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Distribution of Artificial Thrombi Candidates Through Patient-Specific Aortic-Arch Phantoms under Pulsatile Flow Conditions

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Ischemic Stroke is the most frequent type of stroke and is subject to many studies investigating prevention means. Avoiding the difficulties 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 flow conditions. In the in-vitro test bed, using automatic image tracking and analysis, it was made possible detecting and tracking artificial spherical emboli candidates circulating in the anatomic aortic-arch models under a realistic based-patient blood flow profile. 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 artificial emboli sizes, the experimental study shows that the repartition percentages of the emboli closely follow the flowrate repartition percentages for both aortic-arch models, suggesting that higher flowrates 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 artificial emboli.
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Distribution of Articial Thrombi Candidates
Through Patient-Specic Aortic-Arch Phantoms
under Pulsatile Flow Conditions
Marco Testaguzza ( )
University of Mons (UMONS)
Mehdi Benhassine
University of Mons (UMONS)
Haroun Frid
FridMind Technologies
Laurence Gebhart
FridMind Technologies
Karim Zouaoui Boudjeltia
Université libre de Bruxelles, CHU de Charleroi
Axel Vanrossomme
CHU de Charleroi
Gregory Coussement
University of Mons (UMONS)
Research Article
Keywords: Ischemic Stroke, emboli, pulsatile ow conditions
License: This work is licensed under a Creative Commons Attribution 4.0 International License. 
Read Full 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 diculties 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 articial spherical
emboli candidates circulating in the anatomic aortic-arch models under a realistic based-patient blood
ow prole. 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 articial 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 articial emboli.
Background And Purpose
Over 13.7 million people experience a stroke event each year, out of which 9.5 million are ischemic
strokes [1]. Several risk factors are known to increase the propensity of ischemic strokes such as atrial
brillation and diabetes. According to Malone et al [2], 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 [3], [4], [5]. 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 [4] 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 [6] or millimetric thrombi analogues made from bovine blood within the aortic arch [2], [7].
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 [8]. 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 [3] 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 [9] provides simulations and
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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
articial blood liquid as a medium [10].
Based on patients 4D-MRI scanners, two aortic arch geometries were extracted, and two patient-specic
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 [11]. Articial 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
articial 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 [12]. To make sure that the choice of articial emboli is relevant, verication 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 [13].
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 [14]. 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 articial blood.
Aortic Arch Model
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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 prole and AAO
surface area changes over the cardiac cycle at the ascending aorta, quantied 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 ( [15] 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 modied 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
their creation.
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):
Table1Aortic-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%.
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A UMONS patented system of pumps was exploited to reproduce the behavior of the physiological
pulsatile owrate prole [14]. 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 specic displacement prole 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 [7]. 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.
Articial Thrombi Particles
For optical eciency in particle tracking, uorescent green spherical particles made of polyethylene were
used as articial 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 justied as to retain a
mass density close to human thrombi (1.06 g/cc) [16] 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) [17]. A
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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 Thrombi
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 axed to the macro lens for the
camera xed on the tripod to improve contrast and to lter unwanted light reections. 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 dened 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
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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
Algorithm Validation
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 specic time have been
conrmed 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 signicant 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 articial thrombi, although
having various sizes ranging from 1 to 2 mm in size from visual inspection.
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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 [2], [3], 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 conrmed 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 deected.
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 conguration. 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 articial blood.
AAO: Ascending Aorta
DAO: Descending Aorta
BCA: Brachio-Cephalic Artery
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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.
Data Availability
All data generated or analyzed during this study are included in this published article (and its
Supplementary Information les).
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Figure 1
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.
Page 12/18
Figure 2
a STL geometry obtained from 3D Slicer and Inventor modications 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
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Figure 3
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).
Page 14/18
Figure 4
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.
Page 15/18
Figure 5
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.
Page 16/18
Figure 6
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.
Page 17/18
Figure 7
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.
