Abdominal Aortic Aneurysm Growth: The Association of Aortic Wall Mechanics and Geometry

2011 ◽  
Author(s):  
Christopher B. Washington ◽  
Judy Shum ◽  
Satish C. Muluk ◽  
Ender A. Finol
Keyword(s):  
Wall Stress ◽  
Abdominal Ultrasound ◽  
Aneurysm Rupture ◽  
Computational Method ◽  
Maximum Diameter ◽  
Patient Specific ◽  
Element Analysis ◽  
Wall Strength ◽  
Aneurysm Growth ◽  
Peak Wall Stress

In an effort to prevent rupture, patients with known AAA undergo periodic abdominal ultrasound or CT scan surveillance. When the aneurysm grows to a diameter of 5.0–5.5 cm or is shown to expand at a rate greater than 1 cm/yr, elective operative repair is undertaken. While this strategy certainly prevents a number of potentially catastrophic ruptures, AAA rupture can occur at sizes less than 5 cm. From a biomechanical standpoint, aneurysm rupture occurs when wall stress exceeds wall strength. By using non-invasive techniques, such as finite element analysis (FEA), wall stress can be estimated for patient specific AAA models, which can perhaps more carefully predict the rupture potential of a given aneurysm, regardless of size. FEA is a computational method that can be used to evaluate complicated structures such as aneurysms. To this end, it was reported earlier that AAA peak wall stress provides a better assessment of rupture risk than the commonly used maximum diameter criterion [1]. What has yet to be examined, however, is the relationship between wall stress and AAA geometry during aneurysm growth. Such finding has the potential for providing individualized predictions of AAA rupture potential during patient surveillance. The purpose of this study is to estimate peak wall stress for an AAA under surveillance and evaluate its potential correlation with geometric features characteristic of the aneurysm’s morphology.

scholarly journals The Association of Wall Mechanics and Morphology: A Case Study of Abdominal Aortic Aneurysm Growth

2011 ◽  
Vol 133 (10) ◽  
Author(s):  
Christopher B. Washington ◽  
Judy Shum ◽  
Satish C. Muluk ◽  
Ender A. Finol
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Wall Stress ◽  
Aneurysm Rupture ◽  
Maximum Diameter ◽  
Least Squares Regression ◽  
Surveillance Period ◽  
Element Analysis ◽  
Abdominal Aortic ◽  
Peak Wall Stress

The purpose of this study is to evaluate the potential correlation between peak wall stress (PWS) and abdominal aortic aneurysm (AAA) morphology and how it relates to aneurysm rupture potential. Using in-house segmentation and meshing software, six 3-dimensional (3D) AAA models from a single patient followed for 28 months were generated for finite element analysis. For the AAA wall, both isotropic and anisotropic materials were used, while an isotropic material was used for the intraluminal thrombus (ILT). These models were also used to calculate 36 geometric indices characteristic of the aneurysm morphology. Using least squares regression, seven significant geometric features (p < 0.05) were found to characterize the AAA morphology during the surveillance period. By means of nonlinear regression, PWS estimated with the anisotropic material was found to be highly correlated with three of these features: maximum diameter (r = 0.992, p = 0.002), sac volume (r = 0.989, p = 0.003) and diameter to diameter ratio (r = 0.947, p = 0.033). The correlation of wall mechanics with geometry is nonlinear and reveals that PWS does not increase concomitantly with aneurysm diameter. This suggests that a quantitative characterization of AAA morphology may be advantageous in assessing rupture risk.

scholarly journals A Methodology for the Derivation of Unloaded Abdominal Aortic Aneurysm Geometry With Experimental Validation

2016 ◽  
Vol 138 (10) ◽  
Author(s):  
Santanu Chandra ◽  
Vimalatharmaiyah Gnanaruban ◽  
Fabian Riveros ◽  
Jose F. Rodriguez ◽  
Ender A. Finol
Keyword(s):  
Finite Element ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Stress Component ◽  
Wall Stress ◽  
Patient Specific ◽  
Element Analysis ◽  
Nodal Surface ◽  
Abdominal Aortic ◽  
Peak 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 μm 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.

