Hellenic J Cardiol 2015; 56: 418-428
Original Research
Aortic Flow Patterns After Simulated Implantation
of Transcatheter Aortic Valves
AnAstAsios KopAnidis1,2, ioAnnis pAntos2,3, niKolAos Alexopoulos2,
AndreAs theodorAKAKos4, efstAthios efstAthopoulos3, demosthenes KAtritsis2,5
1
Department of Mechanical Engineering, University of Western Macedonia, Kozani, 2Department of Cardiology,
Athens Euroclinic, 3Second Department of Radiology, Medical School, National and Kapodistrian University of
Athens, 4Department of Mechanical Engineering, Technological Education Institute of Piraeus, Egaleo, Greece;
5
Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
Key words:
Bioprosthetic
valves, aortic flow,
computational fluid
dynamics.
Manuscript received:
September 17, 2014;
Accepted:
June 15, 2015.
Address:
Demosthenes Katritsis
Department of
Cardiology
Athens Euroclinic,
9 Athanassiadou St.
115 21 Athens, Greece
dkatritsis@euroclinic.gr,
dkatrits@bidmc.harvard.edu
Introduction: The functional behavior and hemodynamic characteristics of percutaneously implanted bioprosthetic valves are not known.
Methods: We created aortic models after the simulated implantation of two of the most widely used bioprosthetic valves: the Edwards SAPIEN, and the Medtronic CoreValve. By using computational fluid dynamics analysis we sought to investigate variations in the aortic flow patterns induced by the two valve designs
and their association with detrimental phenomena such as vascular remodeling, vascular wall damage and
thrombosis.
Results: The simulated implantation of models that resemble the two valves resulted in different aortic flow
conditions. Vortex formation in the upper ascending aorta was more persistent in the case of the simulated
Medtronic valve. The ranges of average wall shear stress (WSS) values were 2.4-3.5 Pa for Edwards and
3.0-5.3 Pa for Medtronic; the calculated WSS values induced endothelial quiescence and an atheroprotective
setting in both valves. The average shear stress on the simulated valve leaflets was low; however, hotspots
were present in both valves (155.0 Pa for Edwards and 250.0 Pa for Medtronic) which would in theory be
able to cause platelet activation and thus promote thrombosis. The pressure drops along the aorta were
slightly lower for the Edwards compared to the Medtronic valve (198.0 Pa versus 218.0 Pa).
Conclusions: The presented method allows the assessment of aortic flow conditions following the implantation of bioprosthetic valves. It may be useful in predicting detrimental flow phenomena, thus facilitating the
selection of appropriate valve designs.
A
ortic stenosis (AS) is one of the
most prevalent forms of cardiovascular disease in the Western world
and represents the most common form of
valvular heart disease requiring surgery in
Europe.1,2 Percutaneous implantation of
bioprosthetic valves through a transfemoral, subclavian, transaortic, or transapical
route is evolving fast, with promising results in inoperable or high-risk patients.3-10
Although several valves are under study,
the most widely used types so far are the
Edwards SAPIEN valve system (Edwards
Lifesciences Inc., Irvine, CA), which is a
418 • HJC (Hellenic Journal of Cardiology)
trileaflet bovine pericardial valve mounted
on a cobalt chromium stent frame, and the
CoreValve system (Medtronic, Minneapolis, MN), which is a trileaflet porcine pericardial valve mounted on a self-expanding
nitinol stent (Figure 1).5-9,11,12 In-hospital
mortality and procedural complications
such as embolic stroke do not differ significantly between the SAPIEN and CoreValve.5-9,11 Significant atrial regurgitation (AR; grade ≥3) and the need for permanent pacing are more common with the
CoreValve than with the SAPIEN, whereas coronary artery occlusion is more com-
Flow patterns of transcatheter aortic valves
Figure 1. Illustration of the Edwards SAPIEN (left) and Medtronic CoreValve (right) transcatheter aortic valves, which were simulated and virtually implanted in a representative aortic model.
mon with the SAPIEN, occurring mainly in patients
with a lower lying coronary ostium and shallow sinuses of Valsalva.8 Although most of these differences
can be attributed to structural characteristics or scaffolding properties, the functional behavior and hemodynamic characteristics of these particular valves are
not known, and no in vivo or in vitro data exist in this
regard. However, aortic flow conditions are associated with vascular remodeling, vascular wall damage
and thrombosis, and aneurysm formation. Computational fluid dynamics provide the opportunity to assess flow characteristics using representative theoretical models.4,13,14
The purpose of the present study, therefore, was
to apply computational fluid dynamics analysis in order to compare the hemodynamic characteristics of
the CoreValve and SAPIEN systems. We considered
an aortic model free of pathologies, derived from
computed tomography coronary angiography (CTCA), and created aortic models that incorporated the
bioprosthetic valves. By applying the same inflow and
outflow boundary conditions, we sought to investigate
variations in the aortic flow patterns induced by the
two valve designs and their association with detrimental phenomena such as vascular remodeling, vascular
wall damage and thrombosis.
