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Pulmonary arterial hypertension (PAH) is associated with elevated pulmonary arterial pressure. PAH prognosis remains poor with 15% mortality rate within 1 year, even with modern clinical management. Previous clinical studies proposed wall shear stress (WSS) to be an important hemodynamic factor affecting cell mechanotransduction, growth and remodeling, and disease progress in PAH. However, WSS in vivo is typically at most 2.5 Pa and a doubt has been cast whether WSS alone can drive disease progress. Furthermore, our current understanding of PAH pathology largely comes from small animals' studies in which caliber enlargement, a hallmark of PAH in humans, is rarely reported. Therefore, a large-animal experiment on pulmonary arteries (PAs) is needed to validate whether increased pressure can induce enlargement of PAs caliber. In this study, we use an inflation testing device to characterize the mechanical behavior, both nonlinear elastic behavior and irreversible damage of porcine arteries. The parameters of elastic behavior are estimated from the inflation test at a low-pressure range before and after over-pressurization. Then, histological images are qualitatively examined for medial and adventitial layers. This study sheds light on the relevance of pressure-induced damage mechanism in human PAH. This article is protected by copyright. All rights reserved.

The intraluminal thrombus (ILT) has been shown to negatively impact the progression of the abdominal aortic aneurysms (AAAs). The formation of this thrombus layer has been connected to the local flow environment within AAAs, but the specific mechanisms leading to thrombus formation are still not fully understood. Our study investigated the association between vortical structures, near-wall hemodynamic metrics (e.g., time averaged wall shear stress (TAWSS) and oscillatory shear index (OSI)), and ILT accumulation in a longitudinal cohort of 14 AAAs (53 scans total). Vortices and hemodynamic parameters were estimated using hemodynamic simulations performed to each scan of each patient and compared to local 3D changes of ILT thickness between two consecutive scans (∆ILT). Results showed that vortices formed and remained strong and close to the lumen surface in AAAs without an ILT, while in AAAs with ILTs these detached from the lumen surface and dissipated nearby wall region where an increase in ILT thickness was observed. Although low TAWSS was observed in regions with and without ILT accumulation, an inverse correlation between ∆ILT and TAWSS was observed within the regions that experienced a thrombus growth. Our results support the idea that vortical structures might be playing a role modulating ILT accumulation into specific wall regions. Also, it submits the idea that the low TAWSS will be modulating the growth of thrombus within these preferred ILT accumulated regions. This article is protected by copyright. All rights reserved.

Translating recent advances in abdominal aortic aneurysm (AAA) growth and remodeling (G&R) knowledge into a predictive, patient-specific clinical treatment tool requires a major paradigm shift in computational modelling. The objectives of this study are to develop a prediction framework that 1) first calibrates the physical AAA G&R model using patient-specific serial computed tomography (CT) scan images, 2) predicts the expansion of an AAA in the future, and 3) quantifies the associated uncertainty in the prediction. We adopt a Bayesian calibration method to calibrate parameters in the G&R computational model and predict the magnitude of AAA expansion. The proposed Bayesian approach can take different sources of uncertainty; therefore, it is well suited to achieve our aims in predicting the AAA expansion process as well as in computing the propagated uncertainty. We demonstrate how to achieve the proposed aims by solving the formulated Bayesian calibration problems for cases with the synthetic G&R model output data and real medical patient-specific CT data. We compare and discuss the performance of predictions and computation time under different sampling cases of the model output data and patient data, both of which are simulated by the G&R computation. Furthermore, we apply our Bayesian calibration to real patient-specific serial CT data and validate our prediction. The accuracy and efficiency of the proposed method is promising, which appeals to computational and medical communities.

Objective: We propose a novel approach to predict the Abdominal Aortic Aneurysm (AAA) growth in future time, using longitudinal computer tomography (CT) scans of AAAs that are captured at different times in a patient-specific way. Methods : We adopt a formulation that considers a surface of the AAA as a manifold embedded in a scalar field over the three dimensional (3D) space. For this formulation, we develop our Dynamical Gaussian Process Implicit Surface (DGPIS) model based on observed surfaces of 3D AAAs as visible variables while the scalar fields are hidden . In particular, we use Gaussian process regression to construct the field as an observation model from CT training image data. We then learn a dynamic model to represent the evolution of the field. Finally, we derive the predicted AAA surface from the predicted field along with uncertainty quantified in future time. Results : A dataset of 7 subjects (4–7 scans) was collected and used to evaluate the proposed method by comparing its prediction Hausdorff distance errors against those of simple extrapolation. In addition, we evaluate the prediction results with respect to a conventional shape analysis technique such as Principal Component Analysis (PCA). All comparative results show the superior prediction performance of the proposed approach. Conclusion : We introduce a novel approach to predict the AAA growth and its predicted uncertainty in future time, using longitudinal CT scans in a patient-specific fashion. Significance: The capability to predict the AAA shape and its confidence region by our approach establish the potential for guiding clinicians with informed decision in conducting medical treatment and monitoring of AAAs.

Pulmonary hypertension (PH) is one of the least understood and highly elusive cardiovascular conditions associated with elevated pulmonary arterial pressure. Although the disease mechanisms are not completely understood, evidence has accumulated from human and animal studies that irreversible processes of pulmonary arterial wall damage, compensated by stress-mediated growth, play critical roles in eliciting the mechanisms of disease progression. The aim of this study is to develop a thermodynamic modeling structure of the pulmonary artery to consider coupled plastic-degradation-growth irreversible processes to investigate the mechanical roles of the dissipative phenomena in the disease progression. The proposed model performs a model parameter study of plastic deformation and degradation processes coupled with dissipative growth subjected to elevated pulmonary arterial pressure and computationally generates in silico simulations of PH progression using the clinical features of PH, found in human morphological and mechanical data. The results show that considering plastic deformation can provide a much better fitting of the ex vivo inflation tests than a widely used pure hyperelastic model in higher pressure conditions. In addition, the parameter sensitivity study illustrates that arterial damage and growth cause the increased stiffness, and the full simulation (combining elastic-plastic-degradation-growth models) reveals a key postpathological recovery process of compensating vessel damage by vascular adaptation by reducing the rate of vessel dilation and mediating vascular wall stress. Finally, the simulation results of luminal enlargement, arterial thickening, and arterial stiffness for an anisotropic growth are found to be close to the values from the literature.

