9672_Cerebral Autoregulation-Based Blood Pressure Management In The Neuroscience Intensive Care Unit

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Cerebral Autoregulation-Based Blood Pressure Management In
Cerebral Autoregulation-Based Blood Pressure Management In
The Neuroscience Intensive Care Unit: Towards Individualizing
The Neuroscience Intensive Care Unit: Towards Individualizing
Care In Ischemic Stroke And Subarachnoid Hemorrhage
Care In Ischemic Stroke And Subarachnoid Hemorrhage
Andrew Silverman
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Intensive Care Unit: Towards Individualizing Care In Ischemic Stroke And Subarachnoid Hemorrhage”
(2020). Yale Medicine Thesis Digital Library. 3951.
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Cerebral autoregulation-based blood pressure
management in the neuroscience intensive care unit

Towards individualizing care in ischemic stroke and subarachnoid hemorrhage

A Thesis Submitted to the
Yale University School of Medicine
in Partial Fulfillment of the Requirements for the
Degree of Doctor of Medicine

by

Andrew Silverman

Class of 2020

ABSTRACT

The purpose of this thesis is to review the concept of cerebral autoregulation, to establish the
feasibility of continuous bedside monitoring of autoregulation, and to examine the impact of
impaired autoregulation on functional and clinical outcomes following subarachnoid hemorrhage
and ischemic stroke. Autoregulation plays a key role in the regulation of brain blood flow and has
been shown to fail in acute brain injury. Disturbed autoregulation may lead to secondary brain
injury as well as worse outcomes. Furthermore, there exist several methodologies, both invasive
and non-invasive, for the continuous assessment of autoregulation in individual patients. Resultant
autoregulatory parameters of brain blood flow can be harnessed to derive optimal cerebral perfusion
pressures, which may be targeted to achieve better outcomes. Multiple studies in adults and several
in children have highlighted the feasibility of individualizing mean arterial pressure in this fashion.

The thesis herein argues for the high degree of translatability of this personalized approach within
the neuroscience intensive care unit, while underscoring the clinical import of autoregulation
monitoring in critical care patients. In particular, this document recapitulates findings from two
separate, prospectively enrolled patient groups with subarachnoid hemorrhage and ischemic stroke,
elucidating how deviation from dynamic and personalized blood pressure targets associates with
worse outcome in each cohort. While definitive clinical benefits remain elusive (pending
randomized controlled trials), autoregulation-guided blood pressure parameters wield great
potential for constructing an ideal physiologic environment for the injured brain.

The first portion of this thesis discusses basic autoregulatory physiology as well as various tools to
interrogate the brain’s pressure reactivity at the bedside. It then reviews the development of the
optimal cerebral perfusion pressure as a biological hemodynamic construct. The second chapter
pertains to the clinical applications of bedside neuromonitoring in patients with aneurysmal
subarachnoid hemorrhage. In this section, the personalized approach to blood pressure monitoring
is discussed in greater detail. Finally, in the third chapter, a similar autoregulation-oriented blood
pressure algorithm is applied to a larger cohort of patients with ischemic stroke. This section
contends that our novel, individualized strategy to hemodynamic management in stroke patients
represents a better alternative to the currently endorsed practice of maintaining systolic blood
pressures below fixed and static thresholds.

ACKNOWLEDGMENTS

This work would not have been possible without the leadership and encouragement of Dr. Nils
Petersen. I could not have asked for a more insightful, creative, and patient mentor. It has been an
extraordinary opportunity learn about physiology, critical care, and balancing research and clinical
work from such a dedicated and kind role model.

Many thanks also to our larger research team, which includes Sumita Strander, Sreeja Kodali, Alex
Kimmel, Cindy Nguyen, Krithika Peshwe, and Anson Wang. Sumita and Sreeja, now first-year
medial students at Harvard and Yale, respectively, were incredible teammates throughout my
research year. They helped enroll patients, problem solve, and run new scripts. Their energy and
friendship sustained me during some of the longer days (and nights) of neuromonitoring and
abstract construction before midnight deadlines.

More gratitude to my thesis committee and mentors in the Neurology Department, including Dr.
Emily Gilmore, Dr. Kevin Sheth, Dr. Charles Wira, and Dr. Charles Matouk. In particular, Dr.
Gilmore volunteered her time to adjudicate clinical and radiologic scores for over 30 patients with
subarachnoid hemorrhage. Many thanks overall to the Divisions of Vascular Neurology and
Neurocritical Care for hosting me and providing me with a suitable workspace for an entire year.

