An animal-specific FSI model of the abdominal aorta in anesthetized mice

Hemodynamics and wall shear metrics in a pulmonary autograft: Comparing a fluid-structure interaction and computational fluid dynamics approach

OBJECTIVE

In young patients, aortic valve disease is often treated by placement of a pulmonary autograft (PA) which adapts to its new environment through growth and remodeling. To better understand the hemodynamic forces acting on the highly distensible PA in the acute phase after surgery, we developed a fluid-structure interaction (FSI) framework and comprehensively compared hemodynamics and wall shear-stress (WSS) metrics with a computational fluid dynamic (CFD) simulation.

METHODS

The FSI framework couples a prestressed non-linear hyperelastic arterial tissue model with a fluid model using the in-house coupling code CoCoNuT. Geometry, material parameters and boundary conditions are based on in-vivo measurements. Hemodynamics, time-averaged WSS (TAWSS), oscillatory shear index (OSI) and topological shear variation index (TSVI) are evaluated qualitatively and quantitatively for 3 different sheeps.

RESULTS

Despite systolic-to-diastolic volumetric changes of the PA in the order of 20 %, the point-by-point correlation of TAWSS and OSI obtained through CFD and FSI remains high (r > 0.9, p < 0.01) for TAWSS and (r > 0.8, p < 0.01) for OSI). Instantaneous WSS divergence patterns qualitatively preserve similarities, but large deformations of the PA leads to a decrease of the correlation between FSI and CFD resolved TSVI (r < 0.7, p < 0.01). Moderate co-localization between FSI and CFD is observed for low thresholds of TAWSS and high thresholds of OSI and TSVI.

CONCLUSION

FSI might be warranted if we were to use the TSVI as a mechano-biological driver for growth and remodeling of PA due to varying intra-vascular flow structures and near wall hemodynamics because of the large expansion of the PA.

Central Artery Hemodynamics in Angiotensin II-Induced Hypertension and Effects of Anesthesia

Systemic hypertension is a strong risk factor for cardiovascular, neurovascular, and renovascular diseases. Central artery stiffness is both an initiator and indicator of hypertension, thus revealing a critical relationship between the wall mechanics and hemodynamics. Mice have emerged as a critical animal model for studying effects of hypertension and much has been learned. Regardless of the specific mouse model, data on changes in cardiac function and hemodynamics are necessarily measured under anesthesia. Here, we present a new experimental-computational workflow to estimate awake cardiovascular conditions from anesthetized data, which was then used to quantify effects of chronic angiotensin II-induced hypertension relative to normotension in wild-type mice. We found that isoflurane anesthesia had a greater impact on depressing hemodynamics in angiotensin II-infused mice than in controls, which led to unexpected results when comparing anesthetized results between the two groups of mice. Through comparison of the awake simulations, however, in vivo relevant effects of angiotensin II-infusion on global and regional vascular structure, properties, and hemodynamics were found to be qualitatively consistent with expectations. Specifically, we found an increased in vivo vascular stiffness in the descending thoracic aorta and suprarenal abdominal aorta, leading to increases in pulse pressure in the distal aorta. These insights allow characterization of the impact of regionally varying vascular remodeling on hemodynamics and mouse-to-mouse variations due to induced hypertension.

Simulating Subject-Specific Aortic Hemodynamic Effects of Valvular Lesions in Rheumatic Heart Disease

