Multiple Source-detector Distances Research Articles

Quantification of blood flow index in diffuse correlation spectroscopy using a robust deep learning method.

Diffuse correlation spectroscopy (DCS) is a powerful, noninvasive optical technique for measuring blood flow. Traditionally the blood flow index (BFi) is derived through nonlinear least-square fitting the measured intensity autocorrelation function (ACF). However, the fitting process is computationally intensive, susceptible to measurement noise, and easily influenced by optical properties (absorption coefficient and reduced scattering coefficient ) and scalp and skull thicknesses. We aim to develop a data-driven method that enables rapid and robust analysis of multiple-scattered light's temporal ACFs. Moreover, the proposed method can be applied to a range of source-detector distances instead of being limited to a specific source-detector distance. We present a deep learning architecture with one-dimensional convolution neural networks, called DCS neural network (DCS-NET), for BFi and coherent factor () estimation. This DCS-NET was performed using simulated DCS data based on a three-layer brain model. We quantified the impact from physiologically relevant optical property variations, layer thicknesses, realistic noise levels, and multiple source-detector distances (5, 10, 15, 20, 25, and 30mm) on BFi and estimations among DCS-NET, semi-infinite, and three-layer fitting models. DCS-NET shows a much faster analysis speed, around 17,000-fold and 32-fold faster than the traditional three-layer and semi-infinite models, respectively. It offers higher intrinsic sensitivity to deep tissues compared with fitting methods. DCS-NET shows excellent anti-noise features and is less sensitive to variations of and at a source-detector separation of 30mm. Also, we have demonstrated that relative BFi (rBFi) can be extracted by DCS-NET with a much lower error of 8.35%. By contrast, the semi-infinite and three-layer fitting models result in significant errors in rBFi of 43.76% and 19.66%, respectively. DCS-NET can robustly quantify blood flow measurements at considerable source-detector distances, corresponding to much deeper biological tissues. It has excellent potential for hardware implementation, promising continuous real-time blood flow measurements.

Body composition analysis via spatially resolved NIR spectroscopy with multifrequency bioimpedance precision.

Near-infrared spectroscopy (NIRS) is often criticized due to its insufficient accuracy in determining body composition compared to the gold standard methods. In this work, we show that the use of multiple source-detector distances, as well as the simultaneous use of physiological and optical features, can significantly improve the accuracy of determination of fat and lean mass percentage in the human body using NIR spectroscopy. The study performed on the n = 292 cohort revealed the mean absolute errors of 3.5% for fat content and 3.3% for soft lean mass percentage prediction (r = 0.93) using the multifrequency bioimpedance analysis (BIA) as a reference. Hence, NIRS can serve as an independent reliable method for body composition analysis with precision close to that of advanced multifrequency BIA.

Extraction of tissue optical property and blood flow from speckle contrast diffuse correlation tomography (scDCT) measurements.

Measurement of blood flow in tissue provides vital information for the diagnosis and therapeutic monitoring of various vascular diseases. A noncontact, camera-based, near-infrared speckle contrast diffuse correlation tomography (scDCT) technique has been recently developed for 3D imaging of blood flow index (αDB) distributions in deep tissues up to a centimeter. A limitation with the continuous-wave scDCT measurement of blood flow is the assumption of constant and homogenous tissue absorption coefficient (μ a ). The present study took the advantage of rapid, high-density, noncontact scDCT measurements of both light intensities and diffuse speckle contrast at multiple source-detector distances and developed two-step fitting algorithms for extracting both μ a and αDB. The new algorithms were tested in tissue-simulating phantoms with known optical properties and human forearms. Measurement results were compared against established near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) techniques. The accuracies of our new fitting algorithms with scDCT measurements in phantoms (up to 16% errors) and forearms (up to 23% errors) are comparable to relevant study results (up to 25% errors). Knowledge of μ a not only improved the accuracy in calculating αDB but also provided the potential for quantifying tissue blood oxygenation via spectral measurements. A multiple-wavelength scDCT system with new algorithms is currently developing to fit multi-wavelength and multi-distance data for 3D imaging of both blood flow and oxygenation distributions in deep tissues.

