Morphology of the aortic arch: a factor determining aortic

262 Pages·2016·25.46 MB·English

Morphology of the aortic arch: a factor determining aortic
hemodynamics and the load on the heart ?
Celine Joos
Supervisors: Prof. dr. ir. Patrick Segers, Dr. Laurent Demulier (UZ Gent)
Counsellor: Alessandra Bavo
Master’s dissertation submitted in order to obtain the academic degree of
Master of Science in Biomedical Engineering
Department of Electronics and Information Systems
Chair: Prof. dr. ir. Rik Van de Walle
Faculty of Engineering and Architecture
Academic year 2015-2016

The author, Celine Joos, gives permission to make this master dissertation available
for consultation and to copy parts of this master dissertation for personal use. In the case
of any other use, the copyright terms have to be respected, in particular with regard to the
obligation to state expressly the source when quoting results from this master dissertation
- 10/06/2016.
Preface
In this section I would like to thank some people for their intellectual and psychological
support.
Whenitcomestotheintellectualpartofthestory, ProfessorSegersandAlessandraarethe
two major players. I would like to thank them for their valuable insights while generating
the models, adapting the solution methods and interpreting the results. For the correction
of this typoscript special thanks go to Alessandra for her extra-ordinary efforts and late
nights. Further should be thanked: Dr. Demulier for his interesting idea which led to the
production of this work and Dr. Devos for the generation of the high quality data.
Psychological support came especially from Koen, Gerlinde, FM, Joke, Nika and my par-
ents.
Thank you.
Abstract
Abnormalities of the aortic arch, as the most proximal site of the cardiovascular system,
are of great interest due to its major role in blood distribution to all downstream members.
By means of running computational fluid dynamic simulations on (1) idealized geometries
and (2) realistic patient-specific geometries the aortic blood flow patterns related to the
morphology of the aortic arch are investigated. Three separate morphologies - the physio-
logicalromanesquearchmorphologyandtheabnormalcrenelandgothicarchmorphologies
- are compared.
Although the helical blood flow patterns in the aorta are necessary for proper function-
ing of the cardiovascular system, the abnormal gothic arch geometry is associated with a
more widespread helical flow pattern compared to arches with less sharp angles. From the
preliminary results of this work, it could be hypothesized that the pronounced helical flow
reducestheaxialbloodvelocitytoomuchandsoreducestheefficiencyofthecardiovascular
system. Furthermore, the gothic arch morphology, which is known to be correlated with
hypertension induces larger pressure variations when compared to a romanesque or crenel
morphology, which can result in an increased cardiac load. So, it can be hypothesized that
abnormal arch geometry leads to adverse effects on cardiovascular functioning due to (1)
an overexpression of the helical flow pattern and to (2) larger pressure variations.
Morphology of the Aortic Arch: A Factor
Determining Aortic Hemodynamics and the Load of
the Heart?
Celine Joos
Supervisors: Patrick Segers, Alessandra Bavo, Laurent Demulier
enumerated. The disturbed flow patterns are often
Abstract By means of running computational fluid dynamic encountered at certain sites in the human arterial system: at
simulations on (1) idealized geometries and (2) realistic patient- the outer wall of arterial bifurcations and the inner wall of
specific geometries the aortic blood flow patterns related to the curved vessels. Hypertension, another promotor for various
morphology of the aortic arch are investigated. Three separate vascular disorders (acute aortic dissection, aortic dilatation
morphologies - the physiological romanesque arch morphology
and aneurysm formation) occurs in 50\% of the adult Turner
and the abnormal crenel and gothic arch morphologies - are
population. De Groote et al. (2014) found that hypertension is
compared.
independently associated with abnormal arch geometry in TS
Although the helical blood flow patterns in the aorta are
patients.
necessary for proper functioning of the cardiovascular system,
In the analysis of Ou et al (2004) three categories of
the abnormal gothic arch geometry is associated with a more
widespread helical flow pattern compared to arches with less geometries are classified: the romanesque, the crenel and the
sharp angles. From the preliminary results of this work, it could gothic morphology (Figure 1).
be hypothesized that the pronounced helical flow reduces the
axial blood velocity too much and therefore reduces the
efficiency of the cardiovascular system. Furthermore, the gothic
arch morphology, which is known to be correlated with
hypertension induces larger pressure variations when compared
to a romanesque or crenel morphology, which can result in an
increased cardiac load. So, it can be hypothesized that abnormal
arch geometry leads to adverse effects on cardiovascular
functioning due to (1) an overexpression of the helical flow
pattern and to (2) larger pressure variations.
Keywords CFD simulations, aortic arch morphology, Turner
syndrome, helical blood flow patterns

