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Research Papers

Effects of Intraluminal Thrombus on Patient-Specific Abdominal Aortic Aneurysm Hemodynamics via Stereoscopic Particle Image Velocity and Computational Fluid Dynamics Modeling

[+] Author and Article Information
Chia-Yuan Chen

Department of Mechanical Engineering,
National Cheng Kung University,
Tainan 70101, Taiwan

Raúl Antón

Mechanical Engineering Department,
Tecnun-University of Navarra,
Navarra 20018, Spain

Ming-yang Hung, Prahlad Menon

Department of Biomedical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15219

Ender A. Finol

Department of Biomedical Engineering,
The University of Texas at San Antonio,
San Antonio, TX 78249

Kerem Pekkan

Department of Biomedical Engineering,
Carnegie Mellon University,
Pittsburgh, PA 15219
e-mail: kpekkan@andrew.cmu.edu

1Corresponding author.

Contributed by the Bioengineering Division of ASME for publication in the Journal OF Biomechanical Engineering. Manuscript received December 8, 2012; final manuscript received November 30, 2013; accepted manuscript posted December 5, 2013; published online February 13, 2014. Assoc. Editor: Naomi Chesler.

J Biomech Eng 136(3), 031001 (Feb 13, 2014) (9 pages) Paper No: BIO-12-1603; doi: 10.1115/1.4026160 History: Received December 08, 2012; Revised November 30, 2013; Accepted December 05, 2013

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.