Microstructural changes in the pulmonary arteries associated with pulmonary arterial hypertension (PAH) is not well understood and characterized in humans. To address this issue, we developed and applied a patient-specific inverse finite element (FE) modeling framework to characterize mechanical and structural changes of the micro-constituents in the proximal pulmonary arteries using in-vivo pressure measurements and magnetic resonance images. The framework was applied using data acquired from a pediatric PAH patient and a heart transplant patient with normal pulmonary arterial pressure, which serves as control. Parameters of a constrained mixture model that are associated with the structure and mechanical properties of elastin, collagen fibers and smooth muscle cells were optimized to fit the patient-specific pressure-diameter responses of the main pulmonary artery. Based on the optimized parameters, individual stress and linearized stiffness resultants of the three tissue constituents, as well as their aggregated values, were estimated in the pulmonary artery. Aggregated stress resultant and stiffness are, respectively, 4.6 and 3.4 times higher in the PAH patient than the control subject. Stress and stiffness resultants of each tissue constituent are also higher in the PAH patient. Specifically, the mean stress resultant is highest in elastin (PAH: 69.96, control: 14.42 kPa-mm), followed by those in smooth muscle cell (PAH: 13.95, control: 4.016 kPa-mm) and collagen fibers (PAH: 13.19, control: 2.908 kPa-mm) in both the PAH patient and the control subject. This result implies that elastin may be the key load-bearing constituent in the pulmonary arteries of the PAH patient and the control subject.

Growth is a significant factor that results in deformations of tubular organs, and particular deformations associated with growth enable tubular organs to perform certain physiological functions. Configuring growth profiles that achieve particular deformation patterns is critical for analyzing potential pathological conditions and for developing corresponding clinical treatments for tubular organ dysfunctions. However, deformation-targeted growth is rarely studied. In this article, the human cervix during pregnancy is studied as an example to show how cervical thinning and dilation are generated by growth. An advanced hyperelasticity theory called morphoelasticity is employed to model the deformations, and a growth tensor is used to represent growth in three principle directions. The computational results demonstrate that both negative radial growth and positive circumferential growth facilitate thinning and dilation. Modeling such mixed growth represents an advancement beyond commonly used uniform growth inside tissues to study tubular deformations. The results reveal that complex growth may occur inside tissues to achieve certain tubular deformations. Integration of further biochemical and cellular activities that initiate and mediate such complex growth remains to be explored.

Vascular wall stiffness and hemodynamic parameters are potential biomechanical markers for detecting pulmonary arterial hypertension (PAH). Previous computational analyses, however, have not considered the interaction between blood flow and wall deformation. Here, we applied an established computational framework that utilizes patient-specific measurements of hemodynamics and wall deformation to analyze the coupled fluid–vessel wall interaction in the proximal pulmonary arteries (PA) of six PAH patients and five control subjects. Specifically, we quantified the linearized stiffness (E), relative area change (RAC), diastolic diameter (D), regurgitant flow, and time-averaged wall shear stress (TAWSS) of the proximal PA, as well as the total arterial resistance (Rt) and compliance (Ct) at the distal pulmonary vasculature. Results found that the average proximal PA was stiffer [median: 297 kPa, interquartile range (IQR): 202 kPa vs. median: 75 kPa, IQR: 5 kPa; P = 0.007] with a larger diameter (median: 32 mm, IQR: 5.25 mm vs. median: 25 mm, IQR: 2 mm; P = 0.015) and a reduced RAC (median: 0.22, IQR: 0.10 vs. median: 0.42, IQR: 0.04; P = 0.004) in PAH compared to our control group. Also, higher total resistance (Rt; median: 6.89 mmHg × min/l, IQR: 2.16 mmHg × min/l vs. median: 3.99 mmHg × min/l, IQR: 1.15 mmHg × min/l; P = 0.002) and lower total compliance (Ct; median: 0.13 ml/mmHg, IQR: 0.15 ml/mmHg vs. median: 0.85 ml/mmHg, IQR: 0.51 ml/mmHg; P = 0.041) were observed in the PAH group. Furthermore, lower TAWSS values were seen at the main PA arteries (MPAs) of PAH patients (median: 0.81 Pa, IQR: 0.47 Pa vs. median: 1.56 Pa, IQR: 0.89 Pa; P = 0.026) compared to controls. Correlation analysis within the PAH group found that E was directly correlated to the PA regurgitant flow (r = 0.84, P = 0.018) and inversely related to TAWSS (r = −0.72, P = 0.051). Results suggest that the estimated elastic modulus E may be closely related to PAH hemodynamic changes in pulmonary arteries.

ObjectiveThe maximum diameter measurement of an abdominal aortic aneurysm (AAA), which depends on orthogonal and axial cross-sections or maximally inscribed spheres within the AAA, plays a significant role in the clinical decision making process. This study aims to build a large dataset of morphological parameters from longitudinal CT scans and analyze their correlations. Furthermore, this work explores the existence of a “master curve” of AAA growth, and tests which parameters serve to enhance its predictability for clinical use.Methods106 CT scan images from 25 Korean AAA patients were retrospectively obtained. We subsequently computed morphological parameters, growth rates, and pair-wise correlations, and attempted to enhance the predictability of the growth for high-risk aneurysms using non-linear curve fitting and least-square minimization.ResultsAn exponential AAA growth model was fitted to the maximum spherical diameter, as the best representative of the growth among all parameters (r-square: 0.985) and correctly predicted to 74 of 79 scans based on a 95% confidence interval. AAA volume expansion rateswere highly correlated (r=0.80) with thrombus accumulation rates.ConclusionsThe exponential growth model using spherical diameter provides useful information about progression of aneurysm size and enables AAA growth rate extrapolation during a given surveillance period.

Coronary autoregulation is a short-term response manifested by a relatively constant flow over a wide range of perfusion pressures for a given metabolic state. This phenomenon is thought to be facilitated through a combination of mechanisms, including myogenic, shear dependent, and metabolic controls. The study of coronary autoregulation is challenging due to the coupled nature of the mechanisms and their differential effects through the coronary tree. In this paper, we developed a novel framework to study coronary autoregulation based on the constrained mixture theory. This structurally-motivated autoregulation model required calibration of anatomical and structural parameters of coronary trees via a homeostatic optimization approach using extensive literature data. Autoregulation was then simulated for two different coronary trees: subepicardial and subendocardial. The structurally calibrated model reproduced available baseline hemodynamics and autoregulation data for each coronary tree. The autoregulation analysis showed that the diameter of the intermediate and small arterioles varies the most in response to changes in perfusion pressure. Finally, we demonstrated the utility of the model in two application examples: 1) response to drops in epicardial pressure, and 2) response to drug infusion in the coronary arteries. The proposed structurally-motivated model could be extended to study long-term growth and remodeling in the coronary circulation in response to hypertension, atherosclerosis, etc.Key pointsCoronary autoregulation is defined as the capability of the coronary circulation to maintain the blood supply to the heart over a range of perfusion pressures. This phenomenon is facilitated through intrinsic mechanisms that control the vascular resistance by regulating the mechanical function of smooth muscle cells. Understanding the mechanisms involved in coronary autoregulation is one of the most fundamental questions in coronary physiology.This paper presents a structurally-motivated coronary autoregulation model that uses a nonlinear continuum mechanics approach to account for the morphometry and vessel wall composition in two coronary trees in the subepicardial and subendocardial layers.The model is calibrated against diverse experimental data from literature and is used to study heterogeneous autoregulatory response in the coronary trees. This model drastically differs from previous models, which relied on lumped parameter model formulations, and is suited to the study of long-term pathophysiological growth and remodeling phenomena in coronary vessels.

