Biomechanical characterization of abdominal aortic aneurysms (AAAs) has become commonplace in rupture risk assessment studies. However, its translation to the clinic has been greatly limited due to the complexity associated with its tools and their implementation. The unattainability of patient-specific tissue properties leads to the use of generalized population-averaged material models in finite element analyses, which adds a degree of uncertainty to the wall mechanics quantification. In addition, computational fluid dynamics modeling of AAA typically lacks the patient-specific inflow and outflow boundary conditions that should be obtained by nonstandard of care clinical imaging. An alternative approach for analyzing AAA flow and sac volume changes is to conduct in vitro experiments in a controlled laboratory environment. In this study, we designed, built, and characterized quantitatively a benchtop flow loop using a deformable AAA silicone phantom representative of a patient-specific geometry. The impedance modules, which are essential components of the flow loop, were fine-tuned to ensure typical intraluminal pressure conditions within the AAA sac. The phantom was imaged with a magnetic resonance imaging (MRI) scanner to acquire time-resolved images of the moving wall and the velocity field inside the sac. Temporal AAA sac volume changes lead to a corresponding variation in compliance throughout the cardiac cycle. The primary outcome of this work was the design optimization of the impedance elements, the quantitative characterization of the resistive and capacitive attributes of a compliant AAA phantom, and the exemplary use of MRI for flow visualization and quantification of the deformed AAA geometry.

Myocardial bridging (MB) and coronary atherosclerotic stenosis can impair coronary blood flow and may cause myocardial ischemia or even heart attack. It remains unclear how MB and stenosis are similar or different regarding their impacts on coronary hemodynamics. The purpose of this study was to compare the hemodynamic effects of coronary stenosis and MB using experimental and computational fluid dynamics (CFD) approaches. For CFD modeling, three MB patients with different levels of lumen obstruction, mild, moderate, and severe were selected. Patient-specific left anterior descending (LAD) coronary artery models were reconstructed from biplane angiograms. For each MB patient, the virtually healthy and stenotic models were also simulated for comparison. In addition, an in vitro flow-loop was developed, and the pressure drop was measured for comparison. The CFD simulations results demonstrated that the difference between MB and stenosis increased with increasing MB/stenosis severity and flowrate. Experimental results showed that increasing the MB length (by 140%) only had significant impact on the pressure drop in the severe MB (39% increase at the exercise), but increasing the stenosis length dramatically increased the pressure drop in both moderate and severe stenoses at all flow rates (31% and 93% increase at the exercise, respectively). Both CFD and experimental results confirmed that the MB had a higher maximum and a lower mean pressure drop in comparison with the stenosis, regardless of the degree of lumen obstruction. A better understanding of MB and atherosclerotic stenosis may improve the therapeutic strategies in coronary disease patients and prevent acute coronary syndromes.

In this work, we provide a quantitative assessment of the biomechanical and geometric features that characterize abdominal aortic aneurysm (AAA) models generated from 19 Asian and 19 Caucasian diameter-matched AAA patients. 3D patient-specific finite element models were generated and used to compute peak wall stress (PWS), 99th percentile wall stress (99th WS), and spatially averaged wall stress (AWS) for each AAA. In addition, 51 global geometric indices were calculated, which quantify the wall thickness, shape, and curvature of each AAA. The indices were correlated with 99th WS (the only biomechanical metric that exhibited significant association with geometric indices) using Spearman's correlation and subsequently with multivariate linear regression using backward elimination. For the Asian AAA group, 99th WS was highly correlated (R 2 = 0.77) with three geometric indices, namely tortuosity, intraluminal thrombus volume, and area-averaged Gaussian curvature. Similarly, 99th WS in the Caucasian AAA group was highly correlated (R 2 = 0.87) with six geometric indices, namely maximum AAA diameter, distal neck diameter, diameter–height ratio, minimum wall thickness variance, mode of the wall thickness variance, and area-averaged Gaussian curvature. Significant differences were found between the two groups for ten geometric indices; however, no differences were found for any of their respective biomechanical attributes. Assuming maximum AAA diameter as the most predictive metric for wall stress was found to be imprecise: 24% and 28% accuracy for the Asian and Caucasian groups, respectively. This investigation reveals that geometric indices other than maximum AAA diameter can serve as predictors of wall stress, and potentially for assessment of aneurysm rupture risk, in the Asian and Caucasian AAA populations.