Rheumatic heart disease (RHD) is a neglected tropical disease despite the substantial global health burden. In this study, we aimed to develop a lower cost method of modeling aortic blood flow using subject-specific velocity profiles, aiding our understanding of RHD's consequences on the structure and function of the ascending aorta. Echocardiography and cardiovascular magnetic resonance (CMR) are often used for diagnosis, including valve dysfunction assessments. However, there is a need to further characterize aortic valve lesions to improve treatment options and timing for patients, while using accessible and affordable imaging strategies. Here, we simulated effects of RHD aortic valve lesions on the aorta using computational fluid dynamics (CFD). We hypothesized that inlet velocity distribution and wall shear stress (WSS) will differ between RHD and non-RHD individuals, as well as between subject-specific and standard Womersley velocity profiles. Phase-contrast CMR data from South Africa of six RHD subjects with aortic stenosis and/or regurgitation and six matched controls were used to estimate subject-specific velocity inlet profiles and the mean velocity for Womersley profiles. Our findings were twofold. First, we found WSS in subject-specific RHD was significantly higher (p < 0.05) than control subject simulations, while Womersley simulation groups did not differ. Second, evaluating spatial velocity differences (ΔSV) between simulation types revealed that simulations of RHD had significantly higher ΔSV than non-RHD (p < 0.05), these results highlight the need for implementing subject-specific input into RHD CFD, which we demonstrate how to accomplish through accessible methods.

Statistical shape representation of the thoracic aorta: accounting for major branches of the aortic arch

Statistical shape modeling (SSM) is an emerging tool for risk assessment of thoracic aortic aneurysm. However, the head branches of the aortic arch are often excluded in SSM. We introduced an SSM strategy based on principal component analysis that accounts for aortic branches and applied it to a set of patient scans. Computational fluid dynamics were performed on the reconstructed geometries to identify the extent to which branch model accuracy affects the calculated wall shear stress (WSS) and pressure. Surface-averaged and location-specific values of pressure did not change significantly, but local WSS error was high near branches when inaccurately modeled.

Considerations for analysis of endothelial shear stress and strain in FSI models of atherosclerosis

Atherosclerosis is a lipid driven chronic inflammatory disease that is characterized by the formation of plaques at predilection sites. These predilection sites (side branches, curved segments, and bifurcations) have often been associated with disturbed shear stress profiles. However, in addition to shear stress, endothelial cells also experience artery wall strain that could contribute to atherosclerosis progression. Herein, we describe a method to accurately obtain these shear stress and strain profiles. We developed a fluid-structure interaction (FSI) framework for modelling arteries within a commercially available package (Abaqus, version 6.14) that included known prestresses (circumferential, axial and pressure associated). In addition, we co-registered 3D histology to a micro-CT-derived 3D reconstruction of an atherosclerotic carotid artery from a cholesterol-fed ApoE^-/- mouse to include the spatial distribution of lipids within a subject-specific model. The FSI model also incorporated a nonlinear hyperelastic material model with regionally-varying properties that distinguished between healthy vessel wall and plaque. FSI predicted a lower shear stress than CFD (~-12%), but further decreases in plaque regions with softer properties (~-24%) were dependent on the approach used to implement the prestresses in the artery wall. When implemented with our new hybrid approach (zero prestresses in regions of lipid deposition), there was significant heterogeneity in endothelial shear stress in the atherosclerotic artery due to variations in stiffness and, in turn, wall strain. In conclusion, when obtaining endothelial shear stress and strain in diseased arteries, a careful consideration of prestresses is necessary. This paper offers a way to implement them.

Effect of Subject-Specific, Spatially Reduced, and Idealized Boundary Conditions on the Predicted Hemodynamic Environment in the Murine Aorta

Mouse models of atherosclerosis have become effective resources to study atherogenesis, including the relationship between hemodynamics and lesion development. Computational methods aid the prediction of the in vivo hemodynamic environment in the mouse vasculature, but careful selection of inflow and outflow boundary conditions (BCs) is warranted to promote model accuracy. Herein, we investigated the impact of animal-specific versus reduced/idealized flow boundary conditions on predicted blood flow patterns in the mouse thoracic aorta. Blood velocities were measured in the aortic root, arch branch vessel, and descending aorta in ApoE^-/- mice using phase-contrast MRI. Computational geometries were derived from micro-CT imaging and combinations of high-fidelity or reduced/idealized MR-derived BCs were applied to predict the bulk flow field and hemodynamic metrics (e.g., wall shear stress, WSS; cross-flow index, CFI). Results demonstrate that pressure-free outlet BCs significantly overestimate outlet flow rates as compared to measured values. When compared to models that incorporate 3-component inlet velocity data [[Formula: see text]] and time-varying outlet mass flow splits [[Formula: see text]] (i.e., high-fidelity model), neglecting in-plane inlet velocity components (i.e., [Formula: see text])) leads to errors in WSS and CFI values ranging from 10 to 30% across the model domain whereas the application of a steady outlet mass flow splits results in negligible differences in these hemodynamics metrics. This investigation highlights that 3-component inlet velocity data and at least steady mass flow splits are required for accurate predictions of flow patterns in the mouse thoracic aorta.