Objective To investigate the relationship between the characteristics of intraluminal thrombus (ILT) with abdominal aortic aneurysm (AAA) expansion. Methods This retrospective clinical study applied homogeneous multistate continuous-time Markov chain models to longitudinal computed tomography (CT) data from Korean patients with AAA. Four AAA states were considered (early, mild, severe, fatal) and the maximal thickness of the ILT (maxILT), the fraction of the wall area covered by the ILT (areafrac) and the fraction of ILT volume (volfrac) were used as covariates. Results The analysis reviewed longitudinal CT images from 26 patients. Based on likelihood-ratio statistics, the areafrac was the most significant biomarker and maxILT was the second most significant. In addition, within AAAs that developed an ILT layer, the analysis found that the AAA expands relatively quickly during the early stage but the rate of expansion reduces once the AAA has reached a larger size. Conclusion The results recommend surgical intervention when a patient has an areafrac more than 60%. Although this recommendation should be considered with caution given the limited sample size, physicians can use the proposed model as a tool to find such recommendations with their own data.

Pulmonary arterial hypertension (PAH) is a disease characterized by an elevated pulmonary arterial (PA) pressure. While several computational hemodynamic models of the pulmonary vasculature have been developed to understand PAH, they are lacking in some aspects, such as the vessel wall deformation and its lack of calibration against measurements in humans. Here, we describe a computational modeling framework that addresses these limitations. Specifically, computational models describing the coupling of hemodynamics and vessel wall mechanics in the pulmonary vasculature of a PAH patient and a normal subject were developed. Model parameters, consisting of linearized stiffness E of the large vessels and Windkessel parameters for each outflow branch, were calibrated against in vivo measurements of pressure, flow and vessel wall deformation obtained, respectively, from right-heart catheterization, phase-contrast and cine magnetic resonance images. Calibrated stiffness E of the proximal PA was 2.0 and 0.5 MPa for the PAH and normal models, respectively. Calibrated total compliance C T and resistance R T of the distal vessels were, respectively, 0.32 ml/mmHg and 11.3 mmHg∗min/l for the PAH model, and 2.93 ml/mmHg and 2.6 mmHg∗min/l for the normal model. These results were consistent with previous findings that the pulmonary vasculature is stiffer with more constricted distal vessels in PAH patients. Individual effects on PA pressure due to remodeling of the distal and proximal compartments of the pulmonary vasculature were also investigated in a sensitivity analysis. The analysis suggests that the remodeling of distal vasculature contributes more to the increase in PA pressure than the remodeling of proximal vasculature.

Ventricular-arterial coupling plays a key role in the physiologic function of the cardiovascular system. We have previously described a hybrid lumped-finite element (FE) modeling framework of the systemic circulation that couples idealized FE models of the aorta and the left ventricle (LV). Here, we describe an extension of the lumped-FE modeling framework that couples patient-specific FE models of the left and right ventricles, aorta and the large pulmonary arteries in both the systemic and pulmonary circulations. Geometries of the FE models were reconstructed from magnetic resonance (MR) images acquired in a pediatric patient diagnosed with pulmonary arterial hypertension (PAH). The modeling framework was calibrated with pressure waveforms acquired in the heart and arteries by catheterization as well as ventricular volume and arterial diameter waveforms measured from MR images. The calibrated model hemodynamic results match well with the clinically-measured waveforms (volume and pressure) in the LV and right ventricle (RV) as well as with the clinically-measured waveforms (pressure and diameter) in the aorta and main pulmonary artery. The calibrated framework was then used to simulate three cases, namely, (1) an increase in collagen in the large pulmonary arteries, (2) a decrease in RV contractility, and (3) an increase in the total pulmonary arterial resistance, all characteristics of progressive PAH. The key finding from these simulations is that hemodynamics of the pulmonary vasculature and RV wall stress are more sensitive to vasoconstriction with a 10% of reduction in the lumen diameter of the distal vessels than a 67% increase in the proximal vessel's collagen mass.

An abdominal aortic aneurysm (AAA) is a gradual enlargement of the aorta that can cause a life-threatening event when a rupture occurs. Aneurysmal geometry has been proved to be a critical factor in determining when to surgically treat AAAs, but, it is challenging to predict the patient-specific evolution of an AAA with biomechanical or statistical models. The recent success of deep learning in biomedical engineering shows promise for predictive medicine. However, a deep learning model requires a large dataset, which limits its application to the prediction of the patient-specific AAA expansion. In order to cope with the limited medical follow-up dataset of AAAs, a novel technique combining a physical computational model with a deep learning model is introduced to predict the evolution of AAAs. First, a vascular Growth and Remodeling (G&R) computational model, which is able to capture the variations of actual patient AAA geometries, is employed to generate a limited in silico dataset. Second, the Probabilistic Collocation Method (PCM) is employed to reproduce a large in silico dataset by approximating the G&R simulation outputs. A Deep Belief Network (DBN) is then trained to provide fast predictions of patient-specific AAA expansion, using both in silico data and patients' follow-up data. Follow-up Computer Tomography (CT) scan images from 20 patients are employed to demonstrate the effectiveness and the feasibility of the proposed model. The test results show that the DBN is able to predict the enlargements of AAAs with an average relative error of 3.1%, which outperforms the classical mixed-effect model by 65%.

