Special Section on Clinical Near-Infrared Spectroscopy and Imaging of the Brain

Cerebral blood flow and autoregulation: current measurement techniques and prospects for noninvasive optical methods

[+] Author Affiliations
Sergio Fantini, Angelo Sassaroli, Kristen T. Tgavalekos

Tufts University, Department of Biomedical Engineering, 4 Colby Street, Medford, Massachusetts 02155, United States

Joshua Kornbluth

Tufts University School of Medicine, Department of Neurology, Division of Neurocritical Care, 800 Washington Street, Box #314, Boston, Massachusetts 02111, United States

Neurophoton. 3(3), 031411 (Jun 21, 2016). doi:10.1117/1.NPh.3.3.031411
History: Received January 4, 2016; Accepted May 10, 2016
Text Size: A A A

Open Access Open Access

Abstract.  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.

Figures in this Article
Physiological importance and normal values of cerebral blood flow in adult humans

The human brain is an organ with high-energy density demands, amounting to only 2% of the entire body mass (or 1.4  kg) but accounting for about 20% of the total power consumption of a normal adult at rest (or 20  W). Blood perfusion is responsible for the delivery of oxygen, which is necessary for the neuronal oxidative metabolism of energy substrates (mostly glucose, but also ketone bodies and lactate1). Because of the limited capacity of neurons for anaerobic metabolism (at rest, up to 92% of the adenosine triphosphate in the brain results from oxidative metabolism of glucose2), cerebral blood flow (CBF) is critically important for brain function and viability. It ensures proper delivery of oxygen and energy substrates and the removal of waste products of metabolism. Both hypoperfusion (insufficient CBF) and hyperperfusion (excessive CBF) can cause brain damage through ischemic injury, the former, and the breakdown of the blood–brain barrier, the latter, which can cause seizures, headaches, encephalopathy, and both ischemic and hemorrhagic stroke.3

CBF is defined as the blood volume that flows per unit mass per unit time in brain tissue and is typically expressed in units of mlblood/(100  gtissue  min). Alternatively, one may express CBF in terms of flow per unit volume of brain tissue, thus in mlblood/(100  mltissue  min). The numerical values of CBF in the two cases differ by a factor given by the density of human brain tissue, which is about 1.04 to 1.06  g/ml (with reported values, measured ex vivo, as high as 1.08  g/ml).4 The normal average cerebral blood flow (CBF) in adult humans is about 50  ml/(100  gmin),5 with lower values in the white matter [20  ml/(100  gmin)] and greater values in the gray matter [80  ml/(100  gmin)].2

Factors that affect cerebral blood flow

In the spirit of Ohm’s law or Darcy’s law, blood flow (BF) through a vascular segment can be expressed as the ratio between the pressure difference across that segment (δP) and its vascular resistance (R). Poiseuille’s law expresses this resistance of a vascular segment (R) in terms of its radius (r), length (L), and the blood viscosity (η, usually expressed in centipoise, with 1  cP=1  mPas): R=8ηL/(πr4). Even though BF does not strictly fulfill all requirements for the validity of Poiseuille’s law (mostly because blood does not behave as a Newtonian fluid, especially in the microvasculature, blood vessels are not rigid pipes, and the flow velocity profile may deviate from the parabolic shape of steady laminar flow, especially at branching points or curved sections), it is nevertheless useful referring to it to appreciate, at least qualitatively, the factors that affect CBF. According to Poiseuille’s law, the blood flow (BF, in units of blood volume per unit time) through a vascular segment of length L and radius r, driven by a pressure difference δP, is given by Display Formula

BF=δPR=δPπr48ηL.(1)

In the case of CBF, the driving pressure is the so-called cerebral perfusion pressure (CPP), defined in the next paragraph, and the resistance is a total cerebrovascular resistance (CVR), which is associated with the entire brain vascular tree. The main sources of CVR are small arteries and pial arterioles, which can regulate their radius (r) through vasodilatation and vasoconstriction.