Page 18/18
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Atrial fibrillation is the most significant contributor to thrombus formation within the heart and is responsible for 45% of all cardio embolic strokes, which account for approximately 15% of acute ischemic strokes cases worldwide. Atrial fibrillation can result in a reduction of normal cardiac output and cycle length of up to 30% and 40%, respectively. A total of 240 embolus analogues were released into a thin-walled, patient-specific aortic arch under normal (60 embolus analogues) and varying atrial fibrillation (180 embolus analogues) pulsatile flow conditions. Under healthy flow conditions (n = 60), the embolus analogues tended to follow the flow rate split through each outlet vessel. There was an increase in clot trajectories along the common carotid arteries under atrial fibrillation flow conditions. A shorter pulse period (0.3 s) displayed the highest percentage of clots travelling to the brain (24%), with a greater percentage of clots travelling through the left common carotid artery (17%). This study provides an experimental insight into the effect varying cardiac output and cycle length can have on the trajectory of a cardiac source blood clots travelling to the cerebral vasculature and possibly causing a stroke.
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Atrial fibrillation (AF) is the most common irregular heartbeat among the world's population and is a major contributor to cardiogenic embolisms and acute ischemic stroke (AIS). A physiological simulation system designed to analyse the trajectory patterns of bovine embolus analogues (EAs) (n = 720) through four patient specific models, under three flow conditions: steady flow, normal pulsatile flow and AF pulsatile flow. Overall AF flow conditions increased trajectories through the LCCA and RCCA by 25%. There was no statistical difference in the distribution of clot trajectories when the clot was released from the right, left or anterior positions. Overall, the EA trajectory paths were proportional to the percentage flowrate split of 25 - 31% along the branching vessels. Significantly more EAs travelled through the brachiocephalic trunk experienced than through the LCCA or the left subclavian. Yet of the EAs that travelled towards the cerebral vasculature, there was a greater affiliation towards the left common carotid artery compared to the right common carotid artery (p < 0.05).
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Summary Background Comparable data on the global and country-specific burden of neurological disorders and their trends are crucial for health-care planning and resource allocation. The Global Burden of Diseases, Injuries, and Risk Factors (GBD) Study provides such information but does not routinely aggregate results that are of interest to clinicians specialising in neurological conditions. In this systematic analysis, we quantified the global disease burden due to neurological disorders in 2015 and its relationship with country development level. Methods We estimated global and country-specific prevalence, mortality, disability-adjusted life-years (DALYs), years of life lost (YLLs), and years lived with disability (YLDs) for various neurological disorders that in the GBD classification have been previously spread across multiple disease groupings. The more inclusive grouping of neurological disorders included stroke, meningitis, encephalitis, tetanus, Alzheimer's disease and other dementias, Parkinson's disease, epilepsy, multiple sclerosis, motor neuron disease, migraine, tension-type headache, medication overuse headache, brain and nervous system cancers, and a residual category of other neurological disorders. We also analysed results based on the Socio-demographic Index (SDI), a compound measure of income per capita, education, and fertility, to identify patterns associated with development and how countries fare against expected outcomes relative to their level of development. Findings Neurological disorders ranked as the leading cause group of DALYs in 2015 (250·7 [95% uncertainty interval (UI) 229·1 to 274·7] million, comprising 10·2% of global DALYs) and the second-leading cause group of deaths (9·4 [9·1 to 9·7] million], comprising 16·8% of global deaths). The most prevalent neurological disorders were tension-type headache (1505·9 [UI 1337·3 to 1681·6 million cases]), migraine (958·8 [872·1 to 1055·6] million), medication overuse headache (58·5 [50·8 to 67·4 million]), and Alzheimer's disease and other dementias (46·0 [40·2 to 52·7 million]). Between 1990 and 2015, the number of deaths from neurological disorders increased by 36·7%, and the number of DALYs by 7·4%. These increases occurred despite decreases in age-standardised rates of death and DALYs of 26·1% and 29·7%, respectively; stroke and communicable neurological disorders were responsible for most of these decreases. Communicable neurological disorders were the largest cause of DALYs in countries with low SDI. Stroke rates were highest at middle levels of SDI and lowest at the highest SDI. Most of the changes in DALY rates of neurological disorders with development were driven by changes in YLLs. Interpretation Neurological disorders are an important cause of disability and death worldwide. Globally, the burden of neurological disorders has increased substantially over the past 25 years because of expanding population numbers and ageing, despite substantial decreases in mortality rates from stroke and communicable neurological disorders. The number of patients who will need care by clinicians with expertise in neurological conditions will continue to grow in coming decades. Policy makers and health-care providers should be aware of these trends to provide adequate services. Funding Bill & Melinda Gates Foundation.
