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Research Papers

Fluid-Structure Interaction Modeling of Abdominal Aortic Aneurysms: The Impact of Patient-Specific Inflow Conditions and Fluid/Solid Coupling

[+] Author and Article Information
Santanu Chandra

Department of Aerospace and Mechanical Engineering,
University of Notre Dame,
Notre Dame, IN 46556
e-mail: santanu.chandra@gmail.com

Samarth S. Raut

Department of Mechanical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15213
e-mail: sraut@andrew.cmu.edu

Anirban Jana

Pittsburgh Supercomputing Center,
Pittsburgh, PA 15213
e-mail: anirban@psc.edu

Robert W. Biederman

e-mail: rbiederm@wpahs.org

Mark Doyle

e-mail: mdoyle@wpahs.org
Cardiovascular Magnetic Resonance Imaging,
Allegheny General Hospital,
Pittsburgh, PA 15212

Satish C. Muluk

Division of Vascular Surgery,
Western Pennsylvania Allegheny Health Systems,
Pittsburgh, PA 15212
e-mail: muluk@usa.net

Ender A. Finol

Department of Biomedical Engineering,
AET 1.360,
The University of Texas at San Antonio,
One UTSA Circle,
San Antonio, TX 78249
e-mail: ender.finol@utsa.edu

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the JOURNAL OF BIOMECHANICAL ENGINEERING. Manuscript received April 10, 2012; final manuscript received March 22, 2013; accepted manuscript posted April 22, 2013; published online June 12, 2013. Assoc. Editor: Naomi Chesler.

J Biomech Eng 135(8), 081001 (Jun 12, 2013) (14 pages) Paper No: BIO-12-1135; doi: 10.1115/1.4024275 History: Received April 10, 2012; Revised March 22, 2013; Accepted April 22, 2013

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.

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Figures

Grahic Jump Location
Fig. 1

Steps in patient-specific AAA computational modeling: (a) CT images from AAA patient; (b) cross section processed with VESSEG showing segmentation of a CT image to identify lumen, ILT, and wall; (c) ADINA finite element models of lumen (fluid domain) and wall and thrombus (solid domain) and the surfaces and interfaces defined in each mesh. Iliac extensions shown are subject to a fully constrained boundary condition.

Grahic Jump Location
Fig. 2

Derivation of patient-specific inlet velocity boundary conditions: (a) MR imaging at specified planes; (b) segmenting the lumen boundary and extracting velocity components from the lumen region of the MR image at the inlet plane; (c) extracting inlet nodal coordinates from the CFD model; (d) and (e) performing Schwarz–Christoffel (SC) mapping and interpolation to apply the MR-derived velocity as a boundary condition to the CFD inlet nodes

Grahic Jump Location
Fig. 5

Fluid domain results from the fully coupled FSI simulation with three inlet velocity components prescribed from MRI (FSIf-Vxyz). Velocity streamlines depicting the flow at (a) phase 8 (systole, peak flow rate at inlet), (b) phase 10 (systole, peak pressure), (c) phase 20 (transition), (d) phase 30 (early diastole), and (e) phase 40 (late diastole). The colored background illustrates the pressure distribution on the lumen surface; max is the maximum pressure at each phase.

Grahic Jump Location
Fig. 6

Fluid domain results from fully coupled FSI simulation with three inlet velocity components prescribed from MRI (FSIf-Vxyz). Wall shear stress (WSS) at (a) phase 8 (systole, peak flow rate at inlet), (b) phase 10 (systole, peak pressure), (c) phase 20 (transition), (d) phase 30 (early diastole), and (e) phase 40 (late diastole). Max is the maximum WSS at each phase.

Grahic Jump Location
Fig. 12

(a) Volumetric flow rates at inlet (plane 1), aneurysm sac region (planes 2 and 3), and near the aortoiliac bifurcation (plane 4). Results are presented from a fully coupled FSI simulation with patient-specific inlet velocity components (FSIf-Vxyz) and one-way–coupled FSI simulation (FSI1-Vxyz).

Grahic Jump Location
Fig. 7

Structure domain results from fully coupled FSI simulation with three inlet velocity components (FSIf-Vxyz). Maximum principal stress σ1 at (a) phase 8 (systole, peak flow rate at inlet), (b) phase 10 (systole, peak pressure), (c) phase 20 (transition), (d) phase 30 (early diastole), and (e) phase 40 (late diastole). Max is the maximum stress at each phase.

Grahic Jump Location
Fig. 8

Structure domain results (cutaway plane revealing the interior of the AAA sac) from fully coupled FSI simulation with three inlet velocity components (FSIf-Vxyz). Maximum principal strain ε1 at (a) phase 8 (systole, peak flow rate at inlet), (b) phase 10 (systole, peak pressure), (c) phase 20 (transition), (d) phase 30 (early diastole), and (e) phase 40 (late diastole). Max is the maximum strain at each phase.

Grahic Jump Location
Fig. 9

Spatial maximum and averages of (a) σ1, (b) ε1, and (c) WSS are compared among the fully coupled FSI simulation results with three different fluid inlet boundary conditions (FSIf-Vxyz, FSIf-Vz, and FSIf-Vwom). Results are shown for 40 phases in the cardiac cycle.

Grahic Jump Location
Fig. 10

Spatial maxima and averages of (a) σ1, (b) ε1, and (c) WSS are compared between one-way–coupled FSI results with longitudinal velocity component (FSI1-Vz), fully coupled FSI results with same inlet condition (FSIf-Vz), and computational solid stress (CSSt) results. Notice that no fluid shear is obtained from the CSSt simulations. Results are shown for 40 phases in the cardiac cycle.

Grahic Jump Location
Fig. 11

(a) PC-MR images of the lumen and ILT/wall at the AAA midsection compared with velocity profiles obtained from three FSI simulation models (FSIf-Vxyz, FSIf-Vz, and FSIf-Vwom) at phase 4 (early systole), phase 8 (peak systole), phases 10 and 12 (late systole), phase 20 (early diastole), and phase 40 (late diastole); (b) comparison of volume flow rates obtained at the midsection from the PC-MRI (scaled) and FSI simulation results

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