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References

Upchurch, G. R., and Schaub, T. A., 2006, “Abdominal Aortic Aneurysm,” Am. Family Physician, 73(7), pp. 1198–1204.
Lopez-Candales, A., Holmes, D. R., Liao, S. X., Scott, M. J., Wickline, S. A., and Thompson, R. W., 1997, “Decreased Vascular Smooth Muscle Cell Density in Medial Degeneration of Human Abdominal Aortic Aneurysms,” Am. J. Pathol., 150(3), pp. 993–1007. [PubMed]
Ailawadi, G., Eliason, J. L., and Upchurch, G. R., 2003, “Current Concepts in the Pathogenesis of Abdominal Aortic Aneurysm,” J. Vasc. Surg., 38, pp. 584–588. [CrossRef] [PubMed]
Watton, P. N., Raberger, N. B., Holzapfel, G. A., and Ventikos, Y., 2009, “Coupling the Hemodynamic Environment to the Evolution of Cerebral Aneurysms: Computational Framework and Numerical Examples,” ASME J. Biomech. Eng., 131, p. 101003. [CrossRef]
Anderson, R. N., 2002, “Deaths: Leading Causes for 2000,” Natl. Vital Stat. Rep., 50(16), pp. 1–85. [PubMed]
Wassef, M., Baxter, B. T., Chisholm, R. L.Dalman, R. L., Fillinger, Heinecke, J., 2001, “Pathogenesis of Abdominal Aortic Aneurysms: A Multidisciplinary Research Program Supported by the National Heart, Lung, and Blood Institute,” J. Vasc. Surg., 34, pp. 730–738. [CrossRef] [PubMed]
Wang, D. H., Makaroun, M. S., Webster, M. W., and Vorp, D. A., 2002, “Effect of Intraluminal Thrombus on Wall Stress in Patient-Specific Models of Abdominal Aortic Aneurysm,” J. Vasc. Surg., 36, pp. 598–604. [CrossRef] [PubMed]
Harter, L. P., Gross, B. H., Callen, P. W., and Barth, R. A., 1982, “Ultrasonic Evaluation of Abdominal Aortic Thrombus,” J. Ultrasound Med., 1(8), pp. 315–318. [PubMed]
Kleinstreuer, C., and Li, Z., 2006, “Analysis and Computer Program for Rupture-Risk Prediction of Abdominal Aortic Aneurysms,” Biomed. Eng. Online, 5, p. 19. [CrossRef] [PubMed]
Schurink, G. W., van Baalen, J. M., Visser, M. J., and van Bockel, J. H., 2000, “Thrombus Within an Aortic Aneurysm Does Not Reduce Pressure on the Aneurysmal Wall,” J. Vasc. Surg., 31, pp. 501–506. [CrossRef] [PubMed]
Vorp, D. A., Mandarino, W. A., Webster, M. W., and Gorcsan, J., 3rd, 1996, “Potential Influence of Intraluminal Thrombus on Abdominal Aortic Aneurysm As Assessed by a New Non-Invasive Method,” Cardiovasc. Surg., 4, pp. 732–739. [CrossRef] [PubMed]
Biasetti, J., Hussain, F., and Gasser, T. C., 2011, “Blood Flow and Coherent Vortices in the Normal and Aneurysmatic Aortas: A Fluid Dynamical Approach to Intraluminal Thrombus Formation,” J. R. Soc. Interface, 8, pp. 1449–1461. [CrossRef] [PubMed]
Shojima, M., Oshima, M., Takagi, K., Torii, R., Hayakawa, M., Katada, K., 2004, “Magnitude and Role of Wall Shear Stress on Cerebral Aneurysm: Computational Fluid Dynamic Study of 20 Middle Cerebral Artery Aneurysms,” Stroke, 35, pp. 2500–2505. [CrossRef] [PubMed]
Di Martino, E. S., and Vorp, D. A., 2003, “Effect of Variation in Intraluminal Thrombus Constitutive Properties on Abdominal Aortic Aneurysm Wall Stress,” Ann. Biomed. Eng., 31, pp. 804–809. [CrossRef] [PubMed]
Basciano, C., Kleinstreuer, C., Hyun, S., and Finol, E. A., 2011, “A Relation Between Near-Wall Particle-Hemodynamics and Onset of Thrombus Formation in Abdominal Aortic Aneurysms,” Ann. Biomed. Eng., 39, pp. 2010–2026. [CrossRef] [PubMed]
Finol, E. A., and Amon, C. H., 2001, “Blood Flow in Abdominal Aortic Aneurysms: Pulsatile Flow Hemodynamics,” ASME J. Biomech. Eng., 123(5), pp. 474–484. [CrossRef]
Finol, E. A., and Amon, C. H., 2002, “Flow-Induced Wall Shear Stress in Abdominal Aortic Aneurysms: Part I—Steady Flow Hemodynamics,” Comput. Methods Biomech. Biomed. Eng., 5, pp. 309–318. [CrossRef]
Finol, E. A., Keyhani, K., and Amon, C. H., 2003, “The Effect of Asymmetry in Abdominal Aortic Aneurysms Under Physiologically Realistic Pulsatile Flow Conditions,” ASME J. Biomech. Eng., 125(2), pp. 207–217. [CrossRef]
Scotti, C. M., Shkolnik, A. D., Muluk, S. C., and Finol, E. A., 2005, “Fluid–Structure Interaction in Abdominal Aortic Aneurysms: Effects of Asymmetry and Wall Thickness,” Biomed, Eng, Online, 4, p. 64. [CrossRef]
Scotti, C. M., and Finol, E. A., 2007, “Compliant Biomechanics of Abdominal Aortic Aneurysms: A Fluid–Structure Interaction Study,” Comput. Struct., 85, pp. 1097–1113. [CrossRef]
Scotti, C. M., Jimenez, J., Muluk, S. C., and Finol, E. A., 2008, “Wall Stress and Flow Dynamics in Abdominal Aortic Aneurysms: Finite Element Analysis vs. Fluid–Structure Interaction,” Comput. Methods Biomech. Biomed. Eng., 11, pp. 301–322. [CrossRef]
Le, T. B., Borazjani, I., and Sotiropoulos, F., 2010, “Pulsatile Flow Effects on the Hemodynamics of Intracranial Aneurysms,” ASME J. Biomech. Eng., 132(11), p. 111009. [CrossRef]
Lindken, R., Rossi, M., Grosse, S., and Westerweel, J., 2009, “Micro-Particle Image Velocimetry (microPIV): Recent Developments, Applications, and Guidelines,” Lab Chip, 9, pp. 2551–2567. [CrossRef] [PubMed]
Vennemann, P., Lindken, R., and Westerweel, J., 2007, “In Vivo Whole-Field Blood Velocity Measurement Techniques,” Exp. Fluids, 42, pp. 495–511. [CrossRef]