Figure 1: Three different morphologies of the aortic shape (adapted
I. INTRODUCTION from Ou et al., 2004)
In vascular diseases, the local blood flow characteristics
(Ullrich-)Turner syndrome (TS) is the most common
play a significant role in the development and progression of
chromosomal abnormality in females and is associated with
the pathology and should therefore be studied in detail. A
several co-morbidities. It is a congenital endocrine disorder in
detailed knowledge of pressure and flow distributions in the
which one of the two X sex chromosomes is lacking (=
arterial tree is also indispensable in diagnostics and planning
monosomy X = karyotype 45,X) or abnormal. The prevalence
of treatment. Modeling of the cardiovascular system is one
is 1 in 2000-3500 live-born females
way to acquire this knowledge. The main goal of this thesis is
The presence of congenital heart diseases is a clinical
to provide a simple yet reliable tool to numerically investigate
feature developed in 30-50% of TS cases. The most important
the fluid dynamics of the aortic arch and identify the possible
malformations are, among others: dilatation of the ascending
correlations between abnormal flow patterns and the different
aorta, a bicuspid aortic valve, aortic coarctation or narrowing,
morphologies.
an elongated transverse arch, aberrant right subclavian artery,
and aortic arch hypoplasia (Mortensen et al., 2010). It should
be emphasized that these cardiovascular abnormalities often II. MATERIALS AND METHODS
occur simultaneously and increase the overall burden for the Generally, the patient-specific computational fluid
patient. The prevalence of a geometrically abnormal arch is 30 dynamics (CFD) model generation and solution can be
to 50% in TS patients. described in seven main stages: (1) Medical imaging, (2)
Vascular disorders are primarily related to arteriosclerosis. segmentation and reconstruction, (3) discretization, (4)
The development of arteriosclerosis is a multifactorial process Boundary conditions (BCs) and modeling assumptions, (5)
influenced by a combination of several modifiable (obesity) numerical simulation, (6) post-processing and (7) validation
and non-modifiable (age) risk factors. Among the risk factors (Figure 2 and 3).
hemodynamic parameters, such as disturbed blood flow, low
wall shear rate and wall shear stress (WSS) can be A. Idealized geometries
As various cardiac malformations often occur
simultaneously in patients, it is difficult to independently
investigate the impact of the distorted geometry on the
hemodynamics. To isolate the effect of the aortic arch
morphology on the fluid dynamics, simplified CFD models,
which resemble the anatomical arch shapes in the cases of
interest, are derived.
As the idealized geometries were generated in Siemens NX
9.0, this one step replaces the first two stages, being medical
imaging and segmentation/reconstruction (Figure 2). The
dimensions for the generation of the geometries are averaged
from the patient-specific data and are in agreement with
literature data.