Phase dual-slopes in frequency-domain near-infrared spectroscopy for enhanced sensitivity to brain tissue: First applications to human subjects.

We present a first in vivo application of phase dual-slopes (DSϕ), measured with frequency-domain near-infrared spectroscopy on four healthy human subjects, to demonstrate their enhanced sensitivity to cerebral hemodynamics. During arterial blood pressure oscillations elicited at a frequency of 0.1 Hz, we compare three different ways to analyze either intensity (I) or phase (ϕ) data collected on the subject's forehead at multiple source-detector distances: Single-distance, single-slope and DS. Theoretical calculations based on diffusion theory show that the method with the deepest maximal sensitivity (at about 11 mm) is DSϕ. The in vivo results indicate a qualitative difference of phase data (especially DSϕ) and intensity data (especially single-distance intensity [SDI]), which we assign to stronger contributions from scalp hemodynamics to SDI and from cortical hemodynamics to DSϕ. Our findings suggest that scalp hemodynamic oscillations may be dominated by blood volume dynamics, whereas cortical hemodynamics may be dominated by blood flow velocity dynamics.

Depth dependence of coherent hemodynamics in the human head.

We report a near-infrared spectroscopy (NIRS) study of coherent hemodynamic oscillations measured on the human forehead at multiple source-detector distances (1 to 4cm). The physiological source of the coherent hemodynamics is arterial blood pressure oscillations at a frequency of 0.1Hz, induced by cyclic inflation (to a pressure of 200mmHg) 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.

Assessment of a multi-layered diffuse correlation spectroscopy method for monitoring cerebral blood flow in adults.

Diffuse correlation spectroscopy (DCS) is a promising technique for brain monitoring as it can provide a continuous signal that is directly related to cerebral blood flow (CBF); however, signal contamination from extracerebral tissue can cause flow underestimations. The goal of this study was to investigate whether a multi-layered (ML) model that accounts for light propagation through the different tissue layers could successfully separate scalp and brain flow when applied to DCS data acquired at multiple source-detector distances. The method was first validated with phantom experiments. Next, experiments were conducted in a pig model of the adult head with a mean extracerebral tissue thickness of 9.8 ± 0.4 mm. Reductions in CBF were measured by ML DCS and computed tomography perfusion for validation; excellent agreement was observed by a mean difference of 1.2 ± 4.6% (CI95%: -31.1 and 28.6) between the two modalities, which was not significantly different.

Cytochrome c oxidase response to changes in cerebral oxygen delivery in the adult brain shows higher brain-specificity than haemoglobin

The redox state of cerebral mitochondrial cytochrome c oxidase monitored with near-infrared spectroscopy (Δ[oxCCO]) is a signal with strong potential as a non-invasive, bedside biomarker of cerebral metabolic status. We hypothesised that the higher mitochondrial density of brain compared to skin and skull would lead to evidence of brain-specificity of the Δ[oxCCO] signal when measured with a multi-distance near-infrared spectroscopy (NIRS) system. Measurements of Δ[oxCCO] as well as of concentration changes in oxygenated (Δ[HbO2]) and deoxygenated haemoglobin (Δ[HHb]) were taken at multiple source-detector distances during systemic hypoxia and hypocapnia (decrease in cerebral oxygen delivery), and hyperoxia and hypercapnia (increase in cerebral oxygen delivery) from 15 adult healthy volunteers. Increasing source-detector spacing is associated with increasing light penetration depth and thus higher sensitivity to cerebral changes. An increase in Δ[oxCCO] was observed during the challenges that increased cerebral oxygen delivery and the opposite was observed when cerebral oxygen delivery decreased. A consistent pattern of statistically significant increasing amplitude of the Δ[oxCCO] response with increasing light penetration depth was observed in all four challenges, a behaviour that was distinctly different from that of the haemoglobin chromophores, which did not show this statistically significant depth gradient. This depth-dependence of the Δ[oxCCO] signal corroborates the notion of higher concentrations of CCO being present in cerebral tissue compared to extracranial components and highlights the value of NIRS-derived Δ[oxCCO] as a brain-specific signal of cerebral metabolism, superior in this aspect to haemoglobin.

