decrease in calculated Cytox (-0.057 AUs; 95% CI, -0.073 to 0.0040; P < .001). Cyanide led to a decrease in calculated deoxyhemoglobin (-0.037 AUs; 95% CI, 0.046 to -0.029; P < .001), an increase in calculated oxyhemoglobin (0.053 AUs; 95% CI, 0.040-0.065; P < .001), and a decrease in calculated Cytox (-0.056 AUs; 95% CI, -0.064 to -0.048; P < .001). The correlations between "discreet" wavelength algorithms (using 4, 6, 8, and 10 wavelengths) and the broadband algorithm for the measurement of calculated Cytox were 0.54 (95% CI, 0.52-0.56), 0.87 (0.87-0.88), 0.88 (0.88-0.89), and 0.95 (0.95-0.95), respectively.

CONCLUSIONS

The broadband and 10 wavelength algorithm were able to accurately track changes in Cytox for all experiments.

Estimating the Dependence of Differential Pathlength Factor on Blood Volume and Oxygen Saturation using Monte Carlo method

Differential Pathlength Factor (DPF) is a vital parameter for the Beer-Lambert law based calculations in estimating tissue perfusion using non-invasive optical techniques. A significant error in the measured concentration of oxyhemoglobin and deoxyhemoglobin has been reported due to the usage of wrong DPF values. The dependence of DPF on blood oxygen saturation and blood volume has never been studied earlier. In this work, a Monte Carlo model of perfused skin tissue was developed and executed at 660 nm and 940 nm optical wavelengths at a reflectance geometry. DPFs were simulated through 1-10 mm source detector separations at different blood volumes and oxygen saturations. Results showed higher DPFs at lower wavelengths and considerable variation with blood volume and oxygen saturation.

Initial-Dip Existence and Estimation in Relation to DPF and Data Drift

Early de-oxygenation (initial dip) is an indicator of the primal cortical activity source in functional neuro-imaging. In this study, initial dip's existence and its estimation in relation to the differential pathlength factor (DPF) and data drift were investigated in detail. An efficient algorithm for estimation of drift in fNIRS data is proposed. The results favor the shifting of the fNIRS signal to a transformed coordinate system to infer correct information. Additionally, in this study, the effect of the DPF on initial dip was comprehensively analyzed. Four different cases of initial dip existence were treated, and the resultant characteristics of the hemodynamic response function (HRF) for DPF variation corresponding to particular near-infrared (NIR) wavelengths were summarized. A unique neuro-activation model and its iterative optimization solution that can estimate drift in fNIRS data and determine the best possible fit of HRF with free parameters were developed and herein proposed. The results were verified on simulated data sets. The algorithm is applied to free available datasets in addition to six healthy subjects those were experimented using fNIRS and observations and analysis regarding shape of HRF were summarized as well. A comparison with standard GLM is also discussed and effects of activity strength parameters have also been analyzed.

Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise⁻Cognition Science: A Systematic, Methodology-Focused Review

For cognitive processes to function well, it is essential that the brain is optimally supplied with oxygen and blood. In recent years, evidence has emerged suggesting that cerebral oxygenation and hemodynamics can be modified with physical activity. To better understand the relationship between cerebral oxygenation/hemodynamics, physical activity, and cognition, the application of state-of-the art neuroimaging tools is essential. Functional near-infrared spectroscopy (fNIRS) is such a neuroimaging tool especially suitable to investigate the effects of physical activity/exercises on cerebral oxygenation and hemodynamics due to its capability to quantify changes in the concentration of oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) non-invasively in the human brain. However, currently there is no clear standardized procedure regarding the application, data processing, and data analysis of fNIRS, and there is a large heterogeneity regarding how fNIRS is applied in the field of exercise⁻cognition science. Therefore, this review aims to summarize the current methodological knowledge about fNIRS application in studies measuring the cortical hemodynamic responses during cognitive testing (i) prior and after different physical activities interventions, and (ii) in cross-sectional studies accounting for the physical fitness level of their participants. Based on the review of the methodology of 35 as relevant considered publications, we outline recommendations for future fNIRS studies in the field of exercise⁻cognition science.