Numerical analysis of the hemodynamics of rat aorta based on magnetic resonance imaging and fluid-structure interaction

Murine models have been widely used to investigate the mechanobiology of aortic atherosclerosis and dissections, which develop preferably at different anatomic locations of aorta. Based MRI and finite element analysis with fluid-structure interaction, we numerically investigated factors that may affect the blood flow and structural mechanics of rat aorta. The results indicated that aortic root motion greatly increases time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), relative residence time (RRT), displacement of the aorta, and enhances helical flow pattern but has limited influence on effective stress, which is highly modulated by blood pressure. Moreover, the influence of the motion component on these indicators is different with axial motion more obvious than planar motion. Surrounding fixation of the intercostal arteries and the branch vessels on aortic arch would reduce the influence of aortic root motion. The compliance of the aorta has different influences at different regions, leading to decrease in TAWSS and helical flow, increase in OSI, RRT at the aortic arch, but has reversed effects on the branch vessels. When compared with the steady flow, the pulsatile blood flow would obviously increase the WSS, the displacement, and the effective stress in most regions. In conclusion, to accurately quantify the blood flow and structural mechanics of rat aorta, the motion of the aortic root, the compliance of aortic wall, and the pulsation of blood flow should be considered. However, when only focusing on the effective stress in rat aorta, the motion of the aortic root may be neglected.

Preclinical techniques to investigate exercise training in vascular pathophysiology

Atherosclerosis is a dynamic process starting with endothelial dysfunction and inflammation and eventually leading to life-threatening arterial plaques. Exercise generally improves endothelial function in a dose-dependent manner by altering hemodynamics, specifically by increased arterial pressure, pulsatility, and shear stress. However, athletes who regularly participate in high-intensity training can develop arterial plaques, suggesting alternative mechanisms through which excessive exercise promotes vascular disease. Understanding the mechanisms that drive atherosclerosis in sedentary versus exercise states may lead to novel rehabilitative methods aimed at improving exercise compliance and physical activity. Preclinical tools, including in vitro cell assays, in vivo animal models, and in silico computational methods, broaden our capabilities to study the mechanisms through which exercise impacts atherogenesis, from molecular maladaptation to vascular remodeling. Here, we describe how preclinical research tools have and can be used to study exercise effects on atherosclerosis. We then propose how advanced bioengineering techniques can be used to address gaps in our current understanding of vascular pathophysiology, including integrating in vitro, in vivo, and in silico studies across multiple tissue systems and size scales. Improving our understanding of the antiatherogenic exercise effects will enable engaging, targeted, and individualized exercise recommendations to promote cardiovascular health rather than treating cardiovascular disease that results from a sedentary lifestyle.

A novel formulation for the study of the ascending aortic fluid dynamics with in vivo data

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by applying a rigid wall simplification, on the other side the FSI simulation requires a lot of assumptions for the material properties definition and high computational costs. The aim of this study is to investigate the feasibility of a new strategy, based on Radial Basis Functions (RBF) mesh morphing technique and transient simulations, able to introduce the patient-specific changes in aortic geometry during the cardiac cycle. Starting from medical images, aorta models at different phases of cardiac cycle were reconstructed and a transient shape deformation was obtained by proper activating incremental RBF solutions during the simulation process. The results, in terms of main hemodynamic parameters, were compared with two performed CFD simulations for the aortic model at minimum and maximum volume. Our implemented strategy copes the actual arterial variation during cardiac cycle with high accuracy, capturing the impact of geometrical variations on fluid dynamics, overcoming the complexity of a standard FSI approach.