Thank you to Yale’s amazing Office of Student Research: Donna Carranzo, Kelly Jo Carlson,
Reagin Carney, and Dr. John Forrest. Without their coordination efforts and sponsorship, I would
not have been able to obtain funding from the American Heart Association, practice presenting my
work at research in progress meetings, or learn about my peers’ awesome project developments –
not to mention all the coffee and snacks they provided.

Much gratitude, as always, to my grandma, my mom, my older brother, and to Lauren. Although
they are not in the medical field and will probably never read this thesis, they have continually been
enthusiastic and unconditionally supportive.

Finally, I would like to thank the patients and families who volunteered to participate in our studies.
Research reported in this publication was supported by the American Heart Association (AHA)
Founders Affiliate training award for medical students as well as the Richard A. Moggio Student
Research Fellowship from Yale.

TABLE OF CONTENTS

PART I ………………………………………………………………………………………………………………..1
A. Introduction: a brief history of autoregulation research …………………………………….1
B. Cerebral blood flow regulation and physiology………………………………………………..8
C. Methods to measure cerebral autoregulation ………………………………………………….17
D. Autoregulation indices and signal processing…………………………………………………22
E. Comparisons between autoregulatory indices ………………………………………………..28
F. Optimal cerebral perfusion pressure ……………………………………………………………..29
PART II……………………………………………………………………………………………………………..37
A. Subarachnoid hemorrhage …………………………………………………………………………..37
B. Clinical relevance of autoregulation following subarachnoid hemorrhage …………45
C. Pilot study on autoregulation monitoring in subarachnoid hemorrhage
……………..51
D. Results of the subarachnoid hemorrhage pilot study ……………………………………….65
E. Discussion …………………………………………………………………………………………………89
PART III ……………………………………………………………………………………………………………95
A. Large-vessel occlusion (LVO) ischemic stroke
………………………………………………95
B. Clinical relevance of autoregulation following ischemic stroke
………………………..99
C. Pilot study on autoregulation monitoring in ischemic stroke ………………………….103
D. Results of the ischemic stroke pilot study…………………………………………………….111
E. Discussion ……………………………………………………………………………………………….122
PART IV ………………………………………………………………………………………………………….131
A. Concluding remarks and future studies………………………………………………………..131
References
………………………………………………………………………………………………………..138

LIST OF PUBLICATIONS AND ABSTRACTS

Peer-reviewed original investigations

1. Silverman A, Kodali S, Strander S, Gilmore E, Kimmel A, Wang A, Cord B, Falcone G,
Hebert R, Matouk C, Sheth KN, Petersen NH. Deviation from personalized blood pressure
targets is associated with worse outcome after subarachnoid hemorrhage. Stroke 2019
Oct;50(10):2729-37.

2. Silverman A*, Petersen NH*, Wang A, Strander S, Kodali S, Matouk C, Sheth KN.
Exceeding Association of Personalized Blood Pressure Targets With Hemorrhagic
Transformation and Functional Outcome After Endovascular Stroke Therapy. JAMA
Neurology. 2019 Jul 29. doi: 10.1001/jamaneurol.2019.2120. [Epub ahead of
print] (*equally contributed)

3. Silverman A*, Petersen NH*, Wang A, Strander S, Kodali S, et al. Fixed Compared to
Autoregulation-Oriented Blood Pressure Thresholds after Mechanical Thrombectomy
for Ischemic Stroke. Stroke 2020, Mar;51(3):914-921. (*equally contributed)

Abstracts and presentations

1. Silverman A, Kodali S, Strander S, Gilmore E, Kimmel A, Cord B, Hebert R, Sheth K,
Matouk C, Petersen NH. Deviation from Dynamic Blood Pressure Targets Is Associated
with Worse Functional Outcome After Subarachnoid Hemorrhage. Platform
Presentation, Congress of Neurological Surgeons Annual Meeting, San Francisco 2019.

2. Silverman A, Wang A, Strander S, Kodali S, Sansing L, Schindler J, Hebert R, Gilmore E,
Sheth K, Petersen NH. Blood Pressure Management Outside Individualized Limits of
Autoregulation is Associated with Neurologic Deterioration and Worse Functional
Outcomes in Patients with Large-Vessel Occlusion (LVO) Ischemic Stroke. Platform
Presentation, American Academy of Neurology Annual Meeting, Philadelphia 2019.

3. Silverman A, Wang A, Kodali S, Strander S, Cord B, Hebert R, Matouk C, Sheth K, Gilmore
E, Petersen NH. Dynamic Cerebral Autoregulation and Personalized Blood Pressure
Monitoring in Patients with Aneurysmal Subarachnoid Hemorrhage (aSAH). Poster
Presentation, American Academy of Neurology Annual Meeting, Philadelphia 2019.