Figure 2: Applied workflow for the idealized geometries
Figure 4: Four patient-specific aorta models with their distinct unique
shapes
B. Patient-specific geometries
The first patient (P1) shows a romanesque aortic arch, a
dilated aortic root and a common ostium of the
brachiocephalic trunk (BC) and left common carotid artery
(LCC). P2 is a patient with a crenel-shaped arch, a dilated left
subclavian artery (LS) and a common ostium of the BC and
LCC. The subject with the aortic arch most resembling the
gothic shape (P3) has a right-turning aorta and four, instead of
three, supra-aortic arteries. The right common carotid artery
(RCC) and the right subclavian (RS) artery do not originate
from a common brachiocephalic trunk, but branch off
separately. The right subclavian artery is, in this case, the third
branching off from the main aorta. A patient (P4) with a very
asymmetrical and dysmorphic aorta was chosen. This case
cannot be classified into one of the main categories; the aorta
is elongated, it shows a coarctation and a dilated LS.
To create the patient-specific 3D computer models of the
relevant vasculature, the Vascular Modeling ToolKit Lab
software (VMTKLab by Orobix, Bergamo, Italy) is used. The
Figure 3: Applied workflow for the patient-specific geometries
contrast-enhanced MR-images were segmented in order to
Four geometrically relevant models (Figure 4) of patients identify the contours of the vascular tissue. After pre-
with a congenital cardiovascular disease were chosen from a processing this extracted geometry defines the computational
medical database of 80 subjects who suffer from Turner’s domain. Due to the high quality of the images this step of the
syndrome. All subjects received a three-yearly MRI as part of model generation is quite simple, but nevertheless very
their medical follow up. Based on the quality of the MRI operator dependent.
images, the shape of the arch and the availability of additional
clinical data, relevant subjects were selected. C. Meshing and elements
In three of the cases, the shape of the arch was classified as
To solve the Navier-Stokes equations numerically, the flow
in Ou et al. (2004) resulting in romanesque, crenel and gothic
domain has to be split into control volumes (cells) in order to
arches. The fourth case was chosen because of the complexity
compute the solution. A tetrahedral mesh is used due to the
of its arch shape: the presence of a highly distorted geometry
complexity of the patient-specific geometries. To have a more
did not allow for a classification, but it was considered an
reliable description of the WSS at the wall, a boundary layer
interesting testing case for the purposes of this work (Figure
was generated to guarantee a layer of refined cells. A mesh
4).
sensitivity study is conducted. With ANSYS-ICEM (Ansys
Inc., USA) grids with 350.000 - 400.000 elements are E. Hemodynamic parameters
obtained for the simplified geometries. For the patient-specific
The wall shear stress (WSS) is defined as the tangential
geometries the meshes are larger, up to 900.000 elements.
force per unit area that is exerted by the flowing fluid on the
surface of the conduit tube. In arteries in specific, the WSS is
D. Boundary conditions and modeling assumptions the mechanical force generated by the blood flow to shear the
Flow recordings were available from MR analysis in a plane endothelial layer of the vessel wall. The wall shear stress τ is
w
perpendicular on (1) ascending and descending aorta and (2) calculated as:
the supra-aortic arteries. Reynolds and Womersley numbers
are listed in Table 1.

(1)
Table 1: Reynolds and Womersley numbers
with (cid:181) the dynamic viscosity, y the direction perpendicular to
Remean Repeak Wo the wall and v the velocity tangent to the wall.
P1 600 2900 24 To obtain one single value for the wall shear stress over one
P2 1000 4300 15 heart cycle, the time-averaged wall shear stress (TAWSS) is
P3 900 4000 18 commonly used. The TAWSS is calculated by averaging the
P4 800 2800 16 norm of the time dependent wall shear vector, τ, over one
cardiac cycle with period T:
Time-dependent flat velocity profiles are imposed at the
inlets. For the idealized geometries the profile is averaged
from the available patient-specific velocity profiles. The peak
velocity is 0,46 m/s, the average velocity over an entire cycle
(2)
0,12 m/s. The pulse period of this waveform is 1s. This results
with n the number of time steps in the CFD simulation.
in an average Reynolds number of 600, a maximum Reynolds
number of 3400 and a Womersley number of 17. Blood flow
is normally assumed to be laminar in large vessels because the III. RESULTS AND DISCUSSION
mean flow velocity is predicted to be sufficiently low to result

in a relatively low Reynolds number. For pulsatile unsteady A. Flow patterns
flow, turbulence occurs at a Reynolds number much larger
The gothic arch geometry is associated with a more
than expected for steady flow because accelerating flow is
widespread helical flow pattern compared to arches with less

