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General introduction
Taco Kind
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Chapter 1
Introduction
P
ULMONARY HYPERTENSION (PH) is a disorder of the pulmonary vasculature,
characterized by increased pulmonary pressure, leading to right ventricular (RV)
overload. The course of the illness varies from patient to patient, with the worst prognosis
seen in patients with the greatest degree of RV dysfunction1. Thus, assessment of the
current condition of a PH patient requires knowledge of arterial function as well as cardiac
function. This chapter provides an overview of the current insights into anatomy and
function of the pulmonary circulation and the application of invasive and non-invasive
measurements to quantify the circulatory function in physiological and pathophysiological states.
Pulmonary circulation
The pulmonary circulation is complex in terms of anatomy and physiology and differs
considerably from its systemic counterpart. In the systemic circulation, blood pressure
is relatively high with an average arterial pressure of about 90 mmHg in the healthy adult.
With this pressure and a normal blood flow of about 6-7 liter/min an optimal perfusion
to all tissues can be maintained2. The pulmonary circulation receives the same amount
of blood as the systemic circulation, but due to the lower vascular resistance, the pulmonary artery pressure is much lower with an average value of about 14 mmHg in the
healthy adult. The resistance is kept low due to the large number of pulmonary vessels
and the large vascular volume that can be recruited. This large vascular volume and related
large blood-gas exchange area facilitate efficient oxygenation and CO2 exchange. The
low pressure prevents fluids moving from the pulmonary vessels into the interstitial space
and allows the RV to operate efficiently3.
In PH, microvascular narrowing and reduction of the recruitment capacity of blood
vessels occur. These impairments result in an increase in vascular resistance, a decrease in
vascular compliance, and as a consequence, an increase in pulmonary artery pressure
(PAP). Clinically, the diagnosis PH is established when mean PAP is higher than 25
mmHg at rest. PH is classified in several clinical groups, such as pulmonary arterial
hypertension (PAH) of which idiopathic PAH (i.e. with no apparent cause) is most
common. Other clinical groups are pulmonary veno-occlusive disease, PH due to left
heart disease, PH due to lung diseases, chronic thromboembolic pulmonary hypertension, and PH with unclear and/or multifactorial mechanisms4.
Although increased PAP is the hallmark of PH, it has little value in predicting prognosis. It appears that the inability of the RV to cope with the progressive increase in
pressure is the main cause of death5. Due to the increased vascular resistance the RV
10
General introduction
operates at much higher energy cost to maintain sufficient levels of oxygenation. This
results in hypertrophy of the myocardial wall. Although this adaptation process continues
over time, at a certain point the RV fails to hypertrophy sufficiently and starts dilating.
Ultimately, the ventricle fails to maintain sufficient cardiac output, which is the main
cause of death in these patients.
Pulmonary vascular bed
Structural organization
The pulmonary artery originates at the RV and bifurcates into the left and right pulmonary artery, extending into the corresponding lung. Subsequent branching of the arteries
continues progressively over the arterial tree. The proximal arteries are the most compliant
vessels, which contain elastic laminae in the tunica media (middle layer of the vessel) to
facilitate compliance. More distal arteries are less compliant due to increased smooth
muscle and decreased elastic laminae in the tunica media6. These arteries regulate resistance and are therefore especially important in pressure regulation7. The most distal
pulmonary arteries are called the pre-capillary arteries (100-1000 µm). These vessels have
hardly any smooth muscle cells8 and form a network containing more than 300 million
vessels9. Under physiological conditions, resistance of these vessels decreases passively due
to distention and recruitment if pressure increases. In PAH, however, resistance in these
vessel can hardly be reduced due to medial hypertrophy10 and because most vessels have
already been recruited11. As a consequence, total resting resistance is high and arterial
compliance is low in PAH.
The pre-capillary arteries end in the pulmonary capillary network. This network is not
treelike, but forms a very large sheetlike area that facilitates efficient blood oxygenation 12.
From the pulmonary capillaries, oxygenated blood enters, via the venules, the pulmonary
venous vessels, which continue to converge until the left and right pulmonary veins of
both lungs are formed. These veins enter into the left atrium.
