Distribution of Articial Thrombi Candidates
Through Patient-Specic Aortic-Arch Phantoms
under Pulsatile Flow Conditions
Marco Testaguzza ( email@example.com )
University of Mons (UMONS)
University of Mons (UMONS)
Karim Zouaoui Boudjeltia
Université libre de Bruxelles, CHU de Charleroi
CHU de Charleroi
University of Mons (UMONS)
Keywords: Ischemic Stroke, emboli, pulsatile ow conditions
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
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Ischemic Stroke is the most frequent type of stroke and is subject to many studies investigating
prevention means. Avoiding the diculties and ethical problems of experimental in-vivo research, in-vitro
testing is a convenient way of studying in controlled conditions the morphological impact and
mechanical aspects of emboli dynamics. This in-vitro study was performed with two realistic silicone
aortic-arch phantoms submitted to physiological pulsatile ow conditions. In the in-vitro test bed, using
automatic image tracking and analysis, it was made possible detecting and tracking articial spherical
emboli candidates circulating in the anatomic aortic-arch models under a realistic based-patient blood
ow prole. The emboli trajectories as well as their repartition in the different supra-aortic branches are
presented for the two aortic-arch geometries obtained from CT scans. Through a statistical analysis
performed with several articial emboli sizes, the experimental study shows that the repartition
percentages of the emboli closely follow the owrate repartition percentages for both aortic-arch models,
suggesting that higher owrates lead to higher concentrations of emboli in a given artery. Sets of human
thrombi were also injected and the repartition percentages have been established, giving the same trend
as for articial emboli.
Background And Purpose
Over 13.7 million people experience a stroke event each year, out of which 9.5 million are ischemic
strokes . Several risk factors are known to increase the propensity of ischemic strokes such as atrial
brillation and diabetes. According to Malone et al , the embolus size is not the only responsible factor
for stroke propensity as the owrate may also impact the number of emboli which can be recovered in
Some computational studies of emboli dynamics are available , , . Choi’s study focused on the
comparison between atrial brillation and normal heart ow with emboli in the size range of 2 to 6
millimeters. Fabbri  considers micrometric particles but for a study on the Circle of Willis and does not
consider trajectories in the prior part of the anatomy such as the aortic arch where owrates are more
elevated. Experimental works are either considering small spherical polyamide particles in the Circle of
Willis  or millimetric thrombi analogues made from bovine blood within the aortic arch , .
Cardiogenic emboli sizes can range from milliliters to centimeters, depending on ow conditions, but
emboli as small as a few hundred microns can be responsible for ischemic stroke depending on ow
conditions especially in small cerebral capillaries . A critical information is how geometry and shape
(diameter and position) of the aortic arch and arteries affect the probability of emboli passage. The
arteries discussed are the brachio-cephalic artery (BCA), the left-common-carotid artery (LCCA) and the
left subclavian artery (LSA), out of which only one division branch of the BCA (the right common carotid
artery) and the LCCA lead to the brain. The stroke propensity is shown to be directly linked to the diameter
of the arteries in Choi’s study  but only with the atrial brillation ow. The purpose of this study is to
explore, in-vitro, such assumptions, at rst with the normal ow. Carr  provides simulations and
cardiogenic emboli distributions in the aortic arch and shows that, on average, particles in the size from
910 microns to 1920 microns have twice the likelihood of cardiac output to the arteries leading to the
brain. Lately, Malone presented results indicating that blood clots made from bovine blood followed the
owrate percentages of atrial brillation pulsatile signals for aortic-arch phantoms made of silicone with
articial blood liquid as a medium .