Use of the Photoelastic Method to Determine the Wall Stress in Realistic Abdominal Aortic Aneurysm Models

2011 ◽  
Author(s):  
Barry J. Doyle ◽  
Anthony Callanan ◽  
John Killion ◽  
Timothy M. McGloughlin
Keyword(s):  
Wall Stress ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Patient Specific ◽  
Western World ◽  
Photoelastic Method ◽  
Element Analysis ◽  
Abdominal Aortic ◽  
The Us ◽  
Numerical Tools

Abdominal aortic aneurysms (AAAs) remain a significant cause of death in the Western world with over 15,000 deaths per year in the US linked to AAA rupture. Recent research [1] has questioned the use of maximum diameter as a definitive risk parameter as it is now believed that alternative factors may be important in rupture-prediction. Wall stress was shown to be a better predictor than diameter of rupture [1], with biomechanics-based rupture indices [2,3] and asymmetry also reported to have potential clinical applicability [4]. However, the majority of numerical methods used to form these alternative rupture parameters are without rigorous experimental validation, and therefore may not be as accurate as believed. Validated experiments are required in order to convince the clinical community of the worth of numerical tools such as finite element analysis (FEA) in AAA risk-prediction. Strain gauges have been used in the past to determine the strain on an AAA [5], however, the photoelastic method has also proved to be a useful tool in AAA biomechanics [6]. This paper examines the approach using three medium-sized patient-specific AAA cases at realistic pressure loadings.

A Comparative Study of Biomechanical and Geometrical Attributes of Abdominal Aortic Aneurysms in the Asian and Caucasian Populations

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Tejas Canchi ◽  
Sourav S. Patnaik ◽  
Hong N. Nguyen ◽  
E. Y. K. Ng ◽  
Sriram Narayanan ◽  
...  
Keyword(s):  
Wall Thickness ◽  
Gaussian Curvature ◽  
Wall Stress ◽  
Aneurysm Rupture ◽  
Aortic Aneurysms ◽  
Patient Specific ◽  
Backward Elimination ◽  
Abdominal Aortic ◽  
Highly Correlated ◽  
Peak Wall Stress

Abstract 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 (R2 = 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 (R2 = 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.

Porohyperelastic Simulation of Abdominal Aortic Aneurysms

2008 ◽  
Author(s):  
Avinash Ayyalasomayajula ◽  
Bruce R. Simon ◽  
Jonathan P. Vande Geest
Keyword(s):  
Wall Stress ◽  
Aortic Aneurysms ◽  
Maximum Diameter ◽  
Patient Specific ◽  
Infrarenal Aorta ◽  
Stress Studies ◽  
Abdominal Aortic ◽  
Peak Wall Stress ◽  
Work Done

Abdominal aortic aneurysm (AAA) is a progressive dilation of the infrarenal aorta and results in a significant alteration in local hemodynamic environment [1]. While an aneurysmal diameter of 5.5cm is typically classified as being of high risk, recent studies have demonstrated that maximum wall stress could be a better indicator of an AAA rupture than maximum diameter [2]. The wall stress is greatly influenced by the blood pressure, aneurysm diameter, shape, wall thickness and the presence of thrombus. The work done by Finol et al. suggested that hemodynamic pressure variations have an insignificant effect on AAA wall stress and that primarily the shape of the aneurysm determines the stress distribution. They noted that for peak wall stress studies the static pressure conditions would suffice as the in vivo conditions. Wang et al have developed an isotropic hyperelastic constitutive model for the intraluminal thrombus (ILT). Such models have been used to study the stress distributions in patient specific AAAs [3, 4].

