Computational analysis of oxygen transport in a patient-specific model of abdominal aortic aneurysm with intraluminal thrombus

The pathology of the human abdominal aortic aneurysm (AAA) and its relationship to the later complication of intraluminal thrombus (ILT) formation remains unclear. The hemodynamics in the diseased abdominal aorta are hypothesized to be a key contributor to the formation and growth of ILT. The objective of this investigation is to establish a reliable 3D flow visualization method with corresponding validation tests with high confidence in order to provide insight into the basic hemodynamic features for a better understanding of hemodynamics in AAA pathology and seek potential treatment for AAA diseases. A stereoscopic particle image velocity (PIV) experiment was conducted using transparent patient-specific experimental AAA models (with and without ILT) at three axial planes. Results show that before ILT formation, a 3D vortex was generated in the AAA phantom. This geometry-related vortex was not observed after the formation of ILT, indicating its possible role in the subsequent appearance of ILT in this patient. It may indicate that a longer residence time of recirculated blood flow in the aortic lumen due to this vortex caused sufficient shear-induced platelet activation to develop ILT and maintain uniform flow conditions. Additionally, two computational fluid dynamics (CFD) modeling codes (Fluent and an in-house cardiovascular CFD code) were compared with the two-dimensional, three-component velocity stereoscopic PIV data. Results showed that correlation coefficients of the out-of-plane velocity data between PIV and both CFD methods are greater than 0.85, demonstrating good quantitative agreement. The stereoscopic PIV study can be utilized as test case templates for ongoing efforts in cardiovascular CFD solver development. Likewise, it is envisaged that the patient-specific data may provide a benchmark for further studying hemodynamics of actual AAA, ILT, and their convolution effects under physiological conditions for clinical applications.

Download Full-text

Data-Guided Growth and Remodeling Model of Abdominal Aortic Aneurysm Accounting for the Bio-chemical Effects of Intraluminal Thrombus

Computational Biomechanics for Medicine ◽

10.1007/978-3-319-15503-6_2 ◽

2015 ◽

pp. 13-23

Author(s):

Mehdi Farsad ◽

Byron A. Zambrano ◽

Seungik Baek

Keyword(s):

Abdominal Aortic Aneurysm ◽

Aortic Aneurysm ◽

Growth And Remodeling ◽

Guided Growth ◽

Intraluminal Thrombus ◽

Chemical Effects ◽

Abdominal Aortic

Download Full-text

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

Journal of Biomechanical Engineering ◽

10.1115/1.4034425 ◽

2016 ◽

Vol 138 (10) ◽

Cited By ~ 5

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.

Download Full-text