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.

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 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.

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.

Towards Patient-Specific Modeling of an Enlarging Abdominal Aortic Aneurysm

2009 ◽  
Author(s):  
S. Zeinali-Davarani ◽  
A. Sheidaei ◽  
S. Baek
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Patient Specific ◽  
Element Analysis ◽  
Computational Framework ◽  
Aneurysmal Wall ◽  
Constrained Mixture ◽  
Abdominal Aortic ◽  
Modeling Stress ◽  
Patient Specific Modeling

There has been a clear need for better understanding of the progression of abdominal aortic aneurysm (AAA) and obtaining reliable prediction of the AAA rupture. Finite element analysis (FEA) using non-axisymmetric models of AAAs provides better estimation of stress distribution in the aneurysmal wall with complex shapes [1]. However, FEA alone does not provide a mathematical description for the evolution of an AAA through growth and remodeling (G&R). A computational framework for modeling stress-mediated growth and structural remodeling of the arterial wall under physiological and pathological conditions has been suggested using a constrained mixture assumption [2]. Stress-mediated enlargement of intracranial aneurysms has been investigated using idealized axisymmetric geometries [3,4]. The kinetics of stress-mediated turnover of collagen fiber families and degradation of elastin were found to have particular importance in the G&R of aneurysmal wall.

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