Adequate pressure regulation is compromised in PAH due to the increased vascular
resistance and decreased arterial compliance. This leads to impaired capillary blood perfusion and thereby reduced oxygenation. As blood oxygenation is the main function of the
lungs, information of the vascular characteristics and capillary blood perfusion can therefore be of great importance for evaluation of the extent of disease.
Assessment of vascular function
The muscular arteries and pre-capillary arteries mainly determine the total pulmonary
vascular resistance (PVR). Resistance of a vessel can be calculated using Poiseuille’s equa-
11
35
0.4
Impedance modulus
[mmHg/ml/s]
Pulmonary artery pressure
[mmHg]
Chapter 1
30
25
20
15
10
5
0
0
0.2
0.4
Time [s]
Pulmonary artery flow
[ml/s]
0.2
0.1
0
0
0.6
250
2
4
6
8
2
4
6
8
Frequency [Hz]
20
Phase
[degrees]
200
150
0
−20
100
50
−40
0
0
0.3
0.2
0.4
Time [s]
0.6
−60
0
Frequency [Hz]
Figure 1!"!#$%&'()!*+!%,!-&').%,/)!0')/123&!*41%-,).!-,!%!,*2&%(!0345)/16!78)!-&').%,/)!-0!/*&'31).!
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tion, which is derived from the Navier-Stokes equations and describes laminar fluid flow
in a long straight rigid tube with a circular cross section. In a clinical setting, Poiseuille’s
equation is not very practical since it requires knowledge of individual radii and lengths
of vessels and blood viscosity. Therefore, PVR is usually approximated (in analogy to
Ohm’s law in electrical network theory) as the mean transpulmonary pressure gradient
(i.e. mean pulmonary artery pressure minus pulmonary venous pressure or left atrial
pressure) divided by cardiac output. The dimension is in mmHg.min/liter, called Wood’s
unit, but can also be expressed in dynes.sec.cm-5 when multiplied by 80. With this approach,
the pressure-flow relation is assumed linear with the slope equal to PVR. Although
pressure-flow relations are always non-linear at small pressures (due to decruitment at
small blood flows)13, pressure-flow relations are approximately linear over a large range
of higher pressures14. This description of resistance has been proven useful in a clinical
setting15. However, the clinical definition of resistance is an oversimplification since it
assumes steady hemodynamics of the pulmonary vascular bed and completely neglects
the pulsatile behavior of arteries (e.g. arterial compliance).
A more complete characterization of the vascular bed can be obtained from pulsatile
pulmonary artery pressure and flow waves by calculating the arterial input impedance.
Unlike PVR, input impedance cannot be expressed as a single number, but it consists of
a magnitude and a phase as functions of frequency. Impedance can be derived from the
12
General introduction
A
Normal heart
B
Heart in PH
RV
RV
LV
RA
LV
LA
RV
RV
LV
LV
LV
RV
RV
RV
LV
RV
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pulsatile pressure and flow waves and by application of Fourier analysis. An example of
an impedance spectrum is shown in Figure 1.
Although the impedance spectrum is a complete characterization of the vascular bed,
its application in a clinical or experimental setting is hampered by difficulties to recognize
shape changes16. To improve the understanding of vascular impedance several models of
arterial input impedance have been proposed, such as lumped Windkessel models17,18,
tube models19,20 or anatomical distribution models19,21.
Of these, lumped Windkessel models are most frequently used in literature. It was Otto
Frank22 who introduced the two-element Windkessel model consisting of a resistance
and compliance element. In later research, the Windkessel model was extended with a
third element to account for the impedance of the proximal part of the arterial bed, which
is related to wave transmission aspects of the arterial system18, and a fourth element to
account for the inertia of blood23,24.
The three-element Windkessel model is most widely used as a vascular model both of
the systemic and pulmonary vascular bed25-27. The model forms a good description of the
vascular impedance and can be deduced from the impedance spectrum (Figure 1). For
example, the pulmonary resistance is found at zero frequency, while the steepness of the
decrease in impedance modulus is closely related to total arterial compliance. Main
13
Chapter 1
pulmonary artery characteristic impedance can be obtained as the average modulus at
the higher frequency spectrum (>5Hz). This three-element Windkessel model was shown
to be a good representation of the arterial system in PH and that the elements could be
well estimated from clinical data25,26.