Computational Hemodynamic Modeling of Arterial Aneurysms: A Mini-Review

Arterial aneurysms are pathological dilations of blood vessels, which can be of clinical concern due to thrombosis, dissection, or rupture. Aneurysms can form throughout the arterial system, including intracranial, thoracic, abdominal, visceral, peripheral, or coronary arteries. Currently, aneurysm diameter and expansion rates are the most commonly used metrics to assess rupture risk. Surgical or endovascular interventions are clinical treatment options, but are invasive and associated with risk for the patient. For aneurysms in locations where thrombosis is the primary concern, diameter is also used to determine the level of therapeutic anticoagulation, a treatment that increases the possibility of internal bleeding. Since simple diameter is often insufficient to reliably determine rupture and thrombosis risk, computational hemodynamic simulations are being developed to help assess when an intervention is warranted. Created from subject-specific data, computational models have the potential to be used to predict growth, dissection, rupture, and thrombus-formation risk based on hemodynamic parameters, including wall shear stress, oscillatory shear index, residence time, and anomalous blood flow patterns. Generally, endothelial damage and flow stagnation within aneurysms can lead to coagulation, inflammation, and the release of proteases, which alter extracellular matrix composition, increasing risk of rupture. In this review, we highlight recent work that investigates aneurysm geometry, model parameter assumptions, and other specific considerations that influence computational aneurysm simulations. By highlighting modeling validation and verification approaches, we hope to inspire future computational efforts aimed at improving our understanding of aneurysm pathology and treatment risk stratification.

Fluid-structure interaction simulations outperform computational fluid dynamics in the description of thoracic aorta haemodynamics and in the differentiation of progressive dilation in Marfan syndrome patients

Abnormal fluid dynamics at the ascending aorta may be at the origin of aortic aneurysms. This study was aimed at comparing the performance of computational fluid dynamics (CFD) and fluid-structure interaction (FSI) simulations against four-dimensional (4D) flow magnetic resonance imaging (MRI) data; and to assess the capacity of advanced fluid dynamics markers to stratify aneurysm progression risk. Eight Marfan syndrome (MFS) patients, four with stable and four with dilating aneurysms of the proximal aorta, and four healthy controls were studied. FSI and CFD simulations were performed with MRI-derived geometry, inlet velocity field and Young's modulus. Flow displacement, jet angle and maximum velocity evaluated from FSI and CFD simulations were compared to 4D flow MRI data. A dimensionless parameter, the shear stress ratio (SSR), was evaluated from FSI and CFD simulations and assessed as potential correlate of aneurysm progression. FSI simulations successfully matched MRI data regarding descending to ascending aorta flow rates (R 2 = 0.92) and pulse wave velocity (R 2 = 0.99). Compared to CFD, FSI simulations showed significantly lower percentage errors in ascending and descending aorta in flow displacement (-46% ascending, -41% descending), jet angle (-28% ascending, -50% descending) and maximum velocity (-37% ascending, -34% descending) with respect to 4D flow MRI. FSI- but not CFD-derived SSR differentiated between stable and dilating MFS patients. Fluid dynamic simulations of the thoracic aorta require fluid-solid interaction to properly reproduce complex haemodynamics. FSI- but not CFD-derived SSR could help stratifying MFS patients.

Computational Fluid Dynamics of Vascular Disease in Animal Models

Recent applications of computational fluid dynamics (CFD) applied to the cardiovascular system have demonstrated its power in investigating the impact of hemodynamics on disease initiation, progression, and treatment outcomes. Flow metrics such as pressure distributions, wall shear stresses (WSS), and blood velocity profiles can be quantified to provide insight into observed pathologies, assist with surgical planning, or even predict disease progression. While numerous studies have performed simulations on clinical human patient data, it often lacks prediagnosis information and can be subject to large intersubject variability, limiting the generalizability of findings. Thus, animal models are often used to identify and manipulate specific factors contributing to vascular disease because they provide a more controlled environment. In this review, we explore the use of CFD in animal models in recent studies to investigate the initiating mechanisms, progression, and intervention effects of various vascular diseases. The first section provides a brief overview of the CFD theory and tools that are commonly used to study blood flow. The following sections are separated by anatomical region, with the abdominal, thoracic, and cerebral areas specifically highlighted. We discuss the associated benefits and obstacles to performing CFD modeling in each location. Finally, we highlight animal CFD studies focusing on common surgical treatments, including arteriovenous fistulas (AVF) and pulmonary artery grafts. The studies included in this review demonstrate the value of combining CFD with animal imaging and should encourage further research to optimize and expand upon these techniques for the study of vascular disease.