more stable than decelerating flow (Tse et al., 2013).
sharp angles (Figure 5).
The outflow discharges were derived from the flow
According to literature (Morbiducci et al., 2009; Lee et al.,
recordings (Table 2). For the idealized geometries the flow
2014) it can be concluded that helical blood flow patterns are
split distribution of P1 is used.
necessary for proper functioning of the cardiovascular system.
Table 2: Flow split distributions The helical pattern seems to prevent energy dissipation by
keeping the flow laminar and facilitates ventricular ejection.
P1 P2 P3 P4
Additionally the oxygen transfer is promoted and the
BC 11,5 27,0 / 13,5
concentration of low-density lipoproteins on the luminal
LCC 10,5 3,0 5,5 8,0
surface is reduced.
LS 8,0 3,0 3,0 3,0 From the preliminary results of this work, it could be
RCC / / 9,0 / hypothesized that the pronounced helical flow, promoted by
RS / / 5,5 / the acute angle in the gothic morphology, reduces the axial
OUTLET 70,0 67,0 77,0 75,5 blood velocity too much and therefore reduces the efficiency
of the cardiovascular system.
Blood is considered an istotropic, incompressible,
homogeneous, Newtonian, viscous fluid in large arteries with
the dynamic viscosity of 0.0035 Pa s and the mass density of
1060 kg/m3. The aortic wall is assumed to be rigid with no-

slip condition at the wall.
Three cardiac cycles were simulated in a test phase. No
significant difference was observed in the results (< 2%
difference in outlet velocity at peak systole) of the second and
the third cycle. Therefore, only two cycles, with time steps of
5 ms for the idealized geometries and 2 ms for the patient-
specific geometries, for the remaining simulations are
computed. The convergence criterion selected is the relative
reduction of the residuals of the Navier-Stokes equations of
three orders of magnitude.
The simulations are performed on a high performance Linux
computing cluster (6 CPU’s) dedicated to computational
mechanics of Ghent University and are performed in ANSYS
Fluent 14.0.
B. WSS

Figure 6: TAWSS for the simplified geometries (High scale) - left:
romanesque arch - middle: crenel arch — right: gothic arch
High TAWSS values are around 1,5-3 Pa. Only in the
abnormal arches TAWSS > 3,5 Pa are observed. High
TAWSS values are more frequently detected in the gothic
arch than in the other. The TAWSS values in the arch are of
the same order of magnitude as the values reported from the
FSI model of (Lantz et al., 2011).
The occurrence of high TAWSS expresses regions with
high risk of vasodilation and then remodeling to a larger
diameter with the same arterial structure (Ku et al., 1997).
From a fluid mechanical standpoint, this implies that there is a
higher chance for remodeling in a gothic arch than in a
romanesque or crenel one.
C. Pressure
While velocities can be obtained from in vivo
measurements, it is extremely difficult to obtain quantitative
information on pressure. As the current work focuses on CFD

simulations, all the results are reported in terms of pressure

drop. The absolute pressure does not influence the velocity
Figure 5: Streamlines for the patient-specific geometries of P1, P2 field, as the pressure gradient is present in the Navier-Stokes

and P3 in the decelerating phase (late systole) equations.
features of pathological arches to verify the preliminary
results obtained in the simplified model, to gain deeper
insights on the pathological fluid-dynamics of the desired arch
morphology and to propose a comparative study on the impact
of the shape of the arch on the overall hemodynamics of the
region.
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Schepper, and D. De Wolf. Abnormal aortic arch morphology in turner
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specific human aorta - influence of fluid-structure interaction.
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[3] Annals of Biomedical Engineering, 37(3):516—531, 2009.
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Figure 8: Pressure drop along the centerline at peak systole for P4
It is noteworthy that P4 shows a pressure drop (Figure 8)
which is one order of magnitude larger than the remaining
patients (not shown). The coarctation is the most obvious
cause for this large pressure drop across the arch, but the
sharp angle and the tortuosity of the geometry also introduce
additional hydraulic resistance.
IV. CONCLUSION
Disturbed hemodynamics poses a severe risk in terms of
development of cardiovascular diseases. Blood flow in the
human aorta is of particular interest because the highly curved
aorta is the largest vessel in the human vascular system and
plays a major role in blood distribution to all downstream
members. Secondary flow motions are considered to facilitate
ventricular ejection, promote oxygen transfer and reduce the
risk of atherosclerosis. So, a better understanding of the
mechanism of flows in the aortic arch is important.
In conclusion, this work aimed to investigate the influence
of the arch morphology on the flow field with two separated
but complementary models. A simplified model approach was
adopted to separate the shape of the arch from the remaining
complications present in a more refined model. The second
adopted modeling modality was a CFD patient-specific
model. With this technique we targeted the patient-specific