Right ventricle
Anatomy
As discussed above, pulmonary hypertension is a disease of the small vessels, but RV
function is the main determinant of prognosis. Adequate assessment of RV function can
greatly improve the prediction of prognosis, allowing for optimization of treatment efforts.
The RV receives mixed venous blood draining into the right atria from the systemic
circulation via the superior and inferior vena cava. As a consequence of the low pulmonary pressure, the RV can be distinguished morphologically from the LV by a thin (free)
wall and low-pressure structure. The shape of the RV is rather complex in contrast to the
near conical form of the LV. In anterior view, the RV has a triangular shape, but in cross
section, the RV appears like a crescent that is wrapped around the more elliptical LV
(Figure 2). Both the septum and RV free wall play an important role in ejection of blood.
The septum consists of oblique longitudinal fibers with spiral architecture leading to a
twisting motion during contraction28. In contrast, the predominantly transverse fiber
orientation of the RV free wall leads to circumferential compression29.
Assessment of right ventricular pump function
In PH, hypertrophy of the RV wall and enlargement of the RV cavity may occur (Figure
2). These alterations in geometry affect the primary function of the heart: ejecting a
sufficient amount of blood into the circulation. Therefore, quantification of the RV
geometry as well as changes of the geometry during contraction provides important
information of the disease. During contraction, the following changes in geometry occur
more or less simultaneously30: 1) longitudinal movement of the tricuspid valve ring toward
the apex; 2) compression of the RV by transverse movement of the free wall toward the
septum (i.e. bellows action); 3) traction of the RV free wall by contraction of the LV.
From these mechanisms, longitudinal movement of the tricuspid valve toward the apex
is most prominent, and impairment during disease is easily observed. Therefore, different
methods have been developed to quantify this movement as it is assumed to be a reflection of global RV function31. In this context, global RV function is usually quantified as
RV ejection fraction (RVEF), which is defined as the amount of blood ejected in one
beat relative to the end-diastolic (start of contraction) RV volume.
14
General introduction
B
filling
t0,ted
Ves
Ventricular volume [ml]
Ved
Eed
Elastance [mmHg/ml]
stroke volume
s
V0
ejection
ne
Ped
tes
isovolumic contr.
Pes
isovolumic relax.
Ees
ro
ch
iso
Ventricular pressure [mmHg]
A
Ees
Eed
t0
tes
ted
Time [s]
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Although RVEF provides important information on the global functional state of the
RV, it is not an intrinsic ventricular characteristic. It depends on filling and loading
conditions of the RV. For example, changes in loading conditions (e.g. by medical drugs,
medical intervention, or exercise) affect RVEF but do not necessarily alter the structural
behavior of the myocardial fibers. The main factors that determine cardiac performance
are myocardial contractility (activation and inactivation), chronotropy (heart rate), loading
conditions (ventricular preload, ventricular afterload, geometry), and heterogeneity in
contraction (conduction velocity, dyssynchrony). Contractility is an important determinant of the overall pumping characteristics of the ventricle, but is difficult to measure.
Contractility can be obtained from ventricular pressure (P) and volume (V) measurements
from which P-V loops can be constructed. In the 1970s, Suga and Sagawa introduced
the time-varying elastance concept, E(t), to describe LV pump function (Figure 3). E(t)
was defined as: P(t)=E(t)·(V(t)-V0), with V0 a constant intercept volume32. E(t) was shown
to be practically independent of loading conditions in the physiological range and to be
sensitive to inotropic interventions32. In particular, it was shown that the slope of the
end-systolic pressure-volume relation (Ees) was a sensitive and load-independent parameter
15
Chapter 1
of contractility (Figure 3). The time-varying elastance concept has been successfully
applied in the LV in multiple disease conditions33,34, and has also been applied in the RV 35,36.
For the estimation of the E(t) (and thus also Ees) loading conditions should be varied
to obtain multiple PV-loops over a range of different end-systolic pressure. This is usually
performed by a temporal and gradual partial occlusion of the inferior vena cava. In
hemodynamically compromised patients, such as in pulmonary hypertension, this procedure is ethically and practically not feasible. Therefore, several techniques have been
proposed to approximate Ees without the need of preload alterations. These methods are
based on estimating maximum isovolumic ventricular pressure from a single ejecting
pressure beat and are therefore called single-beat methods. These methods have potential
for clinical application, but only few studies exist of their application on the RV37 and
current assumptions of the isovolumic pressure waveform do not correspond to physiology and should be improved.
