UNIVERSITY OF CALIFORNIA SAN DIEGO

Live-Cell In Vitro System using 3D Printing

Athesissubmittedinpartialsatisfactionofthe requirements for the degree Master of Science

in

Bioengineering

by

Quanyou Shi

Committee in charge:

Shu Chien, Chair Alexander Arash Khalessi Geert W Schmid-schoebein Dayu Teng

2021 Copyright Quanyou Shi, 2021 All rights reserved. The thesis of Quanyou Shi is approved, and it is acceptable in quality and form for publication on microfilm and electronically:

Chair

University of California San Diego

2021

iii TABLE OF CONTENTS

SignaturePage ...... iii

TableofContents ...... iv

ListofFigures ...... v

Acknowledgements...... vi

AbstractoftheThesis ...... vii

Introduction ...... 1

MaterialsandMethods ...... 3

Results ...... 9

Discussion...... 16

Results ...... 18

References...... 19

iv LIST OF FIGURES

Figure 1: 3D design of the aneurysm vessels...... 4

Figure 2: Block diagram for the in-vitro perfusion system...... 6

Figure 3: Diagram for aneurysm vessel flow chamber...... 7

Figure 4: Computational simulation and flow validation for the parallel-plate aneurysm vessel...... 10

Figure 5: Computational simulation and flow validation for the half-round aneurysm vessel...... 11

Figure 6: Full vessel scan and zoomed-in images at the vessel center region at Day 0, 4, 6, and 8...... 13

Figure 7: Zoomed-in images at the Proximal and distal aneurysm neck region at Day 0, 4, 6, and 8...... 14

Figure 8: Zoomed-in images at the aneurysm belly region at Day 0, 4, 6, and 8...... 15

Figure 9: In vitro live-HUVECs images overlaid with the shear stress simulation. . . . . 18

v

ACKNOWLEDGEMENTS

I would like to express my deepest gratitude to my committee chair, Dr. Chien, and my advisor, Dr. Teng, for their great mentorship, support and training throughout my project. Their guidance, critics, and patience have helped me to finish my thesis and improve myself along the way. I would also like to thank Dr. Khalessi and Dr. Schmid-schoebein for kindly serving as my committee members. I want to thank Dr. Khalessi for supporting and collaborating in this project and providing crucial insights. Dr. Schmid-schoebein has been a wonderful professor of fluid mechanics course, which is the foundation of this project. I would also like to express my gratitude to current Chien lab members, especially Dr. Yi-shuan Li for her guidance on the project, Phu and Jerry for their great help on the project and daily lab works, and Daniel for his assistance. I would also like to thank all other lab members for their great support.

vi ABSTRACT OF THE THESIS

Live-Cell In Vitro Aneurysm System using 3D Printing

by

Quanyou Shi Master of Science in Bioengineering

University of California San Diego, 2021

Professor Shu Chien, Chair

Intracranial aneurysm (IA) rupture is a major health risk that often leads to per- manent neurological damages and even death. Management of IAs has been challenging due to limited understanding of the underlying cellular mechanism of aneurysm progres- sion. The endothelial cells have been known to play an important role in most vascular diseases. However, there has been a lack of understanding on how endothelial cells contribute to the pathogenesis of . This study aims to develop an in vitro platform that will enable future studies of the e↵ects of fluid mechanical environment on live endothelial cells by using 3D printing technology. The elements of the flow environment, e.g., the velocity field and shear stress in an aneurysm, were simulated using computational fluid dynamics (CFD). These elements were then compared with those computed by particle image velocimetry (PIV) using the videos of tracers flown through a 3D printed aneurysm model. For live-cell experiments, the human umbilical endothelial cells (HUVECs) were cultured on the substrate in the area enclosed by the 3D printed aneurysms perfused at di↵erent flow rates. The results showed a region-specific pattern in HUVECs density that can be correlated to the fluid mechanical elements such as velocity field and shear stress. The cell density decreased significantly at the aneurysm proximal neck and belly regions, where shear

vii stress is low with non-directional flow, and increased at the distal neck region, where shear stress is higher. This study demonstrates the feasibility of a live-cell in vitro aneurysm model created using 3D printing. The development of this system with long-term live-cell culture in 3D printed aneurysm structures will enable future investigations to study the e↵ects of fluid mechanical elements on endothelial cells. Such studies will contribute to better device design and clinical management for the aneurysm patients.

