 

0\

. z... .r...n..

V 5 Wmmeﬁ9imm
a! .....r. .3

: .5Emimelﬁ.

 

2

:MWwa

at : .

1a...
'3‘,

I!)
L

".1

#3».
haw. ..
a...

1...: .sﬁunr , .

.. .. rc, bra.
r; ca... 1.... ‘ : X.

m:

an:
,7 3‘33!» 3.
I i 4
1:51.”? 4..
v...- e. 3.:
(.EJWNI.‘
.151
4....
(.2: s
1.!!3‘, ,
u Iii... 1.... {its
2 93...: .ITK
in 7:1...

.ukﬂuu O

\aiil

5.91:1“!

VrK..~..-\. I‘:

Menu .1 1......
- 41M.

q

.
._ a... ﬂing... and...

i g,:'§pl..
IO;

Sag

.unl‘t‘...ﬂ‘

E". Lys|v1

l.“ 3.

Januzgio
01.. .4k‘!‘ 1

r3:

Eris. v

 

.L A
[on

 

LIBRARY
Michigan State
University

 

 

 

This is to certify that the
dissertation entitled

MECHANISM OF THE POST-CONTRACTILE BLOOD
OXYGENATION LEVEL-DEPENDENT (BOLD) EFFECT IN HUMAN
SKELETAL MUSCLE

presented by

Theodore Francis Towse

has been accepted towards fulﬁllment
of the requirements for the

Doctoral degree in Physiology

 

 

MM

Major Professor’s Signamre

3/12. [as

Date

MSU is an afﬁrmative-action, equal-opportunity employer

 

PLACE IN RETURN BOX to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

5/08 KIIProjIAoc8PreleIRCIDaleDtJe.indd

 

MECHANISM OF THE POST-CONTRACTILE BLOOD OXYGENATION LEVEL-
DEPENDENT (BOLD) EFFECT IN HUMAN SKELETAL MUSCLE

By

Theodore Francis Towse

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Department of Physiology

2008

ABSTRACT
MECHANISM OF THE POST-CONTRACTILE BLOOD OXYGENATION LEVEL-
DEPENDENT (BOLD) EFFECT IN HUMAN SKELETAL MUSCLE
By

Theodore Francis Towse

Blood oxygenation level-dependent (BOLD) contrast is a functional magnetic
resonance imaging (fMRI) technique that can quantify, non-invasively and in real-time,
the biological function of organs and tissues. Recently Hennig et al., showed BOLD-like
contrast in skeletal muscle in response to brief contractile activity with a magnitude and
time course similar to the BOLD response measured in the brain. These ﬁndings however
were preliminary, and no measures of blood volume or hemoglobin saturation were made
to conﬁrm the BOLD mechanism. Therefore the overall aim of this dissertation was to
determine if a post-contractile BOLD effect exists in muscle, and to determine the extent
to which changes in muscle blood ﬂow, blood volume, and hemoglobin saturation
explain the post-contractile muscle BOLD effect.

We ﬁrst measured post-contractile MRI transients in the ankle dorsiﬂexors in
response to single l-second muscle contractions. The MRI transients were compared
across ﬁeld strength (1.5 vs. 3T) and imaging sequence (SE vs. GB). In addition, a set of
parallel studies was performed to measure changes in blood volume and hemoglobin
saturation by Near-Infrared—Spectroscopy (NIRS) in the same muscle group during the
same exercise protocol. The post-contractile MRI transients showed a similar magnitude

and time course to the brain BOLD contrast and, as in the brain, the effect was larger at 3

vs. 1.5 T. Furthermore the NIRS measured changes in hemoglobin saturation of the
ankle dorsiﬂexors displayed a magnitude and time course consistent with the MRI
transients. Therefore we conclude that the post-contractile MRI transient following brief
muscle contractions is due to the BOLD contrast mechanism commonly exploited in
brain functional imaging.

The post-contractile BOLD response is a hyperemic response, the magnitude of
which may be inﬂuenced by habitual physical activity. Therefore we set out to determine
if habitual physical activity inﬂuenced the magnitude of the post-contractile BOLD
response. We compared the magnitude of the post-contractile BOLD response in a group
of habitually active versus sedentary subjects and found that the active subjects had a 3-
fold higher peak post-contractile BOLD response.

The larger post-contractile BOLD response in active subjects could be due to a
larger hyperemic response, or a larger increase in blood volume and/or hemoglobin
saturation. Therefore we measured blood flow, blood volume and hemoglobin saturation
changes in response to single l-second contractions of the ankle dorsiﬂexors in a group
of subjects with a range of physical activity levels. We observed a positive relationship
between physical activity and the magnitude of the post-contractile ﬂow response such
that in general the subjects that participated in more physical activity had larger ﬂow
responses and larger BOLD responses. Furthermore, blood volume and hemoglobin
saturation quantitatively described the measured BOLD response. Finally, a simple model
of muscle perfusion and oxygen consumption aﬁer brief contractions showed that the
balance between muscle blood ﬂow and oxygen consumption together determined the

time course and magnitude of the post-contractile BOLD response.

ACKNOWLEDGEMENTS

I would like to take this opportunity to thank the many people who have supported me

during my graduate work.

First I would like to thank my Ph.D. advisor Dr. Ronald A. Meyer for his guidance and
support during my time at Michigan State. Dr. Meyer’s approach to the science and
professional integrity is exceptional and will provide a standard for me to strive for
during my career. I appreciate that Dr. Meyer gave me the ﬂexibility to work
independently while providing the necessary oversight at critical junctures during both
the research and writing of my dissertation. Other members of my dissertation committee
provided signiﬁcant guidance during the process including Dr. Robert W. Wiseman, Dr.
Mark C. DeLano, Dr. Bruce M. Damon, and Dr. Harvey V. Sparks. In particular I would
like to thank Drs. Wiseman and Sparks whom I relied on heavily for a different

perspective on my data as well as their advice in navigating the Ph.D. process.

I could not have completed my research without the assistance of many talented
undergraduates working in our lab including Jeff Ambrose, Matt Moll, Malak Saddy, and
Cody Weston. These students provided support on many levels including recruiting and
scheduling subjects, collecting and analyzing data and building and repairing laboratory
equipment. I am grateful for their assistance and take comfort in the fact that the next

generation of scientists and physicians are bright, motivated and personable.

iv

My lab mates, Jill Slade, Jeff Brault and Sean Forbes have been proven to be both great
co-workers and good friends. They have read drafts of my writing, sat through my
presentations and provided critical feedback of my work when ever necessary. Jill Slade
in particular has assisted in my dissertation research at every level and her work ethic,
organizational skills and attention to details has greatly improved the quality of my own

work.

The many good friends you meet along the way make the Ph.D. process tolerable. In
addition to those I have already mentioned I would like to thank Dave Pober and Dave
Rice two friends from my days at UMass. I would also like to thank Erica Wehrwein a
good friend and colleague I met during my ﬁrst days at MSU. Erica and I went through
the MSU physiology program together, studying for exams, practicing presentations and
talking science. Erica’s positive attitude and “Spartan Spirit”, although I wouldn’t go so
far as to say it rubbed off on me, it did help to make my time at MSU more fun and

certainly unforgettable.

My family, in particular my Mother and Father, Brothers and Sisters have all been very

supportive and encouraging during my graduate career and for that I thank them.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................. viii

LIST OF FIGURES ................................................................................. ix

KEY TO SYMBOLS AND ABBREVIATIONS ............................................... xii

CHAPTER 1

INTRODUCTION .................................................................................... 1
References .................................................................................... 5

CHAPTER 2

LITERATURE REVIEW ........................................................................... 7
2.1 The Biophysics of Magnetic Resonance Imaging .................................. 7
2.2 BOLD imaging in the Brain ......................................................... 10
2.3 Intravascular and Extravascular contributions to the BOLD effect ............ 12
2.4 Inﬂuence of different vascular compartments ..................................... 13
2.5 Field Strength dependence of the BOLD signal ................................... 14
2.6 Underlying neural basis and the time course of the BOLD response ........... 15
2.7 BOLD time course ..................................................................... 16
2.8 BOLD contrast in other Organs and Tissues ....................................... 17
2.9 BOLD contrast in Skeletal Muscle .................................................. 19
2.10 Skeletal muscle blood flow ......................................................... 32
2.11 Adaptations to the peripheral vasculature in response to regular exercise. . .44
References ................................................................................... 47

CHAPTER 3

BOLD MR1 MAPPING OF TRANSIENT HYPEREMIA IN SKELETAL MUSCLE

AFTER SINGLE CONTRACTIONS ............................................................ 59
3.1 Introduction ............................................................................. 59
3.2 Methods ................................................................................. 60
3.3 Results ................................................................................... 64
3.4 Discussion .............................................................................. 67
References ................................................................................... 85

CHAPTER 4

EFFECT OF PHYSICAL ACTIVITY ON MRI-MEASURED BLOOD OXYGEN
LEVEL-DEPENDENT TRANSIENTS IN SKELETAL MUSCLE AFTER BRIEF

CONTRACTIONS .................................................................................. 89
4.1 Introduction ............................................................................. 89
4.2 Methods ................................................................................. 91
4.3 Results ................................................................................... 96
4.4 Discussion .............................................................................. 98
References ................................................................................. l 13

vi

CHAPTER 5
DETERMINANTS OF THE POST-CONTRACTILE BOLD EFFECT IN SKELETAL

MUSCLE ............................................................................................ 116
5.1 Introduction ............................................................................ 116
5.2 Methods ................................................................................ 118
5.3 Results ................................................................................. 127
5.4 Discussion ............................................................................. 134
5.5 Appendix .............................................................................. 141
References ................................................................................. 1 66

CHAPTER 6

SUMMARY AND CONCLUSIONS ........................................................... 172

Images in this dissertation are presented in color.

vii

LIST OF TABLES

CHAPTER 3
Table 3.1: Time course of post-contraction transients measured by MRI and NIRS ...... 76

Table 3.2: The effects of repetition-time (TR) pulse sequence and force on MRI-measured

post-contractile BOLD transient peak magnitude, % change in signal intensity ........... 77
Table 3.3: The effect of magnetic ﬁeld strength on post-contractile transient peak
magnitude and R2* relaxation ..................................................................... 78
CHAPTER 4

Table 4.1: Subject physical characteristics ..................................................... 103

Table 4.2: Force and post-contraction BOLD transient contrasts (mean 1- SE) in the
muscles of the anterior compartment after l-second maximal isometric ankle

dorsiﬂexion ......................................................................................... 107
CHAPTER 5
Table 5.1: Subject characteristics ............................................................... 144

Table 5.2. Blood ﬂow in the anterior tibial artery, NIRS-estimated blood volume and
percent hemoglobin saturation in the ankle dorsiﬂexors at rest and peak after a l-second
maximal voluntary contraction .................................................................. 150

viii

LIST OF FIGURES

CHAPTER 3

Figure 3.1: Transient increases in MRI signal intensity (SI, percent baseline, top three
traces) at 1.5 T, NIRS-measured relative heme saturation (fourth trace, absorption at 760-
850 nm), and NIRS-measured relative heme content (ﬁfth trace, absorption at 760+850
nm) in anterior tibialis muscle of a subject (33 year old male) performing 1 second
contractions every 30 seconds ..................................................................... 74

Figure 3.2: Simulated extravascular (top panel) and intravascular (bottom panel) BOLD
effects for gradient-echo (solid lines) and spin-echo (dashed lines) acquisitions in skeletal
muscle, computed as described in methods assuming 3 % vascular volume and TE 45

ms ...................................................................................................... 80

Figure 3.3: Representative single voxel time course from anterior tibialis muscle (top)
and idealized waveform used for cross-correlation
(bottom) ............................................................................................... 82

Figure 3.4: Convention spin-echo (left, TR 500, TE 20) and corresponding echo-planar
images with functional overlay (right, GRE, TR 1000, TE 45) from a subject (21 year old
female) performing ankle plantarﬂexion (top), forearm handgrip (middle), and one-leg
knee extension (bottom) contractions, all 1 second duration at 30 second intervals ....... 84

CHAPTER 4

Figure 4.1: Representative anatomical (top: fast-spin-echo, T R/ T E=1500/24) and echo-
planar (bottom: T R/ T E=1000/40) images from an active (left) and sedentary (right)
subject ............................................................................................. 104

Figure 4.2: Representative time course of SI changes in anterior tibialis (top panels) and
posterior muscle (second panels) during single contraction protocol ..................... 106

Figure 4.3: Example magnitude images from the cardiac-gated phase-contrast ﬂow study,
illustrating location at which ﬂow measurements were made in popliteal (top) and tibial
(bottom) arteries before (left) and after repetitive exercise .................................. 108

Figure 4.4: Example cardiac-gated ﬂow waveforms from anterior tibial (top), posterior

tibial (middle), and popliteal (bottom) arteries before (open circles) and after (ﬁlled
circles) repetitive ankle dorsiﬂexion exercise ................................................. 110

ix

Figure 4.5: Mean ﬂow (:tSE) in anterior tibial (top), posterior tibial (middle), and
popliteal (bottom) arteries in active (ﬁlled circles) and sedentary (open circles) subjects

before and after 2 minutes of dynamic, repetitive ankle dorsiﬁexion exercise ............ 112
CHAPTER 5

Figure 5.1: Doppler ultrasound recording of blood velocity (cm/s) over ten cardiac cycles
as measured in the anterior tibial artery ......................................................... 145

Figure 5.2: Time course of ﬂow (mean d: SD) in anterior tibial artery before and after 1
second duration MVC contraction (from -1 to 0 sec) ......................................... 146

Figure 5.3: Relationship between peak increase in ﬂow above rest flow after contractions
vs. 7-day activity monitor counts ................................................................ 147

Figure 5.4: The relationship between fold increase in blood ﬂow and MRI BOLD
response resulting from a l-second maximal contraction of the ankle dorsiﬂexors ...... 148

Figure 5.5: Raw NIRS data (arbitrary units vs. sample pints) for three maximal
contractions separated by 80 seconds of rest ................................................... 149

Figure 5.6: Theoretical intravascular (top panel) and extravascular BOLD effects for
gradient-echo images at TE 35 ms over a range of blood volumes and saturations ...... 152

Figure 5.7: Blood ﬂow (top panel, ml/min/ 100 ml of muscle) blood volume (% change)
hemoglobin saturation (middle panel) and calculated and measured muscle BOLD
response to a l-second MVC of the ankle dorsiﬂexors ....................................... 154

Figure 5.8: Calculated (o) and measured (O) muscle BOLD response from three
individuals .......................................................................................... 156

Figure 5.9: Relationship between peak post-contractile BOLD effect calculated from
NIRS blood volume and saturation data vs. BOLD effect observed by MRI in the same
subjects .............................................................................................. 157

Figure 5.10: Means blood ﬂow (top panel, data linearly interpolated to 3 Hz sample
frequency), blood volume, % saturation (middle panel) and model calculated (a) and
measured (0) muscle BOLD (bottom panel) for 7 subjects for whom ultrasound, NIRS,
and MRI are all available ......................................................................... 159

Figure 5.11: Dynamic model of muscle blood flow, oxygenation, and MRI BOLD effect,
as described in the Appendix, predicts the magnitude and time-course of the muscle
BOLD response

well ................................................................................................... 161

Figure 5.12: Simulation of the relationship between the peak of the ﬁrst phase of the post-
contractile increase in blood ﬂow and the time-course of the muscle BOLD response..163

Figure 5.13: A two-pathway parallel Stella model developed to determine the relationship

between muscle blood ﬂow and the magnitude of the post-contractile muscle BOLD
response ............................................................................................. 165

xi

ABI

ATP
Bo
BMI

BOLD

Ca”
C02
EDHF
FiOz

fIVIRI

KEY TO SYMBOLS AND ABBREVIATIONS

ankle brachial index

adenosine diphosphate

adenosine triphosphate

the main magnetic ﬁeld

body mass index
blood-oxygenation-level-dependent
carbon-13

Calcium

carbon dioxide

endothelium derived hyperpolarizing factor
fraction of inspired oxygen

functional magnetic resonance imaging
gradient echo

hydrogen ion

Potassium

inward rectifying potassium channel
voltage gated potassium channel

local ﬁeld potentials

the net magnetization

magnetic resonance imaging

xii

MUA

NIRS
NMR
NO

02

3 l P
PCr
PET
Pi

P02
POAD

PVD

SE
SI
AS/N

SVR

T1
T2
TE

TR

multi unit activity

Sodium

near infrared spectroscopy
nuclear magnetic resonance imaging
nitric oxide

oxygen

phosphorus-3 1
phosphocreatine

positron emission tomography
inorganic phosphate

partial pressure of oxygen
peripheral occlusive artery disease
peripheral vascular disease
radio frequency

spin echo

signal intensity

contrast to noise ratio
systemic vascular resistance
tesla

longitudinal magnetization
transverse magnetization

echo time

repetition time

xiii

CHAPTER 1: INTRODUCTION

Magnetic resonance imaging (MRI) has long been regarded for its ability to
produce high-resolution anatomical images of living tissue. MRI can now be used to
assess the biological function of tissues and organs in real-time. Known as functional-
MRI (fMRI), this encompasses a variety of imaging techniques capable of measuring
physiological parameters including the direction and rate of water diffusion, tissue
perfusion and blood ﬂow. One of the most widely studied techniques in fMRI is blood-
oxygenation-level-dependent (BOLD) contrast. This phenomenon relies on the fact that
magnetic susceptibility of blood varies depending on its oxygen saturation (10) and
therefore changes in blood oxygenation are detectable using fMRI.

BOLD contrast in living tissue was ﬁrst described by Ogawa et a1. (8, 9) who
demonstrated an attenuation of the MRI signal by the paramagnetic effect of
deoxyhemoglobin (10). Paramagnetism is the property of being weakly attracted to
either pole of the magnetic ﬁeld, slightly increasing the strength of the local magnetic
ﬁeld and thereby altering the MRI detectable signal. Not long after his initial observation
Ogawa showed that the BOLD contrast was sensitive to changes in brain blood ﬂow and
metabolism resulting from insulin induced hypoglycemia and altered respiratory gases
including CO2 and anesthesia (8).

Today changes in brain activity can be detected in response to such simple tasks
as ﬁnger tapping and visual and auditory stimuli. The beneﬁts of BOLD imaging include
high temporal and spatial resolution and the fact that it is entirely non-invasive and

requires no exogenous contrast agents or ionizing radiation. For these reasons BOLD-

based imaging has become the technique of choice for mapping the location and extent of
neural activity in the brain. Although the BOLD contrast is correlated with brain neural
activity it is not a measure of neural activity per se. The contrast is due to a combination
of changes in both blood volume and blood oxygenation and is inﬂuenced by blood flow
and the vascular geometry. Given the underlying source(s) of the BOLD contrast it could
potentially be used to image any tissue or organ that is perfused with blood including the
heart, kidney, and skeletal muscle.

In skeletal muscle, the BOLD contrast has been detected during ischemia,
reactive hyperemia protocols (2, 5, 12), and following brief muscle contractions (3, 7,
14). More recently BOLD based imaging has been used to assess peripheral vascular
function of patients with peripheral occlusive artery disease (POAD) (6), and in
individuals with diabetes (1 l). The magnitude of the muscle BOLD contrast may vary
across different patient and subjects populations (l3, 14) however its physiological
relevance remains unclear. The relevance of the muscle BOLD will become more
evident when the relationship between the magnitude of the BOLD contrast and standard
measures of vascular function including blood ﬂow and blood volume are determined.

The focus of this dissertation project is to determine the physiological mechanism
of post-contractile BOLD contrast in human skeletal muscle. This brief introductory
chapter is followed by a review of the literature in Chapter 2. The literature review
provides a brief introduction to the biophysics of nuclear magnetic resonance imaging
(NMRI) as it relates to the BOLD contrast as well as a review of some of the ﬁrst as well
as most recent developments in BOLD imaging. The majority of the literature review

focuses on the muscle BOLD contrast. The ﬁnal sections of the literature review discuss

the regulation of skeletal muscle blood ﬂow with an emphasis on factors regulating the
blood ﬂow increase following a brief muscle contraction as well as the potential
inﬂuence of chronic physical activity on this phenomenon.

Chapters 3 through 5 are organized-according to the speciﬁc aims of this thesis, as
presented below, and each chapter contains an introduction, methods, results and
discussion section. The general aim of the three studies was to determine if the BOLD
contrast occurs in skeletal muscle and to what extent various physiological factors
including blood ﬂow, blood volume and hemoglobin saturation inﬂuence the magnitude
of the post-contractile BOLD contrast. More speciﬁcally, the study in Chapter 3 seeks to
determine if the transient change in signal intensity of MRI echo planar images following
brief muscle contractions is due to BOLD contrast. The ﬁndings in Chapter 3 conﬁrm
the existence of the post-contractile BOLD effect in skeletal muscle.

The purpose of the study described in Chapter 4 is to determine if chronic
physical activity inﬂuences the magnitude of the post-contractile BOLD contrast.
Chronic physical activity has been shown to result in adaptations to the cardiovascular
system including increased peripheral arteriolar dilatation, and increased vascular
volume. Based on previously published biophysical models (1, 4) of the BOLD contrast
these adaptations may result in a larger post-contractile muscle BOLD contrast. The
ﬁndings from the study presented in Chapter 4 show that habitually active individuals
have larger post-contractile muscle BOLD contrast than healthy sedentary individuals.

The studies presented in Chapter 5 seek to characterize the ﬂow response to single
brief muscle contractions in individuals of varying physical activity levels and to

determine the relationship, if any, between the magnitude of the post-contractile ﬂow

response and physical activity. An additional purpose of the study was to determine if
the time course of the muscle BOLD response could be explained by the magnitude and
time course of the changes in blood volume and hemoglobin saturation measured in the
same individuals by NIRS. Finally, the study in Chapter 5 sought to determine if a -
simple physiological model of blood ﬂow and oxygen consumption both as estimated in
the model could together explain the observed blood volume and hemoglobin saturation
changes, and hence the post-contractile BOLD response. The results presented in Chapter
5 show that the magnitude of the post-contractile blood ﬂow response is inﬂuenced by
physical activity. The result also show that the magnitude and time course of the muscle
BOLD response can, in large part, be determined by the time course of measured changes
in blood volume and saturation. Furthermore a simple model of blood ﬂow and an
estimate of the post-contraction oxygen consumption can together explain the blood
volume and saturation changes, and hence the post-contractile BOLD response.
Concluding this thesis is Chapter 6, which presents a list of the major hypotheses
tested and the experimental results obtained in each study. The limitations of this research
as well as the positive outcomes are discussed. This Chapter concludes with suggestions

for future studies

10.,

ll.

12.

References

Buxton RB, Uludaaeg K, Dubowitz DJ, Liu TT. Modeling the hemodynamic
response to brain activation. NeuroImage 23 Suppl 1, 2004.

Donahue KM, Van Kylen J, Guven S, EI-Bershawi A, Luh WM, Bandettini
PA, Cox RW, Hyde JS, Kissebah AH. Simultaneous gradient-echo/spin-echo EPI
of graded ischemia in human skeletal muscle. J Magn Reson Imaging 8(5): 1 106-
1113, 1998.

Hennig J SK, Schreiber A. Time resolved observations of BOLD effect in muscle
during isometric exercise. Proc’Int Soc Magn Reson Med 8: 1, 2000.

Kennan RP, Zhong J, Gore J C. Intravascular susceptibility contrast mechanisms
in tissues. Magn Reson Med 31(1): 9-21, 1994.

Lebon V, BriIIauIt-Salvat C, Bloch G, Leroy-Willig A, Carlier PG. Evidence of
muscle BOLD effect revealed by simultaneous interleaved gradient-echo NMRI and
myoglobin NMRS during leg ischemia. Magn Reson Med 40: 551-558, 1998.

Ledermann HP, Schulte AC, Heidecker HG, Aschwanden M, Jeager KA,
Schefﬂer K, Steinbrich W, Bilecen D. Blood oxygenation level-dependent
magnetic resonance imaging of the skeletal muscle in patients with peripheral
arterial occlusive disease. Circulation 113(25): 2929-2935, 2006.

Meyer RA , Reid RW, Prior B. BOLD MRI and NIRS detection of transient
hyperemia after single skeletal muscle contractions. Proc Int Soc Mag Reson Med
9, 2001.

Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with
contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A 87: 9868-9872,
1990.

Ogawa S, Lee TM, Nayak AS, Glynn P. Oxygenation-sensitive contrast in
magnetic resonance image of rodent brain at high magnetic ﬁelds. Magn Reson Med
14: 68-78, 1990.

Pauling L, Coryell CD. The Magnetic Properties and Structure of the
Hemochromogens and Related Substances. Proc Natl Acad Sci U S A 22(3): 159-
163, 1936.

Slade JM, Gossain VV, DeLano MC, and Meyer RA. Cross-sectional study of
muscle post-contractile BOLD transients in Type I and Type II diabetes. Workshop
on Investigation of Human Muscle Function In Vivo, Nashville, TN, 2005.

Toussaint JF, Kwong KK, Mkparu F0, Weisskoff RM, LaRaia PJ, Kantor

l3.

l4.

HL. Perfusion changes in human skeletal muscle during reactive hyperemia
measured by echo-planar imaging. Magn Reson Med 35(1): 62-69, 1996.

Towse TF, Slade JM, Meyer RA. MRI-measured BOLD transients in skeletal
muscle after brief contractions in healthy elderly subjects. APS Intergrative Bilogy
of exercise Meeting Indianpolis, IN, 2006.

Towse TF, Slade JM, Meyer RA. Effect of physical activity on MRI-measured
blood oxygen level-dependent transients in skeletal muscle after brief contractions.
JAppl Physio] 99(2): 715-722, 2005.

CHAPTER 2: LITERATURE REVIEW

Magnetic resonance imaging (MRI) has quickly become an indispensable, non-
invasive tool in the clinical practice of medicine as well as in biomedical research. The
ﬁrst MRI was generated by Paul Lauterbur in the 1973. By extending then current one-
dimensional MR techniques to two-and three-dimensions Dr. Lauterbur produced a low
resolution image of two water-ﬁlled test tubes (65). The ability to generate multi-
dimensional images greatly expanded the utility of MR in ﬁelds such as medicine and the
basic and applied sciences. The potential for MRI was quickly recognized and by 1977,
Dr. Raymond Damadain had constructed the ﬁrst whole-body human scanner. Years
earlier Dr. Damadain had discovered that MR could distinguish healthy tissue samples
from tumors and he constructed the scanner for the purpose of detecting tumors, non-
invasively. Although MRI has not become the deﬁnitive tool for detecting tumors it is an
integral part of the practice of present day medicine. Today high-resolution images (<
50 um in-plane resolution) are routinely acquired and have broad clinical applications,
including diagnosis of soft-tissue pathologies, strokes and diverse chronic diseases such

as peripheral vascular disease and multiple sclerosis (30, 34, 57).

2.1 The-Biophysics of Magnetic Resonance Imaging

Nuclear magnetic resonance images (MRI) are constructed from signals derived
from the nuclei of various molecules. The term nuclear magnetic resonance (NMR)
describes the phenomenon that some nuclei possess when placed in an external magnetic

ﬁeld. Nuclei with an either an odd number of neutrons or protons exhibit nuclear

magnetic resonance, including '3 C and 3 IP. Although a variety of nuclei are visible to
MRI the majority of MRI studies use the hydrogen ion (1H, protons) because it is by far
the most abundant nucleus in human tissue.

When placed in an external magnetic ﬁeld the protons act like tiny bar magnets
and align either with or against the magnetic ﬁeld. When the protons are aligned with the
magnetic ﬁeld they are in their low energy-state and when aligned anti-parallel to the
magnetic ﬁeld they are in their high energy-state. Under equilibrium conditions there are
slightly more protons aligned with the magnetic ﬁeld in the low energy-state and the
vector sum of the protons is sufﬁcient to provide an equilibrium net magnetization (M0),
along the main magnetic ﬁeld (Bo).

The protons within the hydrogen nuclei are positively charged and this spinning
charge is effectively a circulating electronic current and as such possesses a magnetic
moment. Along with a magnetic moment protons possess a property called “resonance”
and resonance comes from the fact that when a particle with intrinsic angular momentum
is placed in a strong magnetic ﬁeld the angular momentum of the particle interacts with
the external magnetic ﬁeld. The proton will experience a torque that will tend to align it
along the axis of the magnetic ﬁeld. Because the protons have an angular moment the
vector or axis of the proton will not align directly parallel to the ﬁeld but will precess
about the axis of the ﬁeld in manor similar to a spinning top or gyroscope in the presence
of earth’s gravitational ﬁeld. The rate at which the proton precesses is unique frequency
that is dependent on the particular nuclei and the strength of the magnetic ﬁeld this is

called its “resonance” frequency or the Larmor frequency.

Protons do not align with the magnetic ﬁeld but precess about the ﬁeld therefore
the net magnetization has two components, a longitudinal and a transverse component.
The longitudinal component is deﬁned by the projection along the main ﬁeld B0 and the
transverse component is that which is precessing at right angles to the main ﬁeld. As
mentioned earlier there are slightly more protons aligned parallel to B0 than anti-parallel
and this creates a small, none zero, net magnetization along B0. However under
equilibrium conditions the transverse component is zero because the protons are
precessing out of phase and the net sum of the vectors is zero. The longitudinal and
transverse magnetization can however be manipulated in a manner to provide a MR
detectable signal.

Protons can be stimulated or “excited” to transition from the low energy-state to
their high energy-state with a pulse of radio frequency (RF pulse) energy at the protons
speciﬁc (resonance) frequency. A small fraction of the protons will absorb the energy
from the RF pulse, which is just enough to tip the net magnetization away from B0, The
RF pulse will also cause the protons to oscillate in synchrony (phase—coherent oscillation)
about an axis that is determined by the energy in the RF pulse. A 90° RF pulse will tip
the net magnetization to a 90° angle relative to Bo. Once the RF pulse is turned off the
protons return or “relax” back to their equilibrium condition and this process is described
by two time constants, T I and T2. T I is the time constant for the exponential return of the
longitudinal magnetization and T2 is the time constant that describes the exponential
decay of the transverse magnetization over time.

T r varies between and across tissues and can be used as a contrast to measure

blood ﬂow. Images acquired to accentuate the T. contrast are called Tl-weighted images

and usually have a repetition time of 500 —1500 ms. The TI contrast from a tissue is
dependent on proton density of the tissue and the chemical and physical environment in
which they reside. In living tissue, the majority of hydrogen nuclei are in fat and water
molecules.

Transverse or “T2” relaxation refers to the loss of transverse magnetization by loss
of phase coherence. The loss of phase coherence is due to molecular interaction by
neighboring spins (true T2) and by inhomogeneities in the magnetic ﬁeld (T 2*). Images
acquired using a spin-echo pulse sequence are T 2-weighted, because the 180 degree pulse
refocuses any loss of phase coherence due to inhomgeneities. Images acquired with a GE
sequence are T 2*-wei ghted and include signal decay due to molecular interaction and
ﬁeld inhomogeneities.

The rate of T 2 relaxation (l/T2) will vary depending on the composition and
metabolic state of the tissue. Differences in the rate of T 2 relaxation both between and
within tissues, and following an intervention, i.e., exercise can be used to generate
contrast in tissue. In addition acquisition parameters can be carefully chosen to highlight
contrast in tissue due to differences in fat content, water volume, blood volume or blood
oxygenation. T2 and T 2*-weighted images are the backbone of the blood oxygenation

level-dependent (BOLD) contrast.

2.2 BOLD imaging in the Brain

The body of literature on the brain BOLD effect is tremendous and a number of
excellent reviews are available (10, 17, 71, 93), therefore this section will only brieﬂy

review some concepts of the brain BOLD relevant to the muscle BOLD response.

10

The magnetic susceptibility of hemoglobin was ﬁrst reported by Pauling in 1936
(97). The oxygen saturation of hemoglobin effects the magnetic susceptibility of
hemoglobin such that deoxyhemoglobin is paramagnetic and oxyhemoglobin is
diamagnetic. Therefore a decrease in the ratio of deoxyhemoglobin:oxyhemoglobin
results in a decrease in paramagnetic and a increase in diamagnetic material resulting in a
more homogeneous magnetic ﬁeld and a slower rate of T2 decay. It is these changes in
deoxyhemoglobin and oxyhemoglobin that generate the contrast in MRI images by
slowing the rate of T2 relaxation (l/ T 2). MRI techniques sensitive to changes in blood
volume and tissue oxygenation are the basis of MR functional imaging.

The BOLD contrast in living tissue was ﬁrst described by Ogawa et al., (91, 92)
who demonstrated an attenuation of the MRI signal by the paramagnetic effect of
deoxyhemoglobin. When the oxygen content of the inspired gas was reduced to 20% 02
dark lines developed around the boundary regions of the brain and near organizational
elements. Optical microscopy conﬁrmed that these regions were rich in vascular supply.
The contrast was reversed when the inspired air was switched to 100 % oxygen.