Objective For small abdominal aortic aneurysms (AAAs), a regular follow-up examination is recommended every 12 months for AAAs of 30–39 mm and every six months for AAAs of 40–55 mm. Follow-up diameters can determine if a patient follows the common growth model of the population. However, the rapid expansion of an AAA, often associated with higher rupture risk, may be overlooked even though it requires surgical intervention. Therefore, the prognosis of abdominal aortic aneurysm growth is clinically important for planning treatment. This study aims to build enhanced Bayesian inference methods to predict maximum aneurysm diameter. Methods 106 CT scans from 25 Korean AAA patients were retrospectively obtained. A two-step approach based on Bayesian calibration was used, and an exponential abdominal aortic aneurysm growth model (population-based) was specified according to each individual patient's growth (patient-specific) and morphologic characteristics of the aneurysm sac (enhanced). The distribution estimates were obtained using a Markov Chain Monte Carlo (MCMC) sampler. Results The follow-up diameters were predicted satisfactorily (i.e. the true follow-up diameter was in the 95% prediction interval) for 79% of the scans using the population-based growth model, and 83% of the scans using the patient-specific growth model. Among the evaluated geometric measurements, centerline tortuosity was a significant (p = 0.0002) predictor of growth for AAAs with accelerated and stable expansion rates. Using the enhanced prediction model, 86% of follow-up scans were predicted satisfactorily. The average prediction errors of population-based, patient-specific, and enhanced models were ±2.67, ±2.61 and ± 2.79 mm, respectively. Conclusion A computational framework using patient-oriented growth models provides useful tools for per-patient basis treatment and enables better prediction of AAA growth.

In the study on emergency treatment of massive hemorrhage, it is important to investigate the duration of inflation time in resuscitative endovascular balloon occlusion of aorta (REBOA). REBOA temporarily controls bleeding and maintains the blood pressure while causing side effects to the other organs. To elucidate the side effects of REBOA on the main organs and establish their clinical criteria, both mechanical behavior and clinical examination of each organ tissue must be characterized based on the operation time. Particularly, two rate-dependent mechanical tests (tensile and compression tests) and tissue blood tests (blood urea nitrogen, creatinine, aspartate aminotransferase, and lactate tests) of the kidney, liver, and duodenum tissues were examined according to the inflation time of REBOA. Finally, it was demonstrated that the characteristic of the soft tissue by the loading rate was maintained even in the ischemic tissue. In addition, based on the presented results, it was confirmed that the inflation time of REBOA have an effect on the variation in properties of several organ tissues.

Nerve regeneration after spinal cord injury requires proper axon alignment to bridge the lesion site and myelination to achieve functional recovery. Significant effort has been invested in developing engineering approaches to induce axon alignment with less focus on myelination. Topological features, such as aligned fibers and channels, have been shown to induce axon alignment, but do not enhance axon thickness. We previously demonstrated that surface anisotropy generated through mechanical prestretch induced mesenchymal stem cells to align in the direction of prestretch. In this study, we demonstrate that static prestretch-induced anisotropy promotes dorsal root ganglion (DRG) neurons to extend thicker axon aggregates along the stretched direction and form aligned fascicular-like axon tracts. Moreover, Schwann cells, when cocultured with DRG neurons on the prestretched surface colocalized with the aligned axons and expressed P0 protein, are indicative of myelination of the aligned axons, thereby demonstrating that prestretch-induced surface anisotropy is beneficial in enhancing axon alignment, growth, and myelination.

While it has long been recognized that bi-directional interaction between the heart and the vasculature plays a critical role in the proper functioning of the cardiovascular system, a comprehensive study of this interaction has largely been hampered by a lack of modeling framework capable of simultaneously accommodating high-resolution models of the heart and vasculature. Here, we address this issue and present a computational modeling framework that couples finite element (FE) models of the left ventricle (LV) and aorta to elucidate ventricular - arterial coupling in the systemic circulation. We show in a baseline simulation that the framework predictions of (1) LV pressure - volume loop, (2) aorta pressure - diameter relationship, (3) pressure - waveforms of the aorta, LV and left atrium (LA) over the cardiac cycle are consistent with the physiological measurements found in healthy human. To develop insights of ventricular-arterial interactions, the framework was then used to simulate how alterations in the geometrical or, material parameter(s) of the aorta affect the LV and vice versa. We show that changing the geometry and microstructure of the aorta model in the framework led to changes in the functional behaviors of both LV and aorta that are consistent with experimental observations. On the other hand, changing contractility and passive stiffness of the LV model in the framework also produced changes in both the LV and aorta functional behaviors that are consistent with physiology principles.

The maximum diameter, total volume of the abdominal aorta, and its growth rate are usually regarded as key factors for making a decision on the therapeutic operation time for an abdominal aortic aneurysm (AAA) patient. There is, however, a debate on what is the best standard method to measure the diameter. Currently, two dominant methods for measuring the maximum diameter are used. One is measured on the planes perpendicular to the aneurism's central line (orthogonal diameter) and the other one is measured on the axial planes (axial diameter). In this paper, another method called 'inscribed-spherical diameter' is proposed to measure the diameter. The main idea is to find the diameter of the largest sphere that fits within the aorta. An algorithm is employed to establish a centerline for the AAA geometries obtained from a set of longitudinal scans obtained from South Korea. This centerline, besides being the base of the inscribed spherical method, is used for the determination of orthogonal and axial diameter. The growth rate parameters are calculated in different diameters and the total volume and the correlations between them are studied. Furthermore, an exponential growth pattern is sought for the maximum diameters over time to examine a nonlinear growth pattern of AAA expansion both globally and locally. The results present the similarities and discrepancies of these three methods. We report the shortcomings and the advantages of each method and its performance in the quantification of expansion rates. While the orthogonal diameter measurement has an ability of capturing a realistic diameter, it fluctuated. On the other hand, the inscribed sphere diameter method tends to underestimate the diameter measurement but the growth rate can be bounded in a narrow region for aiding prediction capability. Moreover, expansion rate parameters derived from this measurement exhibit good correlation with each other and with growth rate of volume. In conclusion, although the orthogonal method remains the main method of measuring the diameter of an abdominal aorta, employing the idea of maximally inscribed spheres provides both a tool for generation of the centerline, and an additional parameter for quantification of aneurysmal growth rates.

Venous ulcers are deep wounds that are located predominantly on the lower leg. They are prone to infection and once healed have a high probability of recurrence. Currently, there are no effective measures to predict and prevent venous ulcers from formation. Hence, the goal of this work was to develop a Windkessel-based model that can be used to identify hemodynamic parameters that change between healthy individuals and those with wounds. Once identified, these parameters have the potential to be used as indicators of when internal conditions change, putting the patient at higher risk for wound formation. In order to achieve this goal, blood flow responses in lower legs were measured experimentally by a laser Doppler perfusion monitor (LDPM) and simulated with a modeling approach. A circuit model was developed on the basis of the Windkessel theory. The hemodynamic parameters were extracted for three groups: legs with ulcers (“wounded”), legs without ulcers but from ulcer patients (“nonwounded”), and legs without vascular disease (“healthy”). The model was executed by two independent operators, and both operators reported significant differences between wounded and healthy legs in localized vascular resistance and compliance. The model successfully replicated the experimental blood flow profile. The global and local vascular resistances and compliance parameters rendered quantifiable differences between a population with venous ulcers and healthy individuals. This work supports that the Windkessel modeling approach has the potential to determine patient specific parameters that can be used to identify when conditions change making venous ulcer formation more likely.