viii Introduction

Intracranial aneurysm (IA) is an abnormal focal dilation of a cerebral with attenuation of the vessel wall.[1] Major classifications of IAs based on their geometry include saccular IA, fusiform IA, microaneurysm, and giant IA.[1, 2] Among these, saccular IA, which shapes as a round thin-walled sac, with well-defined aneurysmal dome and neck connecting to the parent vessels, is the most common type of aneurysm and accounts for approximately 90% of the IAs.[1, 2, 3] IAs have a low risk of rupture of approximately 1%.[4] However, IA ruptures often lead to devastating results, causing subarachnoid hemorrhage and are associated with high rates of fatality and permanent disability.[5] Therefore, appropriate management of the unruptured IAs is crucial. The IA treatments include surgical method of aneurysm clipping, and endovascular methods such as coiling and deployment of flow diverters.[5, 6, 7] The flow diverter is a cylin- drical mesh stent that is placed in the parent vessel across the aneurysm dome. The device alters hemodynamic parameters such as flow velocity and shear stress inside the aneurysm dome, thus inducing intra-aneurysmal that can close o↵the aneurysm.[8, 9, 10] In addition, the stent also serves as a sca↵old for endothelization that promote formation of neointima to permanently close o↵the aneurysm.[11, 12] is the latest innovation, with two devices (Pipeline Embolization Device from Medtronic and Surpass Streamline Flow Diverter from Stryker) approved in the last decade.[13] Flow diverters have rapidly become the treatment of choice because of its high cure rates and low complication rates.[8] However, despite the significant progress in the development of flow diverters and exponential increase in their usage in recent years, flow diverters are still associated with a non-negligible rate of complications, including delayed intraparenchymal hemorrhage, thromboembolism, and spontaneous rupture of previously unruptured IAs after flow diverter treatment. Little is known about the causes leading to these complication events.[9, 14, 15] In addition, among all the available treatment techniques, the preferred therapeutical strategy for the unruptured IAs remains uncertain due to a lack of clinical data.[2, 6] Many of these diculties stem from a lack of fundamental understanding of the cellular mechanism associated with aneurysm. The fundamental hemodynamic and cel- lular mechanisms underpinning the e↵ect of flow diverters are still poorly understood.[9] Hence, a deeper understanding of the cellular mechanism of aneurysm formation, growth, and rupture is required for better management of the unruptured IAs in patients. En-

1 dothelial cell (EC) dysfunction is known to play a major role in the pathogenesis and development of IAs. The hemodynamic factor of wall shear stress (WSS) exerted on ECs by blood flow has been demonstrated to be a key regulator.[16, 17] It is gener- ally accepted that the formation of aneurysms is associated with abnormally high WSS. However, there is no consensus on the WSS pattern leading to aneurysm growth and rupture, and controversial results of both high and low WSS have been reported to be responsible.[18, 19, 20] The lack of fundamental understanding of the cellular mechanism underlying the aneurysm growth and rupture is largely due to the limited available research methods. The complexity of individual IA in terms of both its shape and location poses great challenges for conducting studies on the aneurysms. Most of the in vivo studies for EC responses in aneurysms have been conducted in animal models such as rat or rabbit. Even though these in vivo studies provide a physiological condition closer to , there are still significant di↵erence in anatomy, physiology and that could lead to uncertainty.[21] In addition, as costly and time consuming as it, the in vivo studies would not provide an exact control over the WSS and flow pattern over the ECs inside the aneurysm. On the other hand, with the improvement in computational power, computational fluid dynamics (CFD) simulation of patient aneurysm models have also been done extensively to identify risk factor for aneurysm rupture in an attempt for better prediction.[22] CFD analysis has also been performed for the assessment of FD stents by observing the modulation in hemodynamic factors inside aneurysm.[18, 23] However, its applicability in clinical settings is still limited due to several limitations that make it dicult to produce consistent predictions and reliable results. CFD is often limited by the quality of imaging data, absence of patient specific data, controversial assumptions made for fluid and boundary conditions, meshing resolution, discrepancy in post-simulation flow analysis, and lack of validation.[22, 24, 25, 19] These limitations within the current research approaches reveal the need for more in vitro EC studies that would serve to bridge the gap between in silico CFD simula- tions to in vivo animal studies and clinical outcomes. The development of the in vitro platform introduced in this study could provide additional understanding of aneurysmal EC responses by generating a well-defined flow pattern and WSS over the cultured ECs inside an artificially designed 3D-printed aneurysm structure. Such in vitro EC studies could contribute to the overall understanding of the underlying mechanism of aneurysm development in response to flow modulation. The knowledge of the EC responses to di↵erent hemodynamic factors inside the aneurysm can ultimately guide future designs of flow diverters for better management of unruptured IAs.

