Research Article: Frequency-resolved analysis of coherent oscillations of local cerebral blood volume, measured with near-infrared spectroscopy, and systemic arterial pressure in healthy human subjects

Date Published: February 12, 2019

Publisher: Public Library of Science

Author(s): Kristen Tgavalekos, Thao Pham, Nishanth Krishnamurthy, Angelo Sassaroli, Sergio Fantini, Markus M Bachschmid.


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.

Partial Text

Oscillations of systemic arterial blood pressure (ABP) drive hemodynamic changes in the body’s macro- and microvasculature, elicit local responses in the peripheral circulation, and induce oscillations in the cerebral blood volume (CBV), which is the focus of this work. The dynamics between systemic ABP and local CBV reflect a combination of effects due to passive vascular compliance and active vascular reactivity, which in turn elicit dynamic changes in cerebral blood flow (CBF). The passive response is determined by the mechanical properties of blood vessel walls. The active vascular reactivity is responsible for cerebral autoregulation (AR), which maintains a relatively stable CBF despite changes in cerebral perfusion pressure (CPP), defined as the difference between ABP and intracranial pressure (ICP). AR plays an important role in the CBF response to ABP oscillations. There has been an increasing interest in using metrics of AR to assess cerebrovascular health or to guide therapy at the bedside [1]. The characterization of the dynamic relationship between CBV and ABP may help discriminate the passive and active mechanisms of the CBV response to ABP changes to better assess and characterize AR.

We have applied an STFT approach for coherence, amplitude, and phase analysis of non-stationary systemic ABP and cerebral total hemoglobin concentration in the prefrontal cortex of human subjects. Previously, we have used the Hilbert transform-based analytic signal approach for the study of hemodynamic oscillations [40,41]. The benefit of the STFT approach is that it does not require band pass filtering at specific frequencies, which is a time consuming process. Instead, one may consider the data collected over the entire duration of the experiment, and use coherence thresholding to identify coherent dynamics that are associated with both induced and spontaneous ABP oscillations. Analysis of coherence and phase in the time-frequency domain has been used in several studies for analyzing systemic and local signals related to the vascular system [24,25,42–44]. In particular, NIRS-based studies of autoregulation have previously used the wavelet approach for time-frequency analysis [45].

We have reported a human study of the dynamic relationship between cerebral hemoglobin concentration (measured with NIRS in the prefrontal cortex) and systemic arterial blood pressure (measured with finger plethysmography). Specifically, we generated a theoretical transfer function to describe the frequency-dependent relationship between [HbT] and ABP oscillations, and we validated it experimentally in the frequency range 0.04–0.20 Hz, as well as at the heart rate (~1 Hz). Our results are consistent with two mechanisms of [HbT] oscillations, one directly due to ABP oscillations (affecting the arterial compartment and dominating at high frequencies beyond ~1 Hz) and one due to ABP-driven oscillations in CBF (affecting the venous compartment and dominating at low frequency below ~0.1 Hz). According to this interpretation, NIRS measurements of [HbT] reflect the autoregulatory CBF response, at least in the low-frequency range of about 0.1 Hz or below. Consequently, this study sets the stage for a new approach to optical measurements of cerebral autoregulation, on the basis of robust measurements of [HbT] and ABP dynamics.




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