Patient-specific models of wall stress in abdominal aortic aneurysm: a comparison between MR and CT

2006 ◽  
Author(s):  
Sander de Putter ◽  
Marcel Breeuwer ◽  
Frans N. van de Vosse ◽  
Ursula Kose ◽  
Frans A. Gerritsen
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Wall Stress ◽  
Patient Specific ◽  
Abdominal Aortic

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.

Fully Coupled vs. Partially Coupled Fluid-Structure Interaction Methods for Patient-Specific Abdominal Aortic Aneurysm Biomechanics

2007 ◽  
Author(s):  
Christine M. Scotti ◽  
Ender A. Finol
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Fluid Structure Interaction ◽  
Wall Stress ◽  
Patient Specific ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Abdominal Aortic ◽  
Mechanical Factors ◽  
Fully Coupled

Primary among the mechanical factors linked with abdominal aortic aneurysm (AAA) rupture is peak wall stress, frequently quantified as either the maximum principal or Von Mises stress exerted along the diseased arterial wall. Intraluminal pressure, as an impinging normal force on the wall, has been hypothesized as the dominant influence on this stress and thus the majority of numerical modeling studies of AAA mechanics have focused on static computational solid stress (CSS) predictions [1,2]. Unfortunately, retrospective studies comparing the magnitude of wall stress with the failure strength of the aneurysmal wall have yet to consistently predict the outcome for patient-specific AAAs [3,4]. Previous studies have shown that hemodynamics also plays a significant role in both the biological and mechanical factors that exist within AAAs. In the present investigation, partially and fully coupled fluid-structure interaction (p-FSI and f-FSI, respectively) computations of patient-specific AAA models are presented and compared to identify the effect of fluid flow in the biomechanical environment of these aneurysms.

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.

scholarly journals Effect of intraluminal thrombus on wall stress in patient-specific models of abdominal aortic aneurysm

2002 ◽  
Vol 36 (3) ◽  
pp. 598-604 ◽  
Author(s):  
David H.J. Wang ◽  
Michel S. Makaroun ◽  
Marshall W. Webster ◽  
David A. Vorp
Keyword(s):  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Wall Stress ◽  
Patient Specific ◽  
Intraluminal Thrombus ◽  
Abdominal Aortic

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.

scholarly journals Endoleak Assessment Using Computational Fluid Dynamics and Image Processing Methods in Stented Abdominal Aortic Aneurysm Models

2016 ◽  
Vol 2016 ◽  
pp. 1-9
Author(s):  
Yueh-Hsun Lu ◽  
Karthick Mani ◽  
Bivas Panigrahi ◽  
Wen-Tang Hsu ◽  
Chia-Yuan Chen
Keyword(s):  
Fluid Dynamics ◽  
Image Processing ◽  
Computational Fluid Dynamics ◽  
Abdominal Aortic Aneurysm ◽  
Aortic Aneurysm ◽  
Wall Stress ◽  
Patient Specific ◽  
Processing Methods ◽  
Computed Tomography Images ◽  
Abdominal Aortic

Endovascular aortic aneurysm repair (EVAR) is a predominant surgical procedure to reduce the risk of aneurysm rupture in abdominal aortic aneurysm (AAA) patients. Endoleak formation, which eventually requires additional surgical reoperation, is a major EVAR complication. Understanding the etiology and evolution of endoleak from the hemodynamic perspective is crucial to advancing the current posttreatments for AAA patients who underwent EVAR. Therefore, a comprehensive flow assessment was performed to investigate the relationship between endoleak and its surrounding pathological flow fields through computational fluid dynamics and image processing. Six patient-specific models were reconstructed, and the associated hemodynamics in these models was quantified three-dimensionally to calculate wall stress. To provide a high degree of clinical relevance, the mechanical stress distribution calculated from the models was compared with the endoleak positions identified from the computed tomography images of patients through a series of imaging processing methods. An endoleak possibly forms in a location with high local wall stress. An improved stent graft (SG) structure is conceived accordingly by increasing the mechanical strength of the SG at peak wall stress locations. The presented analytical paradigm, as well as numerical analysis using patient-specific models, may be extended to other common human cardiovascular surgeries.

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