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 flowrate at each exit, flowmeters (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 flowrate repartitions. Pressure sensors (First Sensor CTE8001GY4N and CTEM8500GY4N) are placed at each exit to monitor instantaneous pressure. To reproduce the flowrate, 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 flow 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 artificial 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 flow-velocity profile and AAO surface area changes over the cardiac cycle at the ascending aorta, quantified by phase contrast MRI. The first 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/) [15] was used to smooth and clean the 3D chest scanners to extract the final aortic-arch geometry in each case. The three upper arteries final sections were modified for fixation 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 filament (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 flowing warm water until full dissolution of the print occurred. Figure 2 displays the final 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 files 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 flowrate 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 flowrate 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 flowrate profile [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 fixed 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 flowrate value. The linear actuator software (LinMot-Talk v6.6) was programmed to set the piston to follow a specific displacement profile in order to reproduce the imposed reference physiological signal.
The imposed piston motion allowed for the geometry adapted ascending aorta flow to be set (Fig. 3). The in-vitro chamber mean flowrate were measured with the associated standard deviation presented in Table 2.
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 flowrates for the 5 branches.
Artificial Thrombi Particles
For optical efficiency in particle tracking, fluorescent green spherical particles made of polyethylene were used as artificial 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 justified as to retain a mass density close to human thrombi (1.06 g/cc) [16] and satisfy optimal optical conditions for detection (fluorescent 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 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 filled container was injected slowly and in a continuous manner to avoid as much as possible multiple particles entering at the same time.
Imaging
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 fixed 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 affixed to the macro lens for the camera fixed on the tripod to improve contrast and to filter unwanted light reflections. 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 field 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 defined 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.