Samarth S. Raut

The Role of Geometric and Biomechanical Factors in Abdominal Aortic Aneurysm Rupture Risk Assessment

The current clinical management of abdominal aortic aneurysm (AAA) disease is based to a great extent on measuring the aneurysm maximum diameter to decide when timely intervention is required. Decades of clinical evidence show that aneurysm diameter is positively associated with the risk of rupture, but other parameters may also play a role in causing or predisposing the AAA to rupture. Geometric factors such as vessel tortuosity, intraluminal thrombus volume, and wall surface area are implicated in the differentiation of ruptured and unruptured AAAs. Biomechanical factors identified by means of computational modeling techniques, such as peak wall stress, have been positively correlated with rupture risk with a higher accuracy and sensitivity than maximum diameter alone. The objective of this review is to examine these factors, which are found to influence AAA disease progression, clinical management and rupture potential, as well as to highlight on-going research by our group in aneurysm modeling and rupture risk assessment.

Fluid-structure interaction modeling of abdominal aortic aneurysms: The impact of patient-specific inflow conditions and fluid/solid coupling

Rupture risk assessment of abdominal aortic aneurysms (AAA) by means of biomechanical analysis is a viable alternative to the traditional clinical practice of using a critical diameter for recommending elective repair. However, an accurate prediction of biomechanical parameters, such as mechanical stress, strain, and shear stress, is possible if the AAA models and boundary conditions are truly patient specific. In this work, we present a complete fluid-structure interaction (FSI) framework for patient-specific AAA passive mechanics assessment that utilizes individualized inflow and outflow boundary conditions. The purpose of the study is two-fold: (1) to develop a novel semiautomated methodology that derives velocity components from phase-contrast magnetic resonance images (PC-MRI) in the infrarenal aorta and successfully apply it as an inflow boundary condition for a patient-specific fully coupled FSI analysis and (2) to apply a one-way-coupled FSI analysis and test its efficiency compared to transient computational solid stress and fully coupled FSI analyses for the estimation of AAA biomechanical parameters. For a fully coupled FSI simulation, our results indicate that an inlet velocity profile modeled with three patient-specific velocity components and a velocity profile modeled with only the axial velocity component yield nearly identical maximum principal stress (σ1), maximum principal strain (ε1), and wall shear stress (WSS) distributions. An inlet Womersley velocity profile leads to a 5% difference in peak σ1, 3% in peak ε1, and 14% in peak WSS compared to the three-component inlet velocity profile in the fully coupled FSI analysis. The peak wall stress and strain were found to be in phase with the systolic inlet flow rate, therefore indicating the necessity to capture the patient-specific hemodynamics by means of FSI modeling. The proposed one-way-coupled FSI approach showed potential for reasonably accurate biomechanical assessment with less computational effort, leading to differences in peak σ1, ε1, and WSS of 14%, 4%, and 18%, respectively, compared to the axial component inlet velocity profile in the fully coupled FSI analysis. The transient computational solid stress approach yielded significantly higher differences in these parameters and is not recommended for accurate assessment of AAA wall passive mechanics. This work demonstrates the influence of the flow dynamics resulting from patient-specific inflow boundary conditions on AAA biomechanical assessment and describes methods to evaluate it through fully coupled and one-way-coupled fluid-structure interaction analysis.

An approach for patient-specific multi-domain vascular mesh generation featuring spatially varying wall thickness modeling

In this work, we present a computationally efficient image-derived volume mesh generation approach for vasculatures that implements spatially varying patient-specific wall thickness with a novel inward extrusion of the wall surface mesh. Multi-domain vascular meshes with arbitrary numbers, locations, and patterns of both iliac bifurcations and thrombi can be obtained without the need to specify features or landmark points as input. In addition, the mesh output is coordinate-frame independent and independent of the image grid resolution with high dimensional accuracy and mesh quality, devoid of errors typically found in off-the-shelf image-based model generation workflows. The absence of deformable template models or Cartesian grid-based methods enables the present approach to be sufficiently robust to handle aneurysmatic geometries with highly irregular shapes, arterial branches nearly parallel to the image plane, and variable wall thickness. The assessment of the methodology was based on i) estimation of the surface reconstruction accuracy, ii) validation of the output mesh using an aneurysm phantom, and iii) benchmarking the volume mesh quality against other frameworks. For the phantom image dataset (pixel size 0.105 mm; slice spacing 0.7 mm; and mean wall thickness 1.401±0.120 mm), the average wall thickness in the mesh was 1.459±0.123 mm. The absolute error in average wall thickness was 0.060±0.036 mm, or about 8.6% of the largest image grid spacing (0.7 mm) and 4.36% of the actual mean wall thickness. Mesh quality metrics and the ability to reproduce regional variations of wall thickness were found superior to similar alternative frameworks.