Methods
Simulation of aortic flow with the two virtually implanted bioprosthetic valves was accomplished
through the following steps: (i) acquisition of a realistic model of the aorta; (ii) simulation of the shape
of each valve at each operation phase; (iii) merging
of the simulated valves with the aortic model; and (iv)
Figure 2. The 3-D surface of the representative aortic model (colored surface) and the corresponding computed tomography coronary angiography images from which the aortic model was derived.
definition of inflow and outflow boundary conditions
in the combined aortic model, considering blood as a
Newtonian fluid.
Aortic model construction
A typical aortic geometry was obtained by CTCA
from a patient without any aortic pathology. The CTCA examination was performed using a 128-slice CT
scanner (Aquilion CX, Toshiba, Tokyo, Japan) with a
slice thickness of 0.5 mm. We considered axial CTCA
slices of the opacified aortic lumen of the ascending
aorta, starting at the sinus of Valsalva, the aortic arch,
the descending aorta and the lower segments of the
brachiocephalic artery, left common carotid artery,
and left subclavian artery. These slices were fed into a
commercially available software package (Amira 4.0,
Mercury Computer Systems). The lumen of the aorta and branches were semi-automatically segmented
with the aid of an experienced radiologist, using tools
provided by the software package. A total of 360 slices were processed from the patient CT data. The 3-D
surface model of the aorta and branches was generated automatically and semi-automated filtering was
applied to reduce the fine-scale irregularities of the
surface model. Figure 2 shows the 3-D surface model
of the aorta and corresponding CTCA images.
Valve construction
We considered two valves that are currently in widespread use: the balloon-expanded Edwards SAPIEN
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A. Kopanidis et al
XT (Edwards Lifesciences, Irvine, CA, USA) and the
self-expanding CoreValve (Medtronic Inc., Minneapolis, MN, USA) (Figure 1). The virtual construction of the two valves was accomplished by following
the dimensions provided by the manufacturers, published data from relevant studies,15,16 and adopting
simplified topologies of the two valves on a commercial computer-aided design system (SolidWorks 2010,
SolidWorks Corp., Concord, MA, USA). The shape
of both simulated valves followed closely the original
shape, which was defined by the strut scaffold. Nominal dimensions for both valves followed those of the
29 mm diameter models. Each valve was modeled
in three distinct phases of its operation, with varying
valve openings of 1/3, 2/3 and 3/3 (fully opened valve)
of the total surface area. For both valves, the metal
struts of the supporting stent were omitted and only
the moving leaflets were constructed for each simulated operation phase. The morphology of the leaflets was also in accordance with literature reports and
manufacturers’ data and represented the topology of
the leaflets in the three distinct phases of the valve’s
operation. In the case of the Medtronic CoreValve,
data were also extracted via direct measurements on
an available functional valve. We used a scallop shape
for the leaflet geometry design and mounted the leaflets on a rigid straight tube in the case of Edwards
and on a rigid converging–diverging tube in the case
of Medtronic (Figures 3 and 4).
Valve implementation in the aortic model and mesh
generation
The three generated models for each valve were incorporated into the model of the acquired aorta, first
by aligning the axis of the valve to that of the aorta at
the plane of the sinuses of Valsalva, and then by adjusting the plane of the closed leaflets of the simulated valve to that of the bottommost of the Valsalva
sinuses. After the construction of the computational
domain topology had been completed, a numerical
computation mesh was applied, with the use of a commercial package (ANSYS). Hybrid volume elements
of the same element size (2.7×10-5 m) were used for
all cases, resulting in mesh sizes between 1.2×106 and
2.0×106 elements. Mesh independence analysis involved 3 different sizes of mesh (1.6×105, 1.8×106, and
4.0×106). The differences in pressure drop results between the middle mesh sizes were 3.5% and 5.5% for
the two extreme cases, respectively, leading to the
choice of the aforementioned element size.
