Cerebral blood flow (CBF) and cerebral autoregulation (CA) are critically important to maintain proper brain perfusion and supply the brain with the necessary oxygen and energy substrates. Adequate brain perfusion is required to support normal brain function, to achieve successful aging, and to navigate acute and chronic medical conditions. We review the general principles of CBF measurements and the current techniques to measure CBF based on direct intravascular measurements, nuclear medicine, X-ray imaging, magnetic resonance imaging, ultrasound techniques, thermal diffusion, and optical methods. We also review techniques for arterial blood pressure measurements as well as theoretical and experimental methods for the assessment of CA, including recent approaches based on optical techniques. The assessment of cerebral perfusion in the clinical practice is also presented. The comprehensive description of principles, methods, and clinical requirements of CBF and CA measurements highlights the potentially important role that noninvasive optical methods can play in the assessment of neurovascular health. In fact, optical techniques have the ability to provide a noninvasive, quantitative, and continuous monitor of CBF and autoregulation.

Cerebral autoregulation (CA) is the mechanism that allows the brain to maintain a stable blood flow despite changes in blood pressure. Dynamic CA can be quantified based on continuous measurements of systemic mean arterial pressure (MAP) and global cerebral blood flow. Here, we show that dynamic CA can be quantified also from local measurements that are sensitive to the microvasculature. We used near-infrared spectroscopy (NIRS) to measure temporal changes in oxy- and deoxy-hemoglobin concentrations in the prefrontal cortex of 11 human subjects. A novel hemodynamic model translates those changes into changes of cerebral blood volume and blood flow. The interplay between them is described by transfer function analysis, specifically by a high-pass filter whose cutoff frequency describes the autoregulation efficiency. We have used pneumatic thigh cuffs to induce MAP perturbation by a fast release during rest and during hyperventilation, which is known to enhance autoregulation. Based on our model, we found that the autoregulation cutoff frequency increased during hyperventilation in comparison to normal breathing in 10 out of 11 subjects, indicating a greater autoregulation efficiency. We have shown that autoregulation can reliably be measured noninvasively in the microvasculature, opening up the possibility of localized CA monitoring with NIRS.

We propose a new near-infrared spectroscopy (NIRS) method for quantitative measurements of cerebral blood flow (CBF). Because this method uses concepts of coherent hemodynamics spectroscopy (CHS), we identify this new method with the acronym NIRS-CHS. We tested this method on the prefrontal cortex of six healthy human subjects during mean arterial pressure (MAP) transients induced by the rapid deflation of pneumatic thigh cuffs. A comparison of CBF dynamics measured with NIRS-CHS and with diffuse correlation spectroscopy (DCS) showed a good agreement for characteristic times of the CBF transient. We also report absolute measurements of baseline CBF with NIRS-CHS (69 ± 6 ml/100g/min over the six subjects). NIRS-CHS can provide more accurate measurements of CBF with respect to previously reported NIRS surrogates of CBF.

We report a study on twenty-two healthy human subjects of the dynamic relationship between cerebral hemoglobin concentration ([HbT]), measured with near-infrared spectroscopy (NIRS) in the prefrontal cortex, and systemic arterial blood pressure (ABP), measured with finger plethysmography. [HbT] is a measure of local cerebral blood volume (CBV). We induced hemodynamic oscillations at discrete frequencies in the range 0.04–0.20 Hz with cyclic inflation and deflation of pneumatic cuffs wrapped around the subject’s thighs. We modeled the transfer function of ABP and [HbT] in terms of effective arterial ( K ( a ) ) and venous ( K ( v ) ) compliances, and a cerebral autoregulation time constant ( τ (AR) ). The mean values (± standard errors) of these parameters across the twenty-two subjects were K ( a ) = 0.01 ± 0.01 μM/mmHg, K ( v ) = 0.09 ± 0.05 μM/mmHg, and τ (AR) = 2.2 ± 1.3 s. Spatially resolved measurements in a subset of eight subjects reveal a spatial variability of these parameters that may exceed the inter-subject variability at a set location. This study sheds some light onto the role that ABP and cerebral blood flow (CBF) play in the dynamics of [HbT] measured with NIRS, and paves the way for new non-invasive optical studies of cerebral blood flow and cerebral autoregulation.