Automated Methodology for Determination of Stress Distribution in Human Abdominal Aortic Aneurysm

2005 ◽  
Vol 127 (5) ◽  
pp. 868-871 ◽  
Author(s):  
Madhavan L. Raghavan ◽  
Mark F. Fillinger ◽  
Steven P. Marra ◽  
Bernhard P. Naegelein ◽  
Francis E. Kennedy
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Peak Stress ◽  
Wall Stress ◽  
Patient Specific ◽  
Element Analysis ◽  
Biomechanical Stress ◽  
Abdominal Aortic ◽  
Study Population ◽  
Peak Wall Stress

Knowledge of impending abdominal aortic aneurysm (AAA) rupture can help in surgical planning. Typically, aneurysm diameter is used as the indicator of rupture, but recent studies have hypothesized that pressure-induced biomechanical stress may be a better predictor. Verification of this hypothesis on a large study population with ruptured and unruptured AAA is vital if stress is to be reliably used as a clinical prognosticator for AAA rupture risk. We have developed an automated algorithm to calculate the peak stress in patient-specific AAA models. The algorithm contains a mesh refinement module, finite element analysis module, and a postprocessing visualization module. Several aspects of the methodology used are an improvement over past reported approaches. The entire analysis may be run from a single command and is completed in less than 1h with the peak wall stress recorded for statistical analysis. We have used our algorithm for stress analysis of numerous ruptured and unruptured AAA models and report some of our results here. By current estimates, peak stress in the aortic wall appears to be a better predictor of rupture than AAA diameter. Further use of our algorithm is ongoing on larger study populations to convincingly verify these findings.

Aneurysm Wall Stress and Tendency to Rupture are Features of Physical Wall Properties: An Experimental Study

2002 ◽  
Vol 9 (5) ◽  
pp. 665-675 ◽  
Author(s):  
Harpaul S. Flora ◽  
Bijan Talei-Faz ◽  
Leslie Ansdell ◽  
Edmund J. Chaloner ◽  
Aaron Sweeny ◽  
...  
Keyword(s):  
Inflection Point ◽  
Flow Model ◽  
Peak Stress ◽  
Wall Stress ◽  
Maximum Diameter ◽  
Type I ◽  
Aneurysm Wall ◽  
Wall Strength ◽  
Abdominal Aortic ◽  
Peak Wall Stress

Purpose: To use bench top techniques to examine the biophysical phenomena affecting the risk of abdominal aortic aneurysm (AAA) rupture relative to the physical properties of the aneurysm sac. Methods: Three latex AAAs with different wall elasticities were tested in a validated pulsatile flow model (PFM). Strain gauges were wired to each AAA model at the neck, inflection point, and at the maximum diameter. In initial studies, the influence of pressurization and the mechanical properties of AAA wall stress were evaluated. In subsequent studies, the latex AAAs were excluded with a tube graft and retested in the PFM. After creation of either a type I or II endoleak of known size and pressure, the systemic/intrasac pressure and the AAA wall stress were measured. Results: Each model had a complex wall-stress pattern comprising radial, longitudinal, and shear components. The peak wall stress at any point, in the presence of systemic pressurization or endoleak pressure, only reached 1% of the failure strength. In an AAA with a reinforced wall, the peak stress was significantly greater. Statistical analysis showed that wall strength contributed more significantly to wall stress than increasing pressurization within the AAA sac. Conclusions: AAA wall mechanics contribute more significantly to peak wall stress than pressure variations within the system. In particular, increased stiffness (analogous to collagen deposition) significantly increased peak wall stress, which was located at the inflection point rather than at the maximum diameter. Techniques to measure the AAA wall mechanics and the rate of deterioration may predict AAA rupture in the untreated state or in the presence of an endoleak following endovascular repair.

Abdominal Aortic Aneurysm Rupture Risk Assessment Exploiting Dynamic (4D) CT Based Wall Motion Data and Finite Element Analysis

2013 ◽  
Author(s):  
Eleni Metaxa ◽  
Vasileios Vavourakis ◽  
Nikolaos Kontopodis ◽  
Konstantinos Pagonidis ◽  
Christos V. Ioannou ◽  
...  
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Risk Estimation ◽  
Wall Stress ◽  
Aneurysm Rupture ◽  
Patient Specific ◽  
Rupture Risk ◽  
Element Analysis ◽  
Motion Data ◽  
Abdominal Aortic