4. Silverman A, Wang A, Kodali S, Strander S, Cord B, Hebert R, Matouk C, Gilmore E, Sheth
K, Petersen NH. Individualized blood pressure management after subarachnoid
hemorrhage using real-time autoregulation monitoring: a pilot study using NIRS and
ICP-derived limits of autoregulation. Platform Presentation, International Stroke
Conference, Honolulu 2019.

Acronyms
aSAH
Aneurysmal subarachnoid
hemorrhage
MAPOPT
Optimal mean arterial pressure
BP
Blood pressure
PRx
Pressure reactivity index
ICP
Intracranial pressure
TOx
Tissue oxygenation index
NIRS
Near-infrared spectroscopy
%time
outside LA
Percent time outside limits of
autoregulation
DCI
Delayed cerebral ischemia
OR
Odds ratio
MAP
Mean arterial pressure
CI
Confidence interval
IQR
Interquartile range
aOR
Adjusted odds ratio
CBF
Cerebral blood flow
CVR
Cerebrovascular resistance
CPP
Cerebral perfusion pressure
TCD
Transcranial Doppler
CPPOPT
Optimal cerebral perfusion
pressure
LA
Limits of autoregulation
ULA
Upper limit of autoregulation
LLA
Lower limit of autoregulation
mRS
Modified Rankin scale
HH
Hunt and Hess classification
mF
Modified Fisher score
WFNS
World Federation of
Neurological Surgeons score
LoC
Loss of consciousness
ROC
Receiver operating
characteristic
TBI
Traumatic brain injury
LVO
Large-vessel occlusion
tPA
Tissue plasminogen activator
EVT
Endovascular thrombectomy
HT
Hemorrhagic transformation
HI
Hemorrhagic infarction
PH
Parenchymal hematoma
sICH
Symptomatic intracranial
hemorrhage
NIHSS
National Institute of Health
Stroke Scale
ASPECTS
Alberta Stroke Program Early
CT Score
ESCAPE trial
Endovascular Treatment for
Small Core and Anterior
Circulation Proximal Occlusion
with Emphasis on Minimizing
CT to Recanalization Times
DAWN trial
DWI or CTP Assessment with
Clinical Mismatch in the Triage
of Wake-Up and Late
Presenting Strokes Undergoing
Neurointervention with Trevo

1

PART I

A. Introduction: a brief history of autoregulation research

In 1959, Dr. Niels Lassen published a pivotal review on cerebral blow flow and popularized
the concept of cerebral autoregulation. [1] He writes, “Until about 1930 the cerebral
circulation was generally believed to vary passively with changes in the perfusion pressure.
This concept was based mainly on the Monro-Kellie doctrine of a constant volume of the
intracranial contents, from which it was deduced that no significant changes in intracranial
blood volume or vascular diameter were likely to occur.” In fact, Monro promoted this
conceit regarding the skull’s non-compliance in 1783, and it wasn’t until 1890 that Roy
and Sherrington submitted that cerebral blood flow might be dependent on both arterial
pressure in conjunction with intrinsic cerebrovascular properties capable of autonomously
regulating flow. [2, 3] In their letter to the Journal of Physiology, the authors speculate on
the origins of these properties:

“Presumably, when the activity of the brain is not great, its blood-supply is
regulated mainly by the intrinsic mechanism and without notable interference with
the blood-supply of other organs and tissues. When, on the other hand, the cerebral
activity is great, or when the circulation of the brain is interfered with, the
vasomotor nerves are called into action, the supply of blood to other organs of the
body being thereby trenched upon.”

Then, in 1902, Sir W.M. Bayliss performed a series of experiments on anesthetized cats,
dogs, and rabbits, observing peripheral vasoconstriction during increased blood pressure
inductions. [4] In a sample of his meticulous tracings below, one can appreciate that after
excitation of the splanchnic nerve, arterial pressure rises and causes passive distention of
hindleg volume (Figure 1). Bayliss points out that instead of merely returning to its original
2

volume when the blood pressure returns to baseline, the volume of the limb constricts
considerably below its previous level before returning to normal. This phenomenon was
later dubbed the Bayliss effect, referring to a pressure-reactive, myogenic vascular system.