Trabeculae carneae are irregular structures that cover the endocardial surfaces of both ventricles and account for a significant portion of human ventricular mass. The role of trabeculae carneae in diastolic and systolic functions of the left ventricle (LV) is not well understood. Thus, the objective of this study was to investigate the functional role of trabeculae carneae in the LV. Finite element (FE) analyses of ventricular functions were conducted for three different models of human LV derived from high-resolution magnetic resonance imaging (MRI). The first model comprised trabeculae carneae and papillary muscles, while the second model had papillary muscles and partial trabeculae carneae, and the third model had a smooth endocardial surface. We customized these patient-specific models with myofiber architecture generated with a rule-based algorithm, diastolic material parameters of Fung strain energy function derived from biaxial tests and adjusted with the empirical Klotz relationship, and myocardial contractility constants optimized for average normal ejection fraction (EF) of the human LV. Results showed that the partial trabeculae cutting model had enlarged end-diastolic volume (EDV), reduced wall stiffness, and even increased end-systolic function, indicating that the absence of trabeculae carneae increased the compliance of the LV during diastole, while maintaining systolic function.

The maximum diameter (MD) criterion is the most important factor when predicting risk of rupture of abdominal aortic aneurysms (AAAs). An elevated wall stress has also been linked to a high risk of aneurysm rupture, yet is an uncommon clinical practice to compute AAA wall stress. The purpose of this study is to assess whether other characteristics of the AAA geometry are statistically correlated with wall stress. Using in-house segmentation and meshing algorithms, 30 patient-specific AAA models were generated for finite element analysis (FEA). These models were subsequently used to estimate wall stress and maximum diameter and to evaluate the spatial distributions of wall thickness, cross-sectional diameter, mean curvature, and Gaussian curvature. Data analysis consisted of statistical correlations of the aforementioned geometry metrics with wall stress for the 30 AAA inner and outer wall surfaces. In addition, a linear regression analysis was performed with all the AAA wall surfaces to quantify the relationship of the geometric indices with wall stress. These analyses indicated that while all the geometry metrics have statistically significant correlations with wall stress, the local mean curvature (LMC) exhibits the highest average Pearson's correlation coefficient for both inner and outer wall surfaces. The linear regression analysis revealed coefficients of determination for the outer and inner wall surfaces of 0.712 and 0.516, respectively, with LMC having the largest effect on the linear regression equation with wall stress. This work underscores the importance of evaluating AAA mean wall curvature as a potential surrogate for wall stress.

An abdominal aortic aneurysm (AAA) is a permanent focal dilatation of the abdominal aorta of at least 1.5 times its normal diameter. Although the criterion of maximum diameter is still used in clinical practice to decide on a timely intervention, numerical studies have demonstrated the importance of other geometric factors. However, the major drawback of numerical studies is that they must be validated experimentally before clinical implementation. This work presents a new methodology to verify wall stress predicted from the numerical studies against the experimental testing. To this end, four AAA phantoms were manufactured using vacuum casting. The geometry of each phantom was subject to microcomputed tomography (μCT) scanning at zero and three other intraluminal pressures: 80, 100, and 120 mm Hg. A zero-pressure geometry algorithm was used to calculate the wall stress in the phantom, while the numerical wall stress was calculated with a finite-element analysis (FEA) solver based on the actual zero-pressure geometry subjected to 80, 100, and 120 mm Hg intraluminal pressure loading. Results demonstrate the moderate accuracy of this methodology with small relative differences in the average wall stress (1.14%). Additionally, the contribution of geometric factors to the wall stress distribution was statistically analyzed for the four phantoms. The results showed a significant correlation between wall thickness and mean curvature (MC) with wall stress.

In this work, we present a novel method for the derivation of the unloaded geometry of an abdominal aortic aneurysm (AAA) from a pressurized geometry in turn obtained by 3D reconstruction of computed tomography (CT) images. The approach was experimentally validated with an aneurysm phantom loaded with gauge pressures of 80, 120, and 140 mm Hg. The unloaded phantom geometries estimated from these pressurized states were compared to the actual unloaded phantom geometry, resulting in mean nodal surface distances of up to 3.9% of the maximum aneurysm diameter. An in-silico verification was also performed using a patient-specific AAA mesh, resulting in maximum nodal surface distances of 8 μ m after running the algorithm for eight iterations. The methodology was then applied to 12 patient-specific AAA for which their corresponding unloaded geometries were generated in 5–8 iterations. The wall mechanics resulting from finite element analysis of the pressurized (CT image-based) and unloaded geometries were compared to quantify the relative importance of using an unloaded geometry for AAA biomechanics. The pressurized AAA models underestimate peak wall stress (quantified by the first principal stress component) on average by 15% compared to the unloaded AAA models. The validation and application of the method, readily compatible with any finite element solver, underscores the importance of generating the unloaded AAA volume mesh prior to using wall stress as a biomechanical marker for rupture risk assessment.