To conﬁrm that the changes in the rodent brain images were due to changes in
the oxygenation status of the blood Ogawa acquired images of glass capillary tubes
containing either oxygenated or deoxygenated blood. The tubes were placed in a saline
solution either perpendicular or parallel to the main ﬁeld. The images of the tubes ﬁlled
with deoxygenated blood placed perpendicular to the ﬁeld showed dramatic signal
dropout that extended far beyond the tube wall. The tubes ﬁlled with oxygenated blood
showed little signal in the center, however the area surrounding the tube appeared

unaffected. The effect of the deoxygenated blood was less when acquired using the spin-

ll

echo (SE) versus the gradient-echo (GE) images and there was little if any external effect
when the vessel was positioned parallel to the ﬁeld. The difference between the GE and
SE suggest the contrast is due to magnetic susceptibility differences between the blood
and water which are reversed following the 180° refocusing pulse in the SE sequence.
The ﬁndings of Ogawa’s early study are still relevant and suggest the BOLD
effect has both intra and extravascular components (in this case within and outside of the
capillary tube) and the magnitude of the extravascular effect is dependent on the angle of
the vessel relative to the main magnetic ﬁeld. These ﬁndings were supported by image
simulations from the same group (91), and simulations suggest that the changes in SI are

largest following large changes in saturation is greatest in larger vessels.

2.3 Intravascular and Extravascular contributions to the BOLD effect

The susceptibility-induced changes in T2 signal decay due to changes in
deoxyhemoglobin content and blood volume extends beyond the blood vessels. As such
the BOLD contrast is a combination of signal changes that occur within (intravascular)
and external (extravascular effects) to the blood vessels (10, 49, 58). Although the blood
volume fraction in the brain is relatively small, only about ~4%, the intravascular BOLD
effect contribute roughly 50% to the total brain BOLD effect at 1.5 T (10, 16) The
intravascular susceptibility is dependent on the relative concentrations of
deoxyhemoglobin and oxyhemoglobin within the vessel. In fact it has been shown that
there is a quadratic relationship between blood oxygenation and transverse relaxation

rates of blood (122, I42).

12

The extravascular effects are slightly more complicated but in their simplest form
can be represented as a blood vessel, described as a long cylinder placed in a magnetic
ﬁeld, where the tissue or space around the vessel has a different magnetic susceptibility.
The magnetic susceptibility difference between the vessel and the surrounding tissue is
proportional to the fraction oxygen saturation of the blood within the vessel. When the
vessel is positioned parallel to the main magnetic ﬁeld the susceptibility difference is
simply the difference between the blood within the vessels and that of the surrounding
tissue (10, 92). However when the vessel is positioned perpendicular to the ﬁeld, the ﬁeld
perturbations extend beyond the vessel into the adjacent tissue (92). The magnitude of the
extravascular BOLD effect is inﬂuenced by vessel size (16, 58), vascular density, the rate

of water diffusion (58) and by data acquisition parameters (58, 90, 92).

2.4 Influence of different vascular compartments

The BOLD contrast occurs due to changes in oxygenation and blood volume
occurring largely in the capillary and venous vasculature (16). As mentioned above, the
intravascular BOLD effect is simply a function of the relative concentration of
deoxyhemoglobin and oxyhemoglobin in the blood. Assuming the relative saturation of
blood in the capillary is the mean saturation of arterial and venous blood and that the
post-capillary venule and veins have the lowest saturation, the venous end of the
circulation would make the greatest contribution to the intravascular BOLD contrast. The
BOLD signal changes are thought to come largely from the venous vasculature because

this is the site of the largest changes in both saturation and blood volume (20). The

13

venules and veins also make a greater contribution to the BOLD contrast through the
extravascular BOLD effect.

The extravascular BOLD effect depends in part on the rate of spin diffusion
around the vessel. If the diffusion distance of a spin is large relative to the size of the
vessel the distribution of the ﬁeld offset that the extravascular spin experiences will be
large and the phase dispersion will be reduced by diffusional averaging (10, 16).
Therefore capillaries and post-capillary venules will make only a small contribution to

the extravascular BOLD effect relative to the veins.

2.5 Field Strength dependence of the BOLD signal

The magnitude of the BOLD contrast is ﬁeld strength dependent and this effect
has been shown in isolated blood sample (122) as well as in vivo studies of brain (29, 38,
90) and skeletal muscle (82). The ﬁeld dependence is largely due to the increase in bulk
magnetic susceptibility differences between blood deoxyhemoglobin and the relatively
diamagnetic tissue parenchyma; Gati et al., showed that A 1/ T 2* increased in a nearly
linear manner over a ﬁeld strength range of 0.5 - 4T (38). When the contrast-to-noise
ratio (AS/N) was partitioned into tissue and vessels the ﬁeld strength dependence was
greater than linear for the tissue but less than linear for the vessels. In support of these
ﬁndings Okada et al., found that the AS/N was 2.3 times higher at 3 vs. 1.5 T (94). This
relationship between AS/N and ﬁeld strength is a primary reason higher and higher ﬁeld

strengths are used in MRI related clinical and biomedical research.

14

2.6 Underlying neural basis and the time course of the BOLD response.

The brain BOLD response has allowed researchers to evaluate the neural
processing of the brain in a manor previously unheard of. Although this technique is
widely used and already has clinical application the phenomenon and its underlying
physiological signals are poorly understood. For example although the brain BOLD
response is accepted as an indirect measure of brain neural activity the question remains,
what type of activity? Recently Logothetis et al., showed that local ﬁeld potentials
(LFPs), which represent neural input and integration, were more closely correlated to the
BOLD response than multi unit activity (MUA), a measure of neural output (70). Also
given the increase in blood ﬂow that accompanies the neural activity there has to be a
coupling between the neural activity and the increase in blood ﬂow, although the exact
vasodilator is unknown. There is some evidence for K+ as the key vasodilator, although
NO has also been implicated (16). Finally, what is the reason for the increased oxygen
consumption that accompanies neural activity and what can this tell us about brain
metabolism? Some suggest the increase in oxygen consumption largely reﬂects increased
activity of the Na+-K+ pump, which is necessary to restore the ion gradients following
activation, while there is convincing evidence that the increased oxygen cost is related for
neurotransmitter recycling (16). Although there is still many questions to be answered
regarding the underlying physiological basis for the BOLD contrast it offers the best

means for studying brain neuro-physiology non-invasively.

15

2.7 BOLD time course

The time course of the brain BOLD may reﬂect a delicate balance of oxygen
delivery vs. oxygen demand such that the large ﬂow response resulting from neural
activity is necessary to maintain the driving pressure for oxygen across the cell (20). The
pattern of the BOLD time course largely depends on the duration of the stimulus. In
response to long duration stimulus the BOLD contrast occurs following a short delay and
increases to a plateau within 6-8 see. In response to a brief stimulus ~ 6 see, there is an
initial early dip ~ 23cc in the BOLD contrast followed by a peak at 6-8 see and a post-
stimulus undershoot occurring at ~ 40 sec (15, 19, 20, 55). In general this time course is
well accepted however the early dip is not always seen (15, 55, 69). The early dip, when
seen, is credited with a rapid increase in oxygen consumption that occurs before the large
ﬂow increase. Evidence in support of this is an early rise in deoxyhemoglobin content
that peaks at ~ 2 sec (15).

The large increase in the BOLD is clearly related to a decrease in
deoxyhemoglobin and the post-stimulus undershoot is correlated with both a secondary
rise in blood volume and a rise in deoxyhemoglobin. The time course of the BOLD
response may represent a dynamic interaction between blood ﬂow and oxygen
consumption. The early dip, if present, may indicate a rapid increase in oxygen
consumption prior to the large ﬂow increase while the large decrease in
deoxyhemoglobin is due to the relatively large ﬂow response. It is interesting that the
pattern of brain BOLD to a brief stimulus (15, 18, 20) is so similar to the BOLD response

to a brief muscle contraction (see Chapters 3-5). The similarity suggests common

16

mechanisms in both the coupling of tissue metabolic activity to blood ﬂow (K+ or NO),

and in the regulation of oxygen consumption.

2.8 BOLD contrast in other Organs and Tissues

Although most widely used in the ﬁeld of ﬁmctional neuroscience, BOLD
contrast has also been used to assess the functional status of the heart, kidneys, and the
lungs. Recently BOLD contrast was successfully used to differentiate viable (ischemic or
hibernating) cardiac tissue ﬁ'om scarred cardiac tissue, an important delineation in the
diagnosis and treatment of heart disease (31). BOLD based imaging is also capable of
differentiating ischemic from non-ischemic cardiac tissue in healthy individuals and in
patients with clinical coronary artery disease (31). In the above study the ﬁndings were
conﬁrmed using positron emission tomography (PET), a more invasive clinical
technique. One advantage BOLD MR imaging offers over PET is that it does not expose
patients to ionizing radiation or contrast agents.

BOLD contrast has also been successfully used to detect kidney hypoxia
resulting from renal stenosis (57), and can detect changes in the oxygenation status of
fetal kidneys, liver and the lungs (134). Hypoxia in many tissues is an indication of
compromised function. In tumors it is a strong predictor of resistance to radiation
therapy (7). BOLD contrast was used to detect changes oxygenation in murine tumors in
response to altered respiratory oxygen (4) They concluded the BOLD contrast was
sensitive to changes in tumor oxygenation and that its non-invasive nature makes it an

attractive tool for predicting the resistance of tumors to common therapeutic

17

interventions. The above studies are merely examples of the many potential applications
of BOLD based imaging in the ﬁeld of biomedical imaging.

Chronic diseases such as hypertension, diabetes, and peripheral vascular disease
(PVD) have as a common component impaired microvasculature function. A decline in
peripheral vasculature function is a strong predictor of all cause morbidity and mortality.
For example, PVD is considered a marker of systemic atherosclerosis, and even in its
asymptomatic form predicts future cardiovascular events (75). Determining the ratio of
blood pressure in the brachial artery to the ankle blood pressure, termed the ankle
brachial index (ABI) is a common means for diagnosis PVD. Although test is simple and
cost effective the sensitivity of ABI to predict future cardiovascular events is not high
(76). Furthermore microvasculature dysfunction is thought to occur early in the
pathogenesis of many chronic diseases such as diabetes (106). For this reason a tool that
can detect changes in the microvasculature early in the time-course of the disease process
would prove useful not only from the standpoint of diagnosis but also in determining the
efﬁcacy of treatment. Due to its sensitivity to blood volume and oxygenation and the fact
that the signal changes are localized to the microvasculature, BOLD contrast in skeletal

muscle may aid in the diagnosis and treatment of peripheral vascular disorders.

18

2.9 BOLD contrast in Skeletal Muscle
2.9.1 Ischemia and Reactive Hyperemia

Early attempts at detecting a BOLD contrast in skeletal muscle were ambiguous,
with some researchers detecting BOLD-like changes (28, 66, 67), while others did not
(40). Typically these studies employed a cuff-induced ischemia-reactive hyperemia
protocol, which afforded large changes in both blood ﬂow and tissue oxygenation. Using
a T2*-weighted pulse sequence Toussaint et al., detected a signiﬁcant increase in muscle
T 2*during reactive hyperemia (123). The pattern and time course of T 2* changes were
consistent with the well-established changes in blood ﬂow and deoxyhemoglobin in this
protocol. In addition, AR2 [A( 1/ T 2)] with ischemia and reactive hyperemia was
signiﬁcantly correlated with an MRI-adapted plethysmography technique, a measure of
muscle perfusion. Although the changes in T 2*-weighted images were consistent with
changes in blood ﬂow and deoxyhemoglobin, neither were directly measured, and the
association between T 2* and hemodynamic changes were inferred from previous studies.

Tissue oxygenation, by way of near infrared spectroscopy (NIRS), BOLD contrast
( T 2*-weighted), and muscle metabolites (3 lP MR spectroscopy) were measured by Hajnal
et al., in a set of parallel studies also using a cuff-induced ischemia-reactive hyperemia
protocol (40). The 90-minute protocol required 30 minutes each of rest, ischemia and
reactive hyperemia/recovery. The protocol was repeated on three separate occasions to
measure tissue oxygenation, BOLD contrast or energetics. Unfortunately, interpreting
the ﬁndings of this study is challenging due to a very small sample size (n = 2). Of the
two subjects tested, one subject had a decrease in T 2* during ischemia and an increase in

T 2* with reactive hyperemia, while in the other subject (subject A) T 2* did not decrease

l9

with ischemia, although there was an increase in the T 2* during reactive hyperemia.
During ischemia both subjects showed the expected increase in deoxyhemoglobin.
However, subject A had an increase in total hemoglobin during the ischemia, suggesting
blood ﬂow in this subject was not fully occluded. As the same experimental protocol was
used in all conditions we would expect blood ﬂow was not fully occluded during the MR
portions of subject A’s data collection, which would explain no change in T 2* during
ischemia in this subject. Although providing some evidence for a BOLD-like contrast in
skeletal muscle, neither of these studies measured the BOLD contrast and oxygenation
simultaneously.

Of the early studies, Lebon et al., provided the most convincing evidence for a
BOLD contrast in skeletal muscle (66). Using an interleaved protocol they
simultaneously measured BOLD contrast by MRI and tissue oxygenation by myoglobin
MRS.(66). The authors found excellent agreement between the changes in T 2* and tissue
oxygenation. They attributed the changes in the T 2*-weighted images to the BOLD
contrast based on four lines of evidence: its temporal relationship to myoglobin
desaturation, excellent agreement with a physiological model, the ﬁeld dependence of the
changes and the agreement with results from parallel NIRS studies.

Consistent with these ﬁndings Donahue et al., showed that the changes in
transverse relaxation rates (A 21/ T 2 and A 1/ T2*) were proportional to the duration of a
graded ischemia. Interleaved spin-echo (SE) and gradient-echo (GE) echo-planar images
were acquired continuously over a stepwise cuff occlusion protocol. The changes in
AND and Al/ T 2* occurred in a stepwise fashion proportional to the duration of cuff

ischemia. The authors suggested that A 1/ T2 and Al/ T 2* measures might be used as a

20

measure of microvascular perfusion and due to the differential sensitivity of SE and GE
to vessel size it may provide information regarding the distribution of vessels within the
microvasculature (3). This suggestion arises from both theoretical and empirical
evidence that Al/ T 2* is sensitive to. all sizes of vessels while A l/ T 2 is primarily sensitive
to capillary-sized vessels (58). Therefore measures of Al/ T 2*, Al/ T 2 and the ratio Al/ T 2*
/ A 1/ T 2 acquired during the interleaved protocol may provide more information about the
structure and function of the vasculature than standard imaging protocols.

In the above study the magnitude of the BOLD contrast varied across muscle
groups, such that the changes were larger in the soleus versus the gastrocnemius muscle.
The authors suggested these differences were due to differences in vascular volume
secondary to the differences in muscle ﬁber type. Taken collectively the above studies
provide convincing evidence that a BOLD contrast exists in skeletal muscle during an
ischemia-reactive hyperemia protocol. The beneﬁts of this type of protocol are the fairly
large changes in SI in both T2 and T 2*-weighted images on the order of 2-6% during
ischemia and 6- 10% during reactive hyperemia. However, although these changes are
relatively large the protocol is rather uncomfortable and not well tolerated by all subjects.
Furthermore, although the changes in BOLD based images are large due to the large
changes in blood ﬂow and oxygenation in this protocol, to date, they provides little in the

way of relevant diagnostic information about the health of the peripheral vasculature.

21

2.9.2 Post-Contractile BOLD contrast

With dynamic high-intensity exercise skeletal muscle blood ﬂow can increase
from 5-10 ml'min"‘100 g'l oftissue at rest to 150 — 500 ml'min'l‘IOO g'l(18). The
increase in blood ﬂow is also accompanied by an increase in oxygen extraction such that
the venous hemoglobin saturation and P02 decreases relative to resting condition (3).
Although any decrease in hemoglobin saturation would likely result in a negative BOLD
effect, this is offset by a much larger increase in muscle cell T2 resulting from osmotically
driven shifts in water volume (25, 26). The osmotically driven change in muscle cell T2
is mechanistically different from the T2 change resulting ﬁom the BOLD contrast and has
largely been used to map the location and extent of muscle activation after repetitive
exercises (80, 81, 95). However, in some cases such as a single, brief muscle contraction
there is a large increase in blood ﬂow with a relatively small metabolic load placed on the
muscle. The large increase in blood ﬂow, coupled with a smaller increase in oxygen
extraction would result in a relative increase in venous hemoglobin saturation and venous
P02. This transient increase in venous hemoglobin saturation and decrease in the ratio of
deoxyhemoglobin to oxyhemoglobin could potentially be used as an image contrast using
BOLD sensitive imaging (10, 23).

Hennig et al., ﬁrst reported BOLD-like transient changes in skeletal muscle
transverse relaxation (T 2*) in response to single brief muscle contractions (47). These
changes were localized to the muscle exercised and the time-course was similar to the
BOLD contrast in the brain. The authors suggested the increase in SI of T 2*-weighted
images was due to a BOLD-like contrast resulting from the increase in blood ﬂow and

oxygenation following the contraction. This study was preliminary in nature and other

22

than using T 2*-weighted images, no effort was made to conﬁrm that the contrast was
blood oxygenation level-dependent.

Meyer et al., conﬁrmed that the transient changes in skeletal muscle T 2*-weighted
images following single, brief muscle contractions arise from the BOLD contrast ((79,
82), see chapter 3 for more details). The pattern and time-course of the changes in MRI
measured SI and the NIRS-measured increase in relative hemoglobin saturation suggests
they both arise from exercise hyperemia following the muscle contraction (2, 27).
Consistent with the BOLD mechanism, the magnitude of the changes in SI were ﬁeld
strength dependent, being larger at higher ﬁeld strengths (29, 68, 117). In addition the
authors used a biophysical model to predict the contribution from extravascular and
intravascular sources and determined the majority of the contrast was from intravascular
changes in hemoglobin saturation (82). An interesting ﬁnding from this study was the
large between subject variability 1.1 —- 6.5% peak changes from baseline (SEM of 87%).
Because the changes are primarily intravascular in nature, resulting largely from a
contraction induced vasodilation, it was suggested that BOLD contrast in. skeletal muscle

may be an index of microvascular function (3, 19, 37).

2.9.3 BOLD Contrast.with Hyperoxia

The changes in BOLD contrast in skeletal muscle, or in other tissues and organs
for that matter, are relatively small, on the order of 1-5% (20, 45, 82, 134). Therefore
researchers have attempted to maximize the contrast by either increasing the
hemodynamic response, by increasing the intensity of the exercise (88, 133) or increasing

the fraction of inspired oxygen, or both (133). Although increasing exercise intensity

23

will result in a larger increase in blood ﬂow, and blood volume (25, 26, 42-44) oxygen
consumption will also increase and the more metabolically demanding protocol will
likely result in a osmotically driven increase in muscle cell T2 that would mask the BOLD
contrast. For this reason some researchers have used respiratory hyperoxia in an effort to
increase the contrast in BOLD based imaging.

Respiratory hyperoxia has been shown to increase arterial and venous hemoglobin
saturation and the amount of oxygen dissolved in the plasma (1, 61, 112, 135).
Increasing hemoglobin saturation would result in a reduced concentration of
paramagnetic deoxyhemoglobin, and with all other things being equal, would increase the
BOLD contrast. However, arterial hemoglobin saturation is already near 100% (~ 97%) -
under normobaric, normoxic conditions - therefore any reduction in paramagnetic
deoxyhemoglobin would be small (6, 72, 103, 112). Although it’s possible to increase
the partial pressure of oxygen in the plasma to as high as 400-670 mmHg, due to the poor
solubility of oxygen, the amount of oxygen dissolved in the plasma is small, only 0.3 ml
of 02 per 100 m1 of blood. In comparison when hemoglobin is fully saturated with
oxygen it carries about 20 ml of 02 per 100 ml of blood, afﬁrmation of hemoglobin’s
important role as a oxygen transporter in the blood (72, 78). Additionally, were it
possible to increase the amount of dissolved oxygen in the blood sufﬁciently to alter the
MR signal it might actually decrease the signal intensity, not increase it, because
molecular oxygen is paramagnetic. Despite these limitations, many have used respiratory
hyperoxia as a contrast agent with some interesting, yet variable results.

Respiratory hyperoxia, fraction of inspired oxygen = 100% (FiO2 = 100%), has

been shown to decrease the T2 of many tissues and organs including the spleen, arterial

24

blood, and the heart (119). However, in a study by Tadamura et al., respiratory
hyperoxia had no effect on the tissue T2 relaxation times of cardiac muscle or skeletal
muscle. In contrast others have shown that cycles of respiratory hyperoxia (F.02 =
100%) resulted in a signiﬁcant increase in the T2 of skeletal muscle (89). In this study
by Noseworthy eta1., changes in T2 relaxation times were measured in arterial and
venous blood as well as in the muscles of the leg. Using a multi-echo pulse sequence and
bi-exponential ﬁts of the T2 decay they derived two components of T2 decay, one
corresponding to the extravascular space, the short T2 (T 2S), and one corresponding to the
blood, a slower relaxing, long T2 component (T 2L). There was no change in T 2S with
hyperoxia. However, there was a signiﬁcant increase in the T 2L in the veins, the muscles
of the thigh (adductor magnus) and the soleus. The authors suggested the change in the
blood component (T 2L) reﬂects changes in oxygenation in the microcirculation and that
respiratory hyperoxia may be used to determine the degree of hypoxia in patients with
peripheral vascular disease. Although these ﬁndings seem at odds with previous reports
(119), the difference is likely due to their use of a multi-echo pulse sequence to quantify
the T2 decay process as a bi-exponential process versus a more conventional mono-
exponential. Using a typical single echo pulse sequence (TE < 50 ms) and a mono-
exponential ﬁt they would not have detected a change in T 2.

In a subsequent study, Noseworthy et al., found that when respiratory hyperoxia
was coupled with exercise (200 one-legged calf raises) there was a signiﬁcant increase in
the area under the impulse response function (area under the curve of signal intensity
versus time). They also found that the respiratory hyperoxia and exercise induced BOLD

contrast was larger in the soleus compared to the gastrocnemius (17). The authors

25

concluded the difference across muscle groups was due to differences in muscle ﬁber
types in these muscles, and that BOLD-based imaging may be used as a non-invasive
technique to determine muscle ﬁber type. However it is unlikely the difference in BOLD
contrast between the muscle groups is due to differences in muscle ﬁber types because
human skeletal muscle is a mixture of different ﬁber types not exclusively one type of
ﬁber (39, 48, 53). In fact the soleus and gastrocnemius are not all that different with 63%
and 46% slow ﬁbers respectively, and the remainder equally proportioned between fast-
oxidative and fast-glycolytic ﬁbers (39). Furthermore, the metabolic enzyme proﬁles,
and the energy demands of the contractions, reﬂected by the myoﬁbular ATPase activity,
are essentially the same (39). However, one difference between the soleus and
gastrocnemius that may explain the differences in BOLD contrast is their muscle ﬁber
pennation angle.

In the muscles of the lower leg the pennation angle of the muscle ﬁbers varies by
as much as 35° with the average pennation angle for the tibialis anterior, gastrocnemius
and soleus being 10, 26, 46° respectively (42). Because blood vessels within skeletal
muscle are predominately arraigned parallel to the axis of the muscle ﬁbers, which form
regular linear arrays (61, 110), the orientation of the muscle ﬁbers will largely determine
the orientation of the blood vessels within a voxel and relative to the main ﬁeld. Recall
that the magnitude of the extravascular BOLD contrast is determined in part by the angle
of the blood vessels relative to the main magnetic ﬁeld such, that a larger angle creates a
greater extravascular BOLD contrast. In the case of the muscles in the lower leg the
extravascular BOLD contrast and, with all other sources being equal, the total BOLD

contrast, would differ across these muscle groups solely because of the muscle

26

architecture (pennation angle) not ﬁber type, oxidative capacity nor microvascular
density. This complication aside, this study provided evidence that respiratory hyperoxia
may be effective at increase in contrast in BOLD-based images.

Muscle T2 has also been shown to either decrease (133), or not change (133) when
respiratory hyperoxia is combined with exercise. And these changes depend on the .
fraction of inspired oxygen and the exercise duration and intensity. In this study the
largest reduction in T2 occurred with 60% inspired 02 at an exercise duration of 60
seconds or less, at an intensity corresponding to 60% of maximal voluntary contraction
(MVC). It seems likely the higher intensity, longer duration exercise resulted in a
osmotically driven increase in muscle cell T2, which masked any paramagnetic effects of
dissolved oxygen (33, 54, 80, 98, 102).

Much like the early work on BOLD contrast in skeletal muscle, the utility of
hyperoxia as a contrast agent in muscle remains unclear. One reason for the ambiguous
results may be the different concentrations of inspired gases used in these studies which
varied from 20% to 100% (88, 89, 133). Furthermore the exercise protocols
superimposed upon the hyperoxia differed in intensity from relatively light, 7 brief
muscle contractions each separated by 30 seconds of rest (82) to extremely demanding,
200 calf raises (88), and varied in duration, l-second contraction (82) versus a 120
second sustained contraction (133). Another potential problem is the duration of the
hyperoxia, and washout period following the hyperoxia. It takes approximately 3—5
minutes for blood gases to equilibrate and the physiological responses to stabilize with
hyperoxia, and 2-3 minutes for the elevated P02 to washout following the hyperoxia (50,

72, 103). Noseworthy et al., used a protocol that cycled between 90 seconds of

27

hyperoxia and 45 seconds of normoxia likely not allowing sufﬁcient time for blood gases
to equilibrate between conditions. While Tandura eta1., did not explicitly state the
duration of respiratory hyperoxia one can roughly estimate a steady-state was achieved
based on their plots of SI versus images number, which also indicate the point where
respiratory hyperoxia was started and stopped.

An additional consideration with the respiratory hyperoxia protocols is that the
changes are not limited to increased arterial and venous hemoglobin saturation or
increased dissolved oxygen in the plasma. Breathing hyperoxic gas has been shown to
decrease cardiac output, increase systolic blood pressure, increase heart rate, increase the
rate of ventilation, and increase systemic vascular resistance (SVR), in a dose dependent
manner (6, 61, 112). The changes in SVR are most troubling, as it’s unclear if these
changes affect the vascular response to exercise. In hamster cremaster muscle hyperoxia
resulted in a blunted contraction induced vasodilation of arterioles and reduced capillary
recruitment (61). The response was dose dependent with the reductions in vasodilation
being largest at the highest partial pressures of oxygen (61). An interesting ﬁnding of
this study was that the changes in P02 due to the contraction were greater at higher F,O2,
suggesting that oxygen supply was limited at the physiologic P02, although this ﬁnding is
not universal (103). Based on the local and systemic changes, respiratory hyperoxia may

do little to improve the skeletal muscle BOLD contrast. .

28

2.9.4 Skeletal muscle BOLD contrast in special populations

Skeletal muscle BOLD contrast has been used as a measure of vascular function
in patient populations with peripheral arterial occlusive disease (PAOD), diabetes, and in
the elderly. In patients with PAOD, BOLD contrast following a cuff-induced ischemia-
reactive hyperemia protocol was signiﬁcantly lower when compared to healthy age
matched controls. The peak change in T 2*during the reactive hyperemia, was 7.3 versus
13.1%, with a longer time to peak, 109.3 versus 32.2 seconds, in patients with PAOD
versus healthy controls, respectively. Qualitatively there was a trend towards a longer
time to peak change in the patients with lower ankle brachial indexes (ABI), indicated by
the plot of ABI versus time to peak. In a study by Hennig et al., patients with PAOD
showed a trend towards a delayed BOLD-response and a signiﬁcantly smaller slope in
the BOLD response following isometric muscle contractions, of the muscles in the lower
legs (1 1).

In patients with type I and type II diabetes the BOLD response to brief muscle
contractions was not lower compared to age, BMI, and physical activity matched controls
(118). This study did however ﬁnd that older less active subjects tended to have a lower
peak BOLD response (118). Consistent with these ﬁndings the magnitude of the post-
contraction BOLD contrast was only 0.5%, (peak change from baseline) in a group of
recreationally active elderly subjects, mean age 76.3 years (124, 125). In addition six of
the eleven subjects had no detectable post-contraction BOLD response. In comparison,
using the same protocol, Towse et al., found that young healthy subjects had a peak post-

contraction BOLD response of 1.5 %, which is three fold higher than the elderly subjects

29

(126). Although only a preliminary study, these ﬁndings are consistent with the ﬁndings
of a decline in vascular health associated with aging (99-101).

Changes in the peripheral vasculature do not only come about as a result of
pathologies, as chronic physical activity has been shown to result in increased ﬂow
mediated dilation of skeletal muscle arterioles, and increased microvascular volume
including an increase in capillary volume by as much as 30%. Any one or a combination
of these adaptations would result in greater contrast in BOLD based images. Recently
Towse et al., showed that the magnitude of the post-contraction BOLD response was
three-fold greater, 5.5 versus 1.5%, in chronically active versus sedentary subjects
respectively (126). Taken collectively, the above ﬁndings suggest skeletal muscle BOLD
contrast may potentially be used to assess the health of the peripheral vasculature and in

particular the microvasculature.

2.9.5 The physiological basis for the muscle BOLD contrast

Before BOLD-based imaging is fully accepted as a means to study the peripheral
vasculature in either health or disease it will be necessary to determine the underlying
source (s) of the changes in MRI signal intensity. In the brain the origin of the contrast
has been well studied, and although there are some controversies, the contrast is in
general accepted to primarily come from intravascular changes in blood oxygenation with
some changes due to blood volume. The brain literature suggests that the changes in
blood volume are primarily occurring on the arterial side of the circulation with some
changes in blood volume occurring in the capillaries. Changes in capillary blood volume

would suggest one of two things, either capillary recruitment, still a hotly debated topic,

30

or dilation of the capillaries possibly by an increase in the internal diameter by retraction
of the glycocalyx. In skeletal muscle changes in blood volume are thought to occur
primarily on the venous side of the circulation due to the greater compliance of the veins
which under typical venous pressures are partially collapsed. Blood volume can increase
in skeletal muscle by a variety of mechanisms including, arteriolar dilation, capillary
recruitment, an increase in capillary diameter and an increase in the blood volume in the
venous portion of the vasculature. It is possible that advances in MRI may help answer
these questions.

In the study by Meyer et al., using a previously published model of the brain
BOLD effect and data from skeletal muscle, they determined that the majority of the
contrast was from intravascular changes in blood oxygenation (58, 82). A small
contribution was attributed to an increase in total hemoglobin, blood volume, as
measured by NIRS. The fact that only a small change in blood volume occurred comes as
somewhat of a surprise given the nature of the peripheral vasculature and the compliance
of the peripheral veins.

In a study by Wigmore et al., the post-contraction MRI transients were attributed
to changes in blood volume primarily, while intra and extravascular changes in blood
oxygenation contributed to less than 1% of the changes (136). These data appear at odds
with those reported by Meyer et al., however the studies used a different exercise
protocol and a different MRI pulse-sequence to acquire the data. In an effort to reconcile
the differences Damon et al., (26) used NIRS and a dual-echo pulse sequence to estimate
the contribution of oxygenation and blood volume to the post-contraction BOLD contrast

using two different contraction durations. The dual-echo pulse sequence included a short

31

echo of 6 ms and a longer echo of 46 ms and maximal contractions of 2 and 8 seconds.
Based on a comparison of the NIRS and MRI data they found the short echo time was
sensitive to blood volume while the longer echo-time was sensitive to oxygenation.
Furthermore the longer duration contraction resulted in a larger change in both
oxygenation, and to a lesser extent, blood volume. These ﬁndings resolve the apparent
differences between the Meyer et al., and Wigmore et al., studies, and suggest the
contribution of blood volume and blood oxygenation to the BOLD contrast can be
manipulated by altering either the exercise protocol, the acquisition parameters, or both.
In the above studies the contribution of blood volume and oxygenation to the peak
of the post-contraction BOLD contrast was measured. However the post-contraction
hyperemic response is a dynamic process that includes an increase in blood ﬂow, blood
volume and changes in oxygenation that likely evolve over a slightly different time
course. Therefore it is possible that at any given time during the post-contraction
hyperemic response the relative contribution of blood volume or blood oxygenation to the

overall contrast will differ.

2.10 Skeletal muscle blood ﬂow

The increase in blood that occurs in response to a single, brief muscle contraction
has recently received renewed attention and many superb reviews have recently been
written on this topic (22, 51, 110, 130). Part of the interest in this model of blood ﬂow
control is that the increase in blood ﬂow to a single brief muscle contraction is so rapid
(~2 s) that it is likely not regulated in the same manor as. steady-state blood ﬂow. Steady-

state blood ﬂow is closely matched to metabolic rate as a result of the coupling between

32

vasoactive metabolites (ADP, Pi, lactate and H+ concentration, to name a few) directly
linked to the rate of muscle metabolism (63). The rapid nature of the increase in blood
ﬂow to a single brief muscle contraction, along with the relatively low metabolic cost of
the contraction, suggests a mechanism unique to that which regulates steady state ﬂow.
Brief muscle contractions result in an almost immediate increase in blood ﬂow to
the activated muscle (25, 130, 131). The post-contractile increase in blood ﬂow is
proportional to the strength of the contraction (25, 42, 84, 129) and appears to be more
closely related to the metabolic rate of the exercise than the work performed (42, 43). The
increase in blood ﬂow is rapid and occurs within the ﬁrst few seconds (~2 s, 1-2 cardiac
cycle) after the contraction with a peak ﬂow increase occurs between 6~ 10 seconds after
the contraction (8, 23). A variety of mechanisms have been proposed for this increase in
blood ﬂow including neural (32, 37, 121, 127) mechanical (8, 24, 84) and rapid acting
vasodilators (14, 22, 41, 46, 52, 85, 120). Evidence for some, but not all of these
mechanisms exist, however, the extent to which any one contributes to the post-
contractile ﬂow increase appears to depend on the exact nature of the contractile activity,
e.g., isometric contractions versus contractions involving muscle length changes (63),
species of animal (108, 109), and the experimental setup (130). The search for a single
candidate vasodilator has not proven fruitful. Just as for the control of steady-state blood
ﬂow, the initial ﬂow response appears to involve a variety of factors working in concert.
Blood ﬂow is a highly coordinated system that is regulated on multiple levels by
neural, mechanical and humoral factors. In addition to the various control mechanisms,
various sites along the vascular tree are involved in coordinating the ﬂow of blood to the

muscles, including the small arteries, arterioles, capillaries and venules (109, 110, I37).