Co-localization of microstructural damage and excessive mechanical strain at aortic branches in angiotensin-II-infused mice

Animal models of aortic aneurysm and dissection can enhance our limited understanding of the etiology of these lethal conditions particularly because early-stage longitudinal data are scant in humans. Yet, the pathogenesis of often-studied mouse models and the potential contribution of aortic biomechanics therein remain elusive. In this work, we combined micro-CT and synchrotron-based imaging with computational biomechanics to estimate in vivo aortic strains in the abdominal aorta of angiotensin-II-infused ApoE-deficient mice, which were compared with mouse-specific aortic microstructural damage inferred from histopathology. Targeted histology showed that the 3D distribution of micro-CT contrast agent that had been injected in vivo co-localized with precursor vascular damage in the aortic wall at 3 days of hypertension, with damage predominantly near the ostia of the celiac and superior mesenteric arteries. Computations similarly revealed higher mechanical strain in branching relative to non-branching regions, thus resulting in a positive correlation between high strain and vascular damage in branching segments that included the celiac, superior mesenteric, and right renal arteries. These results suggest a mechanically driven initiation of damage at these locations, which was supported by 3D synchrotron imaging of load-induced ex vivo delaminations of angiotensin-II-infused suprarenal abdominal aortas. That is, the major intramural delamination plane in the ex vivo tested aortas was also near side branches and specifically around the celiac artery. Our findings thus support the hypothesis of an early mechanically mediated formation of microstructural defects at aortic branching sites that subsequently propagate into a macroscopic medial tear, giving rise to aortic dissection in angiotensin-II-infused mice.

Strain Mapping From Four-Dimensional Ultrasound Reveals Complex Remodeling in Dissecting Murine Abdominal Aortic Aneurysms

Current in vivo abdominal aortic aneurysm (AAA) imaging approaches tend to focus on maximum diameter but do not measure three-dimensional (3D) vascular deformation or strain. Complex vessel geometries, heterogeneous wall compositions, and surrounding structures can all influence aortic strain. Improved understanding of complex aortic kinematics has the potential to increase our ability to predict aneurysm expansion and eventual rupture. Here, we describe a method that combines four-dimensional (4D) ultrasound and direct deformation estimation to compute in vivo 3D Green-Lagrange strain in murine angiotensin II-induced suprarenal dissecting aortic aneurysms, a commonly used small animal model. We compared heterogeneous patterns of the maximum, first-component 3D Green-Lagrange strain with vessel composition from mice with varying AAA morphologies. Intramural thrombus and focal breakage in the medial elastin significantly reduced aortic strain. Interestingly, a dissection that was not detected with high-frequency ultrasound also experienced reduced strain, suggesting medial elastin breakage that was later confirmed via histology. These results suggest that in vivo measurements of 3D strain can provide improved insight into aneurysm disease progression. While further work is needed with both preclinical animal models and human imaging studies, this initial murine study indicates that vessel strain should be considered when developing an improved metric for predicting aneurysm growth and rupture.