The CPP is defined as the difference between the mean arterial pressure (MAP), which is the weighted average of the systolic and diastolic pressure, and the intracranial pressure (ICP), which is the pressure of the cerebrospinal fluid (CSF) in the subarachnoid space. The normal range for resting MAP is 70 to 100 mmHg and for ICP it is 5 to 15 mmHg. From Eq. (1), it is apparent that changes in perfusion pressure, changes in vascular radius (i.e., vasodilation and vasoconstriction), and changes in blood viscosity all affect the CBF. Changes in perfusion pressure may occur under normal conditions, e.g., during a change in posture or exercise, or they may result from the administration of drugs or from pathological conditions such as subarachnoid hemorrhage (SAH), traumatic brain injury (TBI), and stroke. Blood viscosity is directly related to hematocrit and the concentration of hemoglobin in blood. While lower hematocrit decreases viscosity, thus increasing CBF according to Eq. (1), it also reduces the oxygen-carrying capacity of blood. The effect of the vascular radius r on CBF is of particular interest because it is responsible for the modulation and regulation of CBF, which is highly sensitive to r as indicated by the fourth power of r in Eq. (1), and we consider it next.

There are a number of factors that affect the vascular smooth muscles of small arteries and arterioles, resulting in their constriction or dilation. For example, carbon dioxide (CO2) is a powerful vasodilator, so that CBF increases during hypercapnic conditions. Two processes that are of paramount importance in cerebral hemodynamics are the cerebrovascular responses to brain metabolism (neurovascular coupling) and to changes in perfusion pressure (CA).

Neurovascular coupling is responsible for the increase in CBF to support greater regional or global metabolic demands of the brain. This metabolism-driven increase in CBF is thought to be effected by a number of vasoactive mediators such as ions (K+,H+,Ca2+), metabolic by-products (lactate, CO2, hypoxia, adenosine), vasoactive neurotransmitters (dopamine, gamma-amino butyric acid, acethylcoline), nitric oxide (NO), carbon monoxide (CO), and so on,6,7 with a potential contribution from astrocytes.8

CA is one of the homeostatic mechanisms of the body to keep CBF relatively constant despite changes in CPP. Even though the basic mechanisms responsible for neurovascular coupling and autoregulation are yet to be fully understood, it is nevertheless likely that neurovascular coupling and autoregulation share some common pathways that link them.9,10 In the next section, we consider CA in more detail.

Basic mechanisms and physiological importance of cerebral autoregulation

As discussed above, CBF is affected by a number of physiological and biochemical mechanisms, including changes in CPP. CA is the homeostatic process of regulation of CBF in response to changes in CPP. The way CA is achieved is through the regulation of CVR, which is done most effectively by modulating the radius of cerebral small arteries and arterioles [see Eq. (1)]. In the absence of CA, an increase in MAP causes an increase of CPP and, therefore, an increase of CBF even if the metabolic demand of the brain remains constant. Therefore, the CA mechanism, which can be seen as a negative feedback loop mechanism, counteracts the MAP increase by narrowing the vessels’ radius (thus increasing their resistance to flow) and bringing CBF to the original level. Conversely, a decrease in MAP tends to decrease CBF, and the regulatory mechanism causes vessel dilation to rebalance the CBF. These reactions of the cerebrovascular system to a MAP change occur if CA is working properly, otherwise, in pathological conditions where CA is impaired, CBF follows more or less passively (according to the level of impairment) MAP changes.