33

Feed arteries, external to the muscle, regulate the ﬂow of blood to the muscle (21). Feed
arteries give rise to arterioles within the muscle and provide the majority of the vascular
resistance to blood ﬂow (77, l 10, 137). Typically there are 3 to 4 orders of branching of
the arterioles with the ﬁnal branch point being the terminal arteriole (77, 110). Terminal
arterioles give rise to 15 to 20 capillaries, which terminate in a draining venule. The
terminal arteriole, the 15 to 20 capillaries it supplies, and the draining venule act as
functional unit, a microvascular unit (MVU), and control the perfusion of the muscle.
Capillary ﬂow is regulated by the vascular smooth muscle (VSM) tone of its
parent terminal arteriole. Capillaries are thought to play an active role in the regulation
of their own perfusion and can act as sensors of the local environment and signal vessels
up stream to increase blood ﬂow by conducted vasodilation (104, 108, 132, 141). The
tone of the VSM of the arterioles can be altered by a variety of mechanism including
neural input, as the VSM in the skeletal muscle is richly innervated by sympathetic
nervous system. Mechanical factors may be involved such that the medium and small
arterioles within the muscles, and to a lesser extent the feed arteries external to the
muscle have signiﬁcant myogenic tone. Humeral factors, including ACh, Ki“, EDHF,
ATP, and NO (2, 22), can act on VSM either directly or by way of the endothelial cell

layer lining the vessel.

34

2.10.1 Neural factors

The VSM of skeletal muscle is richly innervated by the sympathetic nervous
system. The sympathetic nervous system exerts control over the skeletal muscle
peripheral vasculature by releasing norepinephrine (NE), a potent VSM constrictor. The
sympathetic nervous system exerts control of blood ﬂow to the muscle at rest and during
exercise (56). Eliminating sympathetic nerve activity (SNA) at rest results in 3-fold
increase in resting blood ﬂow (56). During exercise SNA increases proportional to
exercise intensity and proportional to the mass of activated muscle(121). SNA may be
modulated locally in the active muscle, by reduction in NE release or inhibition of the
post-junctional a—adrenoreceptor (63).

Sympathetically mediated vasoconstriction may be over come, not by altering the
handling of NE per se, but by a variety of local vasodilators related to the muscle
contraction. One mechanism of local control is a K” induced hyperpolarization of the
VSM. Extracellular K+ increases during muscle contractions and this can promote smooth
muscle hyperpolarization by activating the inwardly rectifying K+ channels K+1R or
activating the Na’L-K+ pump. Hyperpolarization would close the voltage gated Ca2+
channels promoting VSM relaxation, and vasodilation. Nitric oxide (NO) is another
potential candidate for the local ﬂow control and has been shown to be a potent
vasodilator.

The mechanisms presented for overriding SNA are usually thought of in the
context of dynamic exercise and it is not clear if modulation of SNA plays a role in the
ﬂow response to a single brief contraction. Concodilas et al., showed that the contraction

induced ﬂow response was not altered in patients with bilateral cervical sympathectomy

35

(25). To determine if SNA withdrawal was rapid enough at the onset of exercise to
contribute to the ﬂow increase to exercise Hughson et al., looked at the ﬁrst (~10 sec)
and second phase (20-30 sec) of the ﬂow response in the presence of increased SNA
(128). They found that the initial ﬂow response was considerably reduced (elevated SNA
could not be overcome) but the second phase was unchanged. Their results suggest that
SNA withdrawal does not contribute to the ﬁrst phase of the ﬂow response to exercise.

Although rapid withdrawal of sympathetic tone does not appear to be involved in
the initial ﬂow response others have suggested that autonomic vasodilators may
contribute to the initial ﬂow response (121). Spillover of ACh from the nerve terminal
has been implicated in the initial ﬂow response to exercise as the arterial vasculature
contains both B-adrenergic and muscarinic receptors (108). Evidence against this
mechanism comes from Buckwalter et al., who showed that neither the magnitude nor the
time course of the ﬂow response to mild exercise was altered in the presence B-adrenergic
and muscarinic receptor blockade (12). Consistent with these ﬁndings, a non-selective
NO inhibitor, and a blocker of muscarinic receptors, atropine, had no effect on the
magnitude or the time course of a brief contraction-induced increase in blood ﬂow (8).
However NO may play a role in the recovery of blood ﬂow following sustained exercise
(114). Although a role for sympathetic vasodilators in the initial ﬂow response to
exercise is suggested by some animal studies (108, 110) it does not appear be an
important mechanism in humans (8, 12).

Other neurally mediated responses may contribute to the initial ﬂow response to
exercise including a reﬂex-mediated vasodilation linked to the emptying of the venous

circulation. Tschakovsky et al., found that when the venous vasculature was emptied by

36

passive arm raising, blood ﬂow increased to the muscle after ~5 sec and reached a peak
ﬂow response at 8 sec. The ﬂow response was eliminated when the veins were prevented
from emptying by inﬂation of a blood pressure cuff around the arm. Although these
results do suggest a role for a reﬂex mediated increase in ﬂow, the time course of the
ﬂow response was much slower than seen in other contraction induced protocols and
peak ﬂow increase was modest 86% especially compared to a 450% increase seen in

other studies (129). The neural network of this reﬂex has yet to be determined and it

likely contributes little to the increase in blood ﬂow to a singe muscle contraction.

2.10.2 Muscle Pump

Blood ﬂow to the muscle is determined by the perfusion pressure gradient across
the vascular bed (arterial —venous) and the resistance to blood ﬂow. Changes in blood
ﬂow are largely due to changes in the caliber of the vessel as mean arterial pressure
(MAP) and mean venous pressure (MVP) are tightly controlled. The muscle-pump refers
to the repeated effect of changes in muscular pressure that accompany rhythmic
contractions (64, 115). This dynamic repetitive motion imparts kinetic energy to the
blood during the contraction, brieﬂy impedes arterial inﬂow during the contraction, and
facilitates the blood ﬂow during relaxation as the venous portions of the vasculature are
reﬁlled. The increased kinetic energy imparted to the blood during the contraction will
have little effect on the post-contractile increase in blood ﬂow with single muscle
contractions but may affect blood ﬂow during rhythmic contractions. However the
pressure differential created following the contraction should result in an increase in

blood ﬂow immediately following the contraction.

37

Intramuscular pressure can increase to greater than 500 mm Hg during a maximal
isometric contraction (l l 1). This increase in intramuscular pressure is sufﬁcient to expel
the blood stored in the venous vasculature and impede the arterial inﬂow of blood to the
muscle. Because of anatomical location and orientation of the venous one-way valves the
blood is expressed from the venous system and pushed back towards the heart (64). The
increase in driving pressure created by emptying the venous vasculature will have its
greatest effect when the pressure differential across the vascular bed is greatest,
immediately upon relaxation of the muscle contraction, within the ﬁrst few cardiac cycles
alter the contraction.

At rest, with the dependent limb below the heart, mean arterial pressure is 130
mm Hg and mean venous pressure is ~ 50 mm Hg with an effective perfusion pressure of
80 mm Hg. Immediately following the muscle contraction the pressure in the veins is
close to zero, if not slightly negative, creating a larger pressure gradient across the
capillaries than resting conditions. It is thought that venous pressure may be negative due
to the physical link between the muscle connective tissue and the vasculature which
might act to pull the vessels open during relaxation of the muscle (64).

The role of the muscle pump is equivocal and may depend on a variety of factors
including the mode and duration of exercise. Patterson and Shepherd showed that blood
ﬂow was doubled when rhythmic contractions were superimposed upon maximal dilation
(96). However Hamann et al., did not detect an increase in hind limb blood ﬂow when
treadmill running was superimposed upon maximal vasodilation by adenosine infusion
(44) in dogs. Tschakovsky showed that the ﬂow response to cuff-induced venous

emptying could account for 60% of the ﬂow increase to a single contraction and that the

38

ﬂow increase was greater when the arm was placed below heart level (131). This might
be an overestimation though, as the cuff induced increase in blood ﬂow was likely the
result in activation of multiple mechanisms including the muscle pump, myogenic
response, and reﬂex vasodilation caused by emptying of the venous vasculature (84,
127)

Whether or not the skeletal muscle pump contributes signiﬁcantly to the exercise
induced muscle blood ﬂow is till being debated ( 105, 115, 130, 131). The inﬂuence of the
muscle pump in contributing to muscle blood ﬂow may vary depending a number of
factors including the muscle recruitment patterns, muscle ﬁber type and the type of
muscle contraction dynamic versus isometric(63). Isometric contractions may produce
less pronounced changes in vascular conductance than dynamic contractions because the
muscle pump is less effective in the absence of length changes (64).

If the muscle pump does contribute to an increase in blood ﬂow it is likely to
occur within the ﬁrst few cardiac cycles following the muscle contraction when the
pressure gradient is the largest. Although ﬂow is certainly increased in the ﬁrst few
contraction cycles (129), blood ﬂow response to a single brief contraction doesn’t peak
until 4-6 cardiac cycles (6-10 see) after the contraction. Therefore although it’s likely that
the muscle pump contributes to the post-contractile ﬂow increase it likely accounts for

only 10-20 % of the peak changes (60).

39

2.10.3 Myogenic response -
The myogenic response, is an extension of the hypothesis ﬁrst suggested by Sir
William Bayliss in 1902 regarding an autoregulatory mechanism of blood vessels (5).

The myogenic response is the autoregulatory mechanism by which VSM cells respond to
changes in transmural pressure, (Ptm = (Pinside — Poutside) (27, 35, 107). Blood vessels

vasoconstrict in response to an increase in transmural pressure and vasodilate in response
to a decrease in transmural pressure (2 7, 35). The myogenic response has been shown to
occur in numerous vascular beds, including the mesenteric, cerebral, renal, coronary, and
skeletal muscle circulation (27, 107), and along various branches of the vasculature
including small arteries , arterioles, veins and venules. The strength of the myogenic
response varies across vascular beds and is relatively pronounced in skeletal muscle
vessels and weaker in the mesenteric vessels. Along with differences between vascular
beds the strength of myogenic tone varies along the vascular tree and is strongest in
intermediate sized arterioles (107).

The underlying mechanism for myogenic vasodilation appears to be
hyperpolarization of the VSM cells. Hyperpolarization of the VSM regulates the entry of
Ca2+ into the cell by closing voltage gated calcium channels (27, 107). Although VSM
cell hyperpolarization appears obligatory for myogenic vasodilation the exact mechanism
for the mechanical coupling between changes in transmural pressure and VSM
depolarization remains unclear. One theory is that a reduction in wall tension deactivates
stretch activated, non—selective cation channels resulting in closure of voltage gated

calcium channels, decreased intracellular calcium, and relaxation of the VSM cells.

40

Other channels have been implicated in the myogenic response including Ca2+

activated K+ (Kc3++) channels and voltage-dependent K+ channels (K2) (27, 52). In

particular, the voltage-dependent K+ channels provide a strong stimulus for repolarization

of the VSM to counteract depolarization, because the open probability of K+v channels

exhibit an exponential increase in response to VSM membrane depolarization (87). The

. . . + . .
link between activation of K v and VSM relaxation is reduced entry of extracellular Ca2+

by inactivation of voltage gated Ca2+ channels.

The myogenic response is believed to be very strong in skeletal muscle and in
particular in the small and medium sized arterioles deep with in the muscle. It is this
branch of the peripheral vasculature that provides the greatest resistance to blood ﬂow
and it has been suggested that the myogenic response contributes to the increase in blood
ﬂow following a single brief muscle-contraction (8, 23, 24, 84). Mohrrnan and colleagues
compared the increase in vascular conductance to a 1 sec stimulated contraction, and a
rapid 1 second cuff-induced compression. The increase in conductance was greater at
higher contraction forces, and higher at higher cuff pressures. Although the cuff-induced
compression resulted in signiﬁcant changes in vascular conductance, the response was
always less than the conductance change due to the contraction (84).

Recently Kirby et al., showed that vascular conductance increased by as much as
150% to a single 1 second cuff compression (60). Although the cuff induced increase in
vascular conductance in this protocol was substantial, it was only a fraction of the change -
resulting from a brief muscle contraction, a 700% increase. Consistent with a myogenic

response, Clifford et al., reported a rapid vasodilation of isolated rat skeletal muscle feed

41

arteries in response to brief changes in transmural pressure (24). The magnitude of the
response peaked within 5 sec and when the endothelium was removed from the
preparation the magnitude of the dilation was greatly reduced. Collectively these ﬁndings
support a role for the myogenic response in the ﬂow response to a brief contraction, or
change in intramuscular pressure, and this response appears to involve both the VSM and
the endothelium. However, the myogenic response does not account for the entire
magnitude of the contraction induced ﬂow response, suggesting a role for a rapid

vasodilator.

2.10.4 Rapid Vasodilators

Evidence suggests that part of the mechanism for the fast ﬂow response is a rapid
vasodilation that may involve hyperpolarization of the VSM membrane (13, 52). One
signal candidate for this hyperpolarization is Endothelium Derived Hyperpolarizing
Factor (EDHF), which may be KL Nitric oxide has also been thought to contribute to the
initial ﬂow response. However recent data suggests it may be more involved in resting
tone of VSM and the recovery phase of blood ﬂow (8, 22). Much of the attention has
focused on K+ as a rapid vasodilator given it temporal association with the muscle
contraction and the wide distribution of K+ channels in the microcirculation (14, 52, 85).

The remainder of this review on rapid vasodilators will focus on K+

42

2.10.5 Potassium Ion

K+ has been linked to the contraction induced ﬂow response (2, 14, 22, 41, 85,
113, 132, 138, 139). Potassium is released by the muscle cell in response to a muscle
contraction. This increase in interstitial K” can act to hyperpolarize the VSM membrane
by a number of mechanisms. K+ can activate the inward-rectiﬁer Kir channel which
would lead to hyperpolarization of the VSM, closing of the voltage gated Ca2+ and
relaxation of the VSM (22, 59). K+ can also initiate hyperpolarization by activating the
Na+- K+ pump which would again lead to hyperpolarization of the VSM cells, and
relaxation of the VSM (52).

Hamann et al., showed that VSM membrane hyperpolarization was obligatory for
the contraction induced ﬂow response (41). In their study, the VSM membrane potential
was clamped with a continuous infusion of K+. When the contraction was initiated the
ﬂow response was almost completely eliminated, compared to the control condition (41).
Murrant et al. showed that the contraction induced ﬂow response required not only a
source of K+ but also ion channels involved in the K+ homeostasis. In this study
stimulated contractions were preformed in the presence or absence of a blocker of the
voltage dependent K+ channel, the Km channel and the Na‘L-K+ pump. They found that
the dilatory response was reduced on average by 65%, across a range of stimulation
frequencies.

Mohrman and Sparks also suggested a role of K+ in the ﬂow response to a brief
contraction. They showed that the time course in the changes in K+ in the venous
circulation followed the time course of the changes in vascular resistance and the time

course is rapid enough to support a causative role for K+ in the change in vascular

43

resistance. Taken together the above studies strongly support a role for K+ as a

vasodilator involved in the ﬂow response to a single brief muscle contraction.

2.11 Adaptations to the peripheral vasculature in response to regular exercise
Habitual physical activity results in myriad of adaptations to the cardiovascular
system which result in an increase in the ability to deliver oxygenated blood to the
muscle, and increase in the ability of the muscle to extract oxygen from the blood.
Central adaptations include increased stroke volume, increased maximal cardiac output,
and an increased blood volume. Peripheral factors include increased mitochondrial
density, increased myoglobin content, and increased enzyme activity of enzymes
involved in aerobic metabolism. A comprehensive review of the adaptations to habitual
physical activity is beyond the scope of this dissertation. In this section I will brieﬂy
review some of the adaptation to training that would be consistent with a greater increase
in blood ﬂow following a brief muscle contraction, and I will review the few studies that

suggest a training effect.

A signiﬁcant adaptation to habitual physical activity occurs at the peripheral
vasculature. Habitual physical activity results in adaptations to the peripheral vasculature
at all sites along the vascular tree (63). Chronic endurance training increases collateral
blood ﬂow (140), and microvascular density including increased density of small
arterioles (62) and capillaries (9). In addition to these structural changes habitual
physical activity improves the functional capacity of the peripheral vasculature. Training
increases ﬂow-mediated dilation and endothelium independent dilation of small arteries

(36, 74), and improves contraction induced dilation of small arterioles (62).

44

Habitual physical activity has also been shown to alter the kinetics of blood ﬂow
during the transition from rest to work. As little as 10 days of cycle ergometer training is
sufﬁcient to increase both the initial rate of blood velocity and the amplitude of the blood
velocity increase at 10 sec, as measured in the femoral artery in response to a knee
extension exercise (116). Although in this study the initial kinetics (called the “on-
response”) of blood velocity were altered with training, the steady state blood velocity

did not change with training and was not different compared to the control group.

Five weeks of treadmill training resulted in greater initial (ﬁrst 30 sec) ﬂow
responses to exercise measured in the absence of differences in the maximal ﬂow (73).
Mackie et al., found that early ﬂow response (ﬁrst 30 sec) to exercise was greater in
treadmill-trained versus sedentary rats. This larger early ﬂow phase occurred in the
absence of a difference in the steady-state ﬂow response to exercise. The greater ﬂow
response in the treadmill-trained rats occurred in muscles with predominantly slow or fast
ﬁbers, however the response was more pronounced in the faster muscles. In these
studies, the increase in the initial blood ﬂow response with training, in the absence of an
increase in the steady-state or maximal ﬂow, suggest that one of the major adaptations to
training is the magnitude of the initial ﬂow response.

Dilation of the small arterioles, and in particular the terminal arterioles, regulates
the blood ﬂow response in the early stages of exercise and in response to a brief muscle
contraction (2, 83, 86, 108, 110). Lash et al., reported a 20% increase in the density of
small arterioles following a 10 week training program in rats (62). The capillary-to

muscle ﬁber ratio increased by 15% and contraction-induced dilation of the small

arterioles was greatly enhanced. The adaptations in the microvasculature occurred in the

45

absence of changes in aerobic capacity of the muscle, as measured by citrate synthase
activity (62). Arteriolar dilation precedes changes in blood ﬂow in the feed arteries which
are located external to the muscle and do not dilate in response to brief muscle
contraction (8, 130, 1.31).

Both the anatomical and functional adaptation to the peripheral vascular would
suggest that the ﬂow response to a brief muscle contraction would be enhanced by
chronic habitual activity. It could be suggested that a larger ﬂow response is necessary to
meet the demand for oxygen in the habitually active to meet the more rapid oxygen
consumption kinetics that are a consequence of an increase in mitochondrial density. An
increase in the ability of the muscle to consume oxygen in the absence of increased
delivery would result in a ﬂow-consumption mismatch that might have deleterious effects

on muscle performance.

46

10.

ll.

12.

References

Adams RP, Welch HG. Oxygen uptake, acid-base status, and performance with
varied inspired oxygen fractions. J Appl Physio] 49: 863-868, 1980.

Armstrong ML, Dua AK, Murrant CL. Potassium initiates vasodilatation
induced by a single skeletal muscle contraction in hamster cremaster muscle. J
Physio] 581: 841-852, 2007.

Bangsbo J. Muscle oxygen uptake in humans at onset of and during intense
exercise. Acta Physiol Scand 168: 457-464, 2000.

Baudelet C, Gallez B. How does blood oxygen level-dependent (BOLD) contrast
correlate with oxygen partial pressure (p02) inside tumors? Magn Reson Med
48(6): 980-986, 2002.

Bayliss WM. On the local reactions of the arterial wall to changes of internal
pressure. J Physio] 28(3): 220-231, 1902.

Becker HF, P010 0, McNamara SG, Berthon-Jones M, Sullivan CE. Effect of
different levels of hyperoxia on breathing in healthy subjects. J Appl Physiol 81(4):
1683-1690, 1996.

Brahimi-Horn MC, Chiche J, Peuyssegur J. Hypoxia and cancer. J Mo] Med 85:
1301-1307, 2007.

Brock RW, Tschakovsky ME, Shoemaker JK, Halliwill JR, Joyner MJ,
Hughson RL. Effects of acetylcholine and nitric oxide on forearm blood ﬂow at
rest and after a single muscle contraction. J Appl Physiol 85(6): 2249-2254, 1998.

Brodal P, Ingjer F, Hermansen L. Capillary supply of skeletal muscle ﬁbers in
untrained and endurance-trained men. Am J Physiol 232(6): H705-712, 1977.

Brown GG, Perthen JE, Liu TT, Buxton RB. A primer on functional magnetic
resonance imaging. Neuropsychol Rev 17: 107-125, 2007.

Buchert M, D. Bilecen, J. Winterer, A. Schulte, M. Langer, J. Hennig. Time
resolved BOLD response in the muscle of patients with peripheral vascular
occlusive disease. Proc Int Soc Mag Reson Med 10: 122, 2002.

Buckwalter JB, Ruble SB, Mueller PJ, Clifford PS. Skeletal muscle vasodilation
at the onset of exercise. J Appl Physiol 85(5): 1649-1654, 1998.

47

l3.

14.

15.

l6.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

Burns WR, Cohen KD, Jackson WF. K+-induced dilation of hamster cremasteric
arterioles involves both the Na+/K+-ATPase and inward-rectiﬁer K+ channels.
Microcirculation I 1: 279-293, 2004.

Burns WR, Cohen KD, Jackson WF. K+-induced dilation of hamster cremasteric
arterioles involves both the Na+/K+-ATPase and inward-rectiﬁer K+ channels.
Microcirculation 1 1(3): 279-293, 2004.

Buxton RB. The elusive initial dip. Neurolmage 13: 953-958, 2001.

Buxton RB. Introduction to Functional Magnetic Resonance Imaging: Principles
and Techniques. Cambridge University Press, 2002.

Buxton RB, Ackerman JH. In Vivo Magnetic Resonance. 2006.

Buxton RB, Frank LR. A model for the coupling between cerebral blood ﬂow and
oxygen metabolism during neural stimulation. J Cereb Blood Flow Metab 17: 64-
72, 1997.

Buxton RB, Uludazeg K, Dubowitz DJ, Liu TT. Modeling the hemodynamic
response to brain activation. Neurolmage 23 Suppl 1, 2004.

Buxton RB, Wong EC, Frank LR. Dynamics of blood ﬂow and oxygenation
changes during brain activation: the balloon model. Magn Reson Med 39(6): 85 5-
864, 1998.

Christensen KL, Mulvany MJ. Location of resistance arteries. J Vasc Res 38: 1-
12, 2001.

Clifford PS, Hellsten Y. Vasodilatory mechanisms in contracting skeletal muscle.
JAppl Physio] 97(1): 393-403, 2004.

Clifford PS, Jasperse JL. Feedforward vasodilatation at the onset of exercise. J
Physiol 583: 811- (epub ahead of print), 2007.

Clifford PS, Kluess HA, Hamann JJ, Buckwalter JB, Jasperse JL. Mechanical
compression elicits vasodilatation in rat skeletal muscle feed arteries. J Physiol 572:
561-567, 2006.

Corcondilas A, Koroxenidis GT, Shepherd JT. Effect of a brief contraction of
forearm muscles on forearm blood ﬂow. J Appl Physiol 19: 142-146, 1964.

Damon BM, Hornberger JL, Wadington MC, Lansdown DA, Kent-Braun JA.

Dual gradient-echo MRI of post-contraction changes in skeletal muscle blood
volume and oxygenation. Magn Reson Med 57: 670-679, 2007.

48

27.

28.

29.

30.

31.

32.

33.

34.

35.

36.

37.

Davis MJ, Hill MA. Signaling mechanisms underlying the vascular myogenic
response. Physiol Rev 79: 387-423, 1999.

Donahue KM, Van Kylen J, Guven S, El-Bershawi A, Luh WM, Bandettini
PA, Cox RW, Hyde JS, Kissebah AH. Simultaneous gradient-echo/spin-echo EPI
of graded ischemia in human skeletal muscle. J Magn Reson Imaging 8(5): 1106-
1113, 1998.

Duong TQ, Yacoub E, Adriany G, Hu X, Ugurbil K, Kim SG. Microvascular
BOLD contribution at 4 and 7 T in the human brain: gradient-echo and spin-echo
MRI with suppression of blood effects. Magn Reson Med 49(6): 1019-1027, 2003.

Egred M, Al-Mohammad A, Waiter GD, Redpath TW, Semple SK, Norton M,
Welch A, Walton S. Detection of scarred and viable myocardium using a new
magnetic resonance imaging technique: blood oxygen level dependent (BOLD)
MRI. Heart 89(7): 738-744, 2003.

Egred M, Waiter GD, Semple SI, Redpath TW, AI-Mohammad A, Norton MY,
Metcalfe MJ, Walton S. Blood oxygen level-dependent (BOLD) magnetic
resonance imaging in patients with dypiridamole induced ischaemia; a PET
comparative study. Int J Cardiol 115: 36—41, 2007.

Emerson GG, Segal SS. Electrical activation of endothelium evokes vasodilation
and hyperpolarization along hamster feed arteries. Am J Physiol 280(1): H160-167,
2001.

Fisher MJ, Meyer RA, Adams GR, Foley JM, Potchen EJ. Direct relationship
between proton T2 and exercise intensity in skeletal muscle MR images. Invest
Radiol 25(5): 480-485, 1990.

Fleckenstein JL, Haller RG, Lewis SF, Archer BT, Barker BR, Payne J,
Parkey RW, Peshock RM. Absence of exercise-induced MRI enhancement of
skeletal muscle in McArdle's disease. J Appl Physiol 71(3): 961-969, 1991.

Folkow B. Description of the Myogenic Hypothesis. Circ Res 15: SUPPL2279-287,
1964.

Fuchsjéager-Mayrl G, Pleiner J, Wiesinger GF, Sieder AE, Quittan M, Nuhr
MJ, Francesconi C, Seit HP, Francesconi M, Schmetterer L, Wolzt M. Exercise
training improves vascular endothelial function in patients with type 1 diabetes.
Diabetes Care 25(10): 1795-1801, 2002.

Fuglevand AJ, Segal SS. Simulation of motor unit recruitment and microvascular
unit perfusion: spatial considerations. J Appl Physio] 83: 1223-1234, 1997.

49

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

48.

49.

Gati JS, Menon RS, Ugurbil K, Rutt BK. Experimental determination of the
BOLD ﬁeld strength dependence in vessels and tissue. Magn Reson Med 38(2):
296-302, 1997.

Gregory CM, Vandenborne K, Dudley GA. Metabolic enzymes and phenotypic
expression among human locomotor muscles. Muscle Nerve 24(3): 387-393, 2001.

Haj nal JV, Roberts 1, Wilson J, Oatridge A, Saeed N, Cox IJ, Ala-Korpela M,
Bydder GM, Young IR. Effect of profound ischaemia on human muscle: MRI,
phosphorus MRS and near-infrared studies. NMR Biomed 9: 305-314, 1996.

Hamann JJ, Buckwalter JB, Clifford PS. Vasodilatation is obligatory for
contraction-induced hyperaemia in canine skeletal muscle. J Physiol 557: 1013-
1020, 2004.

Hamann JJ, Buckwalter JB, Clifford PS, Shoemaker JK. Is the blood ﬂow
response to a single contraction determined by work performed? J App] Physio]
96(6): 2146-2152, 2004.

Hamann JJ, Kluess HA, Buckwalter JB, Clifford PS. Blood ﬂow response to
muscle contractions is more closely related to metabolic rate than contractile work.
J Appl Physio] 98(6): 2096-2100, 2005.

Hamann JJ, Valic Z, Buckwalter JB, Clifford PS. Muscle pump does not
enhance blood ﬂow in exercising skeletal muscle. J Appl Physiol 94: 6-10, 2003.

Hathout GM, Gambhir SS, Gopi RK, Kirlew KA, Choi Y, So G, Gozal D,
Harper R, Luﬂdn RB, Hawkins R. A quantitative physiologic model of blood
oxygenation for functional magnetic resonance imaging. Invest Radio] 30: 669-682,
1995.

Hazeyama Y, Sparks HV. A model of potassium ion efﬂux during exercise of
skeletal muscle. Am J Physio] 236(1): R83-90, 1979.

Hennig J SK, Schreiber A. Time resolved observations of BOLD effect in muscle
during isometric exercise. Proc Int Soc Magn Reson Med 8: l, 2000.

Holmbeack AM, Porter MM, Downham D, Andersen JL, Lexell J. Structure
and function of the ankle dorsiﬂexor muscles in young and moderately active men
and women. J App] Physio] 95(6): 2416-2424, 2003.

Howseman AM, Bowtell RW. Functional magnetic resonance imaging: imaging

techniques and contrast mechanisms. Philos Trans R Soc Lond B Biol Sci
354(1387): 1179-1194, 1999.

50

50.

51.

52.

53.

54.

55.

56.

57.

58.

59.

60.

61.

Hughes RL, Clode M, Edwards RH, Goodwin TJ, Jones NL. Effect of inspired
02 on cardiopulmonary and metabolic responses to exercise in man. J Appl Physio]
24(3): 336-347, 1968.

Hughson RL. Regulation of blood ﬂow at the onset of exercise by feed forward
and feedback mechanisms. Can J Appl Physiol 28(5): 774-787, 2003.

Jackson WF. Potassium channels in the peripheral microcirculation.
Microcirculation 12: ll3-127, 2005.

Jaworowski A, Porter MM, Holmbéack AM, Downham D, Lexell J. Enzyme
activities in the tibialis anterior muscle of young moderately active men and
women: relationship with body composition, muscle cross-sectional area and ﬁbre
type composition. Acta Physio] Scand 176(3): 215-225, 2002.

Jenner G, Foley JM, Cooper TG, Potchen EJ, Meyer RA. Changes in magnetic
resonance images of muscle depend on exercise intensity and duration, not work. J
Appl Physiol 76(5): 2119-2124, 1994.

Jones M, Berwick J, Johnston D, Mayhew J. Concurrent optical
imagingspectroscopy and laser-Doppler ﬂowmetry: the relationship between blood
ﬂow, oxygenation, and volume in rodent barrel cortex. Neurolmage 13: 1002-1015,
2001.

Joyner MJ, Wilkins BW. Exercise hyperaemia: is anything obligatory but the
hyperaemia? J Physio] 583: 855-860, 2007.

J uillard L, Lerman L0, Kruger DG, Haas JA, Rucker BC, Polzin JA, Riederer
SJ, Romero J C. Blood oxygen level-dependent measurement of acute intra-renal
ischemia. Kidney Int 65(3): 944-950, 2004.

Kennan RP, Zhong J, Gore JC. Intravascular susceptibility contrast mechanisms
in tissues. Magn Reson Med 31(1): 9-21, 1994.

Kirby BS, Carlson RE. Potassium, contracting myocytes and rapid vasodilatation:
peaking more than just our interest? J Physiol 586(2): 315-317, 2008.

Kirby BS, Carlson RE, Markwald RR, Voyles WF, Dinenno FA. Mechanical
inﬂuences on skeletal muscle vascular tone in humans: insight into contraction-
induced rapid vasodilatation. J Physiol 583: 861-874, 2007.

Klitzman B, Damon DN, Gorczynski RJ, Duling BR. Augmented tissue oxygen
supply during striated muscle contraction in the hamster. Relative contributions of
capillary recruitment, functional dilation, and reduced tissue P02. Circ Res 51: 711-
721, 1982.

51

62.

63.

64.

65.

66.

67.

68.

69.

70.

71.

72.

Lash JM, Bohlen HG. Functional adaptations of rat skeletal muscle arterioles to
aerobic exercise training. J Appl Physiol 72: 2052-2062, 1992.

Laughlin MH, Korthuis, RJ , Dunker, DJ, Bache, RJ. Control of Blood Flow to
cardiac and skeletal muscle during exercise. Handbook of Physiology 12: 705-769,
1996.

Laughlin MH, Schrage WG. Effects of muscle contraction on skeletal muscle
blood ﬂow: when is there a muscle pump? Med Sci Sports Exerc 31: 1027-1035,
1999.

Lauterbur PC. Progress in n.m.r. zeugrnatography imaging. Philos Trans R Soc
Lond B Biol Sci 289: 483-487, 1980. .

Lebon V, Brillault-Salvat C, Bloch G, Leroy-Willig A, Carlier PG. Evidence of
muscle BOLD effect revealed by simultaneous interleaved gradient-echo NMR] and
myoglobin NMRS during leg ischemia. Magn Reson Med 40: 551-558, 1998.

Lebon V, Carlier PG, Brillault—Salvat C, Leroy-Willig A. Simultaneous
measurement of perfusion and oxygenation changes using a multiple gradient-echo
sequence: application to human muscle study. Magnetic Resonancelimaging 16(7):
721-729, 1998.