Figure 1. Exemplary myogenic reactivity as demonstrated by W.M. Bayliss
at the turn of the 20th century. [4]

In the ensuing decades leading up to Lassen’s review, quantitative studies in both animal
models and humans confirmed observations of autoregulation as an objective homeostatic
phenomenon, first described by Forbes in 1928 and later by Fog in 1938. [5-8] Through
direct observation of feline pial vessels through a pioneering cranial window (a so-called
lucite calvarium), they noticed that systemic blood pressure increases resulted in surface
vessel vasoconstriction, while pressure decrements yielded local vasodilation, thus
3

sustaining the Bayliss effect. In summarizing these studies, Lassen found that optimal and
constant cerebral blood flow tended to occur within a cerebral perfusion pressure range of
roughly 50 to 150 mmHg. This autoregulatory doctrine has now made its way to first-year
medical school classrooms and can be heard on neurocritical care rounds on a virtually
daily basis (Figure 2).

Figure 2. The evolution of the autoregulatory curve from Lassen’s original
1959 publication (left) to the instructive illustration that can be found in
First Aid for the USMLE Step 1 (right). [1]

Furthermore, in 2019, animal model researchers in Belgium have effectively cast the lucite
calvarium into the realm of modern translation medicine. Using a porcine cranial window,
Klein et al. used laser Doppler flow to measure pial arteriole diameter and erythrocyte
velocity, allowing the team to quantify cerebrovascular autoregulation and its limits
(Figure 3). [9] The development of such models has the potential to help close the
translational gap between experimental and clinical work on autoregulation.

4

Figure 3. Adapted from Klein et al., this figure illustrates in vivo
measurements of pial arteriole red blood cell flux. (a) Microscope
positioned over the porcine cranial window with cortical laser Doppler
probe (white) and intraparenchymal ICP-PbtO2 probe (orange) placed
ipsilaterally behind the cranial window. (c) Fluorescent-labeled erythrocyte
moving through a pial arteriole at 200 frames/second. (d) Baseline
visualization of pial arterioles and individual red cell tracks. Individual red
blood cell tracks are superimposed on the original frame in different colors.
(e) Vasodilation of pial arterioles and individual red blood cell tracks during
induced
hypotension,
thereby
demonstrative
of
cerebrovascular
autoregulation. [9]

Clearly, science has evolved, but the definition of autoregulation has remained constant
(much like the plateau of Lassen’s curve). Cerebral autoregulation is the cerebrovascular
tree’s intrinsic capacity to maintain a stable blood flow despite changes in blood pressure
or – more accurately – cerebral perfusion pressure. [10] In his report, Lassen observes that
5

cerebral perfusion pressures vary to a modest extent in a normal person and that “the most
important regulating factor probably [is] the tissue carbon dioxide tensions and the direct
reaction of the muscular cells of the cerebral arteries in response to variations of the
distending blood pressure.” [1] Indeed, under normal circumstances, cerebral blood flow
is regulated through changes in arteriolar diameter, which, in turn, drive changes in
cerebrovascular resistance in accordance with the Hagen-Poiseuille equation. [11] Although decades of subsequent research have illuminated some underpinning
mechanisms, the exact molecular means underlying autoregulation remain elusive. Various
processes, including myogenic, neurogenic, endothelial, and metabolic responses, have
been implicated in the mediation of cerebral vasomotor reactions, but it is important to
differentiate carbon dioxide reactivity and flow-metabolism coupling from cerebral
autoregulation. [12] Carbon dioxide reactivity describes vascular reactions in response to
changes in the partial pressure of arterial carbon dioxide (PaCO2) but does not take into
consideration reactions to pressure changes. Flow-metabolism coupling, in comparison,
involves regulation of cerebral blood flow with regard to local cellular demand, for
example, as a consequence of neural activation during cognitive tasks. Similar to PaCO2
reactivity, flow-metabolism coupling and the neurovascular unit function irrespective of
fluctuations in cerebral perfusion pressure. [11]

With a working definition of autoregulation and an understanding of what it is not,
researchers have built technology that now boasts the ability to collect autoregulation-
derived data in real-time, which may lead to the fine-tuning of decades-old guidelines. [13,
14] By individualizing cerebral perfusion pressure in the neurocritical care unit, updated
guidelines may potentially ameliorate clinical and functional outcomes. [15] 6

Autoregulation can now efficaciously be assessed by examining changes in cerebral blood
flow, or its surrogates, in response to changes in cerebral perfusion pressure, or mean
arterial pressure (MAP) as its surrogate. [11] Individualization of autoregulatory pressure
ranges, together with the developing concept of an optimum mean arterial pressure
landscape for the injured brain, represent a novel and innovate application of autoregulation
neuromonitoring.