2 Materials and Methods

3D Modeling of Saccular Aneurysm Structure

Simplified virtual 3D saccular aneurysm model was created using computer-aided design (CAD) software SOLIDWORKS (Dassault Syst`emes SolidWorks Corp., Con- corde, MA). Saccular aneurysms were modeled as parallel-plate (Figure 1A) and half- round (Figure 1B) vessel structures. The cross-sections of both the parallel-plate and half-round aneurysm structures were modeled to be exactly the same (Figure 1C). For the following experiments, the width (W) of the straight portion of the vessel was mod- eled as 5 mm, the saccular aneurysm diameter (D) as 10 mm, and neck width (n) as 9 mm. These artificially created aneurysm vessel structures were modeled based on typical aneurysm shape. Terms used in this thesis to describe di↵erent regions within the saccular aneurysm are illustrated in Figure 1D. Aneurysm belly is at the tip of the bulging aneurysm. Aneurysm neck connects the bulging aneurysm to the parent vessel. The proximal and distal aneurysm necks are the aneurysm necks upstream and downstream of the flow direction, respectively.

Computational Flow Simulation

Flow simulation through the aneurysm structure is performed using SOLIDWORKS Flow Simulation, which is a CFD (Computational fluid dynamics) analysis software em- bedded in the SOLIDWORKS mechanical design environment. SOLIDWORKS Flow Simulation handles the model geometry with a Cartesian-based immersed-body mesh. The fluid motion is governed by the continuity equation and Navier-Stokes equations. Water was used as the fluid for the flow simulation of the aneurysm model. Water was taken as an incompressible Newtonian fluid, with a density of 0.993 g/ml and a dynamic viscosity of 0.6915 cp at 37°C. When simulating the fluid flow through the aneurysm vessels, the flow rate (Q) was set so that the straight portion of the aneurysm vessel will experience a physiological shear stress of approximately 12 dyn/cm2. Shear stress (⌧)inducedbythefluidisdefined as the product of fluid viscosity (µ) and the shear rate, which is the velocity gradient (@v/@h), the partial derivative of flow velocity (v) with respect to height (h):

@v ⌧ = µ (1) @h

The shear stress (⌧) at the bottom surface of a rectangular parallel-plate chamber with

3 Figure 1: 3D design of (A) the parallel-plate aneurysm vessel and (B) the half-round aneurysm vessel. (C) 2D drawing of the bottom plane for both parallel-plate and half- round aneurysm vessels, the area where ECs are seeded. (D) Terms used for describing di↵erent regions of the saccular aneurysm.

4 height (H) and width (W) and perfused under a given flow rate (Q) can be calculate by:

6Qµ ⌧ = (2) WH2

Therefore, the flow rate (Q) required to produce a desired shear stress (⌧) in the straight portion of the parallel-plate vessel can be calculated inversely from the derived equation:

⌧WH2 Q = (3) 6µ

The flow rate (Q) for the simulation was kept constant throughout the following exper- iments, including flow validation and in vitro perfusion system.

Validation of Flow Simulation in Physical Models

Water suspended with flow tracers was pumped through the 3D printed physical aneurysm vessel at the same flow rate (Q) that was set for the flow simulation. The flow tracers flowing through the aneurysm vessel were video-imaged and tracked with Particle Image Velocimetry (PIV) using PIVlab, a toolbox from MATLAB (Mathworks, Natick, MA). Flow velocity field and flow trajectories can be computed and generated from PIV. The results were then compared with the SOLIDWORKS flow simulation for validation.

3D printing of aneurysm models

Aneurysm models were 3D-printed using Form 2 (Formlabs, Somerville, MA), which is a stereolithography (SLA) 3D printer. The material used for 3D printing was the clear resin from Formlabs. The 3D printed aneurysm model was washed with 99% isopropanol and cured with 368 nm UV light.