To quantify the transport and adhesion of drug particles in a complex vascular environment, computational fluid particle dynamics (CFPD) simulations of blood flow and drug particulate were conducted in three different geometries representing the human lung vasculature for steady and pulsatile flow conditions. A fully developed flow profile was assumed as the inlet velocity, and a lumped mathematical model was used for the calculation of the outlet pressure boundary condition. A receptor–ligand model was used to simulate the particle binding probability. The results indicate that bigger particles have lower deposition fraction due to less chance of successful binding. Realistic unsteady flow significantly accelerates the binding activity over a wide range of particle sizes and also improves the particle deposition fraction in bifurcation regions when comparing with steady flow condition. Furthermore, surface imperfections and geometrical complexity coupled with the pulsatility effect can enhance fluid mixing and accordingly particle binding efficiency. The particle binding density at bifurcation regions increases with generation order and drug carriers are washed away faster in steady flow. Thus, when studying drug delivery mechanism in vitro and in vivo, it is important to take into account blood flow pulsatility in realistic geometry. Moreover, tissues close to bifurcations are more susceptible to deterioration due to higher uptake.

Skin wounds and burns compromise the body's natural barrier to bacteria and other pathogens. While many forms of wound dressings are available, polymeric films are advantageous for various reasons, ranging from the ease of application to durability. One common drawback of using polymeric films for a wound bandage is that the films tend to adhere to common inanimate objects. Patients spend hours in contact with soft and hard materials pressed against their skin, which, if the skin was dressed with a polymeric film, would inflict further wound damage upon body movement. In this work, we present a novel technique that allowed for measuring polymeric tackiness, after a long incubation period, with materials regularly encountered in a hospital or home setting, and soft fabrics. The polymers were exposed to an environment intended to simulate daily conditions and the technique is designed to perform multiple experiments simultaneously with ease. Four commercially available polymers (new-skin, no-sting skin-prep, skin shield, and Silesse) were tested as proof-of-concept to gather preliminary data for an overall assessment of wound treatment efficacy, resulting in the estimation of pull-off stress of the polymers from a specimen of porcine skin. Silesse did not reveal a measurable tackiness, no-sting skin-prep had the highest mean tackiness (13.8 kPa), while the mean tackiness between new-skin and skin shield was approximately equal (9.8 kPa vs. 10.1 kPa, respectively), p = 0.05. Future work on polymeric fluids for wound dressing applications should include tensile stress and dynamic viscosity estimations.

The pathology of the human abdominal aortic aneurysm (AAA) and its relationship to the later complication of intraluminal thrombus (ILT) formation remains unclear. The hemodynamics in the diseased abdominal aorta are hypothesized to be a key contributor to the formation and growth of ILT. The objective of this investigation is to establish a reliable 3D flow visualization method with corresponding validation tests with high confidence in order to provide insight into the basic hemodynamic features for a better understanding of hemodynamics in AAA pathology and seek potential treatment for AAA diseases. A stereoscopic particle image velocity (PIV) experiment was conducted using transparent patient-specific experimental AAA models (with and without ILT) at three axial planes. Results show that before ILT formation, a 3D vortex was generated in the AAA phantom. This geometry-related vortex was not observed after the formation of ILT, indicating its possible role in the subsequent appearance of ILT in this patient. It may indicate that a longer residence time of recirculated blood flow in the aortic lumen due to this vortex caused sufficient shear-induced platelet activation to develop ILT and maintain uniform flow conditions. Additionally, two computational fluid dynamics (CFD) modeling codes (Fluent and an in-house cardiovascular CFD code) were compared with the two-dimensional, three-component velocity stereoscopic PIV data. Results showed that correlation coefficients of the out-of-plane velocity data between PIV and both CFD methods are greater than 0.85, demonstrating good quantitative agreement. The stereoscopic PIV study can be utilized as test case templates for ongoing efforts in cardiovascular CFD solver development. Likewise, it is envisaged that the patient-specific data may provide a benchmark for further studying hemodynamics of actual AAA, ILT, and their convolution effects under physiological conditions for clinical applications.

The goal of this work is to develop a framework for manufacturing nonuniform wall thickness replicas of abdominal aortic aneurysms (AAAs). The methodology was based on the use of computed tomography (CT) images for virtual modeling, additive manufacturing for the initial physical replica, and a vacuum casting process and range of polyurethane resins for the final rubberlike phantom. The average wall thickness of the resulting AAA phantom was compared with the average thickness of the corresponding patient-specific virtual model, obtaining an average dimensional mismatch of 180 μm (11.14%). The material characterization of the artery was determined from uniaxial tensile tests as various combinations of polyurethane resins were chosen due to their similarity with ex vivo AAA mechanical behavior in the physiological stress configuration. The proposed methodology yields AAA phantoms with nonuniform wall thickness using a fast and low-cost process. These replicas may be used in benchtop experiments to validate deformations obtained with numerical simulations using finite element analysis, or to validate optical methods developed to image ex vivo arterial deformations during pressure-inflation testing.