Aim and outline of this study
It is clear that pulmonary hypertension is as much a disease of the pulmonary blood
vessels as it is of the heart. Thus, insight into the current condition of a PH patient requires
knowledge of both arterial and cardiac function, and the interaction between these two.
This is a challenging task given the limited access to the cardiovascular system to perform
hemodynamical measurements. Furthermore, conceptual difficulties may occur in the
interpretation of measured variables in terms of cardiovascular parameters with clear
physiological meanings.
This thesis aims to improve insights in hemodynamics of the cardiovascular system
under physiological and pathophysiological conditions, focusing on clinical application
of diagnostic tools in PH patients. To reach this goal, RV function was assessed by
geometric shape changes during contraction. Furthermore, mathematical models of the
cardiovascular system were used to study characteristics of the arterial function, RV function and their interaction.
The first part: Cardiac function
The clinical standard of RV pump function is RV ejection fraction (RVEF). This measure
can be estimated non-invasively using several modalities (e.g. MRI). However, determining
RVEF using image analysis is time consuming and depends on geometric assumptions,
and this has limited the application in clinical practice. In Chapters 2 and 3 the focus is
on simpler geometric measures to approximate RV function and the clinical value of
these measures is investigated. In literature, many studies focused on longitudinal shortening of the RV during contraction31,38. In contrast, RV transverse shortening has been
studied less39-41 despite the importance of movement of the RV free wall towards the
16
General introduction
septum in RV ejection30. Therefore, in Chapter 2 longitudinal and transverse shortening
of the RV are explored in healthy control subjects and in PH patients and the relation
with RVEF are evaluated. The clinical value of these measures during follow-up is explored
in Chapter 3.
In Chapter 4 the interaction is studied between changes in pulmonary vascular resistance and RVEF in PAH patients under PAH targeted therapies. Despite the fact that
medical therapies reduce resistance, the prognosis of patients with PH is still poor. Possibly,
a reduction in resistance does not necessarily improve RV function. The relations of these
parameters and their prognostic value are described in this chapter.
In Chapter 5, the estimation of the time-varying elastance of the left ventricle from
multiple PV-loops is discussed. This chapter provides practical solutions to improve the
ease and robustness of the estimation of the elastance. The study is based on experimental
data obtained in the left ventricle, but the developed approach can be transferred, in
principle, to the analysis of RV data.
Measurements of multiple PV-loops require a reduction in cardiac preload, which is
not applicable in patients with PH. If in addition to a PV-loop, the maximal isovolumic
pressure (Pmax) could be derived, then the end-systolic elastance can be estimated without
the need of changes in preload. Therefore, in Chapter 6 several methods are evaluated to
estimate Pmax, and a new method is introduced to improve the accuracy in estimating
Pmax with a potential for clinical application.
Second part: Vascular function
In Chapter 7 the time varying elastance model of Chapter 2 is combined with a threeelement Windkessel model to simulate the pulmonary circulation. This model is used to
provide an explanation of the proportional relations, between mean pulmonary artery
pressure, systolic and diastolic pulmonary artery pressure, as reported previously42,43.
In Chapter 8 we address the estimation of the parameters of the Windkessel model.
This chapter is a mathematical approach how the model parameters can be estimated
efficiently.
Subsequent techniques focus on estimation of pulmonary perfusion. Chapter 9 evaluates
several mathematical techniques that can be used to estimate pulmonary perfusion parameters from MRI perfusion data (DCE-MRI). These methods are validated using realistic
simulation data. The use of simulation data has the advantage that “true” perfusion values
are known in advance so that the robustness of the estimation methods can be investigated. In Chapter 10 the same methods to estimate perfusion parameters are applied on
pulmonary perfusion data measured during contrast MRI in healthy control subjects and
in patients with PH.
The results and implications of this thesis are discussed in the concluding Chapter 11.
17
Chapter 1
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