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Stroke is a life threatening event that is expected to more than double over the next 40 years. Atrial fibrillation (AF) has been reported as a strong independent risk factor for stroke. We have previously shown that a hemodynamic perturbation by AF or reduced cardiac output and cycle length may have a significant impact on clot trajectory and thus embolic stroke propensity through the left common carotid artery using an idealized aortic arch model. Here, we show the dependence of flow patterns and hence stroke propensity on geometry of patient-specific aortas. We performed computational fluid dynamics (CFD) simulations to determine the variations of AF-induced stroke propensity over various image-based patient-dependent aorta models. The results demonstrated that curvature pattern of aorta can play a determinant role in AF-induced stroke propensity alteration. Specifically, it was shown that the hemodynamic perturbation by AF considered led to substantial increase in stroke propensity (i.e., 2.5~3.8 fold elevation) for lower curvature angle <90° while the changes in stroke propensity by AF are negligible for higher curvature angle >90°. The present simulations suggest that aortic arch curvature is an important risk factor for embolic stroke which should be tested in future clinical trials.
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Simulation of haemodynamics has become increasingly popular within the research community. Irrespective of the modelling approach (zero-dimensional (0D), one-dimensional (1D) or three-dimensional (3D)), in vivo measurements are required to personalize the arterial geometry, material properties and boundary conditions of the computational model. Limitations in in vivo data acquisition often result in insufficient information to determine all model parameters and, hence, arbitrary modelling assumptions. Our goal was to minimize and understand the impact of modelling assumptions on the simulated blood pressure, flow and luminal area waveforms by studying a small region of the systemic vasculature—the upper aorta—and acquiring a rich array of non-invasive magnetic resonance imaging and tonometry data from a young healthy volunteer. We first investigated the effect of different modelling assumptions for boundary conditions and material parameters in a 1D/0D simulation framework. Strategies were implemented to mitigate the impact of inconsistencies in the in vivo data. Average relative errors smaller than 7% were achieved between simulated and in vivo waveforms. Similar results were obtained in a 3D/0D simulation framework using the same inflow and outflow boundary conditions and consistent geometrical and mechanical properties. We demonstrated that accurate subject specific 1D/0D and 3D/0D models of aortic haemodynamics can be obtained using non-invasive clinical data while minimizing the number of arbitrary modelling decisions.
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Roughly one-third of all strokes are caused by an embolus traveling to a cerebral artery and blocking blood flow in the brain. The objective of this study is to gain a detailed understanding of the dynamics of embolic particles within arteries. Patient computed tomography image is used to construct a three-dimensional model of the carotid bifurcation. An idealized carotid bifurcation model of same vessel diameters was also constructed for comparison. Blood flow velocities and embolic particle trajectories are resolved using a coupled Euler– Lagrange approach. Blood is modeled as a Newtonian fluid, discretized using the finite volume method, with physiologically appropriate inflow and outflow boundary conditions. The embolus trajectory is modeled using Lagrangian particle equations accounting for embolus interaction with blood as well as vessel wall. Both one-and two-way fluid–particle coupling are considered, the latter being implemented using momentum sources augmented to the discretized flow equations. It was observed that for small-to-moderate particle sizes (relative to vessel diameters), the estimated particle distribution ratio—with and without the inclusion of two-way fluid– particle momentum exchange—were found to be similar. The maximum observed differences in distribution ratio with and without the coupling were found to be higher for the idealized bifurcation model. Additionally, the distribution was found to be reasonably matching the volumetric flow distribution for the idealized model, while a notable deviation from volumetric flow was observed in the anatomical model. It was also observed from an analysis of particle path lines that particle interaction with helical flow, characteristic of anatomical vasculature models, could play a prominent role in transport of embolic particle. The results indicate therefore that flow helicity could be an important hemodynamic indicator for analysis of embolus particle transport. Additionally, in the presence of helical flow, and vessel curvature, inclusion of two-way momentum exchange was found to have a secondary effect for transporting small to moderate embolus particles—and one-way coupling could be used as a reasonable approximation, thereby causing substantial savings in computational resources.