Differential Path-Length Factor's Effect on the Characterization of Brain's Hemodynamic Response Function: A Functional Near-Infrared Study

Functional near-infrared spectroscopy (fNIRS) has evolved as a neuro-imaging modality over the course of the past two decades. The removal of superfluous information accompanying the optical signal, however, remains a challenge. A comprehensive analysis of each step is necessary to ensure the extraction of actual information from measured fNIRS waveforms. A slight change in shape could alter the features required for fNIRS-BCI applications. In the present study, the effect of the differential path-length factor (DPF) values on the characteristics of the hemodynamic response function (HRF) was investigated. Results were compiled for both simulated data sets and healthy human subjects over a range of DPF values from three to eight. Different sets of activation durations and stimuli were used to generate the simulated signals for further analysis. These signals were split into optical densities under a constrained environment utilizing known values of DPF. Later, different values of DPF were used to analyze the variations of actual HRF. The results, as summarized into four categories, suggest that the DPF can change the main and post-stimuli responses in addition to other interferences. Six healthy subjects participated in this study. Their observed optical brain time-series were fed into an iterative optimization problem in order to estimate the best possible fit of HRF and physiological noises present in the measured signals with free parameters. A series of solutions was derived for different values of DPF in order to analyze the variations of HRF. It was observed that DPF change is responsible for HRF creep from actual values as well as changes in HRF characteristics.

Multi-pathlength method to improve the spectrometric analysis accuracy based on “M + N” theory

In order to verify the effectiveness of three application methods, an experiment was done to predict the concentration of intra-lipids by single pathlength and multi-pathlength modelling.

Calibration set selection method based on the “M + N” theory: application to non-invasive measurement by dynamic spectrum

An appropriate method for calibration set selection is very important for a robust quantitative model, especially for the non-invasive measurement of blood components.

On the geometry dependence of differential pathlength factor for near-infrared spectroscopy. I. Steady-state with homogeneous medium

This work analytically examines some dependences of the differential pathlength factor (DPF) for steady-state photon diffusion in a homogeneous medium on the shape, dimension, and absorption and reduced scattering coefficients of the medium. The medium geometries considered include a semi-infinite geometry, an infinite-length cylinder evaluated along the azimuthal direction, and a sphere. Steady-state photon fluence rate in the cylinder and sphere geometries is represented by a form involving the physical source, its image with respect to the associated extrapolated half-plane, and a radius-dependent term, leading to simplified formula for estimating the DPFs. With the source-detector distance and medium optical properties held fixed across all three geometries, and equal radii for the cylinder and sphere, the DPF is the greatest in the semi-infinite and the smallest in the sphere geometry. When compared to the results from finite-element method, the DPFs analytically estimated for 10 to 25 mm source–detector separations on a sphere of 50 mm radius with μa=0.01  mm(−1) and μ′s=1.0  mm(−1) are on average less than 5% different. The approximation for sphere, generally valid for a diameter≥20 times of the effective attenuation pathlength, may be useful for rapid estimation of DPFs in near-infrared spectroscopy of an infant head and for short source–detector separation.

Modeling Neurovascular Coupling from Clustered Parameter Sets for Multimodal EEG-NIRS

Despite significant improvements in neuroimaging technologies and analysis methods, the fundamental relationship between local changes in cerebral hemodynamics and the underlying neural activity remains largely unknown. In this study, a data driven approach is proposed for modeling this neurovascular coupling relationship from simultaneously acquired electroencephalographic (EEG) and near-infrared spectroscopic (NIRS) data. The approach uses gamma transfer functions to map EEG spectral envelopes that reflect time-varying power variations in neural rhythms to hemodynamics measured with NIRS during median nerve stimulation. The approach is evaluated first with simulated EEG-NIRS data and then by applying the method to experimental EEG-NIRS data measured from 3 human subjects. Results from the experimental data indicate that the neurovascular coupling relationship can be modeled using multiple sets of gamma transfer functions. By applying cluster analysis, statistically significant parameter sets were found to predict NIRS hemodynamics from EEG spectral envelopes. All subjects were found to have significant clustered parameters (P < 0.05) for EEG-NIRS data fitted using gamma transfer functions. These results suggest that the use of gamma transfer functions followed by cluster analysis of the resulting parameter sets may provide insights into neurovascular coupling in human neuroimaging data.

Optimal optode montage on electroencephalography/functional near-infrared spectroscopy caps dedicated to study epileptic discharges

Functional near-infrared spectroscopy (fNIRS), acquired simultaneously with electroencephalography (EEG), allows the investigation of hemodynamic brain responses to epileptic activity. Because the presumed epileptogenic focus is patient-specific, an appropriate source/detector (SD) montage has to be reconfigured for each patient. The combination of EEG and fNIRS, however, entails several constraints on montages, and finding an optimal arrangement of optodes on the cap is an important issue. We present a method for computing an optimal SD montage on an EEG/fNIRS cap that focuses on one or several specific brain regions; the montage maximizes the spatial sensitivity. We formulate this optimization problem as a linear integer programming problem. The method was evaluated on two EEG/fNIRS caps. We simulated absorbers at different locations on a head model and generated realistic optical density maps on the scalp. We found that the maps of optimal SD montages had spatial resolution properties comparable to those of regular SD arrangements for the whole head with significantly fewer sensors than regular SD arrangements. In addition, we observed that optimal montages yielded improved spatial density of fNIRS measurements over the targeted regions together with an increase in signal-to-noise ratio.