Mechanical cues in the cellular environment play important roles in guiding various cell behaviors, such as cell alignment, migration, and differentiation. Previous studies investigated mechanical stretch guided cell alignment pre-dominantly with cyclic stretching whereby an external force is applied to stretch the substrate dynamically (i.e., cyclically) while the cells are attached onto the substrate. In contrast, we created a static pre-stretched anisotropic surface in which the cells were seeded subsequent to stretching the substrate. We hypothesized that the cell senses the physical environment through a more active mechanism, namely, even without external forces the cell can actively apply traction and sense an increased stiffness in the stretched direction and align in that direction. To test our hypothesis, we quantified the extent of pre-stretch induced anisotropy by employing the theory of small deformation superimposed on large and predicted the effective stiffness in the stretch direction as well as its perpendicular direction. We showed mesenchymal stem cells (MSC) aligned in the pre-stretched direction, and the cell alignment and morphology were dependent on the pre-stretch magnitude. In addition, the pre-stretched surface demonstrated an ability to promote early myoblast differentiation of the MSC. This study is the first report on MSC alignment on a statically pre-stretched surface. The cell orientation induced by the pre-stretch induced anisotropy could provide insight into tissue engineering applications involving cells that aligned in vivo in the absence of dynamic mechanical stimuli.

Blood flow patterns and local hemodynamic parameters have been widely associated with the onset and progression of atherosclerosis in the carotid artery. Assessment of these parameters can be performed noninvasively using cine phase-contrast (PC) magnetic resonance imaging (MRI). In addition, in the last two decades, computational fluid dynamics (CFD) simulation in three dimensional models derived from anatomic medical images has been employed to investigate the blood flow in the carotid artery. This study developed a workflow of a subject-specific CFD analysis using MRI to enhance estimating hemodynamics of the carotid artery. Time-of-flight (TOF) MRI scans were used to construct three-dimensional computational models. PC-MRI measurements were utilized to impose the boundary condition at the inlet and a 0-dimensional lumped parameter model was employed for the outflow boundary condition. The choice of different viscosity models of blood flow as a source of uncertainty was studied, by means of the axial velocity, wall shear stress, and oscillatory shear index. The sequence of workflow in CFD analysis was optimized for a healthy subject using PC-MRI. Then, a patient with carotid artery stenosis and its hemodynamic parameters were examined. The simulations indicated that the lumped parameter model used at the outlet gives physiologically reasonable values of hemodynamic parameters. Moreover, the dependence of hemodynamics parameters on the viscosity models was observed to vary for different geometries. Other factors, however, may be required for a more accurate CFD analysis, such as the segmentation and smoothness of the geometrical model, mechanical properties of the artery's wall, and the prescribed velocity profile at the inlet.

Understanding the mechanical behavior of the arte- rial wall and its spatial variations is essential for the study of vascular physiopathology and the design of biomedical devi- ces that interact with the arterial wall. Although it is generally accepted that the aortic wall gets stiffer along its length, the spatial variations in the mechanical behavior of the thoracic aorta are not well understood. In this study, therefore, we investigate both longitudinal and circumferential variations in the mechanical properties of the porcine descending thoracic aorta. Using a previously developed experimental method and stress-strain analysis, the stress, stretch, tangent modu- lus (TM), and pressure-strain elastic modulus (PSEM) are estimated in the range of in vivo pressure. The results show that the longitudinal differences of both TM and PSEM are statistically significant in the posterior region but not in the anterior region. Both moduli are greater in the posterior dis- tal region when compared with the other test regions. The findings of this study meet a need for clarifying the region investigated, especially in circumferential region, to study the regional variations in biomechanics of blood vessels. V C 2012 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 00A:000-000, 2012.

Advances in theoretical modeling of biological tissue growth and remodeling (G&R) and computational biomechanics have been helpful to capture salient features of vascular remodeling during the progression of vascular diseases. Nevertheless, application of such advances to individualized diagnosis and clinical treatment of diseases such as abdominal aortic aneurysm (AAA) remains challenging. As a step toward that goal, in this paper, we present a computational framework necessary towards patient-specific modeling of AAA growth. Prior to AAA simulations, using an inverse optimization method, initial material parameters are identified for a healthy aorta such that a homeostatic condition is satisfied for the given medical image-based geometrical model under physiological conditions. Various shapes of AAAs are then computationally created by inducing elastin degradation with different spatio-temporal distributions. The simulation results emphasize the role of extent of elastin damage, geometric complexity of an enlarged AAA, and sensitivity of stress-mediated collagen turnover on the wall stress distribution and the rate of expansion. The results also show that the distributions of stress and local expansion initially correspond to the extent of elastin damage, but change via stress-mediated tissue G&R depending on the aneurysm shape. Finally, we suggest that the current framework can be utilized along with medical images from an individual patient to predict the AAA shape and mechanical properties in the near future via an inverse scheme.

Complementary advances in medical imaging, vascular biology and biomechanics promise to enable computational modelling of abdominal aortic aneurysms to play increasingly important roles in clinical decision processes. Using a finite-element-based growth and remodelling model of evolving aneurysm geometry and material properties, we show that regional variations in material anisotropy, stiffness and wall thickness should be expected to arise naturally and thus should be included in analyses of aneurysmal enlargement or wall stress. In addition, by initiating the model from best-fit material parameters estimated for non-aneurysmal aortas from different subjects, we show that the initial state of the aorta may influence strongly the subsequent rate of enlargement, wall thickness, mechanical behaviour and thus stress in the lesion. We submit, therefore, that clinically reliable modelling of the enlargement and overall rupture-potential of aneurysms may require both a better understanding of the mechanobiological processes that govern the evolution of these lesions and new methods of determining the patient-specific state of the pre-aneurysmal aorta (or correlation to currently unaffected portions thereof) through knowledge of demographics, comorbidities, lifestyle, genetics and future non-invasive or minimally invasive tests.

Despite rapid expansion of our knowledge of vascular adaptation, developing patient-specific models of diseased arteries is still an open problem. In this study, we extend existing finite element models of stress-mediated growth and remodelling of arteries to incorporate a medical image-based geometry of a healthy aorta and, then, simulate abdominal aortic aneurysm. Degradation of elastin initiates a local dilatation of the aorta while stress-mediated turnover of collagen and smooth muscle compensates the loss of elastin. Stress distributions and expansion rates during the aneurysm growth are studied for multiple spatial distribution functions of elastin degradation and kinetic parameters. Temporal variations of the degradation function are also investigated with either direct time-dependent degradation or stretch-induced degradation as possible biochemical and biomechanical mechanisms for elastin degradation. The results show that this computational model has the capability to capture the complexities of aneurysm progression due to variations of geometry, extent of damage and stress-mediated turnover as a step towards patient-specific modelling.