Abdominal aortic aneurysm (AAA) disease is primarily a degenerative process, where rupture occurs when stress exerted on the aortic wall exceeds its failure strength. Therefore, knowledge of both the wall stress distribution and the mechanical properties of the AAA wall is required for patient specific rupture risk estimation.

scholarly journals Predictors of Abdominal Aortic Aneurysm Risks

2020 ◽  
Vol 7 (3) ◽  
pp. 79
Author(s):  
Stephen J. Haller ◽  
Amir F. Azarbal ◽  
Sandra Rugonyi
Keyword(s):  
Risk Assessment ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Wall Stress ◽  
Patient Specific ◽  
Rupture Risk ◽  
Element Analysis ◽  
Computational Biomechanics ◽  
Wall Strength ◽  
Abdominal Aortic

Computational biomechanics via finite element analysis (FEA) has long promised a means of assessing patient-specific abdominal aortic aneurysm (AAA) rupture risk with greater efficacy than current clinically used size-based criteria. The pursuit stems from the notion that AAA rupture occurs when wall stress exceeds wall strength. Quantification of peak (maximum) wall stress (PWS) has been at the cornerstone of this research, with numerous studies having demonstrated that PWS better differentiates ruptured AAAs from non-ruptured AAAs. In contrast to wall stress models, which have become progressively more sophisticated, there has been relatively little progress in estimating patient-specific wall strength. This is because wall strength cannot be inferred non-invasively, and measurements from excised patient tissues show a large spectrum of wall strength values. In this review, we highlight studies that investigated the relationship between biomechanics and AAA rupture risk. We conclude that combining wall stress and wall strength approximations should provide better estimations of AAA rupture risk. However, before personalized biomechanical AAA risk assessment can become a reality, better methods for estimating patient-specific wall properties or surrogate markers of aortic wall degradation are needed. Artificial intelligence methods can be key in stratifying patients, leading to personalized AAA risk assessment.

Abstract 482: Attachment Site Curvature of Thoracic Endografts is Correlated to Adjacent Aortic Wall Stress and Stress Distribution

2014 ◽  
Vol 34 (suppl_1) ◽  
Author(s):  
Nathan Couper ◽  
Michael Richards ◽  
Ankur Chandra
Keyword(s):  
Stress Distribution ◽  
Aortic Root ◽  
Mean Curvature ◽  
Aortic Wall ◽  
Attachment Site ◽  
Wall Stress ◽  
Patient Specific ◽  
Clinical Tool ◽  
Element Analysis ◽  
Clinical Series

INTRODUCTION: TEVAR has been seen to cause acute and chronic stent-induced tears of the adjacent aortic wall after treatment in 10-25% of cases with increasing frequency as the stent is placed closer to the aortic valve. The underlying cause for these tears and the ability to predict their occurrence is poorly understood. We hypothesize the cause of these tears is related to stent-induced changes in the adjacent aortic wall which could be quantified and predicted through finite element analysis (FEA) of stent-aorta interface. METHODS: Abaqus TM was used to resolve the FEA model of the stent-aorta interface in three configurations. The maximum principal stress in the vessel wall was averaged over the volume around the stent attachment point and the curvature of the stent was calculated at both the distal and proximal ends. (Figure 1). RESULTS: As the curvature of the attachment site increased, an increase in adjacent aortic wall stress was noted. These ranged from mean curvature (1/m) of 0.1 with wall stress of 49kPa for the distal attachment, position #2 to mean curvature of 6.7 and wall stress of 82kPa for the distal attachment site in position #3. There was an increase in maximum stress distribution as the TEVAR approached the aortic root of 104kPa, 109kPa, and 112kPa for positions 1-3 repectively. CONCLUSIONS: An increase in adjacent aortic wall stress and stress distribution was noted as TEVAR were placed closer to the aortic root which corresponds to the increase in stent-induced aortic tears observed in clinical series. This approach provides the basis for a predictive clinical tool to allow for patient-specific TEVAR planning with associated aortic wall stress analysis to minimize adjacent aortic trauma and assist in future stent design.

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