The Effect of Uncertainty in Vascular Wall Material Properties on Abdominal Aortic Aneurysm Wall Mechanics

Clinical management of abdominal aortic aneurysms (AAA) can benefit from patient-specific computational biomechanics-based assessment of the disease. Individual variations in shape and aortic material properties are expected to influence the assessment of AAA wall mechanics. While patient-specific geometry can be reproduced using medical images, the accurate individual and regionally varying tissue material property estimation is currently not feasible. This work addresses the relative uncertainties arising from variations in AAA material properties and its effect on the ensuing wall mechanics. Computational simulations were performed with five different isotropic material models based on an ex-vivo AAA wall material characterization and a subject population sample of 28 individuals. Care was taken to exclude the compounding effects of variations in all other geometric and biomechanical factors. To this end, the spatial maxima of the principal stress (σ max), principal strain (e max), strain-energy density (ψ max), and displacement (δ max) were calculated for the diameter-matched cohort of 28 geometries for each of the five different constitutive materials. This led to 140 quasi-static simulations, the results of which were assessed on the basis of intra-patient (effect of material constants) and inter-patient (effect of individual AAA shape) differences using statistical averages, standard deviations, and Box and Whisker plots. Mean percentage variations for σ max, e max, ψ max, and δ max for the intra-patient analysis were 1.5, 7.1, 8.0, and 6.1, respectively, whereas for the inter-patient analysis these were 11.1, 4.5, 15.3, and 12.9, respectively. Changes in the material constants of an isotropic constitutive model for the AAA wall have a negligible influence on peak wall stress. Hence, this study endorses the use of population-averaged material properties for the purpose of estimating peak wall stress, strain-energy density, and wall displacement. Conversely, strain is more dependent on the material constant variation than on the differences in AAA shape in a diameter-matched population cohort.

Biological, Geometric and Biomechanical Factors Influencing Abdominal Aortic Aneurysm Rupture Risk: A Comprehensive Review

The current clinical management of abdominal aortic aneurysm (AAA) disease is based to a great extent on measuring the aneurysm maximum diameter to decide when timely intervention is required. Decades of clinical evidence show that aneurysm diameter is positively associated with the probability of rupture, but that other parameters may also play a role in causing or predisposing the AAA to rupture. Biological factors associated with smooth muscle apoptosis are implicated in AAA expansion while geometric and biomechanical factors identified by means of computational modeling techniques have been positively correlated with rupture risk with a higher accuracy and sensitivity than maximum diameter alone. The objective of this review is to examine the factors found to influence AAA disease progression, clinical management and rupture, as well as a patent review that highlights developments in this arena in the past few years.

Estimation of Patient-Specific 3D In Vivo Abdominal Aortic Aneurysm Strain

Abdominal Aortic Aneurysm (AAA) is a localized permanent dilatation occurring in abdominal region of the aorta. Nearly 8% of the population above 65 years old is diagnosed with this disease [1], which has been shown to be associated with smoking history, heredity, and male gender. As it is asymptomatic, vascular surgeons may opt for surgical intervention or follow a wait-and-watch strategy if their assessment of the risk of rupture is low. During surgical intervention grafts are placed inside the aorta. Design of such intravascular devices as well as monitoring the progression of the disease by means of scientific approach may benefit from information on the strains that occur in the aneurysmatic region at different instances due to cyclic internal pressurization during cardiac cycle.Copyright

AAA RUPTURE RISK ASSESSMENT IN THE CLINIC: WALL STRESS OR GEOMETRIC CHARACTERIZATION?

The current clinical management of abdominal aortic aneurysm (AAA) disease is based to a great extent on measuring the aneurysm maximum diameter to decide when timely intervention is required. Decades of clinical evidence show that aneurysm diameter is positively associated with the risk of rupture, but other parameters may also play a role in causing or predisposing the AAA to rupture. Geometric factors such as vessel tortuosity, intraluminal thrombus volume, and wall surface area are implicated in the differentiation of ruptured and unruptured AAAs. Biomechanical factors identified by means of computational modeling techniques, such as peak wall stress, have been positively correlated with rupture risk with a higher accuracy and sensitivity than maximum diameter alone. In the present work, we performed a controlled study targeted at evaluating the effect of uncertainty of the constitutive material model used for the vascular wall in the ensuing peak wall stress. Based on the outcome of this study, a second analysis was conducted based on the geometric characterization of surface curvature in two groups of aneurysm geometries, to discern which curvature metric can adequately discriminate ruptured from electively repaired AAA. The outcome of this work provides preliminary evidence on the importance of quantitative geometry characterization for AAA rupture risk assessment in the clinic.Copyright

MRI-Based Inflow Boundary Conditions for Patient Specific Fluid Structure Interaction Modeling of Abdominal Aortic Aneurysms