We developed an extension-inflation experimental apparatus with a stereo vision system and a stress– strain analysis method to determine the regional mechanical properties of a blood vessel. Seven proximal descending thoracic aortas were investigated during the inflation test at a fixed longitudinal stretch ratio of 1.35 over a transmural pressure range from 1.33 to 21.33 kPa. Four circumferential regions of each aorta were designated as the anterior (A), left lateral (L), posterior (P), and right lateral (R) regions, and the inflation test was repeated for each region of the aortas. We used continuous functions to approximate the surfaces of the regional aortic wall in the reference configuration and the deformed configuration. Circumferential stretch and stress at the four circumferential regions of the aorta were computed. Circumferential stiffness, defined as the tangent of the stress–stretch curve, and physiological aortic stiffness, named pressure–strain elastic modulus, were also computed for each region. In the low pressure range, the stress increased linearly with increased stretch, but the mechanical response became progressively stiffer in the high-pressure range above a transition point. At a transmural pressure of 12.00 kPa, mean values of stiffness were 4167 104 kPa (A), 523799 kPa (L), 6347 91 kPa (P), and 4897 82 kPa (R). The stiffness of the posterior region was significantly higher than that of the anterior region, but no significant difference was found in pressure–strain elastic modulus.

A variational method is employed to obtain governing equations and boundary conditions describing finite strain equilibrium configurations of elastomeric gels. Three situations are considered: a liquid saturated gel, an unsaturated gel, and a gel in equilibrium with a vapor of its own liquid. Surface tractions can lead to equilibrium transitions between these cases. The liquid saturated gel is regarded as immersed in a liquid bath. If this bath becomes depleted, then the gel is unsaturated. The degree of unsaturation – a measure of the amount of liquid that would restore a state of saturation – affects the subsequent mechanical behavior. If the unsaturated system is further allowed to condense or evaporate its liquid component at the gel surface, then a new state of equilibrium is achieved. The transition between the unsaturated case and the case of being in equilibrium with the vapor phase corresponds to the chemical potential variable of the gel changing its value from one that is determined by a volume constraint to the value of the chemical potential in the vapor phase. A finite element method is created on the basis of the variational method and demonstrated in the context of eversion, a deformation that imposes very large finite strains. Liquid migration within the gel is not modeled as our focus is on equilibrium states that occur after all such non-equilibrium processes come to rest.

Advances in modeling vascular tissue growth and remodeling (G&R) as well as medical imaging usher in a great potential for integrative computational mechanics to revolutionize the clinical treatment of cardiovascular diseases. A computational model of abdominal aortic aneurysm (AAA) enlargement has been previously developed based on realistic geometric models. In this work, we couple the computational simulation of AAA growth with the hemodynamics simulation in a stepwise, iterative manner and study the interrelation between the changes in wall shear stress (WSS) and arterial wall evolution. The G&R simulation computes a long-term vascular adaptation with constant hemodynamic loads, derived from the previous hemodynamics simulation, while the subsequent hemodynamics simulation computes hemodynamic loads on the vessel wall during the cardiac cycle using the evolved geometry. We hypothesize that low WSS promotes degradation of elastin during the progression of an AAA. It is shown that shear stress-induced degradation of elastin elevates wall stress and accelerates AAA enlargement. Regions of higher expansion correlate with regions of low WSS. Our results show that despite the crucial role of stress-mediated collagen turnover in compensating the loss of elastin, AAA enlargement can be accelerated through the effect of WSS. The present study is able to account for computational models of image-based AAA growth as well as important hemodynamic parameters with relatively low computational expense. We suggest that the present computational framework, in spite of its limitations, provides a useful foundation for future studies which may yield new insight into how aneurysms grow and rupture.

We generalize an existing model for finite strain induced degradation of polymers so as to treat materials with fiber reinforcing. The model allows for degradation of either the matrix or fiber constituents. It also makes allowance for a simple concept of swelling which can also contribute to the degradation kinetics.

Cerebral vasospasm is a poorly understood clinical condition that appears to result from complex biochemical and biomechanical processes that manifest as yet another example of vascular growth and remodeling. We submit that mathematical modeling holds great promise to help synthesize diverse types of data and thereby to increase our understanding of vasospasm. Toward this ultimate goal, we present constitutive relations and parametric studies that illustrate the potential utility of a new theoretical framework that combines information on wall mechanics, hemodynamics, and chemical kinetics. In particular, we show that chemical and mechanical mediators of cellular and extracellular matrix turnover can differentially dominate the progression and resolution of vasospasm. Moreover, based on our simulations, endothelial damage can significantly alter the time-course and extent of vasospasm as can impairment of autoregulation. Although the present results are consistent with salient features of clinically reported vasospasm, and thus provide some new insight, we suggest that most importantly they reveal areas of pressing need with regard to the collection of additional experimental data. Without appropriate data, our understanding of cerebral vasospasm will remain incomplete.

The etiology, and hence most effective treatment, of cerebral vasospasm remains unknown, thus this devastating sequela to subarachnoid hemorrhage continues to be responsible for significant morbidity and mortality. Based on abundant and diverse clinical and laboratory observations, we hypothesize that vasospasm and its subsequent resolution result from a short-term chemo-dominated turnover of cells and matrix in evolving vasoconstricted states that produces a narrowed lumen and thicker wall, which is stiffer and largely unresponsive to exogenous vasodilators, and a subsequent mechano-dominated turnover of cells and matrix in evolving vasodilated states that restores the vessel toward normal. There is, however, a pressing need for a mathematical model of arterial growth and remodeling that can guide the design and interpretation of experiments to test this and competing hypotheses. Toward this end, we present a new biochemomechanical framework that couples a 2-D model of the evolving geometry, structure, and properties of the affected arterial wall, a 1-D model of the blood flow within the affected segment, and a 0-D model of the biochemical insult to the segment. We submit that such a framework can capture salient features of the time-course of vasospasm and its potential resolution, as illustrated numerically in part II of this paper.

Vascular cells are very responsive to even subtle changes in their local mechanical environment, thus there is a pressing need to quantify normal states of stress and strain as well as any perturbations from these normal states. Toward this end, we must quantify constitutive behaviors for both normal and adapted (maladapted) arteries. In this note, we report the first quantification of changes in the biaxial mechanical behavior of the passive basilar artery due to hypertension.