Based on patients 4D-MRI scanners, two aortic arch geometries were extracted, and two patient-specic
silicone models were created. A non-pathological pulsatile owrate was reproduced in an in-vitro chamber
simulating a vertically standing patient. The pulsatile owrate signal imposed in the ascending aorta
corresponds to the measurement on a real patient and the downstream owrates repartition follows
physiological values from the literature . Articial spherical polyethylene particles of different sizes,
from 250 microns to 1 millimeter, were injected into the ascending aorta (AAO) and the trajectories were
recorded using two video cameras. A computer vision algorithm was employed to detect and count the
passage of the emboli out of the aortic arch through an analysis performed on several thousands of
articial emboli. To study the statistical repartition of the emboli in the aortic arch geometry, spherical
particles were used to remove any shape related effects and provide repeatability like in the study design
of Bushi . To make sure that the choice of articial emboli is relevant, verication experiments are
made with thrombi made from human blood and the repartition results are compared.
Materials And Method
In-Vitro Test-Bed Setup
The system setup and the in-vitro test bed are illustrated on Fig. 1. It is vertically structured to account for
gravity effects, thus offering a better representation of physiological conditions as it is considered that an
average person spends 8 hours sleeping and 16 hours either sitting or standing .
The aortic arch model is placed at eye-level and branched at each exit, namely: ascending and
descending aortas (AAO and DAO), BCA, LCCA and LSA. To record the instantaneous owrate at each
exit, owmeters (Sonotec CO.55/230HV2.0 and CO.55/140V2.0) are employed while solenoid valves
Bürkert 8605 controller and type 2836 valves)
allow tweaking the initial owrate repartitions. Pressure
sensors (First Sensor CTE8001GY4N and CTEM8500GY4N) are placed at each exit to monitor
instantaneous pressure. To reproduce the owrate, a UMONS patented system of pulsatile pump
consisting of a centrifugal rotative pump in series with a piston pump has been exploited to reproduce
physiological ow conditions . Distilled water was chosen in this study as the difference with blood
provides minimal differences in the aortic arch dynamics (the non-newtonian behavior is assumed to be
negligible considering the diameter of the main arteries) and for its convenience and optic properties.
Future works will consider articial blood.
Aortic Arch Model
A set of imaging data was provided by the André Vésale Hospital (CHU de Charleroi, Belgium). Data
included patient aortic arch 3D geometries comprising ascending (AAO) and descending (DAO) aortas,
brachio-cephalic artery (BCA), left common carotid artery (LCCA) and the subclavian artery (LSA),
extracted from computed tomography angiograms (angio-CT) as well as ow-velocity prole and AAO
surface area changes over the cardiac cycle at the ascending aorta, quantied by phase contrast MRI.
The rst geometry (named model 1) came from a patient having suffered a stroke event while the second
geometry (named model 2) came from a non-pathological patient. The open-source software for medical
image informatics 3DSlicer (https://www.slicer.org/)  was used to smooth and clean the 3D chest
scanners to extract the nal aortic-arch geometry in each case. The three upper arteries nal sections
were modied for xation purposes within the in-vitro chamber system using Autodesk Inventor.
The models were then printed in 3D using the open-source software CURA with a polyvinyl-acetate water-
soluble lament (Ultimaker PVA). The model was used as a mold to generate the respective negative cast.
Clear Sylgard 184 silicone elastomer and the hardener (Sigma Aldrich) were used for the molding
process. The procedure to create the models included creating vacuum for degassing and the models
were cured for 48 hours. Upon polymerization, the PVA was dissolved in owing warm water until full
dissolution of the print occurred. Figure 2 displays the nal silicone models as well as the stages towards
The two geometries were characterized as follows: Model 1 and 2 had the following dimensions
measured (three measurements were made on the STL les at the entrance in the middle and on the
upper part of each artery):
Table1Aortic-arch models’ dimensions, AAO is the ascending aorta, BCA is the Brachio-
Cephalic artery, LCCA the left common carotid artery, LSA the subclavian artery and DAO is the
descending aorta. Error bars were determined by taking three measurements at the base,
middle and top parts of each section.
Diameter (mm) AAO BCA LCCA LSA DAO
Model 1 27 11.4 ± 0.4 5.9 ± 0.3 11.3 ± 0.4 20.5
Model 2 27 9.2 ± 1.1 6.43 ± 0.7 9.81 ± 2.2 20.5
Physiological Flow Reproduction
Non-Pathological Signal Reproduction
The AAO pulsatile owrate was measured at André Vésale Hospital. The patient’s aorta diameter was
measured at 34.2 mm resulting in an area of 9.2 10-4 m². The silicone model created has an area of 5.72
10-4 m² and is molded on a different patient, therefore the owrate at the ascending aorta had to be
scaled down by 37.8%.