Objective: Cerebral autoregulation limits the variability of cerebral blood flow (CBF) in the presence of systemic arterial blood pressure (ABP) changes. Monitoring cerebral autoregulation is important in the Neurocritical Care Unit (NCCU) to assess cerebral health. Here, our goal is to identify optimal frequency-domain near-infrared spectroscopy (FD-NIRS) parameters and apply a hemodynamic model of coherent hemodynamics spectroscopy (CHS) to assess cerebral autoregulation in healthy adult subjects and NCCU patients.Methods: In five healthy subjects and three NCCU patients, ABP oscillations at a frequency around 0.065 Hz were induced by cyclic inflation-deflation of pneumatic thigh cuffs. Transfer function analysis based on wavelet transform was performed to measure dynamic relationships between ABP and oscillations in oxy- (O), deoxy- (D), and total- (T) hemoglobin concentrations measured with different FD-NIRS methods. In healthy subjects, we also obtained the dynamic CBF-ABP relationship by using FD-NIRS measurements and the CHS model. In healthy subjects, an interval of hypercapnia was performed to induce cerebral autoregulation impairment. In NCCU patients, the optical measurements of autoregulation were linked to individual clinical diagnoses.Results: In healthy subjects, hypercapnia leads to a more negative phase difference of both O and D oscillations vs. ABP oscillations, which are consistent across different FD-NIRS methods and are highly correlated with a more negative phase difference CBF vs. ABP. In the NCCU, a less negative phase difference of D vs. ABP was observed in one patient as compared to two others, indicating a better autoregulation in that patient.Conclusions: Non-invasive optical measurements of induced phase difference between D and ABP show the strongest sensitivity to cerebral autoregulation. The results from healthy subjects also show that the CHS model, in combination with FD-NIRS, can be applied to measure the CBF-ABP dynamics for a better direct measurement of cerebral autoregulation.

Abstract. We present a near-infrared spectroscopy (NIRS) study of local hemodynamics in the breast and the brain (prefrontal cortex) of healthy volunteers in a protocol involving periodic perturbations to the systemic arterial blood pressure. These periodic perturbations were achieved by cyclic inflation (to a pressure of 200 mmHg) and deflation (at frequencies of 0.046, 0.056, 0.063, 0.071, and 0.083 Hz) of two pneumatic cuffs wrapped around the subject's thighs. As a result of these systemic perturbations, the concentrations of deoxy-and oxyhemoglobin in tissue (D and O, respectively) oscillate at the set frequency. We found that the oscillations of D and O in breast tissue are in-phase at all frequencies considered, a result that we attribute to dominant contributions from blood volume oscillations. In contrast, D and O oscillations in brain tissue feature a frequency-dependent phase difference, which we attribute to significant contributions from cerebral blood flow oscillations. Frequency-resolved measurements of D and O oscillations are exploited by the technique of coherent hemodynamics spectroscopy for the assessment of cerebrovascular parameters and cerebral autoregulation. We show the relevant physiological information content of NIRS measurements of oscillatory hemodynamics, which have qualitatively distinct features in the healthy breast and healthy brain. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

We have recently introduced a new technique, coherent hemodynamics spectroscopy (CHS), which aims at characterizing a specific kind of tissue hemodynamics that feature a high level of covariation with a given physiological quantity. In this study, we carry out a detailed analysis of the significance of coherence and phase synchronization between oscillations of arterial blood pressure (ABP) and total hemoglobin concentration ([Hbt]), measured with near-infrared spectroscopy (NIRS) during a typical protocol for CHS, based on a cyclic thigh cuff occlusion and release. Even though CHS is based on a linear time invariant model between ABP (input) and NIRS measurands (outputs), for practical reasons in a typical CHS protocol, we induce finite “groups” of ABP oscillations, in which each group is characterized by a different frequency. For this reason, ABP (input) and NIRS measurands (output) are not stationary processes, and we have used wavelet coherence and phase synchronization index (PSI), as a metric of coherence and phase synchronization, respectively. PSI was calculated by using both the wavelet cross spectrum and the Hilbert transform. We have also used linear coherence (which requires stationary process) for comparison with wavelet coherence. The method of surrogate data is used to find critical values for the significance of covariation between ABP and [Hbt]. Because we have found similar critical values for wavelet coherence and PSI by using five of the most used methods of surrogate data, we propose to use the data-independent Gaussian random numbers (GRNs), for CHS. By using wavelet coherence and wavelet cross spectrum, and GRNs as surrogate data, we have found the same results for the significance of coherence and phase synchronization between ABP and [Hbt]: on a total set of 20 periods of cuff oscillations, we have found 17 coherent oscillations and 17 phase synchronous oscillations. Phase synchronization assessed with Hilbert transform yielded similar results with 14 phase synchronous oscillations. Linear coherence and wavelet coherence overall yielded similar number of significant values. We discuss possible reasons for this result. Despite the similarity of linear and wavelet coherence, we argue that wavelet coherence is preferable, especially if one wants to use baseline spontaneous oscillations, in which phase locking and coherence between signals might be only temporary.

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