While hemodynamic forces and intraluminal thrombus (ILT) are believed to play important roles on abdominal aortic aneurysm (AAA), it has been suggested that hemodynamic forces and ILT also interact with each other, making it a complex problem. There is, however, a pressing need to understand relationships among three factors: hemodynamics, ILT accumulation, and AAA expansion for AAA prognosis. Hence this study used longitudinal computer tomography scans from 14 patients and analyzed the relationship between them. Hemodynamic forces, represented by wall shear stress (WSS), were obtained from computational fluid dynamics; ILT accumulation was described by ILT thickness distribution changes between consecutives scans, and ILT accumulation and AAA expansion rates were estimated from changes in ILT and AAA volume. Results showed that, while low WSS was observed at regions where ILT accumulated, the rate at which ILT accumulated occurred at the same rate as the aneurysm expansion. Comparison between AAAs with and without thrombus showed that aneurysm with ILT recorded lower values of WSS and higher values of AAA expansion than those without thrombus. Findings suggest that low WSS may promote ILT accumulation and submit the idea that by increasing WSS levels ILT accumulation may be prevented.

Abdominal aortic aneurysms (AAAs) evolve over time, and the vertebral column, which acts as an external barrier, affects their biomechanical properties. Mechanical interaction between AAAs and the spine is believed to alter the geometry, wall stress distribution, and blood flow, although the degree of this interaction may depend on AAAs specific configurations. In this study, we use a growth and remodeling (G&R) model, which is able to trace alterations of the geometry, thus allowing us to computationally investigate the effect of the spine for progression of the AAA. Medical image-based geometry of an aorta is constructed along with the spine surface, which is incorporated into the computational model as a cloud of points. The G&R simulation is initiated by local elastin degradation with different spatial distributions. The AAA–spine interaction is accounted for using a penalty method when the AAA surface meets the spine surface. The simulation results show that, while the radial growth of the AAA wall is prevented on the posterior side due to the spine acting as a constraint, the AAA expands faster on the anterior side, leading to higher curvature and asymmetry in the AAA configuration compared to the simulation excluding the spine. Accordingly, the AAA wall stress increases on the lateral, posterolateral, and the shoulder regions of the anterior side due to the AAA–spine contact. In addition, more collagen is deposited on the regions with a maximum diameter. We show that an image-based computational G&R model not only enhances the prediction of the geometry, wall stress, and strength distributions of AAAs but also provides a framework to account for the interactions between an enlarging AAA and the spine for a better rupture potential assessment and management of AAA patients.

Rupture of intracranial saccular aneurysms is the leading cause of spontaneous subarachnoid hemorrhage, which results in significant morbidity and mortality. Although many have suggested that saccular aneurysms enlarge and rupture due to mechanical instabilities, our recent nonlinear analyses suggest that at least certain classes of aneurysms do not exhibit a quasi-static limit point instability or dynamic instabilities in response to periodic loading. Based on an increased understanding of the ubiquitous role of growth and remodeling within the vasculature and recent histopathological data on saccular aneurysms, it is hypothesized that a stress-mediated regulation of collagen turnover causes their enlargement. There is a need, however, for a theoretical framework to explore this and competing hypotheses. In this paper, we present a 2-D constrained mixture model for growth and remodeling of an ellipsoidally shaped saccular aneurysm and numerically simulate enlargement and changes in material symmetry in the aneurysmal wall. Results suggest that ellipsoidal aneurysms tend toward spherical shapes, and a competition between radial expansion and wall thickening plays a critical role in determining the stability of an enlarging lesion.

In this paper, we develop a model for swelling of an ionic gel in a solvent of varying pH and diffusion of the solvent through the swollen gel by applying a variational method originally presented by Baek and Srinivasa (Int. J. Nonlinear Mech. 39 (2004) 201). The approach presented here, based on the balance laws of a single continuum with mass diffusion and ionic chemical reactions, delivers system equations and boundary conditions by assuming two constitutive scalar functions for the free energy of the system and the rate of dissipation, instead of assuming osmotic pressure, electrostatic repulsive force, etc. In the equilibrium case, the model describes pH-dependent behavior and the effect of other counterions on the swelling of ionic gels. In the non-equilibrium case, it accounts for the pH-dependent mass flux through ionic gels. Moreover, the model shows that the mass flux can be induced by the gradient of chemical potential, the concentration of the mobile species and ionic charges. This model is applied to a typical carboxylated copolymer gel, and compared with an experiment for equilibrium swelling, and predicts the pH-dependence for a pressure-induced mass flux.

Most of the abdominal aortic aneurysms (AAA) include an intraluminal thrombus (ILT) deposited on their internal wall. Active proteolytic enzymes in the ILT may cause bio-chemically weakening the aneurysmal wall, which leads to elevation of the aneurysm rupture risk. On the other hand, lack of oxygen on the aneurysmal wall beneath a thick ILT (hypoxia) causes proteolytic activity on the wall as a secondary effect. In this paper we develop an axisymmetric growth and remodeling model of the AAA considering the bio-chemical effects of the ILT mentioned above. We then estimate the model parameters using nine patients’ longitudinal CT data. The parametric study shows that AAA’s radius and volume increases significantly in existence of ILT because of both hypoxia and proteolytic activity. However, the relation between the AAA volume and its maximum diameter slightly changes due to hypoxia while this relation highly changes because of the proteolytic activity in the luminal layer of the ILT. We also show that our numerical results for the AAA expansion as a function of its maximum diameter can be very close to the clinical data with a proper estimation of the model parameters.

Abdominal Aortic Aneurysms (AAA) is a form of vascular disease causing focal enlargement of abdominal aorta. It affects a large part of population and has up to 90% mortality rate. Since risks from open surgery or endovascular repair outweighs the risk of AAA rupture, surgical treatments are not recommended with AAA less than 5.5cm in diameter. Recent clinical recommendations suggest that people with small aneurysms should be examined 3∼36 months depending on size to get information about morphological changes. While advances in biomechanics provide state-of-the-art spatial estimates of stress distributions of AAA, there are still limitations in modeling its time evolution. Thus, there is no biomechanical framework to utilize such information from a series of medical images that would aid physicians in detecting small aneurysms with high risk of rupture. For the present study, we use series of CT images of small AAAs taken at different times to model and predict the spatio-temporal evolution of AAA. This is achieved using sparse local Gaussian process regression.Copyright © 2013 by ASME