A UMONS patented system of pumps was exploited to reproduce the behavior of the physiological
pulsatile owrate prole . The technology consisted of a centrifugal pump (Brushless DC Motor Water
Pump DKB60TSA 24V) and a piston pump driven by a linear actuator. A membrane was xed directly to
the piston head to maintain a sealed and low friction coupling with a PMMA cylinder. The centrifugal
pump was controlled by a NI-myRIO (National Instruments) together with the NI-LabView 2018 software
and set to provide the mean aortic owrate value. The linear actuator software (LinMot-Talk v6.6) was
programmed to set the piston to follow a specic displacement prole in order to reproduce the imposed
reference physiological signal.
The imposed piston motion allowed for the geometry adapted ascending aorta ow to be set (Fig. 3). The
in-vitro chamber mean owrate were measured with the associated standard deviation presented in Table
Table 2 Mean flowrate measurements as well as repartition with respect to AAO and standard
deviation for the 2 models as measured by the test-bed.
Model 1 Model 2
Artery Flow [l/min] Repartition [%] Flow [l/min] Repartition [%]
AAO 4.22 ± 0.04 100 4.11 ± 0.41 100
BCA 0.85 ± 0.01 20.04 ± 0.31 0.86 ± 0.03 20.87 ± 2.36
LCCA 0.71 ± 0.02 16.91 ± 0.21 0.71 ± 0.04 17.25 ± 1.19
LSA 0.77 ± 0.01 18.33 ± 0.29 0.83 ± 0.03 20.10 ± 2.10
DAO 1.84 ± 0.02 42.60 ± 0.15 1.75 ± 0.31 42.60 ± 4.10
These values remain in the range of physiologically acceptable range . The difference in the
repartitions for the two models can be attributed to the fact that the arteries diameters are different but
AAO signals remained the same as it is a model constraint to have imposed a constant inlet diameter.
The following graph (Fig. 4) presents a 10-seconds excerpt of the test-bed owrates for the 5 branches.
Articial Thrombi Particles
For optical eciency in particle tracking, uorescent green spherical particles made of polyethylene were
used as articial emboli candidates (obtained from Cospheric L.L.C, Santa Barbara, USA). The particle
sizes used in this study were 250-325, 355-425, 600-710 and 850-1000 microns (each particle set has a
dispersion documented by the manufacturer). The size values represent a continuous range to explore
size effects. The density of the spheres was 1.025 g/cc. This density choice was justied as to retain a
mass density close to human thrombi (1.06 g/cc)  and satisfy optimal optical conditions for detection
(uorescent coating). The relative density between water and particles achieved buoyancy and remained
close to the density ratio between blood and a blood clot made from platelets (~ 1067/1050) . A
solution of polyethylene particles was prepared by mixing distilled water with Tween20 surfactant
solution from Cospheric (0.2%). The surfactant solution was used to avoid particles from aggregating
and to reduce sticking in the tube and silicone models.
Human microthrombi were formed from whole blood taken from a volunteer in a tube without
anticoagulant. After 30 min, at 37 °C, the tube was centrifuged at 4000 g for 10 minutes to remove
residual serum. A scalpel was used to cut thrombi of uniform size.
Particles Injection Method
Polyethylene particles were injected via a syringe equipped with a needle (19G and 22G needles) into a
three-way valve to avoid any air being injected into the test-bed. A small magnet was put inside of the
syringe and an agitator allowed to stir the tween-distilled water-polyethylene particles solution. The lled
container was injected slowly and in a continuous manner to avoid as much as possible multiple
particles entering at the same time.
