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Modeling of Subject Arterial Segments Using Arterial Tree Network Boundary Condition

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Modeling of Subject Arterial Segments Using Arterial Tree Network Boundary Condition
Modeling of Subject Arterial Segments Using
3D Fluid Structure Interaction and 1D-0D
Arterial Tree Network Boundary Condition
Magnus Andersson, Jonas Lantz and Matts Karlsson
Department of Management and Engineering, Linköping University, Linköping, Sweden
1D-0D model
The arterial tree network is based on
transmission-line theory represented
by a complex flow impedance model
for the pressure-flow relationship.
INTRODUCTION
In recent years it has been possible to simulate 3D blood flow trough
Computational Fluid Dynamics (CFD) including the dilatation effect in elastic
arteries using Fluid-Structure Interaction (FSI) to better match in vivo data. Outlet
boundary condition (BC) models have been shown crucial and difficult to
implement accurately in order to capture realistic pressure reflection arising from
the distal vascular bed.
The arterial topology was extracted
from literature [2] where only the
central arteries was considered.
This work focus on a full scaled FSI simulation at an arterial section obtained from
Magnetic Resonance Imaging (MRI) data. The outlet BC at the iliac arteries is
connected with a 1D-0D systemic arterial network. This 3D-(0D-1D) connection can
provide the essential features of the peripheral flow , the 1D-0D coupling allow for
investigation of cardiovascular diseases including stenoses and/or hypertension.
150
150
Volume Flow (ml/s)
Volume Flow (ml/s)
100
50
0
0.3
0.6
RI Hypertension
LI Hypertension
RI Normal Pressure
LI Normal Pressure
RI Volume Flow
140
LI Volume Flow
100
Peripheral arterial segments are
terminated with a three-element
windkessel (WK3) model.
90
75
0
Qin
0.9
50
0
0.3
Time (s)
0.6
Iliac pressure
profiles
0.9
Time (s)
3D-FSI model
The FSI use a 2-way interactively
scheme, ANSYS Multifield, for
solving the pressure/displacement
interaction at the shared interface.
Segmentation
The MRI images were segmented using
an in-house software (Segment,
http://segment.heiberg.se,[1]) to obtain
a 3D surface of the vessel lumen.
Elastic support of
surrounding tissue
Mesh
The surfaces was meshed with a high quality
hexahedral elements using ANSYS ICEM CFD 12.0
(ANSYS Inc, Canonsburg, PA, USA).
Prediction of the flow impedance
at the iliac root boundaries for
Hypertension
Normal BP
High (2x)
Typical
1D vascular
1D vascular
stiffness
stiffness
180
Max Acceleration
Peak Systole
Max Deceleration
0
1D-0D
Iliac
Iliacspressure
Pressurevs.
vs flow
Flow profiles
Profiles
Pressure (mmHg)
Reduced PC-MRI flow profile
METHODS
MRI acquisition
Subject specific MRI and PC-MRI scanning
was utilized to acquire geometry and flow
data respectively.
Two cases are studied, normal and
high blood pressure(BP), for different
vascular stiffness.
Approximated
iliac flow profiles
RESULTS
Instantaneous wall shear stress
(WSS) at three different times in
the cardiac cycle, max
acceleration, peak systole and
max deceleration, is presented
for normal BP and hypertension.
3D - FSI
Segment wall stiffness
Typical: 2.6 MPa
Hypertension: 3.9 MPa
Solid
Mechanics
Segment wall stiffness is increase
by 50 % at hypertension.
11% of Qin is forced
into each renal
3D-FSI Simulation
2-way
iterative
scheme
Fluid
Dynamics
Wall Shear Stress
Max
acc.
Peak
systole
Max
dec.
Time
average
Normal
BP
Deformation
at peak systole
for normal BP
Constant wall
thickness and
linear-elastic wall
properties
Right
iliac (RI)
Left
iliac (LI)
1D-0D Arterial
Tree Network
REFERENCES
[1] Heiberg E. et al, Time resolved three-dimensional automated
segmentation of the left ventricle, Computers in Cardiology, Vol.
32, pp.599-602, 2005.
WK3
C
[2] Reymond P. et al, Validation of a one-dimensional model of the
systemic arterial tree, Am. J. Physiol. Heart Circ. Physion.,
297:H208-H222, 2009.
th
6
R1
R2
The
international symposium on Biomechanics in Vascular Biology and
Cardiovascular Disease, April 14-15, 2011, Rotterdam, The Netherlands.
The average WSS over
one cardiac cycle was
evaluated, revealing close
similarities for both
results.
Hypertension
CONCLUSIONS
This method allows for a better insight of large scale vascular
networks effect of the local 3D flow features and also gives a better
representation of the peripheral flow compared to a pure 0D
(lumped parameter/Windkessel) model. PC-MRI will provide data
for validation of velocity profiles in the 3D model. Future work
includes a hyperelastic material model for 3D geometry as well a
MRI-based subject specific 1D vascular topology to be combined
with the 3D model.
Contact:
[email protected]
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