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While it is intuitively clear that aortic anatomy and embolus size could be important determinants for cardiogenic embolic stroke risk and stroke location, few data exist confirming or characterizing this hypothesis. The objective of this study is to use medical imaging and computational modeling to better understand if aortic anatomy and embolus size influence predilections for cardiogenic embolic transport, and right versus left hemisphere propensity. Anatomically accurate models of the human aorta and branch arteries to the head were reconstructed from CT angiography of 10 patients. Blood flow was modeled by the Navier-Stokes equations using a well-validated flow solver with physiologic inflow and boundary conditions. Embolic particulate was released from the aortic root and tracked through the common carotid and vertebral arteries for a range of particle sizes. Cardiogenic emboli reaching the carotid and vertebral arteries appeared to have a strong size-destination relationship that varied markedly from expectations based on blood distribution. Observed trends were robust to modeling parameters. A patient's aortic anatomy appeared to significantly influence the probability a cardiogenic particle becomes embolic to the head. Right hemisphere propensity appeared dominant for cardiogenic emboli, which has been confirmed clinically. The predilections discovered through this modeling could represent an important mechanism underlying cardiogenic embolic stroke etiology.
Objective: To make scientifically sound and practical recommendations for daily sleep duration across the life span. Methods: The National Sleep Foundation convened a multidisciplinary expert panel (Panel) with broad representation from leading stakeholder organizations. The Panel evaluated the latest scientific evidence and participated in a formal consensus and voting process. Then, the RAND/UCLA Appropriateness Method was used to formulate sleep duration recommendations. Results: The Panel made sleep duration recommendations for 9 age groups. Sleep duration ranges, expressed as hours of sleep per day, were designated as recommended, may be appropriate, or not recommended. Recommended sleep durations are as follows: 14-17 hours for newborns, 12-15 hours for infants, 11-14 hours for toddlers, 10-13 hours for preschoolers, 9-11 hours for school-aged children, and 8-10 hours for teenagers. Seven to 9 hours is recommended for young adults and adults, and 7-8 hours of sleep is recommended for older adults. The self-designated basis for duration selection and critical discussions are also provided. Conclusions: Consensus for sleep duration recommendations was reached for specific age groupings. Consensus using a multidisciplinary expert Panel lends robust credibility to the results. Finally, limitations and caveats of these recommendations are discussed.
The observed distribution of cerebral infarcts varies markedly from expectations based on blood-flow volume or Doppler embolus detection. In this study, we used an in vitro model of the cerebral arteries to test whether embolus microspheres encountering the circle of Willis are carried proportionally to volume flow or express a preferred trajectory related to arterial morphology or embolus size. Our model consisted of a patient-specific silicone replica of the cerebral macrocirculation featuring physiologically realistic pulsatile flow of a blood-mimicking fluid at approximately 1000 mL/min and an input pressure of approximately 150/70 mm Hg. Particles of 200, 500, and 1000 microm diameter with equivalent density to thrombus were introduced to the carotid arteries and counted on exiting the model outlets. The middle cerebral arteries (MCAs) of the replica attracted a disproportionate number of emboli compared with the anterior cerebral arteries; 98%+/-3% of 1000 microm and 93%+/-2% of 500 microm emboli entered the MCA compared with 82%+/-5% of the flow. The observed distribution of large emboli was consistent with the ratio of MCA:anterior cerebral artery infarcts, approximately 95% of which occur in territories supplied by the MCA. With decreasing embolus size, the distribution of emboli approaches that of the flow (approximately 89% of 200 microm emboli took the MCA). Embolus trajectory through the cerebral arteries is dependent on embolus size and strongly favors the MCA for large emboli. The 70:30 ratio of MCA:anterior cerebral artery emboli observed by Doppler ultrasound is consistent with the trajectories of small emboli that tend to be asymptomatic.