420 • HJC (Hellenic Journal of Cardiology)
Figure 3. Construction of the virtual model of the Medtronic
CoreValve and integration into the aortic model. In this case both
published data and an actual valve were available and were used in
the modeling of the virtual valve.
Figure 4. Construction of the virtual model of the Edwards SAPIEN and integration into the aortic model. In this case all information regarding the valve was acquired from data provided by the
manufacturer and from the relevant literature.
Flow simulation
All simulated cases were approached using a steadystate computational fluid dynamics iterative methodology in the sense of “freezing” the time and investigating the flow field for each “snapshot” of the considered
valves’ operation phases. No turbulence model was
used, as flow was considered laminar. The Reynolds
number varied from 1808 to 4820 for flow in a cylinder, calculated using the valve’s entry diameter. Even
though flow in a pipe considers flows with Re>4000 to
be in the turbulence range, this was exceeded only locally and when a k-ε model was used, convergence issues made the solution unreliable. The same happened
when a shear-stress transport model was used for the
case of Re=4820; therefore, the original flow field approach with laminar parameters was retained for the
solution. All cases converged after 2000 iterations or
Flow patterns of transcatheter aortic valves
earlier. Boundary conditions in all cases involved blood
mass inflow according to the area of the opened valve,
as defined by the shape of the open valve leaflets for
each considered operation phase. Blood mass flow
conditions during the cardiac cycle were adopted from
a previous relevant study, which acquired flow velocity
and flow rate waveforms in vivo by phase contrast magnetic resonance imaging.4 A quasi-static approach was
used to analyze aortic flow at the various instances of
valve operation.16 Outflow mass fraction for each outlet was defined according to Murray’s law, which suggests that the flow ratio through a main vessel and a
bifurcation is proportional to the inverse ratio of their
diameters raised to the third power.17 Table 1 tabulates inflow values and outflow percentages for each
simulated case. Blood was assumed to be a Newtonian
and incompressible fluid with dynamic viscosity of 3.50
mPa·s and a density of 1060 kg/m3.18
Flow parameters
We assessed flow parameters that are considered relevant to flow-induced detrimental phenomena, such
as thrombosis, vascular wall damage, and valve failure,
and we also considered the impact of valve implantation on myocardial load. We assessed both qualitative and quantitative flow parameters; the former include the visualization of flow path lines by streamtrace tracking of free particles released at the inflow
in order to assess flowing velocity, vortex formation
and flow recirculation, and the latter include the calculation of shear stress, the shearing force exerted on
the vessel walls and valve leaflets due to the flowing
blood. We also considered blood pressures and pressure drops along the flow domain in order to evaluate the efficiency of the implanted valve regarding induced myocardial load. Although we cannot directly
link flow parameters and implantation outcome, it is
plausible that the risk of thrombosis, vascular damage
or valve failure would be higher if regions of the aorta
are continuously exposed to flow conditions that promote these detrimental phenomena.
Results
The complex, time-dependent, three-dimensional nature of the aortic flow field makes its presentation
challenging. To illustrate the intricate dynamics of the
flow field, flow trajectories are presented in Figure 5,
wall shear stress distributions in Figure 6, and shear
stress distributions at the valves’ leaflets in Figure 7.
Table 1. Boundary inflow and outflow conditions for the simulated valves and operation phases.
Mass outflow fraction per outlet
Simulated
case
Mass inflow
(kg/s)
BCA
Edwards 1/3
0.195
Edwards 2/3
0.311
Edwards 3/3
0.384
Medtronic 1/3
0.144
Medtronic 2/3
Medtronic 3/3
0.212
0.384
10.7%
LCCA
LSA
DESC
4.0%
7.0%
78.3%
BCA – brachiocephalic artery; LCCA – left common carotid artery; LSA –
left subclavian artery; DESC – descending aorta.
These figures clearly demonstrate that the implantation of the two simulated valves and also each simulated phase of valve opening have distinct impacts on
the aortic flow conditions. This is reflected in both
the distribution and the magnitude of the flow indices
in the aortic region.