Long term in vitro live-cell perfusion system

A long term in vitro live-cell perfusion system was developed to sustain the cells seeded within the aneurysm model while introducing flow through the aneurysm vessel (Figure 2). The main body of the perfusion system, except for the pump, is placed inside an incubator to ensure a sterile and appropriate environment for the cells. Cell culture media flow between the gas exchange chamber and the media reservoir, driven by a pump placed outside the incubator. A soft media reservoir in the rigid PBS bu↵er chamber was used to transfer the driving pressure from the pump into the perfusion system while separating the perfusion system from the open environment. The media from reservoir will flow through the gas exchange chamber where the level of oxygen

5 Figure 2: Block diagram for the in-vitro perfusion system. All parts of the system except for the pump are placed inside incubator for sterile and appropriate environment for cells. The pump pumps PBS into and out of the rigid PBS bu↵er container, which drives the flow of media between the top and bottom media reservoirs. The flow directions are dictated by the one-way check valves, which allow only unidirectional flow. The flow rate generated by the pump and through the aneurysm vessel are indicated in the two plots. The top media reservoir is made of gas permeable polymer that allows for gas exchange and enables cell survival for weeks. and carbon dioxide are controlled. The flow direction is dictated by the one-way check valves, which allow only unidirectional flow. The pump flow rate alternates between forward and backward flow. The resulting flow rate through the aneurysm model is a square wave that alternates between two phases of constant flow rate and zero flow rate, each for an equal length of time. The human umbilical vein endothelial cells (HUVEC) were seeded inside the aneurysm vessel, which was connected to the perfusion system. The aneurysm chamber was created by gluing the 3D printed aneurysm vessel onto a cell culture petri dish, which serves as a substrate for HUVEC seeding (Figure 3). All the components used for constructing this aneurysm chamber, such as the 3D-printed aneurysm vessel and the glue, have been tested to be biocompatible with the HUVECs. Cells were perfused under a physiological shear stress of 12 dyn/cm2 in the straight

6 portion of the vessel. The flow rate was set at the same flow rate that was used for simulation and flow validation.

Figure 3: Diagram showing the parallel-plate aneurysm vessel flow chamber with live HUVECs seeded within the vessel. The perfusion flow enters the chamber from left port, perfuses through cells to induce shear stress, and exit the chamber from the right port. The aneurysm vessel was glued onto the substrate with biocompatible glue.

Live-cell study of HUVECs seeded inside parallel-plate saccular aneurysm vessel structure under perfusion of physiological shear stress

For the live-cell study of HUVECs under perfusion, parallel-plate aneurysm vessel with a cross-sectional height (H) of 0.5 mm was first used because of its simplicity. HUVECs were first seeded inside the parallel-plate aneurysm vessel at a relatively low density on Day 0. The vessel was then connected within the perfusion system and was perfused under a low flow rate of 2 ml/min, to provide sucient nutrients for the HUVECs to grow. A flow rate of 2 ml/min would induce a low shear stress of 1.1 dyn/cm2 in the straight portion of the parallel-plate aneurysm vessel according to Equation (2). HUVECs were perfused under such low flow rate until reaching near 100% confluency. The flow rate was then turned up to the full speed of 22 ml/min, which induced a physiological shear stress of 12.1 dyn/cm2 in the straight vessel portion of the parallel-plate aneurysm vessel. HUVECs inside the parallel-plate aneurysm vessel subjected to physiological shear stress were then monitored and imaged every 24 to 48 hours.

7 Cell image acquisition

To monitor the cell behavior under perfusion, HUVECs were stained with a live- cell tracking agent MitoTracker Red (Life Technologies). The whole aneurysm chamber containing HUVECs were imaged using a scanning microscope (Nikon, Melville, NY). The perfusion flow through the aneurysm vessel model was paused when HUVECs were stained and imaged, and the flow was resumed after imaging was completed.

Cell image analysis

After the acquisition of microscopic images of the HUVECs inside the vessel, the background illumination was corrected, and the consecutive scanning images were stitched into the whole vessel image using ImageJ (NIH, Bethesda, MD, USA). For each whole vessel scan image, a mask enclosing the aneurysm vessel was created to ascertain that each vessel scan was at exactly the same location. The image for each region within the aneurysm vessel was cropped from the whole vessel scan at exactly the same location using ImageJ.

8 Results

Comparison of computational simulations of flow conditions with cal- culations from particle tracing showed very similar results.