Ledermann HP, Schulte AC, Heidecker HG, Aschwanden M, Jéager KA,
Scheffler K, Steinbrich W, Bilecen D. Blood oxygenation level-dependent
magnetic resonance imaging of the skeletal muscle in patients with peripheral
arterial occlusive disease. Circulation 113(25): 2929-2935, 2006.

Lee SP, Silva AC, Ugurbil K, Kim SG. Diffusion-weighted spin-echo fMRI at 9.4
T: microvascular/tissue contribution to BOLD signal changes. Magn Reson Med
42(5): 919-928, 1999.

Lindauer U, Royl G, Leithner C, Kuhl M, Gold L, Gethmann J, Kohl-Bareis
M, Villringer A, Dirnagl U. No evidence for early decrease in blood oxygenation
in rat whisker cortex in response to functional activation. Neurolmage 13: 988-
1001, 2001.

Logothetis NK, Pauls J, Augath M, Trinath T, Oeltermann A.
Neurophysiological investigation of the basis of the fMRI signal. Nature 412(6843):
150-157, 2001.

Logothetis NK, Wandell BA. Interpreting the BOLD signal. Ann Rev Physiol 66,
2004.

52

73.

74.

75.

76.

77.

78.

79.

80.

81.

82.

83.

84.

Luksch A, Garhéofer G, Imhof A, Polak K, Polska E, Dorner GT, Anzenhofer
S, Wolzt M, Schmetterer L. Effect of inhalation of different mixtures of 0(2) and
C0(2) on retinal blood flow. BrJ Ophthalmo] 86(10): 1143-1147, 2002.

Mackie BG and Terjung RL. Inﬂuence of training on blood ﬂow to different
skeletal muscle ﬁber types. J Appl Physiol 55(4): 1072-1078, 1983.

Maiorana A, O'Driscoll G, Cheetham C, Dembo L, Stanton K, Goodman C,
Taylor R, Green D. The effect of combined aerobic and resistance exercise
training on vascular function in type 2 diabetes. J Am Coll Cardiol 38(3): 860-866,
2001.

McDermott MM, Greenland P, Liu K, Guralnik J M, Criqui MH, Dolan NC,
Chan C, Celic L, Pearce WH, Schneider JR, Sharma L, Clark E, Gibson D,
Martin GJ. Leg symptoms in peripheral arterial disease: associated clinical
characteristics and functional impairment. JAMA 286(13): 1599-1606, 2001.

McDermott MM, Kerwin DR, Liu K, Martin GJ, O'Brien E, Kaplan H,
Greenland P. Prevalence and signiﬁcance of unrecognized lower extremity
peripheral arterial disease in general medicine practice. J Gen Intern Med 16: 384-
390, 2001.

Mellander S, Johansson B. Control of resistance, exchange, and capacitance
functions in the peripheral circulation. Pharmacol Rev 20: 117-196, 1968.

Metzger H, Erdmann W, Thews G. Effect of short periods of hypoxia, hyperoxia,
and hypercapnia on brain 02 supply. J App] Physio] 31(5): 751-759, 1971.

Meyer RA, McCuIly KK, Reid RW, Prior BM. BOLD MRI and NIRS detection
of transient hyperemia after single skeletal muscle contractions. Proc Int Soc Mag
Reson Med 9: 135 2001.

Meyer RA, Prior BM. Functional magnetic resonance imaging of muscle. Exerc
Sport Sci Rev 28(2): 89-92, 2000.

Meyer RA, Prior BM, Siles RI, Wiseman RW. Contraction increases the T(2) of
muscle in fresh water but not in marine invertebrates. NMR Biomed 14: 199-203,
2001.

Meyer RA, Towse TF, Reid RW, Jayaraman RC, Wiseman RW, McCully KK.
BOLD MRI mapping of transient hyperemia in skeletal muscle after single
contractions. NMR Biomed 17(6): 392-398, 2004.

Mihok ML, Murrant CL. Rapid biphasic arteriolar dilations induced by skeletal

muscle contraction are dependent on stimulation characteristics. Can J Physio]
Pharmacol 82: 282-287, 2004.

53

85.

86.

87.

88.

89.

90.

91.

92.

93.

94.

95.

96.

97.

Mohrman DE, Sparks HV. Myogenic hyperemia following brief tetanus of canine
skeletal muscle. Am J Physiol 227(3): 531-535, 1974.

Mohrman DE, Sparks HV. Role of potassium ions in the vascular response to a
brief tetanus. Circ Res 35(3): 384-390, 1974.

Murrant CL, Sarelius IH. Coupling of muscle metabolism and muscle blood ﬂow
in capillary units during contraction. Acta Physiol Scand 168(4): 531-541, 2000.

Nelson MT, Patlak JB, Worley JF, Standen NB. Calcium channels, potassium
channels, and voltage dependence of arterial smooth muscle tone. Am J Physio]
259: C3-18, 1990.

Noseworthy MD, Bulte DP, Alfonsi J. BOLD magnetic resonance imaging of
skeletal muscle. Seminars in musculoskeleta] radiology 7(4): 307-315, 2003.

Noseworthy MD, Kim JK, Stainsby JA, Stanisz GJ, Wright GA. Tracking
oxygen effects on MR signal in blood and skeletal muscle during hyperoxia
exposure. J Magn Reson Imaging 9(6): 814-820, 1999.

Ogawa S, Lee TM. Magnetic resonance imaging of blood vessels at high ﬁelds: in
vivo and in vitro measurements and image simulation. Magn Reson Med 16: 9-18,
1990.

Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with
contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A 87: 9868-987 2,
1990.

Ogawa S, Lee TM, Nayak AS, Glynn P. Oxygenation-sensitive contrast in
magnetic resonance image of rodent brain at high magnetic ﬁelds. Magn Reson Med
14: 68-78, 1990.

Ogawa S, Menon RS, Kim SG, Ugurbil K. On the characteristics of ﬁrnctional
magnetic resonance imaging of the brain. Annu Rev Biophys Biomo] Struct 27: 447-
474, 1998.

Okada T, Yamada H, Ito H, Yonekura Y, Sadato N. Magnetic ﬁeld strength
increase yields signiﬁcantly greater contrast-to-noise ratio increase: Measured using
BOLD contrast in the primary visual area. Acad Rradiol 12(2): 142-147, 2005.

Patten C, Meyer RA, Fleckenstein JL. T2 mapping of muscle. Seminars in
musculoskeleta] radiology 7(4): 297-305, 2003.

Patterson GC, Shepherd JT. The effects of continuous infusions into the brachial
artery of adenosine triphosphate, histamine and acetylcholine on the amount and

54

98.

99.

100.

101.

102.

103.

104.

105.

106.

107.

108.

109.

rate of blood debt repayment following rhythmic exercise of the forearm muscles.
Clin Sci (Lond) 13(1): 85-91, 1954.

Pauling L, Coryell CD. The magnetic properties and structure of the
hemochromogens and related substances. Proc Natl Acad Sci U S A 22(3): 159-163,
1936.

Ploutz—Snyder LL, Nyren S, Cooper TG, Potchen EJ, Meyer RA. Different
effects of exercise and edema on T2 relaxation in skeletal muscle. Magn Reson Med
37(5): 676-682, 1997.

Proctor DN, Koch DW, Newcomer SC, Le KU, Smithmyer SL, Leuenberger U.
Leg blood ﬂow and V02 during peak cycle exercise in younger and older women.
Med Sci Sports Exerc 36(4): 623-631, 2004.

Proctor DN, Le KU, Ridout SJ. Age and regional speciﬁcity of peak limb
vascular conductance in men. J Appl Physiol 98: 193-202, 2005.

Proctor DN, Parker BA. Vasodilation and vascular control in contracting muscle
of the aging human. Microcirculation 13(4): 315-327, 2006.

Reid RW, Foley JM, Jayaraman RC, Prior BM, Meyer RA. Effect of aerobic
capacity on the T(2) increase in exercised skeletal muscle. J App] Physio] 90(3):
897-902, 2001.

Rousseau A, Bak Z, J anerot-Sjeoberg B, Sjéoberg F. Acute hyperoxaemia-
induced effects on regional blood ﬂow, oxygen consumption and central circulation
in man. Acta Physiol Scand 183(3): 231-240, 2005.

Sarelius IH, Cohen KD, Murrant CL. Role for capillaries in coupling blood ﬂow
with metabolism. Clin Exp Pharmacol Physio] 27(10): 826-829, 2000.

Saunders NR, Pyke KE, Tschakovsky ME. Dynamic response characteristics of
local muscle blood ﬂow regulatory mechanisms in human forearm exercise. J Appl

Physio] 98(4): 1286-1296, 2005.

Schaper NC, Nabuurs-Franssen MH, Huijberts MS. Peripheral vascular disease
and type 2 diabetes rnellitus. Diabetes Metab Res Rev 16: 81 1-15, 2000.

Schubert R, Mulvany MJ. The myogenic response: established facts and attractive
hypotheses. Clin Sci (Land) 96: 313-326, 1999.

Segal SS. Microvascular recruitment in hamster striated muscle: role for conducted
vasodilation. Am JPhysiol 261(1): H181-189, 1991.

55

110.

111.

112.

113.

114.

115.

116.

117.

118.

119.

120.

121.

Segal SS. Integration of blood ﬂow control to skeletal muscle: key role of feed
arteries. Acta Physiol Scand 168(4): 51 1-518, 2000.

Segal SS. Regulation of blood ﬂow in the microcirculation. Microcirculation 12(1):
33-45, 2005.

Sejersted OM, Hargens AR, Kardel KR, Blom P, Jensen 0, Hermansen L.
Intramuscular ﬂuid pressure during isometric contraction of human skeletal muscle.
J Appl Physio] 56(2): 287-295, 1984.

Sharkey RA, Mulloy EM, O'Neill SJ. Acute effects of hypoxaemia, hyperoxaemia
and hypercapnia on renal blood ﬂow in normal and renal transplant subjects. Eur
RespirJ 12(3): 653-657, 1998.

Shipley RD, Kim SJ, Muller-Delp JM. Time course of ﬂow-induced vasodilation
in skeletal muscle: contributions of dilator and constrictor mechanisms. Am J
Physiol Heart Circ Physiol 288(4): H1499-1507, 2005.

Shoemaker JK, Halliwill JR, Hughson RL, Joyner MJ. Contributions of
acetylcholine and nitric oxide to forearm blood ﬂow at exercise onset and recovery.
Am J Physiol 273: H2388-2395, 1997.

Shoemaker JK, Hughson RL. Adaptation of blood ﬂow during the rest to work
transition in humans. Med Sci Sports Exerc 31: 1019-1026, 1999.

Shoemaker JK, Phillips SM, Green HJ, Hughson RL. Faster femoral artery
blood velocity kinetics at the onset of exercise following short-terrn training.
Cardiovasc Res 31: 278-286, 1996.

Silvennoinen MJ, Clingman CS, Golay X, Kauppinen RA, van Zijl PC.
Comparison of the dependence of blood R2 and R2* on oxygen saturation at 1.5
and 4.7 Tesla. Magn Reson Med 49(1): 47-60, 2003.

Slade JM, Towse TF, Delano MC, Wiseman RW, Meyer RA. A gated 31P NMR
method for the estimation of phosphocreatine recovery time and contractile ATP
cost in human muscle. NMR Biomed 19(5): 573-580, 2006.

Slade J, Towse T, W Gossain, MC DeLano, RA Meyer. Cross-sectional study of
muscle post-contractile BOLD transients in Type I and Type II diabetes. Workshop
on Investigation of Human Muscle Function In Vivo, Nashville, TN, 2005.

Tadamura E, Hatabu H, Li W, Prasad PV, Edelman RR. Effect of oxygen
inhalation on relaxation times in various tissues. J Magn Reson Imaging 7: 220-225,
1997.

56

122.

123.

124.

125.

126.

127.

128.

129.

130.

131.

132.

133.

Taylor PD, Khan IY, Hanson MA, Poston L. Impaired EDHF-mediated
vasodilatation in adult offspring of rats exposed to a fat-rich diet in pregnancy. J
Physio] 558: 943-951, 2004.

Thomas GD, Segal SS. Neural control of muscle blood ﬂow during exercise. J
Appl Physiol 97(2): 731-738, 2004.

Thulborn KR, Waterton JC, Matthews PM, Radda GK. Oxygenation
dependence of the transverse relaxation time of water protons in whole blood at
high ﬁeld. Biochim Biophys Acta 714(2): 265-270, 1982.

Toussaint JF, Kwong KK, Mkparu FO, Weisskoff RM, LaRaia PJ, Kantor
HL. Perfusion changes in human skeletal muscle during reactive hyperemia
measured by echo-planar imaging. Magn Reson Med 35(1): 62-69, 1996.

Towse TF, Slade JM, Meyer RA. MRI-measured BOLD transients in skeletal
muscle after brief contractions in healthy elderly subjects. APS Intergrative Biology
of Exercise Meeting, Indianapolis, IN, 2006.

Towse TF, JM Slade, VV Gossain, MC Delano, RA Meyer. Muscle post-
contractile BOLD transients decrease with age, inactivity, and BMI, but not with
Type 1 Diabetes. Proc Int] Soc Magn Reson Med 13: 2014, 2005.

Towse TF, Slade JM, Meyer RA. Effect of physical activity on MRI-measured
blood oxygen level-dependent transients in skeletal muscle after brief contractions.
J Appl Physio] 99(2): 715-722, 2005.

Tschakovsky ME, Hughson RL. Venous emptying mediates a transient
vasodilation in the human forearm. Am J Physiol 279(3): H1007-1014, 2000.

Tschakovsky ME, Hughson RL. Rapid blunting of sympathetic vasoconstriction
in the human forearm at the onset of exercise. J Appl Physiol 94(5): 1785-1792,
2003.

Tschakovsky ME, Rogers AM, Pyke KE, Saunders NR, Glenn N, Lee SJ,
Weissgerber T, Dwyer EM. Immediate exercise hyperemia in humans is
contraction intensity dependent: evidence for rapid vasodilation. J Appl Physio]
96(2): 639-644, 2004.

Tschakovsky ME, Sheriff DD. Immediate exercise hyperemia: contributions of the
muscle pump vs. rapid vasodilation. J App] Physio] 97(2): 739-747, 2004.

Tschakovsky ME, Shoemaker JK, Hughson RL. Vasodilation and muscle pump

contribution to immediate exercise hyperemia. Am J Physiol 271(4): H1697-l701,
1996.

57

134.

135.

136.

137.

138.

139.

140.

141.

142.

143.

144.

Tyml K, Song H, Munoz P, Ouellette Y. Evidence for K+ channels involvement
in capillary sensing and for bidirectionality in capillary communication. Microvasc
Res 53(3): 245-253, 1997.

Wadington W, Hornberger J, Lansdown D, Damon B. Effect of increases in
inspired oxygen on the muscle functional MRI signal time course. Abstract: 1-2,
2005.

Wedegartner U, Tchirikov M, Schafer S, Priest AN, Kooijman H, Adam G,
Schroder HJ. Functional MR imaging: comparison of BOLD signal intensity
changes in fetal organs with fetal and maternal oxyhemoglobin saturation during
hypoxia in sheep. Radiology 238: 872-880, 2006.

Welch HG, Bonde—Petersen F, Graham T, Klausen K, Secher N. Effects of
hyperoxia on leg blood ﬂow and metabolism during exercise. J Appl Physio] 42:
385-390, 1977.

Wigmore DM, Damon BM, Pober DM, Kent-Braun JA. MRI measures of
perfusion-related changes in human skeletal muscle during progressive
contractions. J Appl Physiol 97(6): 2385-2394, 2004.

Williams DA, Segal SS. Feed artery role in blood ﬂow control to rat hindlimb
skeletal muscles. J Physiol 463: 631-646, 1993.

Wilson JR, Kapoor SC, Krishna GG. Contribution of potassium to exercise-
induced vasodilation in humans. J Appl Physio] 77(6): 2552-2557, 1994.

Wunsch SA, Muller-Delp J, Delp MD. Time course of vasodilatory responses in
skeletal muscle arterioles: role in hyperemia at onset of exercise. Am J Physiol
279(4): H1715-l723, 2000.

Yang HT, Ogilvie RW, Terjung RL. Training increases collateral-dependent
muscle blood ﬂow in aged rats. Am J Physio] 268(3) Pt 2: H1174-1180, 1995.

Yu J, Bihari A, Lidington D, Tyml K. Gap junction uncouplers attenuate
arteriolar response to distal capillary stimuli. Microvasc Res 59(1): 162-168, 2000.

Zhao JM, Clingman CS, Narvainen MJ, Kauppinen RA, van Zijl PC.

Oxygenation and hematocrit dependence of transverse relaxation rates of blood at
3T. Magn Reson Med 58: 592-597, 2007.

58

CHAPTER 3: BOLD MRI MAPPING OF TRANSIENT HYPEREMIA IN SKELETAL
MUSCLE AFTER SINGLE CONTRACTIONS.

3.1. Introduction

The blood oxygenation level-dependence (BOLD) of transverse relaxation in
tissue is a well-established contrast mechanism in magnetic resonance imaging (MRI)
(14, 27, 28, 38). BOLD contrast has been most thoroughly studied in the brain, and is
now commonly exploited for functional MRI studies (12). Of course changes in blood
oxygenation also occur in other tissues, and BOLD-based relaxation changes have also
been measured in skeletal muscle. This was ﬁrst demonstrated by Toussaint et al., who
measured decreased signal intensity (SI) in T2-weighted echo-planar images of calf
muscle during ischemia, and increased SI during the subsequent reactive hyperemia (35).
Lebon et al., showed that the time course of the SI decrease during ischemia was
consistent with the time course of hemoglobin and myoglobin saturation, which was
estimated from lH-NMR spectroscopic measurements of deoxymyoglobin (17).
Donahue showed that both T2 and T 2* decreased during ischemia, and suggested that the
difference in the magnitude of the changes in the two relaxation times could be exploited
to estimate the distribution of small versus large vessels in the muscle (7). Most recently,
Noseworthy et al., reported transient increases in SI of muscle in T 2-weighted images
during brief cycles of respiratory hyperoxia (26). The magnitude of the hyperoxia-
induced change was enhanced by prior repetitive exercise, and varied across different
muscle groups.

Despite the above studies of ischemic and hyperoxic BOLD effects, few studies

have considered if the BOLD mechanism contributes to relaxation changes observed in

59

skeletal muscle during or immediately after contractile activity. Inasmuch as muscle P02
is well known to decrease during repetitive exercise, one might expect a negative BOLD
effect in muscle during exercise (24, 30). In fact, any negative BOLD effect in muscle
during moderate or intense exercise would probably be masked by the much greater
increase in muscle cell T 2, which has been linked to osmotically driven changes in the
distribution of muscle water (20, 21). However, Hennig et al., recently reported that a
transient BOLD-like increase in SI could be detected in T 2*-weighted images in human
skeletal muscle within seconds after a single, very brief contraction. In this study, we
conﬁrm their report, and suggest that these transient changes arise at least in part from the
intravascular BOLD mechanism. The phenomenon can be exploited for functional
muscle imaging using the same analyses commonly used for BOLD-based functional
brain imaging. The results suggest that the post-contraction transients might be exploited

to map vascular function in skeletal muscle by MRI.

3.2. Methods
3.2.]. Subjects: Healthy adult (n = 19, 18-52 yr., 7 female) subjects were recruited from
the university communities. Subjects gave informed, written consent, and the studies

were approved by the University’s Committee on Research Involving Human Subjects.

3.2.2. MRI studies: Images were acquired using standard clinical extremity coils on 1.5
and 3 T GE Horizon systems (GE Medical Systems, Milwaukee, WI, USA). Subjects
were positioned supine in the imager with the foot secured to a custom-built, rigid

isometric force transducer. Localizers and anatomical images (TR 100, TE 7, 256 x 192

60

acquisition matrix, 1 NEX), one-shot spin-or gradient-echo echo-planar images (TR 500-
200, TE 40-45, 900 pulse 16-18 cm ﬁeld-of-view, 1 cm slice thickness, 62.5 kHz
bandwidth, 64 x 64 matrix) were acquired from a single axial slice transecting the belly
of the tibialis anterior muscle. Echo-planar images were acquired continuously for 4.5 —
5.5 minutes during which time subjects performed a single maximal or half-maximal, 1-
second contraction, every 30 seconds (total 7-10 contractions). Subjects were habituated
to the exercise protocol and exercise apparatus prior to data collection. During the
habituation session each subject performed two to four maximal and half-maximal, 1-
second contractions at 30-second intervals. Maximal force was the mean peak force
recorded after the strongest two contractions during this session. Force data were
digitized (model D1195B, Dataq Instruments, Akron OH, USA) at 100 HZ and recorded
on a personal computer.

In subsets of subjects who participated in the MRI experiments, the above
protocol was repeated following 5 — 10 minutes of rest in order to compare results at TR
500 vs. 2000 ms (n = 4), using spin-echo vs. gradient-echo echo-planar sequences (n = 8)
or using maximal vs. half-maximal contractions (n = 6), and all were performed in
random order at 1.5 T. In an additional subset of subjects (n = 5), the same protocol
(gradient-echo, TR 2000, TE 45) was performed in random order on a 1.5 and 3 T imager.
The apparent transverse relaxation rate, R 2* was measured in the muscles of the anterior
compartment of the shank in a subset (n = 3) of subjects at 1.5 and 3 T using the same
echo-planar sequence at 7 TE ’3 ranging from 25 to 60 ms. R2* was computed from
mono-exponential ﬁts, and the correlation coefﬁcient of the ﬁts ranged from 0.989 to

0.999. One subject participated in three of the above comparisons, and thus was studied

61

three times over a 6-month period. In addition this subject performed the same protocol
while short TE (2.2 ms) proton density images were acquired at 2 second intervals (1.5 T
spiral GRE acquisitions, TR 100, 12 arms, 2048 points/amt, 125 kHz bandwidth, 30° ﬂip
angle, 128 X 128 matrix, acquisition time 1 second). The time-course of the signal
changes was computed from a 2-3cm2 region-of—interest (ROI) in the anterior
compartment. The transient magnitude (%ASI), time-to-peak, time-to-half—recovery were
calculated from the average responses recorded from the last three to four contractions.
The relative speciﬁcity of the response to the anterior compartment muscles was
examined by cross-correlation of single voxel signal intensities versus an arbitrary,
idealized, pulsatile waveform [SI = sin(1tt/30) * exp(-t/8), repeated at 30 second intervals]
using the AFNI software package developed for brain functional imaging (15). Prior to
the cross-correlation the images with contraction induced saturation artifacts (see below)
were eliminated from the series. In some cases the AFNI 2D registration algorithm was

applied to images before analysis.

3.2.3. NIRS Studies: In a separate series of experiments, eight subjects (22-47 years old,
2 females) performed 1 second duration maximal contractions every 30 seconds while
relative hemoglobin saturation (absorption difference at 760 — 850 nm) and relative
hemoglobin content (summed absorption at 760 + 850 nm) were recorded at 1-2 Hz from
the anterior compartment muscles using a Runman CW2000 near-infrared spectrometer
(NIRS, NIM Inc., Philadelphia, PA, USA). NIRS data were also acquired during 5

minutes of cuff ischemia (thigh cuff pressure greater than 240 Torr) and subsequent

62

reactive hyperemia in a subset of 5 subjects (18). Three subjects participated in both the

MRI and NIRS studies.

3.2.4. Modeling Calculations: The potential contribution of extravascular BOLD effects
was estimated using the parallel vessel model presented by Kennan eta]. (13). In brief,
the microvasculature was modeled as a rectangular array of parallel cylindrical vessels
with a diameter of 5 pm, spaced at 25.6 pm (with a vascular volume of 3%) at an angle
30° relative to the main ﬁeld (10, 13, 18). The assumed mean diffusion coefﬁcient of
extravascular spins 2 x 10’5 cmZ/s and the susceptibility difference between tissue and
ﬁilly deoxygenated blood was assumed to be 8 x 10'2 ppm (6, 25). The simulation was
run for 30,000 spins randomly distributed in the extracellular volume as described by
Kennan et a]. (13). The vessel walls were assumed to be impermeable, and each
simulation was run for an echo time of 45ms

The potential contribution of the intravascular BOLD effects at 1.5 and 3.0 T was
estimated from the oxygen saturation dependence of blood R2 and R2* as reported by
Silvennoinen et al., assuming a microvascular hematocrit of 0.28 (20). Unfortunately,
Silvennoinen eta1., did not report blood relaxation at 3 T. Therefore, the oxygenation
dependence of blood relaxation at 3 T was estimated by interpolation between their
values reported at 1.5 and 4.7 T, assuming no oxygen-dependent effects at zero
hematocrit. The estimated dependence of blood R2 and R 2* (in s") on blood saturation

are

at 1.5 Tblood R2 = 3.4 + 6.1*(l-Y) +15="(1-)/)2 and
122* = 4.8 + 5.1*(1-r) + 20*(1—1’)2 and

63

at 3.0 T blood R2 = 7 +12*(l-Y) + 74*(1—r)2 and

122* = 6 + 6*(1-Y) + 95*(1.r)2

where Y is the fractional oxygen saturation (16). The intravascular BOLD effect
arising from the changes in T2 relaxation was calculated assuming 3% vascular volume
(speciﬁcally assuming that blood is 3% of muscle proton density), assuming slow
exchange of spins across the vessel walls and no oxygen dependence of extravascular

relaxation, according to

SI = 0.97*exp (-TE* muscle R2) + 0.03*exp (-TE* blood R2). (1)

For this calculation, TE was 45 ms, and muscle R2 and R 2* were both assumed to be 34

and 38 s'1 at 1.5 and 3.0 T, respectively.

3.3. Results: Figure 1 illustrates the time course of MRI- and NIRS measured transient
changes recorded from the anterior compartment muscles of the leg in one subject
performing a 1 second duration maximal contraction at 30 second intervals. The spikes
in the MRI data (top three panels) coincident with each contraction (force, bottom panel)
are T l desaturation and resaturation artifacts caused by shortening and deformation of the
muscle during the contraction. In the echo-planar images (top two panels) there are
transient increases in anterior muscle intensity which peak 8 seconds after each
contraction artifact, and decay away over the next 10-15 seconds. In contrast to the
contraction artifacts, the relative magnitude of these transients is not different in images

64

acquired at TR 2000 (top panel) versus 500 ms (second panel). However, no comparable
transients are evident after the contraction artifacts in the proton density images acquired
by the spiral sequence at very short TE (2.2 ms). Figure 1 also shows the transient
increases in relative heme saturation (difference, fourth panel) and heme content (sum,
ﬁfth panel) measured by NIRS during the same contraction protocol in the same subject.
Transient changes with a similar time course were recorded from anterior compartment
muscles in all subjects (Table 3.1). Although the time-to-peak and time-to-half-recovery
of the transients measured by NIRS tended to be slower than the MRI-measured
transients, this difference is likely due to the slow response time (2 seconds) of the NIRS
instrument used in this study.

The coefﬁcient of variation (SD/mean) of the MRI-measured peak transient
magnitude in one subject examined on the three separate occasions at 1.5 T was 5.1%.
However, the peak magnitude varied considerably between subjects [mean change in
signal intensity 2.6 i 0.6% (SE, n = 14), range 1.0 — 6.5%, coefﬁcient of variation 84%].
There was no signiﬁcant correlation across subjects between muscle cross-sectional area
or maximal voluntary force versus the peak transient magnitude.

Unfortunately, the NIRS device used in this study does not yield an absolute
measure of percentage hemoglobin saturation. However, a crude calibration can be
obtained by occluding limb blood ﬂow for several minutes, releasing the occlusion, and
measuring the signal change between the end of occlusion and the peak during reactive
hyperemia (18). Assuming that only changes in hemoglobin saturation contribute to the
difference signal (but see Discussion), and assuming that hemoglobin is fully desaturated

during ischemia and fully saturated during reactive hyperemia, the difference signal

65

between these extremes corresponds to the maximum 100% change in saturation. Using
this method, the post-contractile NIRS difference transients after maximal 1 second
duration contractions correspond to a change in hemoglobin saturation of 13 i 2% (mean
t SE, n = 5). The post-contractile NIRS difference signal transient magnitude was 10.8 i
1.5 fold (mean i SE, n = 8) greater than the NIRS sum transient magnitude.

As shown in Figure 3.1 and Table 3.2, the magnitude of the MRI-measured
transients was not signiﬁcantly different when measured at TR 500 versus 2000 ms in the
same subset of subjects. The magnitude was also not signiﬁcantly different using
gradient-echo versus spin-echo sequences at 1.5 T, but was signiﬁcantly less after half-
maximal versus maximal voluntary contractions (Table 3.2).

Figure 3.2 shows the estimated extravascular and intravascular dependence of
muscle SI on blood oxygenation, computed as described above, and assuming a constant
vascular volume of 3% in both cases. In both cases, the computed effects are 2 to 3-fold
greater at 3 T vs. 1.5 T. As expected from previous calculations (13), the predicted
difference between the computed spin-echo and gradient-echo extravascular BOLD
effects is small for diffusion around 5 micron diameter vessels with a diffusion
coefﬁcient of 2 x 10'5 cmZ/s. As indicated by the dashed lines in Figure 3.2, according to
these calculations a peak 13% increase in blood saturation after contraction might
increase signal intensity by 1.2 % at 1.5 T (0.2 % extravascular plus 1.0 % intravascular),
and by 2.7 % at 3 T. Thus, according to these calculations, the combined BOLD effects
can account for up to 75% of the observed transient magnitude at both ﬁelds (e.g.,

compare with Table 3.3).

66

Figure 3.3 shows an anatomical and “activation” overlay image, computed by
cross—correlation of the single voxel intensity time courses (e.g., Figure 3.3A, top) vs. the
idealized transient waveform (Figure 3.3A, bottom). As expected, the correlated
transients are largely conﬁned to the anterior compartment muscle, known to be recruited
by ankle dorsiﬂexion exercise. Similar maps were obtained in all subjects. In order to
illustrate the generality of the post-contractile transients to other muscles, one subject
performed 3 additional exercises in the same pattern of 1 second contractions every 30
seconds: ankle plantarﬂexion, forearm handgrip, and one leg knee extension (Figure 3.4).
In each case the transient response mapped primarily to the muscles expected to be

recruited by these exercises, along with scattered veins.

3.4. Discussion: This study conﬁrms the preliminary report by Hennig et al., (10) that
transient increases in muscle signal intensity can be observed by MRI after single, brief
muscle contractions. The coincidence of the MRI-measured transients and the NIRS-
measured transient increases in relative heme saturation suggests that they both arise
from transient post-contraction hyperemia after the contractions. In fact, the
phenomenon of transient hyperemia in skeletal muscle after single, brief contractions is
well-established, if not well-known, from previous studies. For example, in 1973
Mohrman, et a]. (23), reported increased vascular conductance in calf muscle of
anaesthetized dogs after 1 second duration tetani. More recently, Brock, et al. (2) studied
the transient increase in brachial artery ﬂow after single voluntary contractions of human
forearm muscles. Similar transient increases in limb blood ﬂow were observed after

rapid elevation of limbs by Tschakovsky and Hughson (36), who hypothesized that

67

muscle ﬂow transients are mediated by a veno-arterial reﬂex in response to rapid venous
emptying, although the existence of this neural network has yet to be conﬁrmed. Others
have suggested that the transient hyperemia results from an “intrinsic mechanosensitive”
property of the vasculature, the stimulus for which appears to be an increase in
transmural pressure (3, 22). Recently Clifford (3) showed that isolated rat soleus feed
arteries vasodilated in response to an increase in transmural pressure. The magnitude of
the response was blunted, but not completely abolished, by removal of the vascular
endothelium cells implicating both the vascular smooth muscle cells and endothelial
cells in the post-contraction hyperemia. The time course of the transient increases
measured in all of those studies is remarkably similar to the time course of the MRI
transients reported here. Interestingly, the physiological mechanisms responsible for
transient hyperemia after single contractions (or for that matter, muscle hyperemia during
repetitive exercise (15)) are still not fully identiﬁed. The ﬂow transients measured by
Brock, eta]. (2), were not due simply to mechanical compression caused by the
contraction, because rapid inﬂation of a cuff around the same muscles had a smaller and
less prolonged effect. The transients were unaltered by atropine infusion, and only
modestly attenuated by the Nitric Oxide Synthase inhibitor, L-NMMA.

Although the physiologic phenomenon of post-contractile ﬂow transients is well
established from previous studies, the physical mechanism for the corresponding MRI
transients reported here and by Hennig et a]. (10) is less certain. Unlike the motion
artifacts observed by MRI during contractions, the delayed signal transients cannot be

explained by T1- or proton density-related inﬂow effects, because the transient magnitude

68

is unaltered by decreased TR, and greatly diminished at very short TE. Thus, the
transients must primarily reﬂect a transient change in apparent T2 relaxation.