Trajectories of the emboli were recorded at 180 FPS (with the variable frame rate setting with 100MBPS
8Bit Full HD resolution) using two Panasonic Lumix GH5 cameras with Olympus M.Zuiko Macro 60mm
lenses. One camera was mounted on a Z-tilt mount on the Rexroth Chassis while the other one was xed
on a Genesis A3 tripod. One camera recorded only the BCA, LCCA and LSA branches whereas the other
camera recorded a portion of the transparent tube connected with the ascending Aorta (AAO) into which
particles were injected with a syringe. A polarized diaphragm was axed to the macro lens for the
camera xed on the tripod to improve contrast and to lter unwanted light reections. For this camera, the
GH5 settings were ISO 400, F 11, shutter 1/1600s, a portrait mode and a custom white balance setting
which rendered the best possible contrast for the green particles. Iso, depth of eld and shutter speed
were optimized by trial and error to provide the best possible videos. Another GH5 camera placed in front
of the silicone model had different settings to capture faster emboli: ISO 640, F10 and shutter 1/3200s
were used. The lighting was controlled via two side-LED panels placed on both sides of the silicone block
and a frontal angled panel to avoid direct light into the lens. Two led panels (top and bottom) were also
used in the mentioned tube to enhance particles contrast and therefore detection. This method allowed
for counting how many particles effectively entered the ascending aorta.
Post-Treatment and Video Analysis
The videos were analyzed using a Python script with the OpenCV library. Background subtraction was
performed on each frame followed by a color analysis of the pixels to differentiate particles from
parasitic bubbles. The python script was used to detect and record the position of the center of mass of
any particle at any given frame (a particle was dened by a pixel area range and RGB values relating to
green). Then, a MATLAB script was used to analyze the recorded trajectories and to detect the particles
crossing through each BCA, LCCA, LSA and AAO sections. This method allowed for multiple crossings
within the same frame as well as backwards crossings to be accounted.
Results And Discussion
At rst, the algorithm has been tested and validated on small sets of particles with visual double-check
performed manually. 10 batches of 20-40 particles have been injected and the algorithm mentioned
above was used to count them. The two extreme sizes were used for validation purposes: 250-325
microns and 850-1000 microns. The pulsatile ow rate conditions were used for this validation. For 850
microns no detection errors were made, i.e. all particles detected at each specic time have been
conrmed by visual inspection by 2 independent operators. Only 2% percent of the 10 batches of 250
microns particles have been missed either because the particles were trapped in an air bubble or due to
the lack of image contrast from the background for particles travelling too fast.
Repartition of Particles for the Non-Pathological Signal
The experiments were performed as follows: for each particle size, 4 sets of 200-250 particles were
injected into the test-bed under pulsatile ow conditions. The number of particles needed to be injected
was determined by continuous analysis until the proportions became stable. Each video was analyzed
with the Python and Matlab scripts (Fig. 5) and proportions were established from Excel processing.
Variability between experiments was evaluated and is available in Supplementary Tables 1 and 2.
For each model, polyethylene particles were injected to constitute an experiment in the form of 4 sets of
200-250 of each particle size. The pulsatile owrate was maintained throughout the tests. Then thrombi
made from human bloods were injected into the model constituting 4 sets of 200 clots to verify if the
choice of particle density had a signicant impact.
The percentages displayed in Supplementary Table 1 and 2 are plotted respectively in Fig. 6 and Fig. 7 for
the stroke patient model (model 1) and the healthy patient (model 2).
For each particle size, the statistical repartition of emboli followed the same trend. The pump percentage
is the result of averaging across consecutive owrate periods. From Fig. 6 and Fig. 7, one can point the
fact that, from the statistical dispersion range, smaller-sized particles follow the owrate repartition more
closely. It can be explained by the fact that they have less inertia and are more easily driven by the ow
stream. The opposite seems to hold true for larger emboli. The 850 microns particles are more often
found in the upper arteries as, by their inertia, they are less able to follow the ow curvature in the aortic
arch. Sets of human thrombi were found to follow the same trends as the articial thrombi, although
having various sizes ranging from 1 to 2 mm in size from visual inspection.