Flow simulation was performed for both parallel-plate aneurysm model (Figure 4) and half-round aneurysm model (Figure 5). Simulation for parallel-plate aneurysm vessel showed a decreasing shear stress gradient towards the bulging aneurysm and the proximal neck region, and a high shear stress gradient at the proximal neck region (Figure 4B). The flow trajectories generated from the computational simulation and particle-tracing were very similar in Figure 4C and 4D, showing lower number of tra- jectories towards the proximal neck region and the belly region. The velocity fields generated from computational simulation and particle-tracing were also very similar in Figure 4E and 4F, showing low velocity field in the belly region. Computational simulation of the half-round aneurysm model is shown in Figure 5B. The shear stress in the aneurysm is very low except for the distal neck region and a small area at the proximal neck region, while the shear stress gradient is high across the aneurysm neck. Simulation of the flow pattern in half-round aneurysm vessel showed reverse eddy flow inside the aneurysm dome, centered near the center of the aneurysm (Figure 5C). The flow enters the aneurysm from the distal neck edge of the aneurysm dome and exits from the neck. A similar pattern is shown in the result computed from flow tracing (Figure 5D), with a reversed eddy flow inside the aneurysm.

9 Figure 4: Computational simulation of the flow conditions inside the parallel-plate aneurysm vessel compared to flow conditions calculated from flow tracing. (A) Dia- gram showing the cell-seeded parallel-plate aneurysm vessel and cell-seeding area on the clear substrate, with the direction of the flow. (B) Computational simulation of shear stress distribution over the bottom surface of the parallel-plate aneurysm model using SOLIDWORKS. Simulation shows a decreasing shear stress gradient towards the bulging aneurysm and the proximal neck region. Color bar shows the shear stress magnitude in log scale. (C) Computational simulation of flow trajectories with color indicating the velocity magnitude. The result shows a curved flow bending towards the bulging aneurysm and the distal neck region, and lower numbers of trajectories toward the prox- imal neck region and the belly region. Color bar shows the velocity magnitude. (D) Flow trajectories computed from the flow tracing. Bright speckles are the flow tracers flowing through the aneurysm structure, and red lines indicate the flow trajectories. (E) Computational simulation of velocity field in the mid plane of the parallel-plate aneurysm. (F) Velocity field computed from the flow tracing.

10 Figure 5: Computational simulation of flow condition inside the half-round aneurysm vessel compared to the flow condition calculated from flow tracing. (A) Diagram showing the half-round aneurysm vessel and cell-seeding area on the clear substrate, with the direction of the flow. (B) Computational simulation of shear stress distribution over the bottom surface of the half-round aneurysm model using SOLIDWORKS. Color bar shows the shear stress magnitude in log scale. (C) Computational simulation of flow trajectories shows a reversed eddy flow centered near the center of the aneurysm. Color bar shows the velocity magnitude. (D) Flow trajectories computed from flow tracing. White speckles are the flow tracers flowing through the aneurysm structure, the green arrows indicate the velocity vector, and red lines indicate the flow trajectories.

11 Live-cell study shows region-specific cell responses inside aneurysm ves- sel structure under physiological shear stress.

HUVECs were first seeded on the substrate surface in the aneurysm vessel at a low cell-density on Day 0. After HUVECs were attached, the vessel was connected to the perfusion system and was perfused under a low flow rate of 2 ml/min (shear stress of 1.1 dyn/cm2) to provide sucient nutrients for HUVECs to grow. The HUVECs grew to near confluency and become more elongated after 4 days of low perfusion rate. At the end of Day 4, the flow rate was increased to the full speed of 22 ml/min, which induced a physiological shear stress of 12.1 dyn/cm2 on the HUVECs at the straight portion of the vessel. Figures 6 – 8 show HUVECs images in the perfused aneurysm vessel at the fol- lowing time points: Day 0 (when the HUVECs were just seeded), Day 4 (after 4 days at a low shear stress of 1.1 dyn/cm2 since the cell seeding), Day 6 (2 days after the shear stress was increased to 12.1 dyn/cm2), and Day 8 (4 days after the shear stress was in- creased to 12.1 dyn/cm2). The zoomed-in images are shown at four selected regions: the vessel center region, proximal aneurysm region, distal aneurysm region, and aneurysm belly region. The vessel center region serves as the control region for each time point because it’s under laminar flow and is representative of the average cell density within the straight portion of the aneurysm vessel at each time point.