Hennig et al., (10) originally suggested that post-contractile MRI transients arise
from a BOLD effect, analogous to the BOLD effect commonly exploited for brain
functional imaging. The similarity between the time courses of the MRI and NIRS
transients observed in this study, and also the ﬁeld dependence of the MRI transient
magnitude, are qualitatively consistent with a BOLD mechanism. The observation that
the transient magnitude is the same using spin-echo vs. gradient-echo sequences appears
to argue against a BOLD mechanism, in as much as brain BOLD effects are well-known
to be greater in gradient- compared to spin-echo images (8, 29). However, the oxygen-
dependence of blood R2 and R2* are not substantially different (34), and therefore, the
intravascular BOLD contribution is not expected to be substantially different in gradient
vs. spin echo images. Furthermore, the relative magnitude of extravascular BOLD
effects in gradient- vs. spin-echo images depends critically on the diffusion coefﬁcient of
tissue water, as well as on the geometry of the vessels (13). For faster diffusion around
smaller vessels the static effect of vessel-induced inhomogeneity tends to average, and
the difference between gradient- and spin-echo extravascular BOLD relaxation is
minimized. The diffusion coefﬁcient of water in skeletal muscle is near 2.0 x 10’5 cmZ/s
(6, 25), or near twice that in grey matter of the brain (9). Furthermore, the distribution of
blood vessels in skeletal muscle is dominated by capillaries with mean diameter around 5
microns (19). Thus, the similar magnitude of gradient- vs. spin-echo transients observed
in this study is not necessarily inconsistent with either intravascular or extravascular

BOLD mechanisms.

69

Although our results appear qualitatively consistent with a BOLD mechanism, the
model calculations suggest that BOLD effects cannot quantitatively account for all of the
observed transient magnitude. Of course, the model calculations in Figure 3.2 depend on
many assumptions, variations in which might dramatically alter the predicted effects.
Most notably, the vascular volume of skeletal muscle is likely to vary widely between
individuals, inasmuch as muscle capillary density depends on chronic activity level (19,
33). Therefore, in some subjects muscle vascular volume may be greater than the 3 %
assumed in the model calculations. On the other hand, extravascular BOLD effects
decrease dramatically as vessel orientation approaches the main ﬁeld direction (13). The
orientation of muscle ﬁbers in human anterior tibialis muscle is nearly parallel with the
longitudinal axis of the leg ( l l, 37), and hence with the main ﬁeld direction in this study.
Because the microvessels in skeletal muscle tend to run parallel to the ﬁbers, the mean
vessel angle in anterior tibial muscle is very likely less than the 30 degrees assumed in
the calculation. Therefore, the extravascular BOLD effects simulated at Figure 3.2 are
likely overestimates, as least for the anterior tibialis muscle. Similarly, the extravascular
calculation ignores the time-dependent anisotropic nature of diffusion in muscle (4). If
the diffusion coefﬁcient of water is lower perpendicular to the ﬁbers (and therefore to the
vessels) than along the ﬁbers, then the calculated extravascular effect would be smaller
for spin-echo acquisitions. Therefore, on balance, we conclude that extravascular BOLD
effects contribute at most a very minor component to the transient changes observed in
this study.

Another source of uncertainty in the estimation of both extravascular and

intravascular BOLD effects is the accuracy of the NIRS measurements of hemoglobin

70

saturation. First, the time-resolution of the NIRS device used in this study is poor
compared to MRI, and the penetration depth of the measurement into muscles is likely
different in different individuals. Further uncertainty is caused by the presence of heme
in muscle myoglobin, which is optically indistinguishable from hemoglobin using
standard, transderrnal NIRS methods (18). Changes in myoglobin saturation could not
directly contribute to the transient increases in heme saturation after the brief
contractions, because myoglobin is well-known to be fully-saturated in muscle at rest (24,
30). However, changes in myoglobin saturation could directly contribute to the
calibration of the saturation measurement during ischemia-reperfusion. For example, if
the myoglobin heme content were equal to one-fourth the hemoglobin heme content, and
fully-desaturated during ischemia, the actual change in percent hemoglobin saturation
during the transients would be underestimated by 25 %. Thus, it is possible that the
calculation depicted in Figure 3.2 underestimates the contribution of intravascular BOLD
effects.

It should be noted that the intravascular BOLD effects calculated in Figure 3.2 are
substantially larger than the effects that would be calculated for the brain, because the T2
of skeletal muscle tissue (approximately 30 ms) is substantially shorter than the T2 of
grey matter (> 80 ms). Thus, assuming slow exchange of spins across the vessels,
oxygenation of a small fractional volume of blood adds more to the total signal in muscle
than in brain at longer echo times. For example, according to equation 1, at 1.5 T, fully-
saturated blood (blood R2 = 3.4 5") could contribute 10.9 % of the total spin—echo muscle
signal at TE = 45 ms, assuming muscle R2 of 34 s'l and only 3 % vascular volume. A

clear prediction from this calculation is that, if the slow-relaxing T2-component

71

previously observed in skeletal muscle by high-resolution relaxometry is due to the
vascular volume (16, 32), then the relative magnitude of that relaxation component
should increase with increased muscle P02.

Increased microvascular blood volume could also contribute to the transient signal
increase observed in both T2 and T 2*-weighted images after contractions. Assuming high
P02, and again assuming relatively slow-exchange of spins across the vessel walls,
increased fractional blood volume would directly add increased signal in both T2 and T2*-
weighted images, again because the T2 of oxygenated blood is much longer than the T2 of
muscle cell water. In this study there was measurable transient increase in relative heme
content after the contractions (e.g., Figure l, NIRS sum), although this increase was only
one tenth the magnitude of the transient increase in relative heme saturation (NIRS
difference).

Finally, our results do not rule out the possibility that single, brief contractions
directly induce a delayed, transient change in the T2 or apparent proton-density of muscle
cell water, unrelated to any coincident changes in vascular volume and oxygenation.
However, if such a transient intracellular T2 or proton-density change does occur, it is
unlikely that it could be related to the large increase in T2 of muscle water observed
during and after more intense, repetitive exercises. The T2 increase after intense exercise
persists for up to 30 minutes, and its development has been clearly linked to the
production of metabolic osmolites (5, 20, 21). The metabolic cost of a single l-second
duration maximal voluntary contraction in human muscle is approximately 2 umoles
ATP g", and could not produce a signiﬁcant osmotic load (31). Furthermore, the

recovery time of the transients observed here is several-fold faster than the fastest

72

metabolite recovery in human muscle after contraction (i.e., phosphocreatine resynthesis,
with half-time near 30 seconds (31)). Therefore, based on the preponderance of the
evidence available so far, we conclude that the MRI transients observed in this study
arise primarily from an intravascular BOLD effect, with an additional contribution from
increased vascular volume.

Whatever the physical mechanism(s) for the MRI signal transients observed after
single contractions, Figures 3.3 and 3.4 show that the phenomenon can be exploited for
muscle “functional” MRI using the same analysis methods commonly employed in brain
functional MRI. Of course, unlike for brain functional imaging, the location of the
mapped “activity” in muscle is not of great interest, because it is generally known what
muscles are recruited during simple exercises. 0n the other hand, the intensity and time
Course of the transients could prove interesting. Unlike the brain, the vascularity of
skeletal muscle is likely to vary among individuals, and decreases in vascular density,
conductance, and reactivity occur in various muscle and systemic diseases, for example,
diabetes (1). Thus, measurement of transient changes in muscle oxygenation and/or
microvascular volume by MRI after single contractions might be exploited as a simple

diagnostic test of peripheral vascular function.

73

Figure 3.1: Transient increases in MRI signal intensity (SI, percent baseline, top three
traces) at 1.5 T, NIRS-measured relative heme saturation (fourth trace, absorption at 760-
850 nm), and NIRS-measured relative heme content (ﬁfth trace, absorption at 760+850
nm) in anterior tibialis muscle of a subject (33 year old male) perforrmng 1 second
contractions every 30 seconds. Bottom trace is force of ankle dorsiﬂexion recorded
during the NIRS measurement. The spikes in the MRI traces coincident with the
contractions are saturation artifacts caused by muscle length changes. Note transient
increases in SI after the contractions in the echo-planar traces (TE 40 ms) and NIRS

difference signal, but not in the proton density spiral trace (TE 2.2 ms).

74

116%
114i
112
110
108

106
104
102

$1 (%)

98

EN

MR1
T2000

TE 40

 

SI (%)

‘ EPl

' TE 40

O 50 100 150 200 250

500

 

- MRI

3 TE 2.2

Spiral

 

 

O 0.2«

0 50 100 150 200 250

NIRS
Difference

 

-0.1

1.62-
v1.60‘

(volt) 760-85
0
O

m
_|_l
thin
man

 

0 50 100 150 200 250
NIRS

. Sum

 

760+850 n
2

Force (kg)
at

 

0 50 100 150 200 250

Force

 

0 50 1 00 1 50 200 250

Time (s)

75

Table 3.1: Time course of post-contraction transients measured by MRI and NIRS. The
time course of the MRI measured post-contractile muscle BOLD transients is similar to

that of the NIRS measured post-contractile changes in oxygenation. Data are presented

 

 

mean t SE.
MRI (n = 14) NIRS (n = 8)
Time-to-peak (s) 7.9 i 0.5 9.3 i 0.5
Time-to half-recovery (s) 4.6 i 0.6 6.2 a: 0.8

 

76

Table 3.2: The effects of repetition-time (TR) pulse sequence and force on MRI-
measured post-contractile BOLD transient peak magnitude, % change in signal intensity.
The magnitude of the MRI-measured post-contractile BOLD transient was not different
when the repetition time was decreased from 2000 to 500 ms, nor when acquired using a
gradient-echo versus a spin-echo pulse sequence. However, the magnitude was
signiﬁcantly greater when the force of contraction was maximal versus half-maximal.
Data presented as % change in signal intensity, mean t SE, (*) indicates a statistically

signiﬁcant difference by paired Student’s t-test.

 

 

 

 

TR 500 ms 2000 ms
(n=4) 3.18i0.6 3.24i0.7
Sequence Gradient Echo Spin Echo
(n = 8) 2.86 i 0.6 2.87 :1: 0.4
Force Half-Mgimum Maximum
(n =6) 1.55 3:05 2.36:1:O.5*

 

77

Table 3.3: The effect of magnetic ﬁeld strength on post-contractile transient peak
magnitude and R2* relaxation. Data are presented as mean t SE, (*) indicates

statistically signiﬁcant difference by paired Student’s t—test, p < 0.05, n = 5.

 

 

1.5 T 3.0 T
ASI (%) 1.58 a. 0.23 3.81 3. 0.82*
AR2*(s") 0.35 a 0.05 0.85 a 018*
R2* (5") 33.8 :l: 0.9 37.7 s 1.6

 

78

Figure 3.2: Simulated extravascular (top panel) and intravascular (bottom panel) BOLD
effects for gradient-echo (solid lines) and spin-echo (dashed lines) acquisitions in skeletal
muscle, computed as described in methods assuming 3 % vascular volume and TE 45 ms.

In each case the results are normalized to the SI computed at 100 % blood saturation.

79

Simulated Extravascular BOLD

l

 

 

illT IJIX Illlllllllllllkll
“7“4
“Suva?
"“:M“/
“.m’."/
“m2: /
:i / a.
:3“ %/
.__.:_ _/.

5 uses? as 5 958m

06 08 ‘L0

Fractional 02 saturation

04

02

00

Simulated Intravascular BOLD

~ 1.03 °/o

~ 2.26 °/o

 

 

100-

cm 8658 é a

10

08

00
Fractional 02 saturation

04

02

00

80

Figure 3.3:

A. Representative single voxel time course from anterior tibialis muscle (top) and
idealized waveform used for cross-correlation (bottom). Time points corresponding to
the contraction motion artifacts have been deleted from both waveforms.

B. Conventional spin-echo (TR 100, TE 7) axial mid-calf image (left), and
corresponding echo-planar image (GRE, TR 2000, TE 45) from the same location with
functional overlay (right) computed by cross-correlation as described in methods. The

functional overlay represents voxels with correlation coefﬁcient, r > 0.6.

81

 

 

 

 

115-

110-

A

.
5
0

ea 5

100-

95

120-

100-

....W a a a
omcmco £0

0-1

100 150 200 250

Time (s)

50

 

82

Figure 3.4. Convention spin-echo (left, TR 500, TE 20) and corresponding echo-planar
images with functional overlay (right, GRE, TR 1000, TE 45) from a subject (21 year old
female) performing ankle plantarﬂexion (top), forearm handgrip (middle), and one-leg

knee extension (bottom) contractions all 1 second duration at 30 second intervals.

83

 

10.

11.

References

Baron AD. Vascular reactivity. Am J Cardiology 84(1A): 251-27], 1999.

Brock RW, Tschakovsky ME, Shoemaker JK, Halliwill JR, Joyner MJ,
Hughson RL. Effects of acetylcholine and nitric oxide on forearm blood ﬂow at
rest and after a single muscle contraction. J Appl Physiol 85(6): 2249-2254, 1998.

Clifford PS, Kluess HA, Hamann JJ, Buckwalter JB, Jasperse JL. Mechanical
compression elicits vasodilatation in rat skeletal muscle feed arteries. J Physiol 572:
561-567, 2006.

Damon BM, Ding Z, Anderson AW, F reyer AS, Gore JC. Validation of
diffusion tensor MRI-based muscle ﬁber tracking. Magn Reson Med 48(1): 97-104,
2002.

Damon BM, Gregory CD, Hall KL, Stark HJ, Gulani V, Dawson MJ.
Intracellular acidiﬁcation and volume increases explain R(2) decreases in exercising
muscle. Magn Reson Med 47: 14-23, 2002.

de Graaf RA, van Kranenburg A, Nicolay K. In vivo 3 lP-NMR diffusion
spectroscopy of ATP and phosphocreatine in rat skeletal muscle. Biophys J 78:
1657-1664, 2000.

Donahue KM, Van Kylen J, Guven S, El-Bershawi A, Luh WM, Bandettini
PA, Cox RW, Hyde JS, Kissebah AH. Simultaneous gradient-echo/spin-echo EPI
of graded ischemia in human skeletal muscle. J Magn Reson Imaging 8(5): 1106-
1113, 1998.

Gati JS, Menon RS, Ugurbil K, Rutt BK. Experimental determination of the
BOLD ﬁeld strength dependence in vessels and tissue. Magn Reson Med 38(2):
296-302, 1997.

Helenius J, Soinne L, Perkio J, Salonen O, Kangasmaki A, Kaste M, Carano
RA, Aronen HJ, Tatlisumak T. Diffusion-weighted MR imaging in normal human
brains in various age groups. AJNR Am J Neuroradiol 23: 194-199, 2002.

Hennig J SK, Schreiber A. Time resolved observations of BOLD effect in muscle
during isometric exercise. Proc Int Soc Magn Reson Med 8: 1, 2000.

Hodges PW, Pengel LH, Herbert RD, Gandevia SC. Measurement of muscle
contraction with ultrasound imaging. Muscle Nerve 27: 682-692, 2003.

85

12.

13.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

Howseman AM, Bowtell RW. Wellcome. Functional magnetic resonance
imaging: imaging techniques and contrast mechanisms. Philos Trans R Soc Lond B
Biol Sci 354(1387): 1 179-1194, 1999.

Kennan RP, Zhong J, Gore JC. Intravascular susceptibility contrast mechanisms
in tissues. Magn Reson Med 31(1): 9-21, 1994.

Krishna MC, Subramanian S, Kuppusamy P, Mitchell J B. Magnetic resonance
imaging for in vivo assessment of tissue oxygen concentration. Semin Radiat Oncol
11:58-69, 2001.

Laughlin MH, Korthuis, RJ , Dunker, DJ, Bache, RJ. Control of Blood Flow to
cardiac and skeletal muscle during exercise. Handbook of Physiology 12: 705-769,
1996.

Le Rumeur E, De Certaines J, Toulouse P, Rochcongar P. Water phases in rat
striated muscles as determined by T2 proton NMR relaxation times. Magn Reson
Imaging 5: 267-272, 1987.

Lebon V, Brillault-Salvat C, Bloch G, Leroy-Willig A, Carlier PG. Evidence of
muscle BOLD effect revealed by simultaneous interleaved gradient-echo NMRI and
myoglobin NMRS during leg ischemia. Magn Reson Med 40: 551-558, 1998.

McCully K and Hamaoka T. Near-infrared spectrosc0py: what can it tell us
about oxygen saturation in skeletal muscle? Exerc Sport Sci Rev 28: 123-127, 2000.

Melo RM, Martinho E, Jr., Michelini LC. Training-induced, pressure-lowering
effect in SHR: wide effects on circulatory proﬁle of exercised and nonexercised
muscles. Hypertension 42: 851-857, 2003.

Meyer RA, Prior BM. Functional magnetic resonance imaging of muscle. Exerc
Sport Sci Rev 28(2): 89-92, 2000.

Meyer RA, Prior BM, Siles RI, Wiseman RW. Contraction increases the T2 of
muscle in fresh water but not in marine invertebrates. NMR Biomed 14: 199-203,

2001.

Mohrman DE, Sparks HV. Myogenic hyperemia following brief tctanus of canine
skeletal muscle. Am J Physiol 227(3): 531-535, 1974.

Mohrman DE and Sparks HV. Role of potassium ions in the vascular response to
a brief tetanus. Circ Res 35(3): 384-390, 1974.

Mole PA, Chung Y, Tran TK, Sailasuta N, Hurd R, Jue T. Myoglobin

desaturation with exercise intensity in human gastrocnemius muscle. Am J Physiol
277(1): R173-l80, 1999.

86

25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

35.

Morvan D and Leroy-Willig A. Simultaneous measurements of diffusion and
transverse relaxation in exercising skeletal muscle. Magn Reson Imaging 13: 943-
948, 1995.

Noseworthy MD, Bulte DP, Alfonsi J. BOLD magnetic resonance imaging of
skeletal muscle. Seminars in musculoskeletal radiology 7(4): 307-315, 2003.

Ogawa S, Lee TM, Kay AR, Tank DW. Brain magnetic resonance imaging with
contrast dependent on blood oxygenation. Proc Natl Acad Sci U S A 87: 9868-9872,
1990.

Ogawa S, Menon RS, Kim SG, Ugurbil K. On the characteristics of functional
magnetic resonance imaging of the brain. Annu Rev Biophys Biomo] Struct 27: 447-
474, 1998.

Ogawa S, Menon RS, Tank DW, Kim SG, Merkle H, Ellermann JM, Ugurbil
K. Functional brain mapping by blood oxygenation level-dependent contrast
magnetic resonance imaging. A comparison of signal characteristics with a
biophysical model. Biophys J 64: 803-812, 1993.

Richardson RS, Newcomer SC, Noyszewski EA. Skeletal muscle intracellular
P0(2) assessed by myoglobin desaturation: response to graded exercise. J Appl
Physiol 91: 2679-2685, 2001.

Rossiter HB, Ward SA, Doyle VL, Howe FA, Griffiths JR, and Whipp BJ.
Inferences from pulmonary 02 uptake with respect to intramuscular
phosphocreatine kinetics during moderate exercise in humans. J Physiol 518: 921-
932, 1999.

Saab G, Thompson RT, Marsh GD. Multicomponent T2 relaxation of in vivo
skeletal muscle. Magn Reson Med 42: 150-157, 1999.

Shono N, Urata H, Saltin B, Mizuno M, Harada T, Shindo M, Tanaka H.
Effects of low intensity aerobic training on skeletal muscle capillary and blood
lipoprotein proﬁles. J Atheroscler Thromb 9: 78-85, 2002.

Silvennoinen MJ, Clingman CS, Golay X, Kauppinen RA, van Zijl PC.
Comparison of the dependence of blood R2 and R2* on oxygen saturation at 1.5
and 4.7 Tesla. MagnReson Med 49(1): 47-60, 2003.

Toussaint JF, Kwong KK, Mkparu FO, Weisskoff RM, LaRaia PJ, Kantor

HL. Perfusion changes in human skeletal muscle during reactive hyperemia
measured by echo-planar imaging. Magn Reson Med 35(1): 62-69, 1996.

87

36.

37.

38.

Tschakovsky ME, Hughson RL. Venous emptying mediates a transient
vasodilation in the human forearm. Am J Physiol: Heart Circ Physiol 279( 3):
H1007-1014, 2000.

Vermathen P, Boesch C, Kreis R. Mapping ﬁber orientation in human muscle by
proton MR spectrosc0pic imaging. Magn Reson Med 49(3): 424-432, 2003.

Wacker CM, Hartlep AW, Pﬂeger S, Schad LR, Ertl G, Bauer WR.
Susceptibility-sensitive magnetic resonance imaging detects human myocardium
supplied by a stenotic coronary artery without a contrast agent. J Am Coll Cardiol
41: 834-840, 2003.

88

CHAPTER 4: EFFECT OF PHYSICAL ACTIVITY 0N MRI-MEASURED BLOOD
OXYGEN LEVEL-DEPENDENT TRANSIENTS IN SKELETAL MUSCLE AFTER
BRIEF CONTRACTIONS.

4.1. Introduction

The beneﬁcial effects of physical activity on health and longevity are well-known
(1), and to a signiﬁcant extent these beneﬁts may arise from the effects of activity on
vascular function (13). Documented vascular changes associated with aerobic exercise
training include both macrovascular adaptations (e. g., increased arterial compliance (12),
increased ﬂow-mediated arterial dilation (5)) and microvascular adaptations (e. g.,
increased vascular density, enhanced arteriolar endothelium-mediated dilation (7, 14)).
Assessment of the macro-vascular adaptations to exercise training can be accomplished
by ultrasound or magnetic resonance imaging of major conduit vessels such as the
brachial and popliteal arteries. However, direct assessment of microvascular structure
and function in human subjects in response to exercise or other interventions has been
limited to superﬁcial measurements, for example in the skin (8, 16), or to more invasive
measurements including contrast-enhanced ultrasound and biopsy samples (4, 10, 31).
Thus, to date, the microvascular adaptations in human muscle during disuse or after
training have been largely inferred from gross measurements of muscle blood ﬂow.

Magnetic resonance images of muscle and other tissues are sensitive to micro-
vascular density, perfusion, and oxygenation, as well as to the cellular properties of the
surrounding parenchymal tissue. For example, one version of the brain “functional” MRI
methods now widely used to map neural activity is not actually a measure of neural
activity per se, but is instead an indirect measure of the local micro-vascular response to

neural activity. This brain functional imaging method relies on the fact that the magnetic

89

susceptibility and T2 relaxation time are less in oxygenated blood than in deoxygenated
blood, a phenomenon referred to as the blood oxygen level-dependent (BOLD) effect (16,
21 ). In activated brain regions, the local increase in blood ﬂow exceeds the local increase
in oxygen consumption, so blood oxygen saturation increases, apparent T2 relaxation time
decreases, and the MR signal intensity increases in T2-weighted images. Thus, when
applying this method to measure neural activity an implied assumption is that vascular
density and reactivity are the same in different regions of the brain, and in different
individuals.

A previous report (18) showed that a transient BOLD effect analogous to that in
the brain could be measured by MRI in skeletal muscles of healthy subjects after single,
1- second duration maximal isometric contractions. The time course of the BOLD
transients is similar to the time course of transient hyperemia measured in major conduit
arteries after single contractions of human (2, 3, 28) and dog muscles (8, 19). As in the
brain, the transients are caused at least in part by increased blood oxygen saturation (18),
presumably because the transient hyperemia delivers oxygen in excess of that required to
restore the small PCr depletion (approximately 2 mM/s (22)) during a brief contraction.
However, unlike in the brain, one would expect both the micro-vascular density and
reactivity in skeletal muscle to vary with subject physical activity level. In fact, in the
previous study (18) the magnitude of the post-contractile BOLD transients did vary
widely between different subjects, although subject activity level was not recorded in that
study. Therefore, the main‘purpose of this study was to examine the magnitude and time
course of muscle post-contractile BOLD transients in the anterior tibialis muscle of

healthy sedentary vs. chronically active human subjects as a measure of microvascular

90

reactivity. In addition, to assess macrovascular reactivity, a physical attribute that is
often thought to differ among individuals of different activity levels, anterior tibial blood
ﬂow after repetitive, dynamic ankle dorsiﬂexion exercise was measured in the same
subjects by conventional phase-contrast CINE MR angiography (17). The results
indicate that chronic activity enhances the magnitude of the post-contractile BOLD
contrast by over 3-fold, but has no effect on the peak muscle blood ﬂow after isolated,
repetitive exercise of the same muscle. Thus, post-contractile BOLD transients may be a
more sensitive index of peripheral muscle vascular conditioning than conventional

measurements of peak muscle blood ﬂow.

4.2. Methods

4.2.1. Subjects: Sixteen subjects (18 — 34 yr. of age, 3 female) were recruited from the
university community. Prior to participation the subjects gave informed written consent,
in accordance with the University’s Committee on Research Involving Human Subjects.
All subjects were apparently healthy and were not taking any medications known to
affect blood ﬂow. Subjects were asked to refrain from strenuous physical activity on the
day of the testing. To limit the potential effects of food or caffeine on blood ﬂow
subjects were asked to not eat for two hours prior, nor consume any caffeinated drinks

three hours prior to their scheduled visit.

4.2.2. Physical Activity: Subjects were selected for either the active or sedentary group

on the basis of their self-reported physical activity levels. Subjects reporting

participation in running or other aerobic training greater than 30 minutes a day and at

91

least 5 days/wk were assigned to the active group; subjects in the sedentary group
reported no regular participation in physical activity. Physical activity levels were
conﬁrmed using a 7-day physical activity diary (26) and the 7-day physical activity recall

questionnaire as described by Sallis et a].(23).

4.2.3. MRI measurements: All MRI images were acquired using a standard clinical
extremity coil on a 1.5 T GE Horizon system (GE Medical Systems, Milwaukee, WI,
USA). Subjects lay supine in the imager with both legs extended. The subject’s right
foot was secured to the plate of a custom-built foot device using a nylon strap with
Velcro® closures. The angle of the footplate was either ﬁxed at 120°, for isometric
exercise, or could be moved through a 30° range of motion from 120° to 90°, for dynamic
exercise. The force system consisted of a load cell (Interface Inc., Model SSM-EV-250,
Scottsdale AZ.) mounted to the underside of the footplate. Force during the isometric
and dynamic exercise was digitized, (DATAQ Instruments, model DI-195B, Akron OH)
sampled at 60 Hz, and recorded on a personal computer. Force during both the isometric
and dynamic exercise was measured as the peak force during each contraction.

T l-weighted (3-Plane, TR 100 ms, TE 1.6 ms, 24 cm ﬁeld-of-view (F 0V), 5 mm

slice thickness, 11 slices per plane, 256 x 128 acquisition matrix, 1 NEX ) and T 2-

weighted (axial fast-spin-echo, TR 1500 ms, TE 24 ms, echo-train length 4, 256 x 160
acquisition matrix, 16 cm FOV, 1 cm slice, 1 NEX) images were acquired to locate the
largest cross-sectional area of the anterior tibialis muscle. One-shot gradient-recalled

echo-planer images (TR 1000 ms, TE 40 ms, 90° pulse, 18 cm FOV, 1 cm slice thickness,

62.5 kHz bandwidth, 64 x 64 acquisition matrix) were acquired from a single axial slice

92

transecting the largest cross-sectional area of the tibialis anterior muscle. Echo-planar
images were acquired continuously for 4 minutes, during which time subjects performed
a single, l-second duration maximal isometric ankle dorsiﬂexion every 30 seconds (total
of 7 contractions). The time course of signal intensity (SI) changes in the anterior tibialis
muscle and in posterior muscles were computed from manually demarked regions-of-
interest (ROI), drawn with care taken to exclude any vessels resolved in the
corresponding anatomical images. The peak change in SI above baseline, time-to-peak,
(time in seconds from the end of the contraction artifact to the peak change in SI above
baseline) and half-recovery time (time in seconds from the peak change in SI above
baseline until the time the SI recovered to half of the maximal change from baseline) was
calculated for the post-contractile transients as described previously (18).

Following the above single-contraction protocol, a set of 2D gradient-recalled-
echo time-of—ﬂight (TOF) ﬂow images was acquired to identify suitable axial/oblique
planes for ﬂow measurements. The 2D-TOF sequence consisted of 92 adjacent axial
images (TR 18 ms, TE 4.5 ms, 45° pulse, 16 cm FOV, 1.5 mm slice thickness, 256 x 128
acquisition matrix, 1 NEX) centered on a region 5 cm below the ﬁbular head. The axial
images were used to construct a 3D representation of the vessels within that region.
Based on the 3D image, a pair of parallel slices was chosen, one transecting the popliteal
artery 1 —2 cm above the popliteal bifurcation and the second transecting both the anterior
and posterior tibial arteries 1-3 cm below their bifurcation from the p0pliteal artery. The
two parallel slices were prescribed as near as possible to be perpendicular to the axis of

the two, tibial arteries.

93

Flow velocity images (TR 18 ms, TE 6 ms, 30° pulse, 1 cm slice thickness, 14 cm
FOV, 256 x 160 acquisition matrix, 1 NEX) of the selected slices were acquired in
retrospectively ECG-gated CINE mode as described previously (19). This method
depends on the measurement of the extra phase (A0) acquired by spins moving along the
direction of a bipolar ﬂow-encoding gradient. The extra phase depends directly on
velocity V (cm/s) according to A0 = y A TV, where y (rad/Gauss) is the gyromatic ratio, A
is the time integral of gradient lobes (Gauss*s/cm), and T is the time between the two
gradient lobes. In this study, the ﬂow-encoding gradient was applied perpendicular to the
prescribed slices (i.e., parallel to the vessels), with maximum velocity encoding (VENC,
corresponding to at 180° phase shifts) set at 160 cm/s. Retrospective gating of the data
acquired over 160 heart beats (total acquisition time 2-4 min, depending on the subject’s
heart rate) yielded 32 cardiac-gated ﬂow-velocity and magnitude images per slice. Flow
(ml/min) was calculated from the individual velocity images by integrating velocity
(cm/s) across the area (cm2) of each vessel as described previously (17). Mean ﬂow in
each vessel was then calculated from the mean across all 32 images in each set.

Vessel ﬂow was measured immediately before and twice during the recovery
period after the subjects performed 2 min of dynamic ankle dorsiﬂexion exercise at 50 %
duty cycle, 0.5 Hz contraction rate. For each contraction the subjects moved the footplate
through a 30° range of motion (120° to 90°) against a resistance applied by rubber tubing.
When the footplate was at 900 relative to the perpendicular the resistance applied by the
tubing was approximately equal to 40% of the subjects’ isometric maximal. This
exercise protocol has been shown to activate the anterior tibialis muscle without

signiﬁcant activation of plantar ﬂexor muscles (6).

94

Magnitude images reconstructed from the velocity-encoded data sets were used to
estimate indices of arterial compliance and ﬂow-mediated dilation. Apparent arterial
compliance was estimated as % change in anterior tibial artery cross-sectional area
(100*[systolic vessel area -diastolic vessel area]/diastolic vessel area) from the ﬁrst set of
post-exercise velocity-encoded images. F low-mediated dilation was calculated as the
relative change in anterior tibial artery area during diastole from resting to ﬁrst post-

exercise scans (100*[post-exercise vessel area — resting vessel area]/resting vessel area).

4.2.4. Near-infrared-spectroscopic (NIRS) measurements: On a different experimental
day the subjects repeated the above single contraction protocol (i.e., l-second duration
maximum isometric contractions at 30 second intervals) while relative hemoglobin
saturation was recorded using either a NIM Runman CW2000 dual wavelength
spectrometer (NIM Inc., Philadelphia, PA.) or an INVOS Cerebral Oximeter (Somanetics
Corporation, Troy, Michigan). Following the contraction protocol, saturation data was
acquired during 4-8 minutes of cuff ischemia (thigh cuff pressure greater than 220 Torr)
and the subsequent hyperemia after release of the cuff. The magnitude of the post-
contraction saturation transients is reported as percent of the maximum change observed

after release of the cuff, as described previously (18, 20).

4.2.5. Statistics: Comparisons between groups for descriptive characteristics, mean peak
BOLD magnitude, time-to-peak, and half-recovery, apparent arterial stiffness and ﬂow-
mediated dilation were made using a Student’s t-test. A Folded Form F-statistic was used

to test the assumption of equal variances. If the assumption of equal variances was

95

violated the Satterthwaite approximation for degrees-of freedom was used. Time-series
data from the BOLD and ﬂow portions of the study were analyzed using a two-factor
(group x time) ANOVA, with repeated measures on time point. Data were analyzed
using SAS statistical software package version 9.1.2 (Cary, NC.), using the MIXED
procedure and the REPEATED statement. The appropriate covariance matrix for the
repeated measure was selected based on the structure of the time-series data and the ﬁt
statistics. Data are presented as mean :t standard deviation or standard error where

appropriate.

4.3. Results: Physical characteristics of the subjects are shown in Table 1. There were no
differences between groups in age, height, weight, or maximum cross-sectional area of
the anterior tibialis muscle. The active group was signiﬁcantly more active than the

inactive, sedentary group as estimated by the physical activity questionnaire (42.4 i 3.7

vs. 32.3 i 0.6 (SD) kcal/kg/day, respectively, p<0.001).

Figure 4.1 shows representative axial anatomical and corresponding echo-planar
images from an active and a sedentary subject. The green marks on the echo-planar
images enclose the ROI’s drawn for analysis of the time course of SI changes during the
brief isometric contraction protocol. Figure 4.2 shows the time course of SI changes (as
percent change from baseline) in the anterior tibialis muscle ROI (top row) and in the
posterior muscle R01 (next row) for the same two subjects. The spikes in both anterior
and posterior muscle SI coincident with the contractions (force, third panels) are
saturation artifacts caused by muscle length changes and distortion during the

contractions. As reported previously (18), these motion artifacts are followed by delayed,

96

transient increases in S1 in the anterior, but not in the posterior muscles. The bottom
panels show the mean transient response in anterior muscle, obtained by averaging the
responses after each contraction, and clearly illustrate the larger response observed in the

active compared to the sedentary subject.