Flow velocities and flow recirculation
In the case of the 1/3 valve opening, high flow velocities are evident at longer distances from the valve’s
exit along the ascending aorta for the Medtronic valve
(Figure 5). As a result, blood flow impacts the vessel
wall of the ascending aorta with higher velocity and a
flow vortex is subsequently formed at the aortic arch
between the brachiocephalic and left common carotid branches (red arrow). Such a vortex is not evident
in the case of the Edwards valve. This is likely due to
the different geometries of the two valves. Medtronic’s flow exit is slightly higher (upstream) in comparison to the Edwards’ flow exit; thus, in the case of
the Medtronic valve the flow enters a region of vessel curvature (aortic arch) and branching (brachiocephalic and carotid branches) at higher velocities. The
flow conditions at 2/3 valve opening are similar for
both valves, although now considerably lower flow velocities are evident in the whole flow domain (ascending aorta, aortic arch and descending aorta). The flow
vortex that was formed in the case of the Medtronic valve during the earlier phase of valve opening is
still evident (green arrow); however, the recirculation velocity is now lower and significantly fewer particles participate in the vortex, indicating that forward flow is gradually restored. In the case of the Edwards valve, a small but identifiable vortex is formed
(Hellenic Journal of Cardiology) HJC • 421
A. Kopanidis et al
m/s
Edwards
m/s
m/s
m/s
m/s
m/s
Medtronic
Figure 5. Pathlines and velocity magnitude of blood flow for the simulated Edwards valve (left panel) and Medtronic valve (right panel) at
the three considered phases of valve opening (1/3 upper row, 2/3 middle row and 3/3 lower row).
at this instant (blue arrow), which was not previously
present. The flow conditions at 3/3 are considerably
smoother for both valves, with absence of any flow
422 • HJC (Hellenic Journal of Cardiology)
recirculation and the majority of particles participating in forward flow, with overall lower flow velocities
compared to the previous phases.
Flow patterns of transcatheter aortic valves
Pa
Edwards 1/3
LO view
Edwards 1/3
RO view
Medtronic
1/3 LO view
Medtronic
1/3 RO view
Edwards 2/3
LO view
Edwards 2/3
RO view
Medtronic
2/3 LO view
Medtronic
2/3 RO view
Edwards 3/3
LO view
Medtronic
3/3 LO view
Figure 6. Wall shear stress (WSS) distribution for the simulated Edwards valve and Medtronic valve at the three considered phases of valve
opening. WSS distributions are presented for both the left-oblique (LO) and right-oblique (RO) views of the aorta.
(Hellenic Journal of Cardiology) HJC • 423
A. Kopanidis et al
Wall shear stress
The distributions of WSS in the aorta are similar for the
two simulated valves: at the 1/3 valve opening higher
WSS values are evident in the outer walls of the aorta,
“opposite” the valve opening, and lower WSS at the inner curve of the aortic arch and the descending aorta
(Figure 6). Two “hotspots” of high WSS values are seen
for both valves in the ascending aorta below the brachiocephalic branch; these are due to high-velocity particles in the central axis of the aorta, which impact on
the artery walls. The distributions of WSS in the aorta
are more uniform in the phase of 2/3 valve opening and
overall lower WSS are evident; however, in the case of
the simulated Medtronic valve the two “hotspots” of
high WSS are still identifiable. In the phase with a fully open valve, the distributions of WSS in the aorta are
very similar for both valves, with a uniform distribution of WSS values and absence of any distinct characteristics. The average values of WSS calculated for the
whole aortic model are generally higher for the simulated Medtronic valve for all operation phases (Table 2).
The maximum differences were noted for the 1/3 and
2/3 valve opening phases, where the average WSS values for the Medtronic valve were 1.5-fold higher.
Leaflet shear stress
The average shearing stresses that were exerted on the
leaflets of the two simulated valves were in the range
1.8-15.2 Pa (Table 2). The highest shear stress values were evident at the edges of the leaflets for both
valves, as the greatest flow velocity gradients were at
these points (Figure 7). In the case of the simulated
Medtronic valve, “hotspots” of shear stress were also
seen at the periphery of the valve in the phase of 2/3
opening. In the case of fully open valves (3/3), the highest shear stress values were distributed differently between the two valves: for the Edwards valve, the highest shear stress values of 15.0 Pa were evident at the
bottom of the valve, whereas for the Medtronic valve
the highest shear stress values of 22.0 Pa were distributed in the central part of the valve.
Pressure drop
The pressure drop or pressure gradient along a vessel can be viewed as the force that drives blood flow.
Thus, a low pressure drop indicates that the energy
that has to be supplied by the myocardium to drive
this flow is low, and low pressure drops are therefore
424 • HJC (Hellenic Journal of Cardiology)
Table 2. Average wall shear stress (WSS) and maximum leaflet
shear stress (SS) for the simulated valves and operation phases.