Emboli repartitions from several hundreds of particles were evaluated for both geometries and the data
did not allow to discern between the two models. Data from these in-vitro experimental results indicates
that, statistically, the emboli distribution is close to the owrate repartition in the two tested silicone
model geometries. This experimental result provides insight that the aortic-arch geometry and the
diameter of the arteries can directly affect the probability that an embolus can enter an artery since
owrate repartition will change.
In contrast to other emboli repartition studies, where AF and N owrates are used to make a distinction
between stroke propensity , , our results indicate that in the presence of clots, even under normal
cardiac conditions, emboli are still able to easily exit from arteries leading to the brain, in proportion to the
owrate. For the Circle of Willis, Chung 6 concludes that smaller emboli are carried proportionally to the
ow volume which seems to be conrmed by the present study. A change of model morphology from the
rst model to the second one does not change trends considering experimental error. Larger emboli (850
microns) were found to have, in both models, less frequency to exit through the descending aorta which
can be a consequence of the models being in a vertical position, or that these emboli have more inertia
and possess a lesser chance of having their initial trajectory deected.
These results are to be put in perspective with the modeling limitations, namely that the in-vitro
experiments were performed in a controlled environment using distilled water and spherically size-gauged
particles. Although simplifying the uid dynamics, the level of detail reached by imaging provides
fundamental aspects of particle (and embolus) dynamics within a patient-based aortic-arch phantom.
In-vitro experiments of emboli dynamics in patient-based silicone aortic-arch phantoms have been made
on a novel test-bed placed in a standing-patient conguration. Spherical polyethylene particles serving as
thrombi analogues were injected before the ascending aorta as well as thrombi made from human blood.
Image analysis software was used to count and determine the emboli statistic repartitions across the 4
arteries (BCA, LCCA, LSA and DAO). Results indicate that the repartitions of particles and blood thrombi
into the aortic arch branches closely follow the owrate repartitions suggesting that the morphology of
the arteries has a primordial impact on the number of clots which can be found in arteries and can
potentially provoke stroke. More research is needed in the future to verify this assertion, namely using
different pulsatile ow conditions or other liquids such as articial blood.
AAO: Ascending Aorta
DAO: Descending Aorta
BCA: Brachio-Cephalic Artery
LCCA: Left Common Carotid Artery
LSA: Left Subclavian Artery
HBC: Human Blood Clot
AF: Atrial Fibrillation
Sources of Funding
The authors acknowledge the Région Wallonne (Belgium) for funding under Convention N°7463. The
authors declare no competing interests.
M.B. wrote the manuscript and was responsible for the python software, imaging, analysis of the data.
M.T. has been responsible for the test-bed operation including pump programming and setup, injection of
particles, Matlab programming. M.T. and M.B. both design the experiments and the test-bed. K.Z.
provided the human thrombi, A.V provided the MRI datasets and the hemodynamic data. G.C., L.G. and
H.F. supervised the study. All authors reviewed the manuscript.
All data generated or analyzed during this study are included in this published article (and its
Supplementary Information les).
1. Feigin, V. L., Global, regional, and national burden of neurological disorders during 1990-2015: a
systematic analysis for the Global Burden of Disease Study 2015.
2. Malone, F.
, Investigation of the Hemodynamics Inuencing Emboli Trajectories Through a
Patient-Specic Aortic Arch Model.
, 1531-1538 (2019).
3. Choi, H. W., Luo, T., Navia, J. A. & Kassab, G. S., Role of Aortic Geometry on Stroke Propensity
based on Simulations of Patient-Specic Models.
, 0073485 (2013).
4. Fabbri, D., Lon, Q., Das, S. & Pinelli, M., Computational modelling of emboli travel trajectories in
Biomech Model Mechanobiol 13
, 289-302 (2014).
5. Mukherjee, D., Padilla, J. & Shadden, S. C., Numerical investigation of uid–particle interactions
for embolic stroke.
Theoretical and Computational Fluid Dynamics 30
, 23-39 (2016).
6. Chung, E.
, Embolus Trajectory Through a Physical Replica of the Major Cerebral Arteries.
Stroke 41 (4)
, 647-652 (2010).