On average the peak magnitude of the SI transients was over 3-fold larger in the
active compared to the sedentary group (Table 4.2). The time to peak-magnitude
(measured in seconds after the end of the motion artifact) was similar in the two groups.
However, the half-recovery time was signiﬁcantly longer in the trained compared to the
sedentary group (Table 4.2). Neither the mean peak magnitude nor peak muscle force
changed signiﬁcantly over the course of the 7 contractions in either group, and there was
no signiﬁcant relationship between peak transient magnitude vs. muscle cross-sectional
area (r2 = 0.12, p = 0.20, n = 16) or force of contraction (r2 = -0.033, p = 0.48). NIRS
hemoglobin saturation measurements during the single contraction protocol were
unsuccessﬁll in 5 subjects due to movement of the probes or other instrument
instabilities. Among the remaining subjects, the change in relative hemoglobin saturation
after single contractions tended to be greater in active (14.1 3: 2.6 % [SE], n = 5) 1
compared to sedentary subjects (7.6 i: 1.4 %, n = 6), but this trend was not statistically
signiﬁcant (p = 0.07).

Figure 4.3 shows representative magnitude images from a subject before and after
the dynamic, repetitive exercise, illustrating the location of the ﬂow measurements in
popliteal, anterior tibial, and posterior tibial arteries. Figure 4.4 shows representative
cardiac-gated arterial ﬂow waveforms derived from the pre-exercise and ﬁrst post-

exercise sets of ﬂow images in the same subject. There was no signiﬁcant difference

97

between groups in cross-sectional area or mean pre-exercise ﬂow in any of the three
arteries. Peak force decreased to a similar extent in the two groups by the end of the
repetitive exercise (11.1 i 3.7 [SE] vs. 15.9 3c 5.1 % decrease in active vs. sedentary,
respectively). As expected the increase in ﬂow after this fatiguing, repetitive exercise
was most dramatic in the anterior tibial artery, which supplies the exercised muscle
(Figure 4.5). However, there was no signiﬁcant difference between groups in post-
exercise ﬂow in any of the arteries, either at the two measured time points, or when ﬂow
immediately after the exercise was estimated by extrapolation assuming exponential ﬂow
recovery (plotted at time zero in Figure 4.5). There were trends toward greater ﬂow in
the posterior tibial (ANOVA group x time interaction, p = 0.15) and popliteal (p = 0.08)
arteries in the active compared to the sedentary group, but these trends did not reach
statistical signiﬁcance. Finally, there was no difference between groups in the index of
anterior tibial artery compliance (% change in arterial cross-sectional area from diastole
to systole, 53.4 i 16.4 vs. 58.0 i 23.3 % [SE] in active and sedentary, respectively) or
ﬂow-mediated dilation (% change in diastolic cross-sectional area after exercise, 66.8 i

16.2 vs. 59.7 i 14.6 %

4.4. Discussion: The main result of this study is that the transient increase in MRI-
measured S1 in anterior tibialis muscle following single, l-second contractions is over 3-
fold greater in chronically active compared to sedentary subjects (Figure 4.2, Table 4.2).
In contrast, there was no signiﬁcant difference between groups in anterior tibial artery
ﬂow, or in any other macro-vascular measurement, in response to a 2-minute dynamic

dorsiﬂexion exercise. Thus, it appears that the MRI-measured contrast after single, brief

98

contractions is a more sensitive index of skeletal muscle vascular conditioning than

conventional measurements of vessel ﬂow after repetitive exercise.

The physical mechanism for the MRI-measured BOLD transients after single
contractions is not fully understood. The time course of the transients is similar to the
time course of increased hemoglobin saturation measured by near-infrared spectroscopy
(18), as well as to the time course of conduit artery hyperemia after single contractions of
human forearm muscles (2). Previous model calculations suggested that the MRI
transients arise predominantly from an intravascular BOLD effect ( l8), i.e., from the
increasing contribution of well-oxygenated blood to the total muscle signal when blood
ﬂow transiently exceeds muscle oxygen consumption. Therefore, assuming that the
oxygen cost of muscle contractions is not substantially different in active compared to
sedentary subjects (1 1), our results suggest that the hyperemia after single, brief
contractions is substantially larger in active subjects. The trend toward increased
hemoglobin saturation after contractions in the active subjects is consistent with this
mechanism. Surprisingly, to our knowledge no previous study has examined the effect of
training status on the magnitude of muscle hyperemia after single contractions. However,
there is evidence that the immediate increase in muscle blood ﬂow at the onset of

repetitive exercise occurs more quickly after training (25).

Increased microvascular volume might also contribute to the larger MRI-
measured BOLD transients in active subjects, even if the net change in hemoglobin
saturation after the contraction were the same as in sedentary subjects. Assuming the
same mean change in saturation, but a 50% larger microvascular volume, one would

naively predict a 50% larger intravascular BOLD transient. This possibility might be

99

tested by varying muscle P02 independent of blood ﬂow, for example, by hyperoxia.
Interestingly, Noseworthy et a]. (20) already reported that the increase in SI of resting
muscle during cycles of hyperoxia was greater in the soleus compared to the
gastrocnemius muscle of human subjects, a result attributed to greater vascular volume in
the soleus. 0n the other hand, the effects of vascular volume on the BOLD signal are
more difﬁcult to predict if extravascular effects are considered, because extravascular
BOLD effects depend strongly on the orientation of the vessels in the magnetic ﬁeld (21).
For example, it may be that the greater BOLD contrast in soleus compared to
gastrocnemius (18, 20) is in part due to different muscle ﬁber and vessel orientations in

these muscles (30).

Whatever the precise physical mechanisms of the MRI-observed transients, it is
likely that they are related to the post-contraction hyperemia observed in many previous
studies of human (2, 3, 28) and dog (8, 19) muscles. Despite over four decades of study,
the physiological mechanism for this “immediate” (2 8) hyperemia in response to a
contraction is still unknown. The role of the “muscle pump” in hyperemia after single
contractions is still debated (29), although recent studies strongly suggest that local
microvascular dilation in response to as- yet-unidentiﬁed signal(s) is more important than
the muscle pump (8, 28). Our results agree with this conclusion, inasmuch as muscle
force, and therefore presumably the muscle pump, was the same in our active and
sedentary subjects, but the post-contractile transients were dramatically larger in the
active subjects. Tschakovsky and Hughson (27) showed that hyperemic transients
comparable to those observed after single contractions occur in the brachial artery after

raising the arm, suggesting that the signal might result from rapid venous emptying.

100

However, a more recent study found no effect of arm position on contraction-induced
hyperemia (28). Similarly, neither sympathectomy nor any speciﬁc inhibitory drug (e.g.,
atropine , L-NAME, ketorolac) has been shown to abolish the phenomenon (24, 29) . 0n
the other hand, the hypothesis that the release of potassium (19) and/or other substances

from active muscle cells triggers “immediate” hyperemia has not been clearly disproved.

It may seem surprising that the estimated peak ﬂow in the anterior tibial artery
after the repetitive exercise was similar in the active and sedentary subjects in this study,
in view of the many previous reports that chronic activity or training increases peak
muscle blood ﬂow (9, 14, 15). However, there was a trend toward greater popliteal and
posterior artery ﬂows in the active subjects compared to sedentary subjects. The mean
difference in peak popliteal ﬂows (Figure 5, 439 vs. 309 ml/min, or 42% higher in the
active subjects) is similar to the difference reported in a previous study of peak muscle
ﬂow in active vs. sedentary subjects during exercise of a small muscle mass (9).
Interestingly, the higher popliteal ﬂow after exercise in the active subjects was in part
accounted for by higher ﬂow in the posterior tibial artery, suggesting that there might be
greater collateral ﬂow from the posterior to the anterior muscle compartments in the
active subjects. Exercise training has been shown to increase collateral blood ﬂow to
muscles, at least in rats (32). However, despite the fact that ankle dorsiﬂexion exercise
nominally recruits only the anterior muscles, we cannot rule out the possibility that
posterior muscle perfusion was increased to a greater extent in the active subjects. In any
case, this result illustrates both the unique ability of MR angiography to simultaneously
measure ﬂow in multiple vessels, and a potential pitfall in the estimation of muscle

perfusion from measurements of ﬂow in major conduit vessels.

101

In summary, this study shows that the ﬂow-related muscle BOLD-transients
observed after single, brief contractions are dramatically enhanced in physically active
compared to sedentary subjects. Measurement of these transients by MRI or by other
methods may provide a sensitive index of peripheral microvascular function and its
response to therapy in patients with diabetes or other diseases which alter peripheral

vascular health.

 

 

102

Table 4.1: Subject physical characteristics. The active and sedentary subjects were

similar in age, height, weight and the cross-sectional area of the muscles in the anterior

compartment. Data are presented mean i SD.

 

Active (n = 8, 2 female) Sedentary (n = 8, 1 female)

 

Age (years) 24.9 :1: 4.8 24.6 i 2.9
Height (cm) 178.1 :t 7.7 171.3 :t 10.3
Body weight (kg) 66.8 i 8.8 72.6 i 14.0
Ant. Tibialis x-section (cmz) 10.8 :h 1.1 12.3 i2.1

 

103

Anterior
I _.-

Posterior

 

Figure 4.1: Representative anatomical (top: fast-spin-echo, TR/TE=1500/24) and echo-
planar (bottom: TR/TE=1000/40) images from an active (left) and sedentary (right)
subject. The voxels marked in green on the echo-planar images surround the ROI’s from

which the time courses of SI change were obtained.

104

Figure 4.2: Representative time course of SI changes in anterior tibialis (top panels) and
posterior muscle (second panels) during single contraction protocol. The active (left) and
sedentary (right) subjects are the same as in Figure 4.1. The spikes coincident with the
contractions (force, third panel) are due to changes in signal saturation when the muscles
move in the imaged slice during contraction and relaxation (18). The bottom panel

shows the response for each subject averaged over the 7 contractions.

105

Sedentary

Active

 

5 0 5 0
1 1 O 0

1 1 1 1

g _m 2.29:. 3:25

lain.“

H
U

lilUlt

 

llilwi

5 0 5 0
1 1 0 0
1 1 1 4|

3.. a his: 8:25

100 150 200 250

50

100 150 200 250

50

 

 

 

 

 

 

 

 

 

 

 

0
5
2
0
0
2
0
) 5 \II
(5‘ 1 151
e e
m m
T 0 i
0 T
1
.0
5
. . . 4 0. . ] l4
5 0 5 0 5 0 5 5 5
1| 4| 0 0 2 2 41 w 0 .
4| 1 4| 1
Eu 3.3
3.5 28:58:28“. r \zv u
0
5
A 2
F
IJ O
0
w 2
J
0 ﬁ
) 5 ) i.
kw 1 kw
e e i
m 111% m
T 0 i
0 T
1
ii i
0 v
i 5
5 0 5 0 5 0 5 0 5 0 5
41 4| 0 AU 2 2 1 4| .
1 1 4| 1

3.. _m 28:: 3:23;

rEEz. 020".

150 200 250
Time (s)

100

50

100 150 200 250

50

0

Tlme (s)

 

 

.m
o
o
m.
.....
MD
I
ll|+1111111no
i.
ii“ .
8 6 4 2 0 8
0 o 0 0 0 9
1 1 1 1 1
3.; _m saw: 523:6.
m
.m
s
n
a
k «v
m ..
d i
m a/ .-
M o
be
m D x
.91. o
o I.
M I,
O
.0,
116
llllo 1
8 6 4 2 0 8
0 0 O 0 0 9
1 1 1 4| 1

1:; _w .522 cocoa—.3

 

 

30

20

1O

30

20

10

Time (s)

Time (s)

106

Table 4.2: Force and post-contraction BOLD transient contrasts (mean i SE) in the
muscles of the anterior compartment after l-second maximal isometric ankle
dorsiﬂexion. The active group had signiﬁcantly higher peak BOLD transients than the
sedentary subjects despite no difference in maximal force. In addition, the time-to—half—
recovery was longer in the active versus the sedentary subjects. (*) Indicates statistically

signiﬁcant difference between groups, Student’s t-test (p<0.05).

 

 

Active Sedentary
Peak BOLD (% change in SI) 5.5 :t 1.0 1.5 i 0.4 *
Time-to-peak (sec) 6.7 i 0.5 5.8 i 0.3
Half-recovery (sec) 5.4 :t 0.4 2.7 d: 0.3 *
MVC (N/cmz) 22.7 3: 1.5 19.4 3: 2.0
End Force (% Initial) 95.1 :1: 4.0 98.1 :1: 3.0

 

107

Pre-Exercise Post-

? Popliteal
B .r Artery
<1: “Vein

G
.2
1'6

8
:13
m

E
3 Post./'.

m Tibial

 

Figure 4.3: Example magnitude images from the cardiac-gated phase-contrast ﬂow
study, illustrating location at which ﬂow measurements were made in popliteal (top) and
tibial (bottom) arteries before (left) and alter repetitive exercise. These images are from

peak-systole in the same active subject shown in Figures 4.1 and 4.2.

108

 

Figure 4.4: Example cardiac-gated ﬂow waveforms from anterior tibial (top), posterior
tibial (middle), and popliteal (bottom) arteries before (open circles) and after (ﬁlled

circles) repetitive ankle dorsiﬂexion exercise. Results from the same subject as Figure. 4

109

Flow (ml/min)

Flow (ml/min)

Flow (ml/min)

250 -

200 -

150 ~

100 r

250

200

100 4

50

700

600 a

500

400

300

200

100

-100

 

   
   

Anterior Tibial Artery

——0- Pro-Exercise
—-0- Post-Exercise

 

—

.1

ct

(12 (l4 (16 (18 1.0

 

 

 

-

.4

q

A

 

(12 (14 (16 (18 1.0

Popliteal Artery

 

(12 (14 (16 (18 1.0

110

 

Figure 4.5: Mean ﬂow (iSE) in anterior tibial (top), posterior tibial (middle), and
popliteal (bottom) arteries in active (ﬁlled circles) and sedentary (open circles) subjects
before and after 2 minutes of dynamic, repetitive ankle dorsiﬂexion exercise. The
measurements after exercise are on average slower in the active compared to the
sedentary group due to the slower heart rate in the active group (52.5 :1: 2.5 [SE] vs. 69.5
:1: 4.2 beats/min). The ﬂow immediately after exercise (plotted at time zero) was
computed for each individual measurement assuming exponential ﬂow recovery to the

pre-exercise ﬂow level.

111

 

+ Active
—0— Sedentary

   

Exercise

 

I'll

 

 

 

300
200 *
100 ~

Ecsé 26.”.

-100 O 100 200 300 400 500
Time (sec)

-200

—+— Active
—0— Sedentary

-100

 

-200

 

 

300
200 t
100

3:55 26E

100 200 300 400 500
Time (sec)

0

+ Active
—0— Sedentary

)-
l
l
l
|

l
l
l

-

   

       

Dynamic

  

II'lIl

Exercise

-200

 

 

5.5.5 2,2“.

0 100 200 300 400 500
Time (sec)

-100

112

10.

11.

References

Booth FW, Chakravarthy MV, Gordon SE, Spangenburg EE. Waging war on
physical inactivity: using modern molecular ammunition against an ancient enemy.
JAppl Physio] 93(1): 3-30, 2002.

Brock RW, Tschakovsky ME, Shoemaker JK, Halliwill JR, Joyner MJ,
Hughson RL. Effects of acetylcholine and nitric oxide on forearm blood ﬂow at
rest and after a single muscle contraction. J App] Physio] 85(6): 2249-2254, 1998.

Corcondilas A, Koroxenidis GT, Shepherd JT. Effect of a brief contraction of
forearm muscles on forearm blood ﬂow. J Appl Physio] 19: 142-146, 1964.

Dawson D, Vincent MA, Barrett EJ, Kaul S, Clark A, Leong—Poi H, Lindner
JR. Vascular recruitment in skeletal muscle during exercise and hyperinsulinemia
assessed by contrast ultrasound. Am J Physiol: Endocrinol Metab 282(3): E714-
720, 2002.

Eskurza I, Monahan KD, Robinson JA, Seals DR. Effect of acute and chronic
ascorbic acid on ﬂow-mediated dilatation with sedentary and physically active
human ageing. J Physio] 556: 315-324, 2004.

Fisher MJ, Meyer RA, Adams GR, Foley JM, Potchen lEJ. Direct relationship
between proton T2 and exercise intensity in skeletal muscle MR images. Invest
Radiol 25(5): 480-485, 1990.

Green DJ, Maiorana A, O'Driscoll G, Taylor R. Effect of exercise training on
endothelium-derived nitric oxide function in humans. J Physiol 561: 1-25, 2004.

Hamann JJ, Buckwalter JB, Clifford PS. Vasodilatation is obligatory for
contraction-induced hyperaemia in canine skeletal muscle. J Physiol 557: 1013-
1020, 2004.

Hepple RT, Babits TL, Plyley MJ, Goodman J M. Dissociation of peak vascular
conductance and V(02) max among highly trained athletes. J Appl Physiol 87:
1368-1372, 1999.

Hermansen L, Wachtlova M. Capillary density of skeletal muscle in well-trained
and untrained men. J Appl Physio] 30(6): 860-863, 1971.

Johansen L, Quistorff B. 31P-MRS characterization of sprint and endurance
trained athletes. Int J Sports Med 24(3): 183-189, 2003.

113

 

12.

13.

14.

15.

16.

17.

18.

19.

20.

2'1.

22.

23.

Kingwell BA. Large artery stiffness: implications for exercise capacity and
cardiovascular risk. Clin Exp Pharmacol Physiol 29: 214-217, 2002.

Laughlin MH. Joseph B. Wolfe Memorial lecture. Physical activity in prevention
and treatment of coronary disease: the battle line is in exercise vascular cell
biology. Med Sci Sports Exerc 36: 352-362, 2004.

Laughlin MH, RJ. Korthuis, D.J. Duncker and RJ. Bache. Regulation and
Integration of Multiple Systems. 705-769, 1996.

Lawrenson L, Hoff J, Richardson RS. Aging attenuates vascular and metabolic
plasticity but does not limit improvement in muscle V0(2) max. Am J Physiol:
Heart Circ Physi01286: H1565-1572, 2004.

Logothetis NK, Wandell BA. Interpreting the BOLD signal. Ann Rev Physiol 66,
2004.

Meyer RA, Foley J M, Harkema SJ, Sierra A, Potchen EJ. Magnetic resonance
measurement of blood ﬂow in peripheral vessels after acute exercise. Magn Reson
Imaging 11: 1085-1092, 1993.

Meyer RA, Towse TF, Reid RW, J ayaraman RC, Wiseman RW, McCully KK.
BOLD MRI mapping of transient hyperemia in skeletal muscle after single
contractions. NMR Biomed 17(6): 392-398, 2004.

Mohrman DE, Sparks HV. Role of potassium ions in the vascular response to a
brief tetanus. Circ Res 35(3): 384-390, 1974.

Noseworthy MD, Bulte DP, Alfonsi J. BOLD magnetic resonance imaging of
skeletal muscle. Seminars in musculoskeleta] radiology 7(4): 307-315, 2003.

Ogawa S, Menon RS, Tank DW, Kim SG, Merkle H, Ellermann JM, Ugurbil
K. Functional brain mapping by blood oxygenation level-dependent contrast
magnetic resonance imaging. A comparison of signal characteristics with a
biophysical model. Biophys J64: 803-812, 1993.

Russ DW, Elliott MA, Vandenborne K, Walter GA, Binder-Macleod SA.
Metabolic costs of isometric force generation and maintenance of human skeletal
muscle. Am J Physiol: Endocrinol Metab 282(2): E448-457, 2002.

Sallis JF, Haskell WL, Wood PD, Fortmann SP, Rogers T, Blair SN,

Paffenbarger RS, Jr. Physical activity assessment methodology in the Five-City
Project. Am JEpidemio] 121(1): 91-106, 1985.

114

24.

25.

26.

27.

28.

29.

30.

31.

32.

Saunders NR, Dinenno FA, Pyke KE, Rogers AM, Tschakovsky ME. Impact of
combined N0 and PG blockade on rapid vasodilation in a forearm mild-to-
moderate exercise transition in humans. Am J Physiol: Heart Circ Physiol 288:
H214-220, 2005.

Shoemaker JK, Phillips SM, Green HJ, Hughson RL. Faster femoral artery
blood velocity kinetics at the onset of exercise following short-term training.
Cardiovasc Res 31: 278-286, 1996.

Timperio A, Salmon J, Rosenberg M, Bull FC. Do logbooks inﬂuence recall of
physical activity in validation studies? Med Sci Sports Exerc 36(7): 1181-1186,
2004.

Tschakovsky ME, Hughson RL. Venous emptying mediates a transient
vasodilation in the human forearm. Am J Physiol: Heart Circ Physiol 279(3):
H1007-1014, 2000.

Tschakovsky ME, Rogers AM, Pyke KE, Saunders NR, Glenn N, Lee SJ,
Weissgerber T, Dwyer EM. Immediate exercise hyperemia in humans is
contraction intensity dependent: evidence for rapid vasodilation. J Appl Physiol
96(2): 639-644, 2004.

Tschakovsky ME, Sheriff DD. Immediate exercise hyperemia: contributions of the
muscle pump vs. rapid vasodilation. J Appl Physiol 97(2): 739-747, 2004.

Vermathen P, Boesch C, Kreis R. Mapping ﬁber orientation in human muscle by
proton MR spectroscopic imaging. Magn Reson Med 49(3): 424-432, 2003.

Vincent MA, Dawson D, Clark AD, Lindner JR, Rattigan S, Clark MG,
Barrett EJ. Skeletal muscle microvascular recruitment by physiological
hyperinsulinemia precedes increases in total blood ﬂow. Diabetes 51(1): 42-48,
2002.

Yang HT, Laughlin MH, Terjung RL. Prior exercise training increases collateral-

dependent blood ﬂow in rats after acute femoral artery occlusion. Am J Physiol:
Heart Circ Physiol 279: H1890-1897, 2000.

115

 

CHAPTER 5: DETERMINANTS OF THE POST-CONTRACTILE BOLD EFFECT IN
SKELETAL MUSCLE.

5.1. Introduction

Blood oxygenation level-dependent (BOLD) contrast is a functional magnetic
resonance imaging (fMRI) technique that can quantify, non-invasively and in real-time,
the biological function of organs and tissues. In the brain, BOLD contrast is used to map
the location and extent of neural activity in response to a variety of stimuli.» The BOLD
contrast however, is not a measure of neural activity per se but is derived from hyperemia
spatially and temporally correlated with neural activity. Coupling between cellular
activity and blood ﬂow is not exclusive to the brain. Many organs and tissues including
skeletal muscle experience changes in hemodynamics as part of their normal
physiological processes, the pattern of which may be altered by pathology or in response
to habitual physical activity (5, 11, 56).

Recently BOLD contrast was detected in skeletal muscle and the magnitude and
time course is clearly related to changes in hemoglobin saturation (30, 31, 39). In fact a
post-contractile BOLD contrast has been detected in skeletal muscle following a single, 1
second contraction (39). This may come as somewhat of a surprise given the transient
nature of the exercise, however blood ﬂow can increase by as much as 6-fold ﬁom a
single brief muscle contraction (6, 61). This muscle contraction induced ﬂow increase
can be two or more orders of magnitude greater than the typical ﬂow values reported in
brain functional studies (9, 10). The underlying mechanism(s) for the post-contractile
ﬂow increase is thought to be a combination of factors including the muscle pump -

contraction induced widening of the arterial-venous pressure gradient - (28, 29, 62), the

116

myogenic effect —vascular smooth muscle relaxation induced by a change in transmural
pressure - (14, 42) and a host of vasodilators including K+ (12, 13, 20).

The post-contractile muscle BOLD response, similar to the brain, is a result of
both changes in blood volume and oxygenation (15). Recently we reported the
magnitude of the response is 3-fold greater in active versus sedentary individuals (59).
The reason for this difference may be one of the many well-established adaptations to the
peripheral vasculature that result from habitual physical activity (7, 27, 37, 64). These
adaptations include increased collateral blood ﬂow (65, 66) increased microvascular
density (7, 23) and increased contraction induced dilation of the microvasculature (27).
Any one of these adaptations could explain the greater post-contractile BOLD response
observed in the active subjects. It is possible however that the magnitude of the post-
contractile ﬂow response is greater in the active subjects and this might explain the
observed differences.

Although activity-dependent differences in the ﬂow response to single brief
contractions have not been reported, training has been shown to increase the “on-
response” (56) of blood ﬂow to exercise and the initial ﬂow response to repeated
contractions is greater in trained versus sedentary controls (32). The “on-response” is the
blood ﬂow increase measured in the ﬁrst few seconds (~9 s) of exercise and the factors
that control this response may be similar to those involved for brief contractions (12).
Furthermore the adaptations observed with habitual physical activity, in particular
increased microvascular density and reactivity, would be consistent with a greater single
contraction induced blood ﬂow response because the ﬂow response to a brief contraction

is controlled at the level of the microvasculature.

117

 

Therefore, the purpose of this study was to: 1) characterize the post-contractile
ﬂow response in active versus inactive subjects, 2) to determine if the magnitude and
time course of the BOLD is quantitatively explained by the magnitude and time course of
measured changes in blood volume and saturation, 3) to examine if the ﬂow response and
estimates of the post-contractile oxygen consumption together can explain the blood

volume, saturation changes, and hence the BOLD response.

5.2. Methods

5.2.1. Subjects: Eleven subjects (3 female, age 24.5 a: 5.6 yrs) participated in the study.
Subjects gave informed written consent in accordance with the University’s Committee
on Research Involving Human Subjects. A pre-test screening, including a magnetic
material safety questionnaire and a medical history questionnaire were completed by all
subjects prior to enrollment. All subjects were apparently healthy and with no family
history of cardiovascular disease and no musculoskeletal disorder that would preclude
participation. Subjects were selected to cover a range of self-reported physical activity
levels, ranging from sedentary (no regular exercise program) to very active (>6

hours/week intense aerobic training).

5.2.2. General Methods: Subjects reported to the laboratory for testing on two separate
occasions, one day for Doppler ﬂow and NIRS testing and a second day for MRI testing.
The testing days, either Doppler and NIRS or MRI, were randomized to avoid an order
effect. Testing was scheduled at approximately the same time of day (i 1 hour) and at

least one week apart. To limit the potential effects of food or caffeine on blood ﬂow

118

subjects reported to the laboratory following an overnight fast. Subjects were asked to
refrain from taking any medications including over the counter medications on the
mornings of testing. In addition subjects were asked to refrain from any intense physical
activity for at least 24 hours prior to their visits. Compliance with pre-test criteria was
determined by a questionnaire. In the event that pre-test criteria were not met the subject
was rescheduled for a later date. All women were tested in the early follicular phase of
the menstrual cycle, within 4 days of the start of their most recent menses.

Blood pressure was measured in the brachial artery using a standard arm blood
pressure cuff and a sphygmomanometer. Ankle blood pressure was measured in the
posterior tibial artery using a portable hand-held ultrasound device and a leg blood
pressure cuff positioned around the calf. Blood pressure was measured in duplicate and
the highest value for systolic blood pressure in the brachial and posterior tibial artery was
used to calculate the ankle brachial index (ABI, ratio of ankle systolic blood pressure to
brachial blood pressure). An ABI of <1.0 is an indicator of compromised peripheral
vascular function (36) .

Subject’s physical activity levels were estimated using a physical activity
accelerometer (Model GTlM, ActiGraph, LLC. Pensacola, FL 32502). The
accelerometer measures changes in accelerations in an intensity dependent manner at 30
samples per second and records the accelerations as counts which are summed and stored
over user deﬁned time periods. The counts recorded by the accelerometer are highly
correlated with independent measures of metabolic rate in both laboratory settings and a
free-living environment (48). Subjects wore the physical activity monitor on a belt

around their waist during all waking hours for 7 days including one weekend day. Total

119

accumulated counts were averaged over the total days the subjects wore the monitors and

this values is reported at average daily counts/1,000.

5.2.3 Doppler Blood flow: Subjects lay quietly on a patient table in a supine position
with arms folded across their chest and with both legs extended. Subjects rested quietly
in this position for 15 minutes prior to data collection. The subjects’ right leg was
positioned at approximately heart level, supported by foam postioners and secured in
place using nylon straps. The subject’s right foot was placed in a custom-built foot
device for measuring the force of isometric ankle dorsiﬂexion. The footplate of the
device was ﬁxed at an angle of 120°, and the foot was strapped to the footplate using a
nylon strap with Velcro® closures. A strain gauge force transducer (Interface, model
SSM-EV—250, Scottsdale, AZ) was mounted to the underside of the footplate and force
during the isometric exercise was digitized (DATAQ Instruments, model DI-l95B,
Akron, OH), sampled at 120 Hz, and recorded on a personal computer.

Prior to data collection each subject performed a series of practice contractions
and the highest force recorded during the practice contractions was used as the subject’s
maximal voluntary contraction (MVC). To ensure consistent contraction intensity and
duration, visual feedback of force was provided to each subject by a computer monitor
and target force was indicated by a red line bisecting the screen at the appropriate force.
To allow for sufﬁcient recovery of blood flow to pre exercise levels a ten-minute rest
period followed the practice contractions.

During the exercise protocol each subject performed a series of l-second duration

maximal isometric ankle dorsiﬂexion contractions. Subjects were instructed to perform

120

 

the contractions at maximal effort and to exhale during the contraction to avoid
performing a Valsalva maneuver. Blood velocity was measured continuously in the
anterior tibial artery (ATA), 2-3 cm distal to the head of the ﬁbula, using a duplex
Doppler ultrasound scanner (LOGIQ Book, GE Medical Systems, Milwaukee, WI 53201
USA.) mounted with an 8 MHz linear probe (Model 8L-RS). Duplex Doppler
ultrasound is capable of acquiring B-mode anatomical images and pulse-wave mode
blood velocity images simultaneously using the same ultrasound probe. The sampling
depth, and gate width was optimized to sample the entire vessel along a 1-2 cm length
during the data acquisition. The probe was held securely in place with an insonation
angle of 60° or less, and was angle corrected to 60°. Data were acquired and stored for
data processing in cinematic loops of 30-60 second duration, and were analyzed using
the GE software available on LOGIQ book system.

Prior to the exercise high-resolution B-mode images were acquired to measure the
resting diameter of the ATA. In a subset of subjects the ATA diameter was measured in
ten images before and ten images after the exercise. All diameter measurements were
made during diastole by the same investigator. Resting ATA diameter was not
signiﬁcantly different than the post-exercise diameter, therefore the pre-exercise value
was used to calculate blood ﬂow. ATA blood ﬂow (BF) in milliliters per minute was
calculated by multiplying the cross-sectional area of the ATA by the mean blood velocity
over the duration of the pulse-waveform (time average mean, TAMEAN) according to
the following equation:

BF ml/min = (TAMEAN blood velocity (cm/s) - n - (ATA diameter (cm) /2) 2 -

60).

121

Flow was normalized to anterior tibial muscle volume, estimated for each individual from

MR images (see below), and is reported as ml/min/ 100 ml muscle.

5.2.4. Near Infrared Spectroscopy: NIRS data were acquired simultaneously with
Doppler measures of blood velocity. The NIRS light emitting diode imager (LEDI)
imager (Near Infrared Monitoring Inc., Philadelphia PA, USA) has two separate probes
of the following dimensions, 11.5 x 7 x 2 cm. Each probe has 6 detectors and 2 light
sources with a detector-light source separation of 3 cm. The NIRS system measures
absorption of light at two different wave lengths, 730 and 850 nm and provides relative
measures of oxyhemoglobin (HbOz), deoxyhemoglobin (Hb) and blood volume (BV, sum
of HbOz + Hb). The NIRS device gain was standardized prior to each data collection
using a muscle tissue phantom provided by NIM Inc. The probes were positioned, one
on each leg (leﬁ leg as a control), over the belly of the anterior compartment muscles,
primarily the anterior tibialis muscle. In the case of the right leg the probe was
positioned just distal to the site of ﬂow measurement, and lateral to the anterior border of
the tibia. Each probe was secured to the leg using an ACE bandage wrapped ﬁrmly
enough around the leg to prevent movement and pollution by ambient light during the
exercise however not so tight as to compromise blood ﬂow. NIRS data were acquired
continuously during the protocol, sampled at 3 Hz and stored on a personnel computer for
post processing.

NIRS data were analyzed using the commercially available LED imager analyzer
program (Near Infrared Monitoring Inc., Philadelphia PA, USA). To calibrate the

recorded, relative NIRS signals an ischemia-reactive hyperemia protocol was performed

122

immediately following the exercise (35). A large contoured vascular cuff (Model CC22
24 x 122.5 cm, Hokanson, Bellevue, WA 98005 USA) was placed around the thigh just
proximal to the knee joint. During the ischemia protocol the cuff was rapidly inflated to
220 mm Hg using a rapid cuff inflator (Model E20. Hokanson, model 666 Bellevue, WA
98005 USA). The cuff pressure corresponded to a pressure of approximately 60 mm Hg
higher than the systolic blood pressure in the posterior tibial artery systolic blood
pressure. The ischemia was maintained for 5 minutes, at which time the cuff was
released to obtain peak reperfusion values.