12 13

Figure 6: Full vessel scan and zoomed-in images at the vessel center region on Day 0 (after cells were seeded); Day 4 (after 4 days at a low shear stress of 1.1 dyn/cm2 since the cell seeding); Day 6 (2 days after the shear stress increased to 12.1 dyn/cm2); and Day 8 (4 days after the shear stress increased to 12.1 dyn/cm2) 14

Figure 7: Zoomed-in images at proximal and distal aneurysm neck regions on Day 0 (after cells were seeded); Day 4 (after 4 days at a low shear stress of 1.1 dyn/cm2 since the cell seeding); Day 6 (2 days after the shear stress increased to 12.1 dyn/cm2); and Day 8 (4 days after the shear stress increased to 12.1 dyn/cm2) 15

Figure 8: Zoomed-in live-cell images at aneurysm belly region on Day 0 (after cells were seeded); Day 4 (after 4 days at a low shear stress of 1.1 dyn/cm2); Day 6 (2 days after the shear stress increased to 12.1 dyn/cm2); and Day 8 (4 days after the shear stress increased to 12.1 dyn/cm2) Discussion

The intracranial hemorrhage resulted from aneurysm rupture has been a devas- tating disease that may lead to disability and death. The flow environment such as wall shear stress and its e↵ects on vascular endothelial cells are crucial in the pathogenesis of aneurysms.17,18 Much work has been done in computational simulations and in vivo animal models on aneurysms. However, neither approach shows how endothelial cells respond to various flow conditions in a controlled environment. The computational sim- ulation can predict the fluid mechanical conditions in a geometric aneurysm structure, but does not reveal cellular behaviors; whereas the in vivo models can show the outcome of the endothelial cells in a randomly occurring aneurysm structure at the end of the ex- periment, but does not control the aneurysm’s geometric shape nor provide the real-time dynamic live-cell imaging of the endothelial cells during the experiment. It would be very valuable to have an in vitro model that can assume the geometric structure of any aneurysm with long-term cell culture and real-time live-cell imaging. The availability of biocompatible 3D printing made such an in vitro model possible. In this work, a 3D printed aneurysm model was created to sustain live endothelial cells (ECs) for a period long-enough so that the flow-induced cell remodeling can be observed and imaged at any time point. Computer-aided design (CAD) provides the capability of customized design of any aneurysm structure. A well-controlled saccular aneurysm was first created into a parallel-plate and half-aneurysm model as a proof- of-concept. The cells were cultured on a cell-compatible clear surface (Figure 4A) for easy imaging of the cells. The current surface cell-seeding within the aneurysm vessel is sucient to validate this model. The fluid environment in the 3D printed aneurysms was simulated by the com- putational fluid dynamics (CFD) and compared with results from the particle image velocimetry (PIV). The CFD simulation predicted the velocity streams based on the geometry, viscosity of the fluid, and the inflow velocity. The PIV results were calculated based on video capturing of the suspended particles flowing through the aneurysm struc- ture. In this study, the CFD simulation results for the parallel-plate aneurysm vessel were compared with the PIV results. Both the flow trajectories and velocity field result from the simulation and the PIV showed a similar pattern (Figure 4C, D, E, and F). Shear stress is a derived parameter from flow velocity (v) and two other elements: the viscosity (µ) of the fluid and the cross-sectional height (H) (Equation 1). Since both the viscosity (µ) and the cross-sectional height (H) can be accurately measured, the validated velocity field can provide an accurate calculation of the shear stress. The

16 shear-stress simulation in the parallel-plate model is shown in Figure 4B. For the half- round aneurysm vessel, the simulation and validation results for flow trajectories also show similar patterns in Figure 5C and D. However, because the imaging system used in the flow tracing could not trace z-directional motions of the tracers, the validation results require further study to provide 3D information. In order to observe the endothelial cells behavior for days, a perfusion system was developed to sustain the cells and allow easy access for live-cell imaging. The results showed that human umbilical vein endothelial cells (HUVECs) were able to grow to confluency under low-flow (1.1 dyn/cm2) perfusion that refreshed the culture media in the aneurysm chamber, but did not induce significant shear stress stimulation to a↵ect cell behavior (Figure 6). In this study, the in vitro live-cell study has demonstrated di↵erent endothelial cell responses specific to di↵erent regions in the aneurysm: aneurysm belly, proximal and distal aneurysm neck (Figure 6 – 9). Such di↵erences in cellular responses coincide with the di↵erent flow parameters in those specific regions (Figure 3, 6 – 9). The control vessel perfused under a low shear stress of 1.1 dyn/cm2 for 4 days had a relatively even distribution of cell density at all locations (Figure 6). In comparison, the experimental vessel with a physiological shear stress at 12.1 dyn/cm2 for 2 and 4 days exhibited a significantly lower cell density in the proximal neck and aneurysm belly regions, and higher cell density in the distal neck region shown in Figure 7 and 8. These in vitro HUVECs images were overlaid with the simulated shear-stress field in the aneurysm (Figure 9), and the results suggested a close correlation between the cell density and the magnitude and gradient of the shear stress. The cell density was uniform and the highest when a low perfusion was applied prior to the start of the physiological flow. After the start of physiological flow, the cell density decreased continuously in the low- shear stress region and non-directional flow region (proximal neck and belly region), whereas the cell density maintains at a higher level in the distal neck region, where shear stress is higher, as shown in Figure 7 – 9. The scope of this study was to establish a system to analyze live endothelial cell responses to the fluid mechanical stimulations in an aneurysm. These observations demonstrate that the fluid environment plays a crucial role in endothelial cell behavior in aneurysms. This system will allow various elements such as cell density, gene and protein expressions to be quantified and analyzed in future studies. The contribution of di↵erent fluid mechanical parameters to the cell behaviors can also be studied by adjusting the geometric variables in the aneurysms.