Sex-dependent differences in central artery haemodynamics in normal and fibulin-5 deficient mice: implications for ageing

Mouse models provide unique opportunities to study vascular disease, but they demand increased experimental and computational resolution. We describe a workflow for combining in vivo and in vitro biomechanical data to build mouse-specific computational models of the central vasculature including regional variations in biaxial wall stiffness, thickness and perivascular support. These fluid-solid interaction models are informed by micro-computed tomography imaging and in vivo ultrasound and pressure measurements, and include mouse-specific inflow and outflow boundary conditions. Hence, the model can capture three-dimensional unsteady flows and pulse wave characteristics. The utility of this experimental-computational approach is illustrated by comparing central artery biomechanics in adult wild-type and fibulin-5 deficient mice, a model of early vascular ageing. Findings are also examined as a function of sex. Computational results compare well with measurements and data available in the literature and suggest that pulse wave velocity, a spatially integrated measure of arterial stiffness, does not reflect well the presence of regional differences in stiffening, particularly those manifested in male versus female mice. Modelling results are also useful for comparing quantities that are difficult to measure or infer experimentally, including local pulse pressures at the renal arteries and characteristics of the peripheral vascular bed that may differ with disease.

Should We Ignore What We Cannot Measure? How Non-Uniform Stretch, Non-Uniform Wall Thickness and Minor Side Branches Affect Computational Aortic Biomechanics in Mice

In order to advance the state-of-the-art in computational aortic biomechanics, we investigated the influence of (i) a non-uniform wall thickness, (ii) minor aortic side branches and (iii) a non-uniform axial stretch distribution on the location of predicted hotspots of principal strain in a mouse model for dissecting aneurysms. After 3 days of angiotensin II infusion, a murine abdominal aorta was scanned in vivo with contrast-enhanced micro-CT. The animal was subsequently sacrificed and its aorta was scanned ex vivo with phase-contrast X-ray tomographic microscopy (PCXTM). An automatic morphing framework was developed to map the non-pressurized, non-stretched PCXTM geometry onto the pressurized, stretched micro-CT geometry. The output of the morphing model was a structural FEM simulation where the output strain distribution represents an estimation of the wall deformation, not only due to the pressurization, but also due to the local axial stretch field. The morphing model also included minor branches and a mouse-specific wall thickness. A sensitivity study was then performed to assess the influence of each of these novel features on the outcome of the simulations. The results were supported by comparing the computed hotspots of principal strain to hotspots of early vascular damage as detected on PCXTM. Non-uniform axial stretch, non-uniform wall thickness and minor subcostal arteries significantly alter the locations of calculated hotspots of maximal principal strain. Even if experimental data on these features are often not available in clinical practice, one should be aware of the important implications that simplifications in the model might have on the final simulated result.

Heterogeneous mechanics of the mouse pulmonary arterial network

Individualized modeling and simulation of blood flow mechanics find applications in both animal research and patient care. Individual animal or patient models for blood vessel mechanics are based on combining measured vascular geometry with a fluid structure model coupling formulations describing dynamics of the fluid and mechanics of the wall. For example, one-dimensional fluid flow modeling requires a constitutive law relating vessel cross-sectional deformation to pressure in the lumen. To investigate means of identifying appropriate constitutive relationships, an automated segmentation algorithm was applied to micro-computerized tomography images from a mouse lung obtained at four different static pressures to identify the static pressure-radius relationship for four generations of vessels in the pulmonary arterial network. A shape-fitting function was parameterized for each vessel in the network to characterize the nonlinear and heterogeneous nature of vessel distensibility in the pulmonary arteries. These data on morphometric and mechanical properties were used to simulate pressure and flow velocity propagation in the network using one-dimensional representations of fluid and vessel wall mechanics. Moreover, wave intensity analysis was used to study effects of wall mechanics on generation and propagation of pressure wave reflections. Simulations were conducted to investigate the role of linear versus nonlinear formulations of wall elasticity and homogeneous versus heterogeneous treatments of vessel wall properties. Accounting for heterogeneity, by parameterizing the pressure/distention equation of state individually for each vessel segment, was found to have little effect on the predicted pressure profiles and wave propagation compared to a homogeneous parameterization based on average behavior. However, substantially different results were obtained using a linear elastic thin-shell model than were obtained using a nonlinear model that has a more physiologically realistic pressure versus radius relationship.