Simulated case
WSS (Pa)
Leaflet SS (Pa)
Edwards 1/3
Edwards 2/3
Edwards 3/3
Medtronic 1/3
Medtronic 2/3
Medtronic 3/3
3.5
2.5
2.4
5.3
3.7
3.0
5.3
2.1
5.5
15.2
1.8
3.1
considered beneficial in terms of myocardial load
(Table 3). For all considered vessels, pressure drops
were lower for the simulated Edwards valve than for
the Medtronic valve. The highest pressure drops were
evident between the ascending and descending aorta
(198.0 Pa and 218. 0 Pa for Edwards and Medtronic,
respectively). The differences in pressure drop between the two simulated valves were 9% for the descending aorta, 21% for the brachiocephalic artery,
6% for the left common carotid artery, and 7% for
the left subclavian artery.
Discussion
Although the percutaneous implantation of bioprosthetic valves is promising, the clinical value of this
approach is still under study. The reported one-year
mortality after transcatheter aortic valve replacement
is 20%, similar to that of high-risk patients who undergo surgical valve replacement (18%).5-7,9,11,19 Twoyear mortality is rather similar (33.9% vs. 35%),4 and
long-term results (5 years) have detected a valve failure rate of 3.4%.20 The technical characteristics of
the implanted valve may be of importance in this respect. A plausible influence on implantation outcome
is the aortic flow setting induced by the bioprosthetic
valve, since aortic flow conditions are associated with
various detrimental phenomena, such as vascular remodeling, vascular wall damage and thrombosis. Although the genesis of aortic aneurysms can be explained in many ways,21 recent evidence indicates that
flow dynamics (turbulence or stagnation) may in fact
stress vessel walls, affecting the development of aortic aneurysms.22,23 The WSS reflects the shear stress
of fluid against the vascular wall or the viscous drag
of blood.24 This force is minimal (1-20 Pa) compared
with arterial blood pressure (100 mmHg ≈13000 Pa),
however endothelial cells are responsive to variations
in WSS.25 Such changes have a strong link with the
onset and development of atherosclerosis, and possi-
Flow patterns of transcatheter aortic valves
Pa
Edwards
Pa
Pa
Pa
Medtronic
Pa
Pa
Figure 7. Shear stress distribution at the valve leaflets for the simulated Edwards valve (left panel) and Medtronic valve (right panel) at the
three considered phases of valve opening (1/3 upper row, 2/3 middle row and 3/3 lower row).
bly the occurrence of aneurysms. This study sought to
comparatively evaluate post-implantation aortic flow
conditions with two popular bioprosthetic valves, using
computational flow dynamics to simulate aortic flow.
The aortic flow patterns induced by the two valves
were generally similar; however, several variations
were also identifiable. These variations were due to
the different geometries and design modules of the
(Hellenic Journal of Cardiology) HJC • 425
A. Kopanidis et al
Table 3. Pressure drop between the ascending aorta and the descending aorta and branches.
Simulated case
Edwards 3/3
Pressure drop per outlet (Pa)
BCA
LCCA
LSA
DESC
66.0
163.0
153.0
198.0
Medtronic 3/3
84.0
172.0
165.0
218.0
Abbreviations as in Table 1.
valves. The Medtronic valve has a taller profile and
the valve’s outlet is slightly upstream in comparison
to the Edwards valve, although both valves were virtually implanted so as to have the transverse plane defined by the closed valve leaflets at the same location.