17 Figure 9: Overlaying the in vitro Live-HUVECs images with the shear stress simulation. (A) Full vessel scan on Day 4 (after 4 days after inlet flow at 1.1 dyn/cm2, before the starting of 12.1 dyn/cm2 shear stress) overlaid with shear stress simulation. (B) Full vessel scan on Day 6 (4 days after inlet flow at 12.1 dyn/cm2) overlaid with shear stress simulation. (C) Full vessel scan on Day 8 (6 days after inlet flow at 12.1 dyn/cm2) overlaid with shear stress simulation.

Conclusion

This study demonstrated the successful creation of an in vitro aneurysm model to study the live-cell remodeling in response to various fluid conditions in a complex vas- cular structure. This provides the foundation to study more complex live-cell aneurysm models in the future. Such studies contribute insights into the pathogenesis and poten- tial treatments of vascular diseases such as intracranial aneurysms.

18 References

[1] Philip M Meyers, H Christian Schumacher, Randall T Higashida, Colin P Derdeyn, Gary M Nesbit, David Sacks, Lawrence R Wechsler, Joshua B Bederson, Sean D Lavine, and Peter Rasmussen. Reporting standards for endovascular repair of sac- cular intracranial cerebral aneurysms, 2010.

[2] Junjie Zhao, Hao Lin, Richard Summers, Mingmin Yang, Brian G Cousins, and Janice Tsui. Current treatment strategies for intracranial aneurysms: an overview. , 69(1):17–30, 2018.

[3] Roberto Gasparotti and Roberto Liserre. Intracranial aneurysms. European radi- ology, 15(3):441–447, 2005.

[4] Vernard S Fennell, M Yashar S Kalani, Gursant Atwal, Nikolay L Martirosyan, and Robert F Spetzler. Biology of saccular cerebral aneurysms: a review of current understanding and future directions. Frontiers in , 3:43, 2016.

[5] Stanlies D’Souza. Aneurysmal subarachnoid hemorrhage. Journal of neurosurgical , 27(3):222, 2015.

[6] B Gregory Thompson, Robert D Brown Jr, Sepideh Amin-Hanjani, Joseph P Broderick, Kevin M Cockroft, E Sander Connolly Jr, Gary R Duckwiler, Cather- ine C Harris, Virginia J Howard, S Claiborne Johnston, Philip M. Mayers, Andrew Molyneux, Christopher S. Ogilvy, Andrew J. Ringer, and James Torner. Guide- lines for the management of patients with unruptured intracranial aneurysms: a guideline for healthcare professionals from the american heart association/american association. Stroke, 46(8):2368–2400, 2015.

[7] Bowen Jiang, Michelle Pa↵, Geo↵rey P Colby, Alexander L Coon, and Li-Mei Lin. Cerebral aneurysm treatment: modern neurovascular techniques. Stroke and vascular , 1(3):93–100, 2016.

[8] Brad Seibert, Ramachandra Tummala, Ricky Chow, Alireza Faridar, Seyed Ali Mousavi, and Afshin A Divani. Intracranial aneurysms: review of current treatment options and outcomes. Frontiers in neurology, 2:45, 2011.

[9] AA Dmytriw, K Phan, JM Moore, VM Pereira, T Krings, and AJ Thomas. On flow diversion: the changing landscape of intracerebral aneurysm management. American Journal of , 40(4):591–600, 2019.