Stamatopoulos, C., Mathioulakis, D. S., Papaharilaou, Y., and Katsamouris, A., 2011, “Experimental Unsteady Flow Study in a Patient-Specific Abdominal Aortic Aneurysm Model,” Exp. Fluids, 50, pp. 1695–1709. [CrossRef]
Boutsianis, E., Guala, M., Olgac, U., Wildermuth, S., Hoyer, K., Ventikos, Y., 2009, “CFD and PTV Steady Flow Investigation in an Anatomically Accurate Abdominal Aortic Aneurysm,” ASME J. Biomech. Eng., 131(1), p. 011008. [CrossRef]
Yoganathan, A. P., Wang, C. A., Pekkan, K., de Zelicourt, D., Horner, M., Parihar, A., 2007, “Progress in the CFD Modeling of Flow Instabilities in Anatomical Total Cavopulmonary Connections,” Ann. Biomed. Eng., 35, pp. 1840–1856. [CrossRef] [PubMed]
Hoi, Y., Woodward, S. H., Kim, M., Taulbee, D. B., and Meng, H., 2006, “Validation of CFD Simulations of Cerebral Aneurysms With Implication of Geometric Variations,” ASME J. Biomech. Eng., 128(6), pp. 844–851. [CrossRef]
Scottie, C., 2007, “In Vitro and in Vivo Dynamics of Abdominal Aortic Aneurysms: A Fluid–Structure Interaction Study,” Ph.D., Biomedical Engineering, Carnegie Mellon University.
Lara, M., Chen, C. Y., Mannor, P., Dur, O., Menon, P. G., Yoganathan, A. P., 2011, “Hemodynamics of the Hepatic Venous Three-Vessel Confluences Using Particle Image Velocimetry,” Ann. Biomed. Eng.
Fraser, K. H., Li, M. X., Lee, W. T., Easson, W. J., and Hoskins, P. R., 2009, “Fluid–Structure Interaction in Axially Symmetric Models of Abdominal Aortic Aneurysms,” Proc. Inst. Mech. Eng. H, 223, pp. 195–209. [CrossRef] [PubMed]
Keane, R. D., and Adrian, R. J., 1990, “Optimization of Particle Image Velocimeters. 1. Double Pulsed Systems,” Measure. Sci. Technol., 1, pp. 1202–1215. [CrossRef]
Wieneke, B., 2005, “Stereo-PIV Using Self-Calibration on Particle Images,” Exp. Fluids, 39, pp. 267–280. [CrossRef]
Lindken, R., Westerweel, J., and Wieneke, B., 2006, “Stereoscopic Micro Particle Image Velocimetry,” Exp. Fluids, 41, pp. 161–171. [CrossRef]
Antiga, L., Ene-Iordache, B., Caverni, L., Cornalba, G. P., and Remuzzi, A., 2002, “Geometric Reconstruction for Computational Mesh Generation of Arterial Bifurcations From CT Angiography,” Comput. Med. Imaging Graphics, 26, pp. 227–235. [CrossRef]
Prakash, S., and Ethier, C. R., 2001, “Requirements for Mesh Resolution in 3D Computational Hemodynamics,” ASME J. Biomech. Eng., 123(2), pp. 134–144. [CrossRef]
Ge, L., and Sotiropoulos, F., 2007, “A Numerical Method for Solving the 3D Unsteady Incompressible Navier-Stokes Equations in Curvilinear Domains With Complex Immersed Boundaries,” J. Comput. Phys., 225, pp. 1782–1809. [CrossRef] [PubMed]
Menon, P., Teslovich, N., Chen, C.-Y., Undar, A., and Pekkan, K., 2013, “Characterization of Neonatal Aortic Cannulae Jet Flow Regimes for Improved Cardiopulmonary Bypass,” J. Biomech., 46, pp. 362–372. [CrossRef] [PubMed]
Pekkan, K., de Zelicourt, D., Ge, L., Sotiropoulos, F., Frakes, D., Fogel, M. A., 2005, “Physics-Driven CFD Modeling of Complex Anatomical Cardiovascular Flows—A TCPC Case Study,” Ann. Biomed. Eng., 33, pp. 284–300. [CrossRef] [PubMed]
Bluestein, D., Niu, L., Schoephoerster, R. T., and Dewanjee, M. K., 1996, “Steady Flow in an Aneurysm Model: Correlation Between Fluid Dynamics and Blood Platelet Deposition,” ASME J. Biomech. Eng., 118(3), pp. 280–286. [CrossRef]
Salsac, A. V., Sparks, S. R., and Lasheras, J. C., 2004, “Hemodynamic Changes Occurring During the Progressive Enlargement of Abdominal Aortic Aneurysms,” Ann. Vasc. Surg., 18, pp. 14–21. [CrossRef] [PubMed]
Deplano, V., Knapp, Y., Bertrand, E., and Gaillard, E., 2007, “Flow Behaviour in an Asymmetric Compliant Experimental Model for Abdominal Aortic Aneurysm,” J. Biomech., 40, pp. 2406–2413. [CrossRef] [PubMed]
Lawson, N. J., and Wu, J., 1997, “Three-Dimensional Particle Image Velocimetry: Error Analysis of Stereoscopic Techniques,” Measure. Sci. Technol., 8, pp. 894–900. [CrossRef]
Kung, E. O., Les, A. S., Medina, F., Wicker, R. B., McConnell, M. V., and Taylor, C. A., 2011, “In Vitro Validation of Finite-Element Model of AAA Hemodynamics Incorporating Realistic Outlet Boundary Conditions,” ASME J. Biomech. Eng., 133(2), p. 041003. [CrossRef]
Antón, R., Chen, C.-Y., Hung, M.-Y., Finol, E. A., and Pekkan, K., “Experimental and Computational Investigation of the Patient-Specific Abdominal Aortic Aneurysm Pressure Field,” Comput. Methods Biomech. Biomed. Eng., in press.

Figures

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Fig. 1

Transparent patient-specific rapid prototype replica, representative measurement planes, and corresponding anatomical views showing the geometry of each lumen. (a) AAA model without ILT and (b) AAA model with ILT. Left column: Transparent models; middle and right column: CFD models. Positions of three stereoscopic PIV measurement planes are outlined in red (top plane), green (middle plane), and blue (bottom plane).

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Fig. 2

Schematic representation of stereoscopic PIV configuration [45]

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Fig. 3

Before and after image preprocessing of stereoscopic PIV data from AAA model without ILT (left column: before; right column: after image preprocessing). Time between frame 1 and frame 2 was