This geometric variation, in combination with the
higher outflow velocities for the simulated Medtronic
valve, leaves less room for smooth flow development
before flow enters the curved section of the aorta, resulting in the formation of a larger and more persistent flow vortex. Thus, a shorter valve profile appears
theoretically advantageous. A transvalvular jet was
suggested as one of the important factors contributing to aneurysmal dilatation of the thoracic aorta,
by regulating the matrix metalloproteinase level in
the wall tissue.26 Similarly to our findings, a previous
MRI study in patients who underwent implantation
of an Edwards SAPIEN valve revealed asymmetrical
systolic left ventricular outflow, with a flow jet forming along the right anterior outer curvature of the ascending aorta that caused the development of marked
helical flow.27 These findings are of particular interest
in light of a recent study in high-risk patients with severe aortic stenosis, which showed that transcatheter
replacement resulted in much more frequent perivalvular aortic regurgitation, possibly related to a less
seamless alignment of the transcatheter prosthesis
compared with surgically repaired valves.28
The WSS distribution following transcatheter
aortic valve implantation is also of interest, since it
may affect the endothelial and biological functions
of the aorta. In this study, the highest WSS values
for both valves were noted at the aortic arches. Our
results are in keeping with those of a previous study
that compared ascending aortic flow and WSS patterns in bicuspid and tricuspid aortic valves and found
that the maximum WSS values were localized around
the mid-ascending aorta level, highlighting the effect
of the jet flow on this portion of the wall.29 Our results regarding average WSS values are higher than
those of relevant previous studies that calculated average WSS at a level of less than 1.0 Pa.4,22,30 How426 • HJC (Hellenic Journal of Cardiology)
ever those studies calculated the time-averaged WSS
throughout the cardiac cycle; thus, they also considered time intervals during valve closing when there
was a reduced blood flow and thus reduced WSS values, whereas in our study we considered three distinct
time points during valve opening, all with considerable blood flow rates. Nevertheless, the calculated
average WSS values in our study are in a range that
induces endothelial quiescence and an atheroprotective gene expression profile,31 but not high enough
to cause matrix degradation in the wall, with the possible consequence of local enlargement and aneurysm.32
Previous experimental and numerical blood studies have shown that high shear stress levels cause
platelet activation, while long exposure times to
these shear stresses combined with flow recirculation promote thromboembolism. 33 Similarly to a
previous study, 34 we have demonstrated that the
WSS increases gradually from the base of the leaflet toward the tip, and reaches its peak at the edge
of the leaflet tip, where the maximum axial flow acceleration occurs. Additionally, the WSS distributions presented in this study clearly showed complex
stress development patterns during the opening of
the valve, which is considered to be the most detrimental factor for fatigue failure analysis.34 Platelet
activation is pronounced at the region of the bioprosthetic valve, owing to the complex flow conditions that the blood experiences at this region.35,36
Activated platelets with a long residence time in
these flow regions may aggregate, leading to the formation of free emboli. 37 We were not able to gain
insight into platelet activation, since this requires
assessing the trajectories of particles and the duration of exposure to elevated shear stresses throughout the cardiac cycle. However, very high shear rates
in the order of 10,000 s-1, which correspond to shear
stresses of 35 Pa, may cause immediate platelet activation.38 Although the average leaflet shear stresses
calculated in this study were considerably lower for
both valves, there were some “hotspots”, at which
shear stress was higher than 35 Pa, for both simulated valves.
Our study demonstrated that the virtual implantation of bioprosthetic aortic valves and the prediction of post-implantation aortic flow patterns by computational methodologies are feasible. Previous studies have also used computational methods to simulate
implant deployment, in order to select the appropriate implant size and type,39 or to model the interac-
Flow patterns of transcatheter aortic valves
tion between the device and the aortic root anatomy,
in order to study device performance.40 Therefore,
such computational methodologies can theoretically
be jointly applied in preoperative planning to assess
the structural, functional and rheological outcome of
implantation with a view to the selection of the most
appropriate valve system.
Our study has several limitations. We considered
an aortic model from a normal subject in which the
bioprosthetic valves were incorporated, instead of directly reconstructing the anatomy of patients with implanted valves. However, this approach allowed a direct comparison of the flow variations induced by the
valve design. Inflow boundary conditions were not
acquired from the same subject from whom the vessel model was acquired. Although this would not be
expected to influence the distribution of flow indices at the aorta, it could have a significant impact on
their absolute values. As in most relevant studies, the
aortic wall was assumed to be rigid and fixed, with
no radial expansion or translational motion; however, the effect of this assumption is likely to be insignificant.41,42 A quasi-static approach was considered, rather than pulsatile flow conditions; however, at each phase of the simulated valve operation
we considered varying inflow conditions according
to the phases of valve opening. The arterial model
that we considered was taken from a normal subject;
therefore, simulation results would be different in the
case of aortic pathologies, such as aortic dilation or
constriction. The simulated models of the two valves
closely resemble the geometry and dimensions of the
actual valves; however, they cannot be considered as
exact reproductions. Since the metal struts of the supporting stent were omitted, their impact on the WSS
distribution was not considered. 15,16 Finally, we assumed an ideal valve configuration after implantation
and non-compliant valve geometries;16 however, during implantation of transcatheter aortic valves into
calcified aortic annuli, misdeployment is likely, given
the asymmetric shape of the target region.43
Conclusions
Acknowledging the various limitations, our study demonstrates that aortic flow conditions after the simulated
implantation of transcatheter aortic valves can be assessed using computational fluid dynamics. This methodology may be of value in the selection of appropriate
valve systems and the future design of prosthetic valves,
for either surgical or transcatheter implantation.
Acknowledgments
This work was supported by a grant from the S. Niarchos Foundation.
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