[10] Krishnan Ravindran, Amanda M Casabella, Juan Cebral, Waleed Brinjikji, David F Kallmes, and Ram Kadirvel. Mechanism of action and biology of flow diverters in

19 the treatment of intracranial aneurysms. , 86(Supplement 1):S13–S19, 2020.

[11] Pietro I D’Urso, Giuseppe Lanzino, Harry J Cloft, and David F Kallmes. Flow diversion for intracranial aneurysms: a review. Stroke, 42(8):2363–2368, 2011.

[12] Yoshikazu Matsuda, Joonho Chung, and Demetrius K Lopes. Analysis of neointima development in flow diverters using optical coherence tomography imaging. Journal of neurointerventional surgery, 10(2):162–167, 2018.

[13] Ramanathan Kadirvel, Yong-Hong Ding, Daying Dai, Issa Rezek, Debra A Lewis, and David F Kallmes. Cellular mechanisms of aneurysm occlusion after treatment with a flow diverter. , 270(2):394–399, 2014.

[14] Georgios A Maragkos, Adam A Dmytriw, Mohamed M Salem, Vincent M Tutino, Hui Meng, Christophe Cognard, Paolo Machi, Timo Krings, and Vitor Mendes Pereira. Overview of di↵erent flow diverters and flow dynamics. Neuro- surgery, 86(Supplement 1):S21–S34, 2020.

[15] Aymeric Rouchaud, Waleed Brinjikji, Giuseppe Lanzino, Harry J Cloft, Ra- manathan Kadirvel, and David F Kallmes. Delayed hemorrhagic complications after flow diversion for intracranial aneurysms: a literature overview. Neuroradiol- ogy, 58(2):171–177, 2016.

[16] Francesco Briganti, Giuseppe Leone, Mariano Marseglia, Giuseppe Mariniello, Fer- dinando Caranci, Arturo Brunetti, and Francesco Maiuri. Endovascular treatment of cerebral aneurysms using flow-diverter devices: a systematic review. The neuro- radiology journal, 28(4):365–375, 2015.

[17] Dallas L Sheinberg, David J McCarthy, Omar Elwardany, Jean-Paul Bryant, Evan Luther, Stephanie H Chen, John W Thompson, and Robert M Starke. Endothelial dysfunction in cerebral aneurysms. Neurosurgical focus, 47(1):E3, 2019.

[18] Brittany Staarmann, Matthew Smith, and Charles J Prestigiacomo. Shear stress and aneurysms: a review. Neurosurgical focus, 47(1):E2, 2019.

[19] Daniel M Sforza, Christopher M Putman, and Juan R Cebral. Computational fluid dynamics in brain aneurysms. International journal for numerical methods in , 28(6-7):801–808, 2012.

[20] Melissa C Brindise, Sean Rothenberger, Benjamin Dickerho↵, Susanne Schnell, Michael Markl, David Saloner, Vitaliy L Rayz, and Pavlos P Vlachos. Multi- modality cerebral aneurysm haemodynamic analysis: in vivo 4d flow mri, in vitro volumetric particle velocimetry and in silico computational fluid dynamics. Journal of the Royal Society Interface, 16(158):20190465, 2019.

[21] Alexander M Nixon, Murat Gunel, and Bauer E Sumpio. The critical role of in the development of cerebral : a review. Journal of neurosurgery, 112(6):1240–1253, 2010.

[22] Bongjae Chung and Juan Raul Cebral. Cfd for evaluation and treatment planning of aneurysms: review of proposed clinical uses and their challenges. Annals of biomedical engineering, 43(1):122–138, 2015.

20 [23] John W Thompson, Omar Elwardany, David J McCarthy, Dallas L Sheinberg, Carlos M Alvarez, Ahmed Nada, Brian M Snelling, Stephanie H Chen, Samir Sur, and Robert M Starke. In vivo cerebral aneurysm models. Neurosurgical focus, 47(1):E20, 2019.

[24] Robert J Damiano, Ding Ma, Jianping Xiang, Adnan H Siddiqui, Kenneth V Sny- der, and Hui Meng. Finite element modeling of endovascular coiling and flow diversion enables hemodynamic prediction of complex treatment strategies for in- tracranial aneurysm. Journal of biomechanics, 48(12):3332–3340, 2015.

[25] Philipp Berg, Sylvia Saalfeld, Samuel Voß, Oliver Beuing, and G´abor Janiga. A review on the reliability of hemodynamic modeling in intracranial aneurysms: why computational fluid dynamics alone cannot solve the equation. Neurosurgical Focus, 47(1):E15, 2019.

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