The changes in HbOz and Hb during the exercise were expressed as a percentage
of the maximum changes in HbOz and Hb observed during the ischemia and reactive
hyperemia (35). Percent saturation of hemoglobin during exercise was calculated from

Saturation (%) = (HbOz-0.4)/(HbOz-0.4+Hb),
where the constant (0.4) accounts for the contribution of myoglobin heme groups to the
HbOz signal. This correction assumes that myoglobin is fully saturated in resting muscle
(30, 51) and during the post-contractile transients, and that 40% of the maximum HbOz
signal recorded during ischemia-reperfusion is due to myoglobin ((16)). For BV a resting
value of 3% was assumed and the changes during exercise were expressed relative to rest

(41, 49, 50).

5.2.5. MRI measurements. On a separate day, at least one week apart from the
ﬂow/N IRS testing day, and at approximately the same time of day (i1 hour), subjects
reported to the MR imager to perform the muscle BOLD protocol. All MR images were

acquired using a standard clinical extremity coil on a 3.0-T GE Horizon system (GB

123

Medical Systems, Milwaukee, WI). Subjects were ﬁtted with a four-lead ECG used to
monitor heart rate and to gate the acquisition of CINE-PC (59) blood ﬂow images. The
leg was positioned in the imaging coil such that the same portion of the right leg that was
under the NIRS probe was contained within the imaging coil. In the case of individuals
that performed the MRI testing ﬁrst the maximal CSA of the ankle dorsiﬂexors, as
determined by visual inspection, was positioned in the center of the coil. Soft foam
positioners were placed in the coil and around the leg to minimize motion of the leg
during the exercise. The same foot device was used for both protocols and the foot was
positioned in the device in the same manor as described previously.

A set of two-dimensional (2D) gradient-recalled, echo time-of—ﬂight (TOF) ﬂow
images was acquired to identify a suitable axial/oblique plane for ﬂow measurements.
The 2D TOF sequence consisted of 92 adjacent axial images (TR 10 ms, TE 3.9 ms, 45°
pulse, l6-cm FOV, 1.5-mm slice thickness, 256 x 128 acquisition matrix, 1 NEX)
centered on a region 5 cm below the ﬁbular head. The axial images were used to
construct a 3D representation of the vessels within that region. Based on the 3D image,
an oblique slice was selected which transected the anterior and posterior tibial arteries 1—
3 cm below their bifurcation from the popliteal artery. Flow velocity images (TR 18 ms,
TE 6 ms, 20° pulse, l-cm slice thickness, l4-cm FOV, 256 x 160 acquisition matrix, 1
NEX, 100 cm/s VENC) of the selected slices were acquired in retrospectively ECG-gated
CINE mode as described previously (3 8). Retrospective gating of the data acquired over
128 heartbeats (total acquisition time 2—4 min, depending on the subject's heart rate)
yielded 32 cardiac-gated ﬂow-velocity and magnitude images per slice. Flow (ml/min)

was calculated by integrating velocity (cm/s) across the area (cm2) of ATA as described

124

 

previously (59). Mean ﬂow in the ATA was then calculated from the mean across all 32
images. Flow images were acquired at rest, just prior to the exercise protocol.

The largest cross-sectional area of the ankle dorsiﬂexor muscles was located from
a series of Tl-weighted [3-plane, TR 500 ms, TE 1.32 ms, 22-cm ﬁeld of View (FOV), 5—
mm slice thickness, 7 slices per plane, 256 x 160 acquisition matrix, 1 NEX] and T 2-
weighted (axial fast spin echo, TR 500 ms, TE 12.264 ms, echo train length 4, 256 x 256
acquisition matrix, 18-cm FOV, l-cm slice, 1 cm slice separation, l NEX) images.
Muscle volume was estimated from the T z-weighted images. The CSA of each slice was
measured and multiplied by the slice thickness to obtain muscle volume for that slice.
The volume of the muscle between slices was estimated by linear interpolating the CSA
from the two adjacent slices and multiplying this value by the slice spacing. Total muscle
volume was calculated by adding the volume of each slice over the entire length of the
muscle. In cases where the images did not extend over the whole length of an individual’s
muscle, the additional volume was estimated assuming a linear tapering of the muscle to
the extemally-measured length of the anterior compartment.

One-shot gradient-recalled echo-planar images (TR 1,000 ms, TE 35 ms, 60°
pulse, 16-cm FOV, l-cm slice thickness, 62.5-kHz bandwidth, 64 x 64 acquisition matrix)
were acquired from a single axial slice transecting the largest cross-sectional area of the
ankle dorsiﬂexor muscles. Echo planar images were acquired continuously for 7
minutes, during which time subjects performed a single, l-second isometric MVC of the
ankle dorsiﬂexors every 60 5 (total of 7 contractions). Signal intensity in a ﬁxed region-
of —interest in the anterior tibial muscle was measured across all images, and reported as

% relative to the baseline as described previously ((59), see Chapter 4).

125

5.2.6. Model Calculations: The theoretical effects of blood volume and blood saturation
changes on muscle signal intensity were calculated as follows. The intravascular BOLD
effect was estimated from the oxygen saturation dependence of blood R 2* at 3.0 T, as
recently reported by (67):

Blood R2* = 17.5 + 39.l*(1-Y) + 119*(1-v)2
where Y is the fractional oxygen saturation. The intravascular BOLD effect depends on
the relative relaxation rates of blood vs. muscle according to

S1 = (l-BV)*exp (-TE* muscle R23!) + BV*exp (-TE* blood R2.) (1),
where SI is the total MR signal and BV is the fractional blood volume. For this
calculation, TE was 35 ms, and muscle R2* was assumed to be constant at 38 s'I at 3.0 T
(39).

The potential contribution of the extravascular BOLD effect was estimated using
the parallel vessel model as described previously (25). In brief, the microvasculature was
modeled as a rectangular array of parallel cylindrical vessels with a base diameter of 5
pm, spaced initially at 25.6 pm (for a vascular volume of 3%), and at an angle of 15
degrees relative to the main ﬁeld (26). The assumed mean diffusion coefﬁcient of
extravascular spins was 2 x 10'5 cmz/s and the susceptibility difference between tissue
and fully deoxygenated blood was assumed to be 8 x 10'2 ppm. The simulation was run
for 30,000 spins randomly distributed in the extracellular volume, and phase
accumulation was followed to an echo time of 35 ms, and for blood saturation values
ranging from 0 to 100%. The simulation was repeated with the vascular volume varied

from 2.5 to 6%, either by decreasing the spacing between vessels, or by increasing the

126

diameter of the vessels. Results of both intravascular and extravascular calculations were
normalized to the calculated values of muscle SI at 50% saturation and 3% blood volume.
In order to explore the effects of blood ﬂow changes on muscle post-contractile
BOLD response, a dynamic model of muscle oxygen delivery, consumption, and efﬂux
was developed using the Stella® software (ISEE systems Lebanon, NH 03766 USA). In
this model input time courses of arterial blood ﬂow and muscle oxygen consumption
were used to calculate the time course and magnitude of changes in blood saturation and
blood volume, and from these the time course and magnitude of the BOLD effect. We
assumed a single, well-mixed vascular chamber within the muscle, and delays in the
development of blood volume and saturation changes due to vascular transit time were
implemented by applying simple smoothing functions. Further details of this model are

provided in the Appendix.

5.2.7. Statistics: Comparisons between the calculated and measured values for the peak
muscle BOLD, resting versus peak blood ﬂow, blood volume and % hemoglobin
saturation changes were made using a paired t-test. The level of signiﬁcance was set at

p<0.05.

5.3. Results

Table 5.1 shows descriptive characteristics for the subjects. The subjects were
college age with a normal blood pressures and an ABI > 1.0. Subjects were recruited to
represent a wide range of physical activity levels. In this subject population the physical

activity levels activity varied across subjects such that some were highly active

127

participating in regular physical activity for 1 hour, 6 or more days per week while others

participated in no regular physical activity outside of activities of daily living.

5.3.1. Post-contractile flow vs. the BOLD response: Figure 5.1 shows an example
Doppler ultrasound recording of blood ﬂow velocity in the anterior tibial muscle of one
subject before and after a single 1 second duration ankle dorsiflexion MVC. The
observed pulsatile blood ﬂow and a triphasic pulse waveform are typical of this and other
peripheral arteries. The phases of the waveform include a large positive increase in blood
flow during systole, followed by a period of retrograde ﬂow and second small increase in
blood ﬂow during diastole. Following the muscle contraction (indicated by the yellow
arrow), there is a large increase blood ﬂow that peaks 5 cardiac cycles after the
contraction. Noticeably, the retrograde ﬂow is absent following the contraction as blood
flow is greatly increased during both systole and diastole. The large initial spike in blood
velocity apparent immediately after the contraction was not used to calculate post-
contraction blood ﬂow, because it is difﬁcult to differentiate from an artifactual change
due to movement. It is clear, however, that volume ﬂow is already elevated during the
second cardiac cycle and peaks at the 5th cardiac cycle aﬁer the contraction.

Figure 5.2 shows the mean time course of anterior tibial artery blood ﬂow in
response to 1 second contractions in all 11 subjects. The peak ﬂow was elevated by 5.9 d:
0.7 fold (SE, n=1 1, range 2.6 to 10.2) above rest, and occurred between the 4th and 6th
heartbeat after contraction in all subjects, i.e., an average of 6 seconds after the
contraction. After this rapid response, there was a more modest, slowly developing,

secondary phase of flow increase which peaked 40-50 seconds after the contraction.

128

Figure 5.3 shows the relationship between the peak post-contractile flow change
and the physical activity level of the subjects, as estimated from the 7 day activity
monitor recordings which were obtained in 10 of the 11 subjects. In 8 of these 10
subjects, there was a strong linear correlation (r2 = 0.93) between activity and the peak
flow response. Two subjects clearly diverged from this relationship. One of these
subjects had been a competitive soccer player for several years, but had recently stopped
participating in the sport. Thus, even 7 days activity monitoring does not always
accurately reﬂect a subject’s chronic physical activity level.

Figure 4 shows the relationship between the peak post-contractile ﬂow vs. the
peak magnitude of the MRI-measured muscle BOLD response measured in the same
subjects. Although there was a signiﬁcant correlation (r2 = 0.37), the relationship is not
strong, indicating that other factors besides the post-contractile ﬂow increase are

important in determining the MRI-measured BOLD response.

5.3.2. Post-contractile blood volume, hemoglobin saturation vs. the BOLD response.
Figure 5.5 shows representative data from the NIRS device acquired during a sequence of
three 1 second duration contractions performed at 80 second intervals.

Deoxyhemoglobin (Hb) is plotted in blue, oxyhemoglobin (HbOz) in red, and blood
volume (BV) in black. The post-contractile changes in Hb, HbOz and BV occur over
multiple phases. There is an initial increase in all three that evolves over a slightly
different time course for each. The small increase in Hb peaks at ~2 seconds while both
the initial increase in blood volume (6 s) and HbOz (8- 10 5) peak later at approximately

the nadir of Hb (8-10 5). In addition there is an additional increase in both Hb and blood

129

volume above baseline values that peaks 40-50 seconds after the contraction, coincident
with the second phase ﬂow response noted above.

Unfortunately, NIRS acquisitions were not successful in 4 of the 11 subjects (3
female) due to inadequate penetration of light through the skin and subcutaneous fat.
Table 5 .2 shows the mean resting and peak post-contractile increases in blood flow,
blood volume, hemoglobin saturation, and MRI-measured muscle SI in response to single
l-second duration MVC’s for these 7 subjects for whom all modalities are available. The
mean peak increase in blood ﬂow in this group is over 6-fold above rest. Resting blood
ﬂow as measured by Doppler ultrasound was not different than resting blood ﬂow
measured by CINE-PC MR angiography in these same seven subjects (3.77 i 0.5 vs. 5.06
i 0.9 ml/min/ 100 m1 muscle, p >005). Blood volume more than doubled from 3 to 6.29
%, hemoglobin saturation increased from a resting level of 5 1 .6 % to 73.2% , and muscle
SI increased by 3.4%.

If the assumptions applied in converting the relative NIRS HbOz and Hb
measurements into absolute values are correct, then it should be possible to calculate the
MRI post-contractile BOLD response from the NIRS-measured changes in blood volume
and hemoglobin saturation for any individual subject. Figure 6 shows the theoretical
dependence of MRI SI on blood volume and saturation for both the extravascular and
intravascular BOLD effects, computed as described in methods. It is apparent from these
calculations that, assuming a ﬁber angle of 15 degrees relative to the main ﬁeld for the
anterior tibial muscle (26), the contribution of the extravascular effect is minor compared

to the intravascular effect over the range considered. Therefore, in the following

130

calculations of BOLD responses from NIRS-measured blood volume and saturation
changes, the minor extravascular contribution is ignored.

Figure 5.7 shows the time course of changes in anterior tibial artery blood flow
(top panel), blood volume and saturation (middle), and MRI-measured SI (bottom panel,
open symbols) after single contractions in the most highly active subject studied. Also
shown in the bottom panel is the time course of the MRI BOLD response calculated from
the blood volume and saturation time course for this subject. The agreement between the
calculated MRI response and the response actually measured by MRI in this subject is
close, both with respect the peak magnitudes (calculated 105.9 % vs 105.6 %) and the
decay rate (time from peak to half peak amplitude 13 vs. 11 seconds). The time course of
the MRI response clearly depends on the time course of the blood volume and saturation
changes. For example, both the calculated and true MRI time course peak after the peak
in volume but before the peak in saturation.

Figure 5.8 shows the comparison between calculated vs. MRI-measured BOLD
responses in 3 other subjects: a moderately active subject (600 Kcounts/day, peak ﬂow
6.53 fold above resting) with a large BOLD response (top panel), in another moderately
active subject (660 Kcounts/day, peak flow 6.52-fold above rest) with a smaller BOLD
response (middle), and in a sedentary subject (170 Kcounts/day, peak ﬂow 2.7-fold above
rest). In all three cases the calculated and MRI-measured changes have a comparable
pattern, but these patterns differ greatly between subjects. In particular, as the peak SI
change is diminished, this peak is preceded by a decrease in signal intensity below the
pre-contraction baseline. In the most sedentary subject, the initial decrease in SI after the

contraction is dominant, and no prominent increase in SI above the baseline is observed.

131

Including all seven subjects, there is a good correlation (r2 =0.64) between the peak
calculated vs. observed MRI post-contractile 81 change (Figure 5.9). Finally, despite the
marked individual differences in response between subjects, the MRI-measured SI
response averaged across all seven subjects also agrees well with the averaged response

calculated from the individual blood volume and saturation changes (Figure 5.10).

5.3.3. Modeling of the BOLD response from ﬂow and oxygen consumption. The
similarity of the calculated and observed MRI post-contractile BOLD responses indicates
that post-contractile changes in blood volume and saturation are the main factors which
directly determine the MRI responses. However, how are the changes in volume and
saturation, and hence in MRI response, related to the observed post-contractile ﬂow
response? In order to quantitatively explore this question, a dynamic model of muscle
blood ﬂow, vascular volume, oxygen delivery, and oxygen consumption was
implemented (see appendix for details). The model includes an idealized two-phase
arterial ﬂow response similar in shape to the measured arterial ﬂow waveform (Figure
5.2). Blood volume is assumed to vary in proportion to arterial ﬂow after a 2 sec delay
(implemented by a smoothing function), as observed above (e.g., Figure 5.10). The
modeled time course of muscle oxygen consumption was based on the following
assumptions. First, the ATP cost of maximum voluntary contractions in human anterior
tibial muscle in a similar group of young adult subjects is 1.7 mM/s (57). During the
short contraction this ATP utilization is provided entirely by PCr depletion, which is

resynthesized entirely by mitochondrial respiration aﬁer the contraction. Furthermore,

132

PCr recovery rate after short contractions peaks within less than 2 seconds, and follows
an exponential time course with an average time constant of 40 seconds (57).

(APCr) = -1.7* exp(-t/40),
where APCr is the change in PCr compared to the resting state. Assuming the
contraction-induced recovery oxygen consumption depends on the rate of PCr recovery,
and assuming the P/Oz ratio = 6 (22), the post-contraction oxygen consumption (in
mM/s) is therefore

Q02 (t) = QOg(rest) + 1.7/(6*40)*exp(-t/40).

The model assumes a single, well-mixed vascular compartment. In order to simulate the
effect of delays due to vascular transit time, the computed hemoglobin saturation result
was smoothed to produce a delay of 4 seconds relative to the peak ﬂow response.

Finally, the MRI SI time course was computed from the time course of blood volume and
saturation changes according to Equation 1, as above.

Figure 5.11 shows the input arterial ﬂow (top panel), input oxygen consumption
(second panel), and output blood volume, saturation (third panel), and MRI response
(bottom panel) from the model. Although the computed time courses do not perfectly
match the observed group average result in Figure 5.10, the main characteristics are
clearly reproduced by the model. For example, blood saturation increases from a
baseline of 51.8 % to a peak of 79.0%, compared to the measured change from 51.6 % to
73.2 % (Table 5.2). There is an initial dip in the computed SI, followed by a peak at
103.8 %, vs. the MRI-measured peak 81 of 103.4 %.

The exact results of the model depend critically on the balance between the input

ﬂow and oxygen consumption time courses. For example, Figure 5.12 shows the effect

133

 

of varying the magnitude of the ﬁrst, fast phase of arterial flow increase after contraction
on the computed SI. For these calculations, the ATP cost of contraction and rate of PCr
recovery were held constant. Decreased ﬂow ampliﬁes the initial dip in SI, and decreases
the magnitude of the peak SI change after the contraction. At the lowest input peak ﬂow
(12 m1/min/100 ml, or 3.2 fold above resting flow), the positive BOLD effect is
eliminated. On the other hand, at the highest peak ﬂow (34.5 ml/min/100ml, or 9.1 fold
above resting) the initial dip in SI is nearly eliminated (and would be obscured by the
contraction artifact in the MRI data), and SI is near the maximum observed SI of 106%
(e.g., Figure 5.7). The opposite changes can be produced in the model by holding ﬂow
constant and varying the assumed ATP cost of the contraction, or the time constant of
PCr recovery, and hence the peak post-contractile oxygen consumption. If peak oxygen
consumption is decreased, the dip decreases and the amplitude of the SI peak increases.
Thus, individuals with similar post-contractile ﬂows (e.g., subjects 6 and 5 in Figure 5.8),

can have substantially different MRI-measured BOLD transients.

5.4. Discussion

The main results of this study are: l) the magnitude of the post-contractile
increase in blood flow following a single 1 second contraction varies across individuals
based on physical activity, 2) there are two phases of the post-contractile flow response,
an initial fast phase that peaks at 6 seconds after the contraction and a secondary phase
that peaks at near 40 seconds, 3) NIRS estimates of blood volume and oxygenation

changes together quantitatively explain the BOLD response, and 4) the ﬂow response

134

qualitatively explains the BOLD response, however, the BOLD response also depends
critically on the kinetics of oxygen consumption.

Although we are the ﬁrst to report that the magnitude of the fast post—contractile
ﬂow response depends on physical activity, this ﬁnding should come as no surprise.
Habitual physical activity results in adaptations to the peripheral vasculature at all sites
along the vascular tree (28). Chronic endurance training increases collateral blood ﬂow
(66), and microvascular density including increased density of small arterioles (27) and
capillaries (7). In addition to these structural changes habitual physical activity improves
the functional capacity of the peripheral vasculature. Training increases ﬂow-mediated
dilation and endothelium independent dilation of small arteries (17, 33), and improves
contraction induced dilation of small arterioles (27).

Habitual physical activity has also been shown to alter the kinetics of blood ﬂow
during the transition from rest to work. As little as 10 days of cycle ergometer training is
sufﬁcient to increase both the initial rate of blood velocity and the amplitude of the blood
velocity increase at 10 seconds, as measured in the femoral artery in response to a knee
extension exercise (56). Although in that study the initial kinetics (called the “on-
response”) of blood ﬂow velocity were altered with training, the steady state blood
velocity did not change with training and was not different compared to the control
group. Similarly, in rats a 5 week treadmill training program resulted in greater initial
(ﬁrst 30 sec) ﬂow responses to exercise, but no differences in the maximal ﬂow (32).
Thus, the major muscle blood ﬂow adaptation to training appears to be the magnitude of

the initial ﬂow response, rather than the ﬂow achieved during steady-state exercise.

135

Dilation of the small arterioles and in particular the terminal arterioles regulates
the blood flow response in the early stages of exercise and in response to a brief muscle
contraction (2, 40, 46, 53, 55). Arteriolar dilation precedes changes in blood ﬂow in the
feed arteries which are located external to the muscle and do not dilate in response to
brief muscle contraction (6, 60, 62). The control of blood ﬂow by feed arteries may be
greater during steady state exercise (54, 63) although there appear to be species
differences (54). Therefore the blood ﬂow response to brief contractions represents a
response controlled at the microvascular level, and may be used as an indicator of
microvascular reactivity.

Although the anatomical location of the ﬂow control has been clearly deﬁned the
underlying mechanism is still being debated (12, 60). The increase in blood ﬂow is likely
due to a variety of mechanisms including the muscle pump, myogenic response and rapid
vasodilation resulting from a contraction induced increase in interstitial KL The muscle
pump effect is a contraction induced widening of the arterial- venous pressure gradient
due to the emptying of the venous vasculature. Although the muscle pump has been
shown to impact the magnitude of the post-contractile ﬂow response, its contribution is
relatively small, less than 20% to the overall blood ﬂow response (62). Based on the time
course of the flow response in this study, as well as on the time course of the BOLD
response, it is unlikely that the muscle pump makes a major contribution to the fast ﬂow.
The muscle pump effect would be greatest during the ﬁrst 1-2 seconds post contraction
when the pressure gradient is largest, whereas the peak flow response measured in this

study peaked at 6 seconds after the contraction, see Figure 5.2 (29, 62). Furthermore the

136

peak ﬂow response, up to a 10 fold increase, is much larger than could be attributed
solely to reﬁlling ofthe muscle venous volume.

The initial ﬁow response to a brief muscle contraction has been linked to both the
myogenic response (14, 42) and K+ -induced vasodilation (12, 20). The myogenic
response refers to the mechanism by which the vascular smooth muscle (VSM) tone is
altered in response to a change in transmural pressure. K+ released during depolarization
of the muscle membrane is thought to initiate vasodilation by hyperpolarizing the smooth
muscle membrane and closing of voltage gated calcium channels resulting in VSM
relaxation (8, 24, 43, 45). Changes in K+ concentration in the venous efﬂuent following a
contraction follow a time course similar to that of the ﬂow response (43, 44) and the ﬂow
response is almost completely prevented when the preparation is pre-treated with K+
channel blockers (2) or the VSM membrane potential is clamped to prevent
hyperpolarization (20).

Although the mechanisms for the initial phase of the ﬂow response have been
well studied, our data clearly show a secondary ﬂow response that peaks near 40 seconds
after the contraction. To our knowledge we are the ﬁrst to report such a ﬁnding in
humans. A biphasic contraction induced vascular response has been shown previously in
intact preparations of canine and rodent muscles (18, 34, 44) and in situ rodent
preparations (3, 18). Mohrman et al., showed a biphasic change in vascular conductance
with the initial response peaking at near 10 seconds and the second phase at 25-35
seconds. The authors attributed the ﬁrst phase to K+ induced vasodilation and suggested
the second phase was due entirely to low P02 as [C was near baseline by 15 seconds

(44). A biphasic pattern of arteriolar dilation was also reported by Gorczynski and

137

Duling and the magnitude of the secondary dilation was signiﬁcantly reduced when the
preparation was superfused with elevated P02 (18).

The precise mechanism for the secondary phase of the ﬂow response is unknown.
However, our ﬁndings are consistent with a link between low tissue PO; and the
secondary ﬂow response. Deoxyhemoglobin reached at peak at near 40 seconds and the
nadir of hemoglobin saturation is at approximately the same time point as the peak of the
secondary ﬂow response. This suggests an oxygen sensor coupled to the VSM or a
vasodilator related to muscle oxidative metabolism. An attractive candidate is
hemoglobin itself, which has been linked to hypoxic vasodilation (1). Under conditions
of low P02 during hemoglobin desaturation, hemoglobin is thought to increase NO
bioactivity which can act as a potent vasodilator of the peripheral vasculature (1).

In this study blood volume increased nearly two fold after the contractions. This
change in volume was not fully considered in our previous study (39), largely because
.NIRS device employed in that study was limited compared to the device used in this
study. These new results, in combination with the modeling, support an important role
for blood volume in determining the post-contractile BOLD effect, and are in line with
the ﬁndings of Damon et al. (15). It is important to note that the contribution of blood
volume to the BOLD contrast is saturation dependent. If saturation remains at or below
baseline values near 50%, an increase in blood volume results in a decrease in the BOLD
signal. At higher saturations an increase in blood volume results in an increase in the
BOLD signal. At near 45 seconds when blood volume is near its secondary peak and
saturation has returned to baseline, the BOLD signal is near or slightly below baseline.

These dynamic relationships between blood flow, blood volume and saturation can result

138

 

in a post-stimulus undershoot seen in some of our subjects, and in some brain MRI
studies (10). In fact, the similarity between the magnitude and time course of our muscle
BOLD and NIRS data and those of some brain functional studies is striking. We clearly
see a early dip in many of the MRI and NIRS responses followed by a peak in the MRI
transient and a post-stimulus undershoot which is temporally correlated with elevated
deoxyhemoglobin (9, 10). This similarity in the response suggests common mechanism
coupling blood flow to activation in brain and skeletal muscle.

The Stella model used in this study reproduces the main features of post-
contractile changes in blood volume, saturation, and muscle BOLD, despite some
obvious simpliﬁcations. For example, blood volume in our model assumes a delayed
linear function between ﬂow and volume. However, blood volume changes are more
likely related to microvascular compliance and pressure than to ﬂow per se. It would be
more appropriate to model the ﬂow relationship by incorporation of compliance of the
capacitance vessels, similar to the balloon model proposed by Buxton et al. (10). The use
of a single well-mixed vascular compartment is a major simpliﬁcation. A more complete
model would consider the incremental extraction of oxygen as blood travels through the
capillaries, as well as the diffusion of oxygen within the muscle cells, and possible
heterogeneity of perfusion rates and oxygen consumption across the muscle.

The success of our simple Stella model depends critically on the assumed kinetics
of 02 consumption following the contraction. We implemented a fast increase in 0;
consumption after the contraction with a time constant of 0.5 seconds, such that peak 0;
consumption is reached within 2 seconds. This assumption is supported by many

previous studies. For example, Territo et al. (58) showed that isolated mitochondria

139

increase respiration rate to a new steady state in response to step changes in ADP or

inorganic phosphate within 3 seconds. A recent NMR study of PCr kinetics shows that

PCr recovery rate reaches a maximum with 3 seconds (the earliest time measured) after

short MVC’s of human anterior tibial muscle (57). Furthermore, studies of mouse

muscle with genetic knockout of creatine kinase demonstrate that muscle 02 consumption

can increase very rapidly during short bursts of twitch contractions (52). L

In contrast, it has been argued that there is an inherent delay of up to 15 seconds

I D'HILE'I

in the activation of mitochondrial respiration in muscle. In the exercise literature this

 

delay is typically referred to as “metabolic inertia”, and has been variously attributed to
delayed activation of the pyruvate dehydrogenase, delayed supplementation of TCA
cycle intermediates, or delayed diffusion of metabolites to and within mitochondria (4,
19). In fact, the results of this study provide further evidence that there is no major
“inertial” delay in the onset of muscle respiration after contractions. For example, had we
used a much longer time constant for activation of respiration in our model (e.g., 7-15
seconds), blood saturation would rapidly increase along with the fast phase of post—
contractile blood ﬂow, there would be no initial dip in the BOLD response, and the peak
BOLD response would be higher, and would occur much earlier than the actual measured
BOLD response.

The importance of post-contractile 0; consumption kinetics in determining the
BOLD response may explain why, although there is a signiﬁcant correlation between
peak post-contractile ﬂow and the BOLD magnitude, the correlation is not perfect
(Figure 4). The time course of Oz consumption is likely to vary between individuals, both

because of individual variations in ﬁber type, which determines the ATP cost of

140

contraction (21), and because of variations in mitochondrial content, which determine
PCr recovery rate (47). Thus, the muscle BOLD response is an integrated measure of at
least three related but distinguishable aspects of an individual’s muscle aerobic ﬁtness:
microvascular dynamics, ﬁber type, and mitochondrial content.

In summary, this study shows that physical activity influences the magnitude of
the post-contractile ﬂow response, and that this ﬂow response has two distinct phases: a
fast initial phase and a slower, secondary phase. The post-contractile muscle BOLD
response can be quantitatively explained by changes in blood volume and saturation.
These are ultimately determined by the balance between muscle blood ﬂow and Oz

consumption kinetics.

5.5. Appendix

A “map” of the Stella model appears in Figure 5.13. The map has two interacting
“ﬂow paths” corresponding to blood ﬂow and tissue blood volume (top path) and oxygen
delivery, efﬂux and consumption through a single muscle blood 02 content “reservoir”
(bottom path). The model ignores any changes in dissolved or myoglobin-bound oxygen
outside the vasculature.

Arterial blood ﬂow was simulated by an arbitrary waveform mimicking the
amplitude and shape of the measured ﬂow changes:

Flow = Resting Flow + Al *t*exp (-t/Taul) + A2*sin ((rt/2)* t / Tau2),

where Al and Taul together determine the amplitude and shape of the large, ﬁrst
phase of post-contractile ﬂow, and A2 and Tau2 determine the amplitude and peak time

of the smaller, secondary phase of post-contractile ﬂow, and time is in seconds. For the

141

base model shown in Figure 5.1 1, A1 = 15 ml/min/lOOml, Taul = 4 seconds, A2 = 4
ml/min/ 100ml, Tau2 = 40 seconds, and resting flow = 3.8 ml/min/100ml. For t<=0, ﬂow
was simply equal to resting flow. Venous blood ﬂow was assumed to equal arterial blood
ﬂow, adjusted for a capacitive ﬂow, which was computed from the derivative of the
modeled blood volume changes. (This trick was necessary because Stella does not allow
the content of a “reservoir” box to be directly manipulated). Changes in blood volume
(BV) were modeled proportional to blood ﬂow according to a simple linear function:

BV (%) = 3 + 21 .5*(Arterial ﬂow -Rest Arterial F low),
where ﬂows are in ml/ml muscle. The resulting BV was smoothed in order to introduce a
delay before the derivative and capacitive ﬂow was computed.

Oxygen consumption was assumed to be proportional to the rate of PCr recovery
after an MVC contraction, assuming a P/Oz ratio of 6, a PCr depletion of 1.7 mM after
the 1 second duration contraction (t>0), and assuming a PCr recovery time constant of 40
seconds:

Q02 (mM/s) = QOzrest + l.7/(6*40)*exp(-t/40)*(1-exp(-t/0.5).

The last term prevents an instantaneous peak in oxygen consumption at t=0, and is
consistent with the observation that respiration in isolated mitochondria reaches a new
steady-state within less than 3 seconds after step changes in ADP and inorganic
phosphate (58). Converting to mlOz/min/ml:

QOz (mlOZ/min/ml muscle) = Q0; (mM/s) * (22.4 mlOz/mmol) * (60 s/min)/

(1000 ml/l).

Arterial 02 content was ﬁxed at 20 mlOz/ 100 ml blood, and resting 0; consumption was

0.38 mlO2/min/ 100 ml. The model dynamically computes the change in muscle blood

142

02 concentration ([02], mlOz/ 100 ml blood) over time, which was used to estimate
muscle fractional 02 saturation according to the standard clinical formula, assuming 14
mg Hb/100 ml blood:

Fractional Saturation = [Oz]/ (14 mg Hb * 1.34 mlOz/mg Hb)

In order to simulate the effect of transit time delays through the vasculature,
saturation was smoothed to produce a 4 second delay relative to the peak ﬂow. Finally,
muscle SI was computed from blood volume and saturation using the intravascular

BOLD effect according to Equation 1 as described in the methods.

143

Table 5.1: Subject characteristics (meaniSD, n=1 1)

 

 

Age (yrs.) 24.5 d: 5.6
Height (cm) 172.0 d: 9.2
Weight (kg) 71.1 i 14.6
Blood Pressure (SBP/DBP mmHg) 113.9 / 74.6 i 11.0 / 7.5
ABI 1.2 at 0.1
Physical Activity (1,000 counts/day) 432.5 :t 315.3
Muscle CSA (cm) 12.1 :1: 2.3

MVC (N/cmz) 20.8 e 2.8

 

 

144

Post-contraction

Contraction

 

Figure 5.1: Doppler ultrasound recording of blood velocity (cm/s) over ten cardiac
cycles as measured in the anterior tibial artery. The arrow indicates the time of the
muscle contraction. In this image the green and blue lines trace the triphasic pulse
waveform time-averaged maximal velocity (green, TAMAX) and time-averaged mean
velocity (blue, TAMEAN), respectively. The TAMEAN was used to calculate blood
ﬂow as detailed in the methods section. Blood velocity increases immediately following
the muscle contraction and reaches a peak typically 4-6 cardiac cycles after the

contraction

145

30 -
25 -

20 -

15 - '
10 ~ I II II I II I

 

Flow (ml/min/1OO ml)

 

 

O r I I I I ﬁ
-10 0 10 20 30 40 50
Time (s)

Figure 5.2: Time course of flow (mean 3: SD) in anterior tibial artery before and after 1
second duration MVC contraction (from -1 to 0 see). In order to average data from
subjects with different heart rates, and therefore different sampling intervals, results for
each subject were linearly interpolated to 1 second intervals. Vertical lines indicate when
data collection ended for an individual. Thus, from -10 to 12 seconds, n=1 1, from 12 to

23 seconds, n=10, etc.