Numerous studies in recent years have demonstrated that large differences between actual
MAP and an optimal, calculated MAP (based on autoregulatory status) associate with poor
outcome across several disease states. These papers encompass traumatic brain injury,
intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke, adults undergoing
cardiac bypass surgery, children with moyamoya vasculopathy, and neonates with
hypoxic-ischemic encephalopathy. [13, 16-22] The cumulative strength of these findings
triggered the Brain Trauma Foundation to recommend autoregulation monitoring in an
effort to optimize brain perfusion in patients with traumatic brain injury. [23]

Nevertheless, guidelines for blood pressure management persistently recommend a single,
fixed target value for many critically ill patients. For example, the American Heart
Association and American Stroke Association endorse a systolic blood pressure of less
than 140 mmHg after intracerebral hemorrhage; they also suggest systolic pressures under
160 mmHg before aneurysm obliteration, and less than 140 mmHg after clipping or coiling
of the aneurysm following a subarachnoid hemorrhage. [24, 25] The same societies
recommend systolic readings of less than 180 mmHg after intravenous recombinant tissue
7

plasminogen activator for ischemic stroke. [26] In contrast, the European Society of
Intensive Care Medicine acknowledges that septic patients with a history of hypertension
may have autoregulation curves shifted to the right, thus requiring a higher MAP for
adequate cerebral perfusion. [27] These guidelines, however, do not currently consider
autoregulation-guided hemodynamic management of critically ill patients. In this
omission, many questions in the field of neuromonitoring are left unanswered. [15] First
and foremost, with respect to this thesis, is it feasible to effectively personalize MAP
targets based on an individual’s dynamic autoregulatory composition? Might this method
be clinically beneficial? How can it be tailored across various monitoring techniques and
disease states?

Notwithstanding such unanswered questions, the science of autoregulation has come a long
way since 1959. [1] Speaking perhaps to the incremental, and yet potentially
groundbreaking nature of scientific investigation, Dr. Lassen concludes his 56-page review
with the following remarks:

“These major findings and the wealth of additional observations have very
substantially increased our understanding of this important area of human
physiology. Undoubtedly our knowledge is still incomplete at various points.
However, a solid foundation for relevant physiological thinking and for future
studies has been established.”

It is now 60 years down the line, and autoregulation research is at the precipice of tangibly
translatable use at the bedside, as clinical trials of autoregulation-guided therapy are
underway across Europe (NCT02982122). [28] Moreover, this thesis will discuss two
prospective, observational studies at Yale-New Haven Hospital, each investigating the
feasibility of using an innovative algorithm to determine personalized, autoregulation-
8

based blood pressure targets at the bedside. To our knowledge, these studies are the first to
examine the impact of deviation from personalized, autoregulation-based blood pressure
limits in patients with subarachnoid hemorrhage and large-vessel occlusion ischemic
stroke. [13, 14] Thus, these studies arguably set the stage for imminent interventional trials
within Yale’s Divisions of Vascular Neurology as well as Neurocritical Care and
Emergency Neurology. [29] Before delving into the details of these studies, it is important
to more meticulously review autoregulation physiology, monitoring techniques, and the
development of the optimal cerebral perfusion pressure. In doing so, perhaps Lassen’s solid
foundation will grow, and future studies will be all the more within reach.

B. Cerebral blood flow regulation and physiology

Cerebral oxygen delivery is a function of brain blood flow and blood oxygen content,
whereby cerebral blood flow (CBF) is gradient between cerebral perfusion pressure (CPP)
and cerebrovascular resistance (CVR). Another way to conceptualize blood flow to the
brain is via the gradient between the brain’s arteries and veins, the latter being
approximately equivalent to intracranial pressure (ICP).

CBF = CPP/CVR = (MAP – ICP)/CVR

The brain’s vascular resistance reflects the smooth muscle tone of the vessels, partially
influenced by mean arterial pressure (MAP). If CPP increases or decreases, the myogenic
reflex will result in vasoconstriction or vasodilation, respectively. This dictum is the
classical view of pressure-flow autoregulation. If intracranial pressure is stable, CPP can
9

be replaced by MAP. In this manner, changes in brain blood flow can be measured for a
range of blood pressures to determine autoregulation.