Heart rate reduction with ivabradine promotes shear stress-dependent anti-inflammatory mechanisms in arteries

Blood flow generates wall shear stress (WSS) which alters endothelial cell (EC) function. Low WSS promotes vascular inflammation and atherosclerosis whereas high uniform WSS is protective. Ivabradine decreases heart rate leading to altered haemodynamics. Besides its cardio-protective effects, ivabradine protects arteries from inflammation and atherosclerosis via unknown mechanisms. We hypothesised that ivabradine protects arteries by increasing WSS to reduce vascular inflammation. Hypercholesterolaemic mice were treated with ivabradine for seven weeks in drinking water or remained untreated as a control. En face immunostaining demonstrated that treatment with ivabradine reduced the expression of pro-inflammatory VCAM-1 (p<0.01) and enhanced the expression of anti-inflammatory eNOS (p<0.01) at the inner curvature of the aorta. We concluded that ivabradine alters EC physiology indirectly via modulation of flow because treatment with ivabradine had no effect in ligated carotid arteries in vivo, and did not influence the basal or TNFα-induced expression of inflammatory (VCAM-1, MCP-1) or protective (eNOS, HMOX1, KLF2, KLF4) genes in cultured EC. We therefore considered whether ivabradine can alter WSS which is a regulator of EC inflammatory activation. Computational fluid dynamics demonstrated that ivabradine treatment reduced heart rate by 20 % and enhanced WSS in the aorta. In conclusion, ivabradine treatment altered haemodynamics in the murine aorta by increasing the magnitude of shear stress. This was accompanied by induction of eNOS and suppression of VCAM-1, whereas ivabradine did not alter EC that could not respond to flow. Thus ivabradine protects arteries by altering local mechanical conditions to trigger an anti-inflammatory response.

Ascending Aortic Aneurysm in Angiotensin II-Infused Mice: Formation, Progression, and the Role of Focal Dissections

OBJECTIVE

To understand the anatomy and physiology of ascending aortic aneurysms in angiotensin II-infused ApoE(-/-) mice.

APPROACH AND RESULTS

We combined an extensive in vivo imaging protocol (high-frequency ultrasound and contrast-enhanced microcomputed tomography at baseline and after 3, 10, 18, and 28 days of angiotensin II infusion) with synchrotron-based ultrahigh resolution ex vivo imaging (phase contrast X-ray tomographic microscopy) in n=47 angiotensin II-infused mice and 6 controls. Aortic regurgitation increased significantly over time, as did the luminal volume of the ascending aorta. In the samples that were scanned ex vivo, we observed one or several focal dissections, with the largest located in the outer convex aspect of the ascending aorta. The volume of the dissections moderately correlated to the volume of the aneurysm as measured in vivo (r(2)=0.46). After 3 days of angiotensin II infusion, we found an interlaminar hematoma in 7/12 animals, which could be linked to an intimal tear. There was also a significant increase in single laminar ruptures, which may have facilitated a progressive enlargement of the focal dissections over time. At later time points, the hematoma was resorbed and the medial and adventitial thickness increased. Fatal transmural dissection occurred in 8/47 mice at an early stage of the disease, before adventita remodeling.

CONCLUSIONS

We visualized and quantified the dissections that lead to ascending aortic aneurysms in angiotensin II-infused mice and provided unique insight into the temporal evolution of these lesions.

A Review of Computational Methods to Predict the Risk of Rupture of Abdominal Aortic Aneurysms

Computational methods have played an important role in health care in recent years, as determining parameters that affect a certain medical condition is not possible in experimental conditions in many cases. Computational fluid dynamics (CFD) methods have been used to accurately determine the nature of blood flow in the cardiovascular and nervous systems and air flow in the respiratory system, thereby giving the surgeon a diagnostic tool to plan treatment accordingly. Machine learning or data mining (MLD) methods are currently used to develop models that learn from retrospective data to make a prediction regarding factors affecting the progression of a disease. These models have also been successful in incorporating factors such as patient history and occupation. MLD models can be used as a predictive tool to determine rupture potential in patients with abdominal aortic aneurysms (AAA) along with CFD-based prediction of parameters like wall shear stress and pressure distributions. A combination of these computer methods can be pivotal in bridging the gap between translational and outcomes research in medicine. This paper reviews the use of computational methods in the diagnosis and treatment of AAA.