146

12 a

 

 

1O -
3
.9
u.
:5 "
028‘
E
E o
_6,
“- 0
ﬁ
E ' '
4 -
o
2 I I I l I I 1
0 20 40 60 80 100 120 140

Activity level (counts/day/10000)

Figure 5.3: Relationship between peak increase in flow above rest flow after contractions
vs. 7-day activity monitor counts. In eight subjects the correlation was strong (r2 = 0.93).
Two outlying subjects reported low activity counts during monitoring, but strong ﬂow

responses.

147

 

107 «

 

 

 

106 « O
"o‘
o\
V
D
_l
0
cn
o:
2
x
m
a)
CL

Y = 0.49* x + 99.8
100 « Q
99 . 1 . . n
2 4 6 8 1o 12

Peak Flow/Rest Flow

Figure 5.4: The relationship between fold increase in blood ﬂow and MRI BOLD
response resulting from a l-second maximal contraction of the ankle dorsiﬂexors. In
general, the individuals with the largest BOLD response also displayed large ﬂow

- 2
lncreases, r = 0.37.

148

 

 

 

 

 

_ R \ —BV

 

 

 

 

 

6 —— H302 -
4 .
l. _
«ﬁt:
.4. . . . . _
2200 2400 2600 2800

Sample Point

Figure 5.5: Raw NIRS data (arbitrary units vs. sample pints) for three maximal
contractions separated by 80 seconds of rest. Data were collected at 3Hz with the sensors
placed over the belly of the anterior tibialis muscle just lateral to the tibia. The peak in
blood volume (black line) occurs before the peak in oxyhemoglobin (red) and the nadir of
deoxyhemoglobin. Interestingly there are three phases of deoxyhemoglobin, an initial
rapid rise, which peaks at ~2 seconds after the contraction, a large decrease that reaches a
nadir at approximately 10-12 seconds and a secondary rise approximately 45 seconds
after the contraction. Blood volume follows a biphasic pattern with a secondary increase

at approximately 45-50 seconds after the contraction.

149

 

Table 5.2. Blood flow in the anterior tibial artery, NIRS-estimated blood volume and

percent hemoglobin saturation in the ankle dorsiflexors at rest and peak after a l-second

maximal voluntary contraction. Blood volume as rest is assumed to be 3% for all

subjects. The increases in blood ﬂow, blood volume, hemoglobin saturation and MRI

signal intensity from rest to peak post are all signiﬁcant (p<0.05). Data are mean :E SE, n

=7.

 

 

Rest Peak Post-Contraction
Blood Flow (ml/min/ml muscle) 3.77 i 0.5 23.2 :1: 3.7
Blood Volume (%) (3.0) 6.29 i 0.7
Hemoglobin Saturation (%) 51.6 i 2.8 73.2 :l: 5.6
MRI SI (%) (100) 103.4 :1: 0.8

 

150

 

 

Figure 5.6: Theoretical intravascular (top panel) and extravascular BOLD effects for E
gradient-echo images at TE 35 ms over a range of blood volumes and saturations. SI is

normalized relative to the value at baseline conditions of 50% hemoglobin saturation and

a 3% blood volume (black dot locations on the surfaces). The extravascular plot assumes

blood volume increased by adding more vessels. Increasing blood volume by increasing

vessel size had even smaller extravascular effects on SI.

151

SI (We)

51 (%)

Intravascular

 

Extravascular

106-.

104

102.

100.

98

 

96>-
100 ‘

  

ex.
60

turatio 40 \2d\ ///‘:3/// I
" " 9009

II (%)

0 ’72

152

 

Figure 5.7: Blood ﬂow (top panel, mein/ 100 ml of muscle) blood volume (% change)
hemoglobin saturation (middle panel) and calculated and measured muscle BOLD
response to a l-second MVC of the ankle dorsiﬂexors. The above three panels are data
from an individual with one of the largest increases in blood ﬂow, blood volume, %
saturation and MRI BOLD responses in the study. Blood ﬂow increased approximately
10-fold to ~ 20 ml/min/ 100 ml of muscle. The NIRS measured increase in blood volume
was double resting blood volume and % saturation increased to over 90%. In this
individual the NIRS data are the average from four contractions and are shown without
error bars for clarity. The arterial flow data was linearly interpolated to the to the same
sample rate (3 Hz) as the NIRS data). The large spike in observed S1 is a Tl-related
motion artifact caused by movement of unsaturated muscle into the imaging plane during
and immediately after the contraction (39). Time zero indicates the l-second duration

MVC.

153

25

E
O
O
‘—
\
E
E
2
E
V
3
.9
LL
7
6
e\°
v
GE, 5
2
O
>
"O 4
O
2
OJ
3
2
108
106
A 104
e
U) 102
100

98

 

 

 

 

  
 

 

Time

60

 

 

—0— Blood Volume

—0— Saturation

 

 

 

uuuuuuuuuu

 

[100

~80

~70

~50

 

 

 

 

 

 

Time (s)

.1

 

 

+ Calculated BOLD
—o—— MRI BOLD

 

 

 

 

 

20

Time (s)

40

154

Saturation (%)

 

Figure 5.8: Calculated (o) and measured (O) muscle BOLD response from three
individuals. Data are from three individuals representing a span of responses from one of

the largest, Sub6, to the smallest, and actually the only negative BOLD response, Sub4.

155

108 ~

 

_._.. Calculated BOLD
—o—— MRI BOLD

Sl (%)

Sl (%)

sr (%)

 

106~

 

 

 

 

 

 

 

98 1 ﬂ 1
20 40
Time (s)
108 -
106 1 Sub5
104 .

 

 

 

 

 

 

Time (s)
106 1

104 <

102 ‘

 

 

100 r

98*

 

 

Sub4

 

96

Time (s)

 

156

 

 

 

 

107 -

106 -

105 4

104 ~

103 ~

102 -

 

10‘ ‘ Y= 1.02x-1.4a

MRI Peak BOLD (% change)

100 . 'D

 

 

99 I I I I T I 1
100 101 102 103 104 105 106 107

Calculated Peak BOLD (% change)

Figure 5.9: Relationship between peak post-contractile BOLD effect calculated from
NIRS blood volume and saturation data vs. BOLD effect observed by MRI in the same
subjects. Note that the slope of the linear regression (r2 = 0.64) is near 1, and the

intercept is near zero.

157

 

Figure 5.10: Means blood ﬂow (top panel, data linearly interpolated to 3 Hz sample
frequency), blood volume, % saturation (middle panel) and model calculated (0) and
measured (O) muscle BOLD (bottom panel) for 7 subjects for whom ultrasound, NIRS,

and MRI are all available.

158

 

Blood Volume (0%,) Flow (ml/min/100ml)

Sl (%)

14‘

12-

‘IO'4

 

 

 

   

 

.1
.i
.1
-1

Time

 

—0— Blood Volume
—0— Saturation

 

 

 

 

 

[-75

~70

~55

 

 

108 -

106-1

104 j

102 .

 

Time (s)

 

—0— Calculated BOLD
—o— MRI BOLD

 

 

 

 

 

 

 

 

o'l
N
O
A.
C)
O)
O

159

Saturation (%)

Figure 5.11: Dynamic model of muscle blood ﬂow, oxygenation, and MRI BOLD effect,
as described in the Appendix, predicts the magnitude and time-course of the muscle
BOLD response well. The modeled post-contractile increase in blood ﬂow shown in the
top panel is idealized from the mean ﬂows reported in Figures 5.2 and 5.8. The cost of
the muscle contraction was set at 1.7 mM ATP/s, and oxygen consumption was modeled
such that it increased to a peak after the contraction occurred with a time constant of 0.5
seconds, and such that it recovered to resting oxygen consumption as an exponential

decay with a time constant of 40 seconds.

160

ml 02/ min I100 ml)

SI (%)

ml/min I100 ml

Blood Volume (%)
OI

30-
25-
20~
15-
10‘

 

Flow

 

 

14'-
1.2 ~
1.0 4

O2 Consumption

 

 

 

~ 90
— Blood Volume

  
  

— 80
- — - Saturation
~ 70
_ 60

// ~50

 

 

105 -
104 -
103 d
102 4
101 -
100 -
99 -
98

 

0 10 20 30 40 50

MRI BOLD

 

0 10 20 30 40 50

Time (s)

161

Saturation (%)

 

 

Figure 5.12: Simulation of the relationship between the peak of the ﬁrst phase of the
post-contractile increase in blood ﬂow and the time-course of the muscle BOLD
response. In this simulation blood ﬂow was varied over a range similar to that seen in the
l 1 subjects for a peak ﬂow increase of 3 to 9 fold above resting. This variation in blood
ﬂow resulted in a range of peak BOLD from a negative BOLD 99% to a positive BOLD

ranging from 101-106%

162

Flow (fold change above rest)

81 (%)

10 -

 

108 a

106 -

104 -

102 -

100 -

 

 

Simulated Flow

 

I I I I I

10 20 30 40 50 -

Time (3)

Simulated MRI BOLD

 

 

98

0 10 20 30 40 50

Time (s)

163

Figure 5.13: A two-pathway parallel Stella model developed to determine the
relationship between muscle blood ﬂow and the magnitude of the post-contractile muscle
BOLD response. In the Stella programming language large arrows indicate bulk ﬂow
and the rectangles are reservoirs which accumulate material to a degree determined by
the dynamics of inﬂow and outﬂow from the reservoir. The small circles are converters
and along with the small thin arrows are used to transfer information to ﬂows, between
converters or from a reservoir. For example the small arrow connecting the arterial blood
ﬂow to the arterial 02 delivery, along with the information about the oxygen content of
the arterial blood will determine the delivery of oxygenated blood to the muscle. In this
case the delivery of oxygen can be altered by altering the blood ﬂow, or the arterial 02

content, for example, by altering hemoglobin content.

164

 

 

 

<0_ 03003 :30

p330 m 40c 2:000 4 Am: 0 0<9
O . O b ,
0...me N >Z=U 3.5mm A >30 4Q)..- .lJQl.

Q l C 9229 m3 m_:..<0_ QLHXM

 

 

 

 

 

Q . . z _. \omumozzm .._0<<
mmmza >3 305 my. _ .. Z0006 w_000 <0E3m .
O .C. L r_ A41- 6
. i . ...Om 00:
Q . , >103. w_000 =02 / <0:0:m w_000 30E ...4..
now” 2:032 Om 00: ”W ﬂv 300:0:2 mm"
>nm:m_ ON 00:62 . ,.
Q. @000 ON 00:83 ._ . ., . Avg: 480.205. mm"
9 Mix,- .. - . . w 6 0 0.000 4m 064
>303; ON 00:52 <0:0cm Om macx
,, . 2:.QO @000 <0_E.:m
2.9.71- . -
3000.0 ON 00:05:30: ,
M.” vmraw \lll© ,.
\ulf... X.- >._._u 000” O
. Q . .119 l/..,. 3:020 «N
Swag 0» 0050330: . .
0033020: 50:80 0

ON 00:33:20: @010:

165

10.

11.

References

Allen BW, Piantadosi CA. How do red blood cells dilate blood vessels? Circ Res
94: e105, 2004.

Armstrong ML, Dua AK, Murrant CL. Potassium initiates vasodilatation
induced by a single skeletal muscle contraction in hamster cremaster muscle. J
Physi01581: 841-852, 2007.

Armstrong ML, Dua AK, and Murrant CL. Time course of vasodilation at the
onset of repetitive skeletal muscle contractions. Am J Physio]: Regul Integr Comp
Physiol 292: R505-515, 2007.

Bangsbo J. Muscle oxygen uptake in humans at onset of and during intense
exercise. Acta Physiol Scand 168: 457-464, 2000.

Berry KL, Skyrme-Jones RA, Cameron JD, O'Brien RC, Meredith IT.
Systemic arterial compliance is reduced in young patients with IDDM. Am J
Physiol 276(6) Pt 2: H1839—1845, 1999.

Brock RW, Tschakovsky ME, Shoemaker JK, Halliwill JR, Joyner MJ,
Hughson RL. Effects of acetylcholine and nitric oxide on forearm blood ﬂow at
rest and after a single muscle contraction. J Appl Physiology 85(6): 2249-2254,
1998.

Brodal P, Ingjer F, Hermansen L. Capillary supply of skeletal muscle ﬁbers in
untrained and endurance-trained men. Am J Physiol 232(6): H705-712, 1977.

Burns WR, Cohen KD, Jackson WF. K+—induced dilation of hamster cremasteric
arterioles involves both the Na+/K+-ATPase and inward-rectiﬁer K+ channels.
Microcirculation 11(3): 279-293, 2004.

Buxton RB, Uludazeg K, Dubowitz DJ, Liu TT. Modeling the hemodynamic
response to brain activation. Neurolmage 23: 8220-33, 2004.

Buxton RB, Wong EC, Frank LR. Dynamics of blood ﬂow and oxygenation
changes during brain activation: the balloon model. Magn Reson Med 39(6): 855-
864, 1998.

Candido R, Allen TJ. Haemodynamics in microvascular complications in type 1
diabetes. Diabetes Metab Res Rev 18: 286-304, 2002.

166

 

 

12.

l3.

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

Clifford PS, Hellsten Y. Vasodilatory mechanisms in contracting skeletal muscle.
J App] Physio] 97(1): 393-403, 2004.

Clifford PS, Jasperse JL. F eedforward vasodilatation at the onset of exercise. J
Physi01583: 811, 2007.

Clifford PS, Kluess HA, Hamann JJ, Buckwalter JB, Jasperse JL. Mechanical
compression elicits vasodilatation in rat skeletal muscle feed arteries. J Physio] 572:
561-567, 2006.

Damon BM, Hornberger JL, Wadington MC, Lansdown DA, Kent-Braun JA.
Dual gradient-echo MRI of post-contraction changes in skeletal muscle blood
volume and oxygenation. Magn Reson Med 57: 670-679, 2007.

Duteil S, Bourrilhon C, Raynaud JS, Wary C, Richardson RS, Leroy-Willig A,
Jouanin JC, Guezennec CY, Carlier PG. Metabolic and vascular support for the
role of myoglobin in humans: a multiparametric NMR study. Am J Physiol: Regul
Integr Comp Physio] 287(6): R1441-1449, 2004.

Fuchsjéager-Mayrl G, Pleiner J, Wiesinger GF, Sieder AE, Quittan M, Nuhr
MJ, Francesconi C, Seit HP, Francesconi M, Schmetterer L, Wolzt M. Exercise
training improves vascular endothelial function in patients with type 1 diabetes.
Diabetes Care 25(10): 1795-1801, 2002.

Gorczynski RJ and Duling BR. Role of oxygen in arteriolar functional
vasodilation in hamster striated muscle. Am J Physio] 235: H505-515, 1978.

Grassi B. Regulation of oxygen consumption at exercise onset: is it really
controversial? Exerc Sport Sci Rev 29: 134-138, 2001.

Hamann JJ, Buckwalter J B, Clifford PS. Vasodilatation is obligatory for
contraction-induced hyperaemia in canine skeletal muscle. J Physio] 557: 1013-
1020, 2004.

Harkema SJ, Adams GR, Meyer RA. Acidosis has no effect on the ATP cost of
contraction in eat fast- and slow-twitch skeletal muscles. Am J Physio] 272(2):
C485-490, 1997.

Harkema SJ, Meyer RA. Effect of acidosis on control of respiration in skeletal
muscle. Am J Physiol 272(2): C491-500, 1997.

Hermansen L, Wachtlova M. Capillary density of skeletal muscle in well-trained
and untrained men. J Appl Physiol 30(6): 860-863, 1971.

167

 

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

34.

35.

Jackson WF. Potassium channels in the peripheral microcirculation.
Microcirculation 12: 113-127, 2005.

Kennan RP, Zhong J, Gore JC. Intravascular susceptibility contrast mechanisms
in tissues. Magn Reson Med 31(1): 9-21, 1994.

Lansdown DA, Ding Z, Wadington M, Hornberger JL, Damon BM.
Quantitative diffusion tensor MRI-based ﬁber tracking of human skeletal muscle. J
App] Physio] 103(2): 673-681, 2007.

Lash JM, Bohlen HG. Functional adaptations of rat skeletal muscle arterioles to
aerobic exercise training. J Appl Physio] 72: 2052-2062, 1992.

Laughlin MH, Korthuis RJ, Dunker DJ, Bache RJ. Control of Blood Flow to
cardiac and skeletal muscle during exercise. Handbook of Physiology 12: 705-769,
1996.

Laughlin MH, Schrage WG. Effects of muscle contraction on skeletal muscle
blood ﬂow: when is there a muscle pump? Med Sci Sports Exerc 31: 1027- 1035,
1999.

Lebon V, Brillault-Salvat C, Bloch G, Leroy-Willig A, Carlier PG. Evidence of
muscle BOLD effect revealed by simultaneous interleaved gradient-echo NMR] and
myoglobin NMRS during leg ischemia. Magn Reson Med 40: 551-558, 1998.

Lebon V, Carlier PG, BrillauIt-Salvat C, Leroy-Willig A. Simultaneous
measurement of perfusion and oxygenation changes using a multiple gradient-echo
sequence: application to human muscle study. Magnetic Resonance Imaging 16(7):
721-729, 1998.

Mackie BG, Terjung RL. Inﬂuence of training on blood ﬂow to different skeletal
muscle ﬁber types. J App] Physio] 55(4): 1072-1078, 1983.

Maiorana A, O'Driscoll G, Cheetham C, Dembo L, Stanton K, Goodman C,
Taylor R, Green D. The effect of combined aerobic and resistance exercise
training on vascular ﬁJnction in type 2 diabetes. J Am Coll Cardiol 38(3): 860-866,
2001.

Marshall J M, Tandon HC. Direct observations of muscle arterioles and venules
following contraction of skeletal muscle ﬁbres in the rat. J Physiol 350: 447-459,
1984.

McCully KK, Hamaoka T. Near-infrared spectrosc0py: what can it tell us about
oxygen saturation in skeletal muscle? Exerc Sport Sci Rev 28: 123-127, 2000.

168

 

 

36.

37.

38.

39.

40.

41.

42.

43.

44.

45.

46.

47.

McDermott MM, Kerwin DR, Liu K, Martin GJ, O'Brien E, Kaplan H,
Greenland P. Prevalence and signiﬁcance of unrecognized lower extremity
peripheral arterial disease in general medicine practice. J Gen Intern Med 16: 384-
390, 2001.

Meredith CN, Frontera WR, Fisher EC, Hughes VA, Herland JC, Edwards J,
Evans WJ. Peripheral effects of endurance training in young and old subjects. J
Appl Physiol 66(6): 2844-2849, 1989.

Meyer RA, Foley JM, Harkema SJ, Sierra A, Potchen EJ. Magnetic resonance
measurement of blood ﬂow in peripheral vessels after acute exercise. Magn Reson
Imaging 11: 1085-1092, 1993.

Meyer RA, Towse TF, Reid RW, Jayaraman RC, Wiseman RW, McCulIy KK.
BOLD MRI mapping of transient hyperemia in skeletal muscle after single
contractions. NMR Biomed 17(6): 392-398, 2004.

Mihok ML, Murrant CL. Rapid biphasic arteriolar dilations induced by skeletal
muscle contraction are dependent on stimulation characteristics. Can J Physiol
Pharmacol 82: 282-287, 2004.

Mizuno M, Kimura Y, Iwakawa T, Oda K, Ishii K, Ishiwata K, N akamura Y,
Muraoka I. Regional differences in blood volume and blood transit time in resting
skeletal muscle. Jpn J Physiol 53: 467-470, 2003.

Mohrman DE, Sparks HV. Myogenic hyperemia following brief tetanus of canine
skeletal muscle. Am J Physio] 227(3): 531-535, 1974.

Mohrman DE, Sparks HV. Role of potassium ions in the vascular response to a
brief tetanus. Circ Res 35(3): 384-390, 1974.

Mohrman DE, Sparks HV. Dynamics of Exercise Hyperemia. Journal of Dynamic
Systems, Measurements, and Control: 285-287, 1973.

Murrant CL, Sarelius IH. Multiple dilator pathways in skeletal muscle
contraction-induced arteriolar dilations. Am J Physio]: Regul Integ Comp Physio]
282(4): R969-978, 2002.

Murrant CL, Sarelius III. Coupling of muscle metabolism and muscle blood ﬂow
in capillary units during contraction. Acta Physio] Scand 168(4): 531-541, 2000.

Paganini AT, Foley JM, Meyer RA. Linear dependence of muscle

phosphocreatine kinetics on oxidative capacity. Am J Physio]: Cell Physiol 272(2):
C501-510, 1997.

169

 

 

48.

49.

50.

51.

52.

53.

54.

55.

56.

57.

58.

Plasqui G, Westerterp KR. Physical activity assessment with accelerometers: an
evaluation against doubly labeled water. Obesity 15(10): 2371-2379, 2007.

Raitakari M, Knuuti MJ, Ruotsalainen U, Laine H, Makea P, Teras M, Sipila
H, N iskanen T, Raitakari OT, Iida H. Insulin increases blood volume in human

skeletal muscle: studies using [150]CO and positron emission tomography. Am J

Physiol 269: E1000-1005, 1995.

Raitakari M, Nuutila P, Knuuti J, Raitakari OT, Laine H, Ruotsalainen U,
Kirvela O, Takala TO, Iida H, Yki-Jarvinen H. Effects of insulin on blood ﬂow
and volume in skeletal muscle of patients with IDDM: studies using [lSO]H20,
[150]CO, and positron emission tomography. Diabetes 46: 2017-2021, 1997.

Richardson RS, Newcomer SC, and Noyszewski EA. Skeletal muscle
intracellular P0(2) assessed by myoglobin desaturation: response to graded
exercise. J Appl Physiol 91: 2679-2685, 2001.

Roman BB, Meyer RA, Wiseman RW. Phosphocreatine kinetics at the onset of
contractions in skeletal muscle of MM creatine kinase knockout mice. Am J
Physiol: Cell Physiol 283(6): C1776-1783, 2002.

Segal SS. Microvascular recruitment in hamster striated muscle: role for conducted
vasodilation. Am J Physiol 261(1) : H181-189, 1991.

Segal SS. Integration of blood ﬂow control to skeletal muscle: key role of feed
arteries. Acta Physiol Scand 168(4): 511-518, 2000.

Segal SS. Regulation of blood ﬂow in the microcirculation. Microcirculation 12(1):
33-45, 2005.

Shoemaker JK, Phillips SM, Green HJ, Hughson RL. Faster femoral artery
blood velocity kinetics at the onset of exercise following short-term training.
Cardiovasc Res 31: 278-286, 1996.

Slade JM, Towse TF, Delano MC, Wiseman RW, Meyer RA. A gated 31P NMR
method for the estimation of phosphocreatine recovery time and contractile ATP
cost in human muscle. NMR Biomed 19(5): 573-580, 2006.

Territo PR, French SA, Dunleavy MC, Evans FJ, Balaban RS. Calcium

activation of heart mitochondrial oxidative phosphorylation: rapid kinetics of
mVO2, NADH, AND light scattering. J Biol Chem 276: 2586-2599, 2001.

170

 

 

 

59.

60.

61.

62.

63.

64.

65.

66.

67.

Towse TF, Slade JM, Meyer RA. Effect of physical activity on MRI-measured
blood oxygen level-dependent transients in skeletal muscle after brief contractions.
JAppl Physio] 99(2): 715-722, 2005.

Tschakovsky ME, Sheriff DD. Immediate exercise hyperemia: contributions of the
muscle pump vs. rapid vasodilation. J App] Physio] 97(2): 739-747, 2004.

Tschakovsky ME, Shoemaker JK, Hughson RL. Beat-by-beat forearm blood
ﬂow with Doppler ultrasound and strain-gauge plethysmography. J App] Physio]
79(3): 713-719, 1995.

Tschakovsky ME, Shoemaker J K, Hughson RL. Vasodilation and muscle pump
contribution to immediate exercise hyperemia. Am J Physiol: Heart Circ Physiol
271(4): H1697-1701, 1996.

Williams DA and Segal SS. Feed artery role in blood ﬂow control to rat hindlimb
skeletal muscles. J Physio] 463: 631-646, 1993.

Xiang L, N aik J, Hester RL. Exercise-induced increase in skeletal muscle
vasodilatory responses in obese Zucker rats. Am J Physiol: Regul Integr Comp
Physio] 288(4): R987-99l, 2005.

Yang HT, Laughlin MH, and Terjung RL. Prior exercise training increases
collateral-dependent blood ﬂow in rats after acute femoral artery occlusion. Am J
Physio]: Heart Circ Physio] 279: H 1890-1897, 2000.

Yang HT, Ogilvie RW, Terjung RL. Training increases collateral-dependent
muscle blood ﬂow in aged rats. Am J Physiol: Heart Circ Physiol 268(3): H1174-
1180, 1995.

Zhao JM, Clingman CS, Narvainen MJ, Kauppinen RA, van Zijl PC.

Oxygenation and hematocrit dependence of transverse relaxation rates of blood at
3T. Magn Reson Med 58: 592-597, 2007.

171

CHAPTER 6: SUMMARY AND CONCLUSIONS

The overall aim of these studies was to determine if the transient changes in MRI
signal intensity following a brief muscle contraction are quantitatively explained by the
blood oxygenation level-dependent (BOLD) contrast mechanism commonly exploited in
brain functional imaging. It was hypothesized that if the transient increase in MRI signal
intensity following a brief muscle contraction were due to BOLD contrast, then blood
ﬂow, blood volume and hemoglobin saturation would also increase in parallel. Presented
below are the speciﬁc aims for each study and the speciﬁc hypotheses tested. Results for

each speciﬁc aim are summarized below.

6.1 Study 1 (Chapter 3)

Speciﬁc Aim #1: To determine if the transient changes in skeletal muscle signal intensity

 

(SI) in T 2*-weighted images following single, brief muscle contractions are due to the
blood oxygen level-dependent (BOLD) contrast commonly used in brain ﬁmctional

imaging.

Hypothesis 1: NIRS measures of blood volume and hemoglobin saturation will increase

transiently following a single, brief muscle contractions.

Hypothesis 2: The time course of the change in blood volume and hemoglobin saturation

will be similar to the time course of the SI changes in the T 2*-weighted images.

172

Hypothesis 3: The magnitude of the transient changes in skeletal muscle signal intensity
(SI) in T 2*-weighted images following single, brief muscle contractions will be higher at

higher ﬁeld strength.

Hypothesis 4: The magnitude of the transient changes in skeletal muscle signal intensity
(SI) following single, brief muscle contractions will be larger when measured by a GE

versus SE pulse sequence.

Results:

a. Blood volume and hemoglobin saturation increased transiently following a single,
brief muscle contractions.

b. Within the limits of the NIRS device employed, the time to peak and time to half
recovery of the post-contractile MRI transients were similar to the NIRS
transients.

c. The magnitude of the transient changes in skeletal muscle signal intensity (S1) in
T 2*-weighted images was ﬁeld strength dependent and as such was greater when
measured at 3 versus 1.5 T.

d. The magnitude of the transient changes in skeletal muscle signal intensity (SI) in
T 2*-weighted images were not different when measured by GE versus SE pulse

sequence.

173

6.2 Study 2 (Chapter 4)

Speciﬁc Aim #2: Determine if the magnitude and the time-course of the post-contractile

 

muscle BOLD response is different in a group of habitually active versus sedentary

subjects.

Hypothesis 1: The magnitude of post-contractile BOLD response will be larger in the

habitually active versus the sedentary subjects.

Hypothesis 2: The time to the peak BOLD response and the half-recovery time of the

response will be shorter in the habitually active versus the sedentary subjects.

Hypothesis 3: The magnitude of the ﬂow response to a dynamic sustained exercise will

be similar for between the habitually active versus sedentary subjects.

Results:

a. The peak of the post-contractile muscle BOLD response was higher in the

habitually-active versus sedentary subjects.

b. The time to peak BOLD was not different across the groups, although the active

subjects took signiﬁcantly longer to return to half-maximal BOLD than the

174

 

sedentary subjects.

c. The peak ﬂow response to a 2-minute dynamic exercise of the ankle dorsiﬂexors,
as measured in the anterior tibial arterym was not different between the active

versus sedentary subjects.

6.] Study 3 (Chapter 5)

 

Speciﬁc Aim #3: To characterize the post-contractile ﬂow response in active versus
inactive subjects, and to determine if the magnitude and time course of the post-
contractile muscle BOLD can be quantitatively explained by the magnitude and time

course of measured changes in blood volume and saturation.

Hypothesis 1: Habitual activity will be positively associated with the magnitude of the

post-contractile ﬂow response.

Hypothesis 2: The magnitude and time course of the post-contractile muscle BOLD will
be explained by the magnitude and time course of the measured changes in blood volume

and saturation.

Hypothesis 3: The magnitude and the time course of the ﬂow response and an estimate of

rapid onset of oxygen consumption will explain the blood volume ad saturation changes,

and hence the BOLD.

175

Results:

a. The magnitude of the post-contractile increase in blood ﬂow following a single 1

second contraction varies across individuals based on physical activity.

b. NIRS estimates of blood volume and oxygenation changes together quantitatively

explain the BOLD response.

c. The ﬂow response qualitatively explains the BOLD response. However, the

BOLD response also depends critically on the kinetics of oxygen consumption.

6.4 Limitations of these studies.

1.

The main limitation of this study was that, although blood ﬂow and NIRS
were measured simultaneously, they were measured separately from the MRI
muscle BOLD. It was necessary to measure the blood ﬂow and NIRS

separately as the NIRS system was not MR compatible.

Currently there are no MR compatible human Doppler systems and MRI

measures of blood ﬂow have relatively poor temporal resolution.

The NIRS device we used only provides relative measures of blood volume
and saturation. However the NIRS data was expressed relative to post-
ischemia values of deoxyhemoglobin and oxyhemoglobin, a common
physiological calibration. Obtaining an NIRS system that provides absolute

values for deoxyhemoglobin and oxyhemoglobin was cost prohibitive.

176

4. In the model myoglobin was assumed to be 40% of the maximal post-
ischemia hemoglobin content and was assumed to remain fully saturated
during and following the contraction. In fact, here would likely be some
between=subject variability in myoglobin content and the assumption that
myoglobin remains fully saturated during and after the contraction has not
been validated. Despite our assumptions regarding myoglobin content and
saturation, the measured MRI bold effect our was in excellent agreement with

the effect calculated from NIRS estimates of blood volume and saturation.

5. The measures of physical activity are only snap-shots of each subject’s
physical activity patterns, and do not necessarily reﬂect the subject’s long
term physical activity. Although we attempted to recruit subjects with
physical activity patterns that were consistent over the span of multiple years,

we have no way of conﬁrming this.

Every tool to measure physical activity has strengths and weaknesses, however
when multiple tools are used in combination as was the case in this study they can
provide a more accurate picture of a subject’s true physical activity patterns. A training
study would appear a logical option for addressing the questions of whether or not
training impacts either the blood ﬂow response to a single contraction of the muscle

BOLD response, however at this time a training study was outside the scope of the

177

investigation. . The space, equipment, patience and organizational skills to successfully

complete a training study were not made available to the author.

6.5 Positive outcomes of the study.

This thesis research sought to determine if a post-contractile BOLD response
occurs in skeletal muscle. The three studies within this project characterized the post-
contractile muscle BOLD response and determined contributions from blood ﬂow, blood
volume and saturation. Furthermore the studies sought to determine the impact of
habitual physical activity on the post-contractile ﬂow and BOLD response, and the
interrelationship between blood ﬂow and BOLD.

Although there was preliminary evidence for a post-contractile BOLD response,
our research conﬁrmed the existence of the response in muscle. Based on the changes in
NIRS-measured blood volume, hemoglobin saturation, as well as the ﬁeld strength
dependence, the post-contractile MRI transient is clearly due to the BOLD effect.

The ﬁnal two studies support a role for the BOLD contrast as a measure of
microvascular ﬁlnction, and suggest that habitual physical activity inﬂuences the
magnitude of both the post-contractile ﬂow and BOLD responses. The factors that
regulate the ﬂow response to a single, brief muscle contraction has received much
attention. The interest stems in part from the fact that the response is controlled by the
terminal arterioles. Vascular resistance in the peripheral circulation is largely a function
of the tone of the arterioles and the terminal arterioles regulate the perfusion of the
capillary bed. Therefore the single contraction model may provide an indicator of

microvascular function.

178

To my knowledge we are the ﬁrst group to show that habitual physical activity
results in a greater post-contractile ﬂow response to a single brief contraction. Our results
suggest that habitual physical activity improves microvascular function. Future studies
will be needed to more clearly deﬁne the relationship between physical activity and the
ﬂow response to a brief contraction. In addition if the ﬂow response to a brief contraction
is a good tool for assessing microvascular health, it might be used for evaluation of a

variety of patient populations with diseases that impact the microvasculature.

179

 

      

   

  

AAAAAAAAAAA

lllllllllll llllll

3 1293

 

llllllllllllllllllllll”