In general, however, four mechanisms regulate cerebral blood flow, including myogenic,
neurogenic, endothelial, and metabolic processes, illustrated in Figure 4 (ChemDraw
Professional, Version 17.1.0.105). [10] Each of these classical mechanisms will be
reviewed in this section, with an important caveat that the interplay and relative
contributions of each of these mechanisms is highly complex and poorly understood. [30] Additionally, an imprecise border zone between conductive and resistive facets in the
cerebrovascular tree suggests that autoregulation may involve both large and small arteries
and arterioles. For instance, large extracranial arteries and intracranial pial vessels
comprise roughly half of the brain’s vascular resistance, with the remainder stemming from
penetrating parenchymal arteries and arterioles. [31, 32] These parenchymal arteries
possess distinctive, resistive properties compared to pial vessels; ensuing segmental and
spatiotemporal heterogeneity in autoregulation, as well as pathophysiologic correlates of
this heterogeneity, will be reviewed in this section.

10

Transmural pressure
on blood vessel wall
Nitric oxide
Acetylcholine
Serotonin
Neuropeptide Y
PaCO2
Endothelium-smooth
muscle interaction
Cerebral blood flow
Mean arterial pressure
Endothelin-1
Thromboxane A2
Nitric oxide

Figure 4. Physiology of cerebral autoregulation. This illustration shows the
four classical mechanisms contributing to cerebral autoregulation. Through
myogenic tone, transmural pressure influences arterial diameter through
direct smooth muscle contraction or relaxation. In the metabolic
mechanism, fluctuations in the partial pressure of carbon dioxide lead to
vasoconstriction or dilatation. The endothelium secretes paracrine
substances that may act directly on smooth muscle cells. Lastly, in the
neurogenic response, neurons and glia mediate smooth muscle physiology
by releasing various neurotransmitters with vasoactive properties. This
figure was created using ChemDraw software.

1) Myogenic Tone

Myogenic tone is produced when arteriole and small artery smooth muscle cells
contract in response to increased pressure. [33, 34] In contrast, myogenic tone
relaxes in response to decreased pressure. This phenomenon is manifest in the
aforementioned Bayliss effect (see Figure 1 in the introduction). More recent work
11

has unearthed some details about the effect. For example, a rapid change of pressure
(ΔP = 10 to 25 mmHg/sec) induces rapid changes in the diameter of the vessel, and
the latency of such transmural stimulation typically occurs in under 250 msec. [35]

Transmural pressure changes, in turn, activate mechanically sensitive ion channels
and proteins in the vessel wall, triggering various downstream cascades. For
instance, membrane depolarization opens voltage-gated calcium channels, leading
to an influx of calcium cations into the smooth muscle cell. [36] Calcium activates
myosin light chain kinase (MLCK), which goes on to activate myosin by
phosphorylation. Phosphorylated MLCK increases actin-myosin interaction,
causing muscle cell contraction and vasoconstriction. Furthermore, activation of
RhoA, a small GTPase, stimulates Rho-associated kinase (ROCK), which inhibits
myosin light chain phosphatase. [37] Inhibiting the dephosphorylating inhibitor in
this way potentiates vasoconstriction. Other parallel pathways involve protein
kinase C activation, which stabilizes the actin-myosin interaction. [38] More recent
hypotheses implicate arachidonic acid metabolites like 20-hydroxyeicosatetraenoic
acid (20-HETE), a known vasoconstrictor, and epoxyeicosatrienoic acids (EETs)
in the mediation of vessel wall stretch and basal tone. [39]

The importance of smooth muscle cell myogenic regulation can be seen in cerebral
autosomal
dominant
arteriopathy
with
subcortical
infarcts
and
leukoencephalopathy (CADASIL). [40, 41] Patients with CADASIL show a degree
of smooth muscle cell degeneration in small cerebral arteries, and studies have
12

demonstrated impaired myogenic autoregulatory functioning in both animal models
and individuals with the genetic condition. [42, 43] This disease is caused by a
mutation in the NOTCH3 gene and marked by recurrent ischemic strokes, cognitive
impairment, subcortical dementia, mood disturbances like depression and apathy,
as well as premature death. Lacombe et al. provided evidence that transgenic mice
expressing a mutant NOTCH3 in vascular smooth muscle cells exhibited impaired
cerebral vasoreactivity, including reduced responses to vasodilatory challenges and
a shift of the lower limit of autoregulation toward higher pressures. [44] Interestingly, parenchymal arteries exhibit greater basal tone than pial arteries. This
difference may buffer effects of upstream rapid changes in blood pressure on
cerebral perfusion and thus attenuate transmission of pulsatile mechanical stress
into the brain’s microcirculation. Disturbance of this basal tone may exacerbate
stroke burden in CADASIL patients. [41, 45]

Increased transmural pressure translates to increased flow, and there is evidence
that flow may induce vessel diameter changes independent of pressure changes. In
2011, for example, Toth et al. showed that both human and rodent cerebral arteries
constrict in response to increased flow when pressure was held constant, possibly
due to an increase in reactive oxygen species and cyclooxygenase activity. [46]