Rupture of abdominal aortic aneurysm (AAA) is the 10th leading cause of death for men over age of 50 in US. The decision for surgical intervention is currently based on aneurysm diameter or its expansion rate. However, the use of these criteria for all patients is debatable. For example, small aneurysms do rupture or become symptomatic before reaching the critical diameter. Computationally predicted mechanical wall stress is considered a viable alternative criterion for rupture risk assessment. Hence, it is important to evaluate the effect of different modeling approaches on the accuracy of the predicated AAA wall stress. For computational solid stress (CSS) analysis or finite element analysis (FEA), a uniform static or transient intraluminal pressure is generally applied on the wall-lumen surface whereas in fluid-structure interaction (FSI) modeling the wall-lumen surface experiences transient and non-uniform fluid stress. An earlier comparison on idealized AAA models [1] revealed that static and transient CSS underestimate the peak wall stress (PWS) by an average 20–30% for variable wall thickness and 10% for uniform wall thickness when compared to fully coupled FSI. However, FSI-predicted stresses and strains were observed to be sensitive to inflow and outflow boundary conditions, warranting further study on a more accurate approach for FSI modeling. Though significant work has been performed on modeling outflow boundary conditions [2], studies on the sensitivity of computed stress or strain to the type of FSI inflow boundary condition is scarce [2–4]. We hypothesize that a FSI framework with a patient specific velocity boundary condition derived from magnetic resonance imaging (MRI) data applied to patient specific AAA geometry would provide better accuracy of PWS calculations compared to a FEA model. In this work, we present a framework where the AAA geometry is reconstructed from computed tomography (CT) images, on which FSI simulations were performed with inlet velocity components extracted from patient MR images of the abdominal aorta. Fully coupled FSI simulations were performed and results were compared with CSS simulations with uniform transient pressure boundary conditions.Copyright

Aortic Wall Mechanics: A Geometry-Driven Problem

Abdominal Aortic Aneurysm (AAA) is a vascular disease that occurs predominantly in people over 60 years of age. The rupture of an AAA is a catastrophic event associated with up to a 90% mortality rate. Hence, it is important for vascular surgeons to justify the risk of repair vis-a-vis the risk of aneurysm rupture. In clinical practice, rupture risk assessment is based on measuring the maximum aneurysm diameter where 5.5 cm is accepted as the critical size for recommending (surgical or endovascular) intervention. However, this criterion is based on an extensive history of evidence-based medicine rather than an individualized assessment of the aneurysm’s potential to rupture. Primary among the biomechanical factors associated with the rupture assessment of an AAA is mechanical wall stress, which is dependent on the accuracy of the geometry reconstruction, intraluminal pressure loading and the constitutive material model used for the aortic wall. We hypothesize that in unruptured, asymptomatic AAA, the wall mechanics is the outcome of primarily the patient specific aneurysm shape and to a lesser extent, the constitutive material property model used to characterize the vascular wall. Evaluating the relative contributions of wall material properties and AAA geometry to wall mechanics estimation will increase our understanding of the factors that influence peak wall stress as an indicator for rupture risk assessment. In the present work, we evaluate the aforementioned hypothesis using a size-matched approach.Copyright

Phase contrast MRI derived boundary conditions for patient specific AAA fluid flow modeling

Abdominal Aortic Aneurysm (AAA) is a common disease among Caucasian males above the age of 60 and its rupture is the 10th leading cause of death in the U.S. [1] An AAA is commonly defined as a 50% local increase in diameter of the normal infrarenal aorta, and is located below the renal arteries and the iliac bifurcation. At present the measured maximum diameter or the rate of increase of the diameter over time are used as clinical parameters to judge the suitability of surgical intervention to prevent rupture. As a clinical diagnosis rule, aneurysms with diameter less than 4 cm are kept under periodic surveillance and between 5 cm and 6 cm, or expansion rates greater than 1 cm / year, are recommended for surgical or endovascular intervention. Unfortunately, retrospective studies reveal that about 33% of ruptured aneurysms had a maximum diameter less than 5 cm at the time of the rupture [2]. This demonstrates that the correlation between a critical diameter and rupture risk assessment of AAAs has its limitations and thus opens the opportunity for further research on other critical parameters that may be suitable for future diagnosis and rupture prediction. Our ongoing computational efforts [3] focus on this issue as we propose the use of patient specific fluid-structure interaction (FSI) models to investigate the potential of individual flow-induced wall stress as a key biomechanical parameter that can be used for rupture risk evaluation. In this work we report on the setup of the computational protocol for patient specific analysis and assess the effect of modeling parameters on the derivation of individual inflow and outflow boundary conditions for AAA fluid flow simulation and validation.Copyright