Neonatal hemodynamic response to visual cortex activity: high-density near-infrared spectroscopy study

The neurodevelopmental outcome of neonatal intensive care unit (NICU) infants is a major clinical concern with many infants displaying neurobehavioral deficits in childhood. Functional neuroimaging may provide early recognition of neural deficits in high-risk infants. Near-infrared spectroscopy (NIRS) has the advantage of providing functional neuroimaging in infants at the bedside. However, limitations in traditional NIRS have included contamination from superficial vascular dynamics in the scalp. Furthermore, controversy exists over the nature of normal vascular, responses in infants. To address these issues, we extend the use of novel high-density NIRS arrays with multiple source-detector distances and a superficial signal regression technique to infants. Evaluations of healthy term-born infants within the first three days of life are performed without sedation using a visual stimulus. We find that the regression technique significantly improves brain activation signal quality. Furthermore, in six out of eight infants, both oxy- and total hemoglobin increases while deoxyhemoglobin decreases, suggesting that, at term, the neurovascular coupling in the visual cortex is similar to that found in healthy adults. These results demonstrate the feasibility of using high-density NIRS arrays in infants to improve signal quality through superficial signal regression, and provide a foundation for further development of high-density NIRS as a clinical tool.

Noninvasive assessment of testicular torsion in rabbits using frequency-domain near-infrared spectroscopy: prospects for pediatric urology

We present a quantitative near-IR spectroscopy study of the absolute values of oxygen saturation of hemoglobin before and after surgically induced testicular torsion in adult rabbits. Unilateral testicular torsions (0, 540, or 720 deg) on experimental testes and contralateral sham surgery on control testes are performed in four adult rabbits. A specially designed optical probe for measurements at multiple source-detector distances and a commercial frequency-domain tissue spectrometer are used to measure absolute values of testicular hemoglobin saturation. Our results show: (1) a consistent baseline absolute tissue hemoglobin saturation value of 78+/-5%, (2) a comparable tissue hemoglobin saturation of 77+/-6% after sham surgery, and (3) a significantly lower tissue hemoglobin saturation of 36+/-2% after 540- and 720-deg testicular torsion surgery. Our findings demonstrate the feasibility of performing frequency-domain, multidistance near-IR spectroscopy for absolute testicular oximetry in the assessment of testicular torsion. We conclude that near-IR spectroscopy has potential to serve as a clinical diagnostic and monitoring tool for the assessment of absolute testicular hemoglobin desaturation caused by torsion, with the possibility of serving as a complement to conventional color and spectral Doppler ultrasonography.

Toward Noninvasive 3-D Imaging of the Time Course of Cortical Activity: Investigation of the Depth of the Event-Related Optical Signal

The event-related optical signal (EROS) has been recently proposed as a method for studying noninvasively the time course of activity in localized cortical areas (G. Gratton and M. Fabiani, 1998, Psychonomic Bull. Rev. 5: 535–563). Previous data have shown that EROS has very good temporal resolution and can provide detailed surface activity maps. In the present study we investigated whether the depth of the active area can also be estimated. Nine subjects were run in a study in which the eccentricity of the visual stimuli was varied, and EROS was recorded from medial occipital areas using multiple source–detector distances. Seven of the same subjects were also run through a functional magnetic resonance imaging (fMRI) study using the same protocol. The fMRI data indicated that the depth from the head surface to the cortical area activated increased systematically with the eccentricity of the visual stimuli. The EROS recording indicated a response with a latency of 60–80 ms from stimulation. This response varied systematically with eccentricity, so that the greater the eccentricity of the stimuli, the longer the source–detector distance (and thus the depth) at which the EROS effect was observed. The depth of the brain area generating the EROS effect was estimated using a simple algorithm derived from phantom studies on homogeneous media. The average depth estimates for each eccentricity condition obtained with EROS corresponded with those obtained with fMRI, with discrepancies of less than 1 mm. These data demonstrate that multiple source–detector distances can be used to estimate the depth of the cortical areas responsible for the EROS effects.