Abdominal Aortic Aneurysm (AAA), a focal enlargement of the abdominal aorta is an ongoing process that can be affected by many parameters. Among these parameters, hemodynamics and intraluminal thrombus layer (ILT) play important roles on AAA growth. It is widely accepted that hemodynamic forces (normal and shear forces) have a profound impact on the mechano-homeostasis of the arterial wall and its vascular remodeling. The role of ILT, however, remains controversial. Some studies suggest that ILT may be beneficial by shieling the weak aneurysm wall, whereas others claim that the presence of ILT can lead to immune responses that increase protease breakdown of collagen and elastin, adversely affecting wall strength. ILT is formed by the deposition of blood clots called thrombus. Thrombus formation is achieved through different mechanisms, but all research agrees that shear fluid forces are one of the key parameters for the formation and development of ILT. There are few studies to date that use these three parameters to assess the evolution of AAAs growth. Here, we explore the relation between wall shear stress (WSS), ILT and AAA expansion using longitudinal CT images from follow-up studies from 3 patients (a total of 8 scans). We used geometrical models of AAAs segmented from patient images to estimate outer surface displacement, ILT, and tissue thickness. Additionally, we used fluid dynamic data to estimate wall shear stress at peak systolic. These parameters were then used to investigate possible relationships with each other.

Abdominal aortic aneurysms (AAAs) are characterized by significant changes in the architecture of the aortic wall, notably, loss of functional elastin and smooth muscle. Because collagen is the principal remaining load-bearing constituent of the aneurysmal wall, its turnover must play a fundamental role in the natural history of the lesion. Nevertheless, detailed investigations of the effects of different aspects of collagen turnover on AAA development are lacking. A finite-element membrane model of the growth and remodelling of idealized AAAs was thus used to investigate parametrically four of the primary aspects of collagen turnover: rates of production, half-life, deposition stretch (prestretch) and material stiffness. The predicted rates of aneurysmal expansion and spatio-temporal changes in wall thickness, biaxial stresses and maximum collagen fibre stretch at the apex of the lesion depended strongly on all four factors, as did the predicted clinical endpoints (i.e. arrest, progressive expansion or rupture). Collagen turnover also affected the axial expansion, largely due to mechanical changes within the shoulder region of the lesion. We submit, therefore, that assessment of rupture risk could be improved by future experiments that delineate and quantify different aspects of patient-specific collagen turnover and that such understanding could lead to new targeted therapeutics.

Abdominal Aortic Aneurysms (AAA), a focal enlargement of abdominal aorta, is a form of vascular diseases that affects large part of the population. It can cause the mortality up to 90% of the cases when it ruptures. Currently, the best known treatment to reduce risk is open surgery or endovascular repair. Since the risk of such surgery repair is high, in most patients with AAAs< 55mm in its maximum diameter the surgical treatment is postponed. An effort to enhance the accuracy of the risk assessment and to prevent AAA’s growth and rupture is being made, but the mechanisms promoting AAAs growth are still largely unknown. AAAs can be affected by different factors, among those, hemodynamics is known to play important roles in AAA initiation and progression. Particularly, the wall shear stress is believed to contribute to AAA expansion and rupture. For the present study, we use geometries constructed from longitudinal CT images obtained during AAA follow-up studies and investigate relations between multiple hemodynamics factors with local expansion of AAAs.Copyright © 2012 by ASME

The role of spine and other surrounding tissues as geometrical constraints on abdominal aortic aneurysm (AAA) enlargement has been suggested [1] but its biomechanical effects among patients have not been thoroughly investigated yet. In this study, we use longitudinal CT images obtained from AAA follow-up studies and investigate geometrical features and their changes indicating interactions with spine during the progression of AAAs. We also study biomechanical effects of the interaction with spine on the AAA enlargement and stress distribution using growth and remodeling (G&R) model of AAAs.Copyright © 2012 by ASME

The mechanical properties of arterial wall have been assumed isotropic and homogeneous, but advances in biomedical imaging and computational biomechanics bring a need for understanding regional difference in the biomechanical properties of arties. Particularly, vascular diseases such as aortic aneurysm and dissection are likely to be developed in the elderly and they are still life-threatening. Thus understanding of the regional variation in the mechanical behavior of arteries is critical for the clinical treatments and biomedical engineering applications.Copyright © 2012 by ASME

For an abdominal aortic aneurysm (AAA) in vivo there are multiple tissues contacting its boundary, none of which have been fully considered for their effect throughout disease progression. Trends such as arterial asymmetry, surface curvature flattening, and arterial tortuosity could be significantly influenced by both surrounding tissue and hemodynamic factors. In order to quantify either the combined or separate influence of such factors during disease progression a precise characterization of aneurysm geometry evolution is needed. Multiple methods for geometrical parameterization of abdominal aortic aneurysms (AAAs) have been previously developed using isolated patient CT scan data but the focus has been mainly on the association of such geometrical parameters with the rupture risk and the efficacy of the parameterization is not fully investigated for a longitudinal study yet (multiple CT scans per patient at progressive intervals) [1]. For this study we have produced a series of 3D models for AAAs in longitudinal studies, developed an arterial centerline generation algorithm, and automated a geometric parameterization procedure for the arterial surfaces. It should be noted that the caliber of our collection of data is relatively rare as it is high resolution, features many patients, and on average has 4–5 images per patient.Copyright © 2012 by ASME

While the advancement and widespread use of medical imaging have greatly aided in the diagnosis of abdominal aortic aneurysms (AAAs), many questions remain regarding the natural progression of AAAs and most importantly predicting their likelihood of rupture — an event carrying a mortality rate of over 80% [1]. Current guidelines recommend surgical intervention when the aneurysm achieves a diameter of 5.5 cm [2]; however, it has been documented by at least one study of 161 consecutive patients that approximately 10% of AAA ruptures occur in aneurysms measuring 5 cm or less [3]. It is also unknown how many surgically repaired aneurysms may not have proceeded to rupture in a patient’s lifetime. For this reason, there is much interest in identifying better predictors of rupture risk than diameter alone.Copyright © 2011 by ASME

Characterization of the mechanical properties of a blood vessel is essential in understanding the progression of a vascular disease and for computational studies of vascular adaptation. For example, stiffness of vascular tissue is one of the major indicators to diagnose the vascular disease and make a clinical decision. Although previous studies reported the heterogeneity of the mechanical properties of arterial wall along the arterial tree [2], little was taken account for its circumferential variations. With the lack of experimental studies for investigating the circumferential variation, the aortic wall is typically assumed to have uniform deformation. Our previous study, however, has observed that there are circumferential variations in aortic wall stress and stiffness [1]. In addition to our previous study, we investigate further regional variations of the porcine thoracic aorta in both circumferential and longitudinal directions during the inflation test. Hence, we additionally test the distal thoracic aorta at each anterior and posterior side, respectively, and compare with the proximal thoracic aorta.