The physiological origin of CA is still unclear, with proposed mechanisms invoking myogenic, metabolic, and neurogenic processes.3,11 Myogenic mechanism: a myogenic response of vascular smooth muscle to transmural pressure changes was proposed to occur through arterial membrane depolarization, and to result in changes in the concentration of Ca2+ in the arterial wall.12 Metabolic mechanism: the altered concentration of vasoactive metabolites (such as adenosine) was proposed to result from initial blood-pressure-induced changes in BF.13 Neurogenic mechanism: perivascular neurons were proposed to have autoregulatory effects on cerebral arterioles.14 Regardless of which mechanism is responsible or prevalent, CA is mediated through the release of chemical mediators, which implies that a finite amount of time is required to regulate the CVR. Therefore, a finite amount of time is needed to restore the original value of CBF following a MAP change.11

Static versus dynamic cerebral autoregulation

Studies on CA can be divided into static and dynamic ones. Even though the mechanisms underlying static and dynamic CA might be the same or share some common basis, the time scale at which they are observed is different: static CA refers to MAP and CBF values under steady state conditions that are observed over a time scale of minutes or hours, while dynamic CA refers to transient MAP and CBF changes that are observed in a time scale of seconds. Early studies on CA relied on relatively “slow” methods for measuring CBF, like the Kety–Schmidt technique15 (see Sec. 3.2.1), or the Xe133 [Ref. 16] or Kr85 [Ref. 17] uptake technique (see Sec. 3.3.1). MAP was changed either by shifting central blood volume with mechanical maneuvers (like changing posture from supine to standing, head-up tilting, or introducing lower-body negative pressure), or, more commonly, by vasoactive drug injection. For a list of methods used to change MAP in static CA studies, we refer to the review by Numan et al.18 The measurements of MAP and CBF were taken only at baseline (i.e., before the MAP was changed) and after the effect of the challenging mechanism was complete (usually after minutes). Therefore, with the typical methods used for measuring static CA, it was not possible to study the temporal evolution of the transients in MAP and CBF as they reached their steady-state values. Moreover, according to these methods, CA was conceived as an all-or-nothing mechanism, i.e., either it was present (if CBF recovered to the initial value) or not (if CBF followed passively the MAP change).

With the advent of transcranial Doppler ultrasound (TCD, see Sec. 3.6.1), it was possible to sample the flow velocity of a large cerebral vessel [usually the middle cerebral artery (MCA)] with a high-sampling rate. This capability allowed for new methods of measuring a dynamic CA response. One of the typical MAP challenging mechanisms is the thigh pressure cuff release method,19 which will be described in more detail in Sec. 2.2.2. In both static and dynamic CA processes, the regulation of CBF is confined to the arterial compartment primarily at the level of small arteries and arterioles, which are able to dilate or constrict in order to change their resistance to flow.

Static cerebral autoregulation

A first review on static CA was written by Lassen.20 The MAP–CBF curve reported in this work showed a constant CBF for MAP values between 60 and 170 mmHg, indicating a highly active static regulatory system. The work of Lassen had a profound effect on the scientific and medical community, and the MAP–CBF curve presented in his paper was considered an important reference for the upper and lower cutoff values of MAP within which CA was effective. Figure 1 shows the CBF plateau over the MAP range for static autoregulation. The MAP–CBF curve in Lassen’s work was obtained by combining the results from seven human studies with 11 different subject groups, where in each group CBF was measured at a single MAP. The results on different subject groups were mixed regardless of whether the subjects were healthy, diseased, or under medication. Therefore, the curve represented intersubject values under different health conditions, rather than an intrasubject MAP–CBF relationship measured on a cohort of subjects in similar health conditions. As previously noted, this way of extrapolating the CA static curve from a limited number of different subjects can lead to misleading results, even if the subjects are all healthy, because of individual variability and unaccounted for effects of other variables.11 It is possible that the static CA curve is more pressure passive than previously described by Lassen, or, in other words, that the CBF–MAP curve in the autoregulation range is not exactly a flat plateau (as in Fig. 1), but has a slightly positive slope. This is in agreement also with some theoretical models of CA based on a feedback loop.21 Moreover, it is nowadays known that the static CA curve is affected by other variables, like the concentrations of carbon dioxide (CO2) and O2 in blood. For a theoretical model of the influence of blood gas levels on CA, we refer to the work of Payne et al.22