7. Malone, F.
, Embolus Analog Trajectory Paths Under Physiological Flowrates Through
Patient-Specic Aortic Arch Models.
Journal of Biomechanical Engineering
8. Itoh, Y. & Suzuki, N., Control of brain capillary blood ow (32(7)), 1167-1176 (2012).
9. Carr, I., Nemoto, N., Schwartz, R. S. & Shadden, S., Size-dependent predilections of cardiogenic
embolic transport (305), H732-H739 (2013).
10. Malone, F.
, An in vitro assessment of atrial brillation ow types on cardiogenic emboli
Proceedings of the Institution of Mechanical Engineers Part H Journal of
Engineering in Medicine
(234(12)), 1421-1431 (2020).
11. Alastruey, J., Xiao, N., Fok, H., Schaeffter, T. & Figueroa, C. A., On the impact of modelling
assumptions in multi-scale, subject-specic models of aortic haemodynamics.
J. R. Soc.
Interface 13: 20160073
12. Bushi, D.
, Hemodynamic Evaluation of Embolic Trajectory in an Arterial Bifurcation: An In-
Vitro Experimental Model.
, 2696-2700 (2005).
13. Hirshkowitz, M. e. a., National Sleep Foundation’s updated sleep duration recommendations:
nal report, 233-243 (2015).
14. Chodzynski, K., Coussement, G. & Zouaoui-Boudjeltia, K., France, Netherlands, Belgium,
Luxemburg Patent No. EP2779144 (2014).
15. Kikinis, R., Pieper, S. & Vosburgh, K.,
3D Slicer: a platform for subject-specic image analysis,
visualization, and clinical support. Intraoperative Imaging Image-Guided Therapy
16. Cutnell, J. & Kenneth, J.,
Physics Fourth Edition
17. Guyton, A. C. & Hall, J. E.,
Textbook of medical physiology
(Elsevier Science, 2005).
18. Beldi, G., Beng, L., Siegel, G., Bisch-Knaden, S. & Candinas, D., Prevention of perioperative
thromboembolism in patients with atrial brillation.
British Journal of Surgery
a Schematic front view of the in-vitro test-bed and instruments chain. A: owmeter, B: pressure sensor, C:
solenoid valve, D: aortic-arch model, E: injection site. b Front view photography of the in-vitro test-bed.
a STL geometry obtained from 3D Slicer and Inventor modications for model 1. b Silicone block upon
dissolution of the model’s 3D pva print. c STL for model 2 and. d Associated silicone block
Adapted patient owrate for the model geometry to keep the speed constant (solid line) as well as the
owrate reproduction by the test-bed (dotted line).
Instantaneous pulsatile owrates for the 5 branches of Model 1. AAO (black line), DAO (red line), BCA
(green), LCCA (yellow) and LSA (Blue) cycles for ten seconds of continuous test-bed operation.
Algorithm owchart. On the left, the Python owchart for which data is gathered. Background subtraction
is made on each frame to obtain a mask. For each detection, the pixels’ center of mass is saved and the
RGB pixel value. On the right the same data is used by Matlab to count the emboli.
Repartition percentages for the different types of N injected particles, for 250µm the total number of
injected particles N=845; for 355µm N=1275; for 600µm, N=969; for 850µm, N=1185 and for human
blood clots, N=1197. Each set of bars represent the repartition percentages with corresponding error
calculated in each case as the variability for each experiment. For each artery with the pump owrate
associated percentage in the following order: in dark green, brachiocephalic artery; in lime green, left
common carotid artery; in green, left subclavian artery and in uo grey the descending aorta.
Repartition percentages for the different types of N injected particles, for 250µm the total number of
injected particles N=929; for 355µm N=973; for 600µm, N=726; for 850µm, N=608. Each set of bars
represent the repartition percentages with corresponding error calculated in each case as the variability
for each experiment. For each artery with the pump owrate associated percentage in the following order:
in dark green, brachiocephalic artery; in lime green, left common carotid artery; in green, left subclavian
artery and in uo grey the descending aorta.