2) Neurogenic Response

Neurogenic mediation of cerebral vasoreactivity involves control of small- and
medium-sized vessel diameters. Neurons and other cell types like astrocytes and
microglia secrete a variety of neurotransmitters with vasoactive properties. For
13

instance, acetylcholine and nitric oxide are relatively potent vasodilators, while
serotonin and neuropeptide Y stimulate vasoconstriction. [47]

Through the creative use of infrared video-microscopy of interneurons and adjacent
microvessels in rodents, Cauli et al. showed that increased depolarizing activity of
single cortical interneurons results in precise vasomotor responses in neighboring
microvessels. [48] They further showed that these neuronally induced vasomotor
responses can be mimicked by perivascular application of vasoactive neuropeptides
directly on microvascular receptors.

On a larger scale, these changes in blood flow in response to neuronal activation
can be observed as the blood oxygen level dependent (BOLD) signal, which is
employed in functional magnetic resonance imaging (fMRI). The BOLD response
has been adapted in many fMRI studies investigating increased cerebral metabolic
demand in cognitive tasks, spatial memory, visual processing, and across various
disease states. [49-51]

Interestingly, the neurogenic response exhibits both segmental and regional
heterogeneity, as vessel reactivity varies from the pial arteries as they branch into
the parenchyma and become arterioles. [30] Regarding segmental variability, pial
arteries receive perivascular innervation from the peripheral autonomic system,
with roots in the superior cervical, sphenopalatine, otic, and trigeminal ganglia. [47,
52] This anatomic pathway is referred to as extrinsic innervation. The brain’s
14

parenchymal arteries and arterioles, in contrast, are primarily innervated by
intrinsic nerves originating from subcortical neurons, such as those found within
the locus coeruleus, raphe nucleus, basal forebrain, or local cortical interneurons.
These areas then project to the perivascular space surrounding the parenchymal and
arteriolar vessels. It follows that this pathway is referred to as intrinsic innervation.

This difference in anatomy entails divergent expression levels of neurotransmitter
receptors. For instance, α-adrenoreceptor reactivity is relatively absent in
parenchymal arteries due to a shift toward β-adrenoreceptor density. [53] Similar
heterogeneity has been shown with serotonin receptor levels. Accordingly,
serotonin- and norepinephrine-induced pial vasoconstriction is absent in the
parenchymal and arteriolar arteries, sometimes even causing vasodilation. [54] This
mosaic topography in neurogenic regulation may provide the brain with the ability
to flexibly modulate blood flow to meet local metabolic demand. [30]

Regarding regional heterogeneity, the anterior circulatory system of the brain
possesses denser sympathetic innervation than that of the posterior system. The
anterior circulation is controlled mostly by adrenergic sympathetic relays from the
superior cervical ganglion as they travel up the carotid arteries. The posterior
vessels instead depend on the sympathetic chain via the vertebrobasilar arteries.
[55] Autoregulation has also been shown to be more effective in the brainstem. For
example, in severe hypertension in anesthetized cats, cerebral blood flow
significantly increases in the anterior circulation, whereas the brainstem only
15

requires modest increases in flow. [56] This vascular resistance differential points
to a likely regional incongruity in cerebral autoregulation.

This regional variability may play a key role in the development of posterior
reversible
encephalopathy
syndrome
(PRES).
This
syndrome,
which
parenthetically is not always posterior or even reversible, is otherwise characterized
radiologically by transient bilateral subcortical vasogenic edema in the territory of
the posterior circulation. [57] Among several etiologic theories involving
immunologic dysfunction, vasospasm, and endothelial and blood-brain barrier
breakdown, one interesting explanation for the edema’s apparent posterior
predilection is the relative dearth of sympathetic tone in that area, leading to poor
autoregulation of blood flow in the setting of abrupt hypertensive episodes. [55]

3) Metabolic Mechanism

The metabolic mechanism subserving autoregulation occurs in smaller vessels that
are subject to changes in the local environment. [58] Most notably, carbon dioxide
overtly alters vasomotor responses; every 1 mmHg increase in PaCO2 corresponds
to a roughly 4% increase in cerebral blood flow. [59] The concentration of cerebral
carbon dioxide can accumulate and cause vasodilation in this fashion when, for
example, hypotension below the lower autoregulatory limit results in tissue
hypoperfusion and thus anaerobic respiration. The opposite physiology transpires
in the setting of hyperperfusion with consequent decreases in PaCO2 and
vasoconstriction. [60, 61]

16

It is hypothesized that this vasomotor response is regulated by the H+ concentration
in the smooth muscle of cerebral vessels. [59] Proton gradients are regulated by
carbonic anhydrase activity, the catalytic activity of which depends on the tight
regulation of pH (normally hovering around 7.4 in the human body). Prolonged
hypocapnia that generates tissue alkalosis may increase carbonic anhydrase
activity. [11]

Additionally, decreased oxygen partial pressures can increase cerebral blood flow,
as can be seen in Figure 2. This effect does occur unless there is severe hypoxemia
of less than 50 mmHg, or 6.6 kPa. [62] Similarly, severe hypoglycemia at levels of
less than 2 mmol/L can lead to increases in cerebral blood flow. [63]

4) Endothelial Mechanism

Lastly, endothelial tissue begets a gamut of signals that affect vascular tone. The
endothelium secretes vasodilators like nitric oxide (NO) and vasoconstrictors like
thromboxane A2 and endothelin-1 in a paracrine manner. [10, 64]

Further, as an interesting bedside-to-bench endeavor, researchers have looked at
the ability of statins to regulate autoregulation. In more detail, statins have the
capacity to upregulate nitric oxide synthase, causing cerebral artery dilation and
increased cerebral blood flow. [65, 66] This mechanism occurs through the
inhibition of small G-proteins known as Rho and Rac. Rho negatively regulates
endothelial nitric oxide synthase. Statins inhibit Rho GTPase activity via inhibition
17

of a process known as geranylgeranylation (a form of prenylation), which
ultimately confers nitric oxide synthase upregulation.

At this point, it should be stressed that conventional measurements of cerebrovascular
reactivity are not exactly synonymous with measurements of cerebral autoregulation. The
response to vasodilatory stimuli like CO2, nitric oxide, or acetazolamide, has been used
traditionally in the quantification of vasomotor reactivity. [6, 66] These agents dilate
cerebral arterioles and small arteries to locally increase cerebral blood flow through a
variety of neurogenic, metabolic, and endothelial processes. Although an intact
endothelium is quite necessary for adequate pressure regulation, this approach does not
assess fluctuations in cerebrovascular resistance in strict response to perfusion changes.
Therefore, vasomotor reactivity and cerebral autoregulation are non-interchangeable
physiologic phenomena. In other words, when vasomotor reactivity is exhausted, brain
blood flow becomes dependent on systemic arterial blood pressure. Cerebral
autoregulation is one critical aspect of this reactivity and involves vascular tone changes in
response to pressure fluctuations. Vessels may continue to exhibit responses to further
changes in PaCO2, and these responses fall within the domain of the cerebral autoregulatory
mechanism protecting the brain. For example, vasodilation may reach its maximum at
arterial pressures below the lower limit for constant cerebral blood flow. [6, 12]

C. Methods to measure cerebral autoregulation

Pressure autoregulation has traditionally been assessed by calculating cerebral blood flow
at two different equilibrium states of arterial blood pressure. These steady-states
18

correspond to particular cerebral blood flow values. One pressure measurement could be
taken at baseline, and the second could be measured after manual or pharmacologic
manipulation of blood pressure, at which point brain blood flow could be measured again.
Because this approach involves stable pressures and flows, it is referred to as a static
autoregulatory measurement. [67] Other stimuli include body tilt, hand grip, lower body
negative pressure, Valsalva, paced breathing, and squat-stand maneuvers. [6, 11] An
advantage of these maneuvers is the precise control of the magnitude and time of the
hemodynamic response; they are accurate insofar as the stimuli drive a synchronized
response of brain blood flow. However, the methods are all temporally limited and, for the
most part, cannot be performed more than once per day.

The advent of transcranial Doppler (TCD) ultrasound allowed for visualization of real-time
blood-flow velocities (with a temporal resolution of approximately 5 msec), paving the
road for dynamic assessments of autoregulation. [6, 68] Dynamic autoregulation refers to
short-term, fast responses of the brain’s blood flow to changes in systemic pressure. As
TCD cannot measure flow directly, blood flow velocity is used as a surrogate. In this
manner, methods like carotid compression or inflation of a leg cuff, each followed by
release and subsequent autoregulatory hyperemia, can be utilized to induce rapid changes
in middle cerebral artery flow velocity (taken as a surrogate for global hemispheric
perfusion). [11, 69] Alternatively, one may insonnate intracranial vessels without any
particular blood pressure challenges, such that monitoring takes place throughout
spontaneous fluctuations of arterial blood pressure. [70] This latter approach renders
dynamic assessments of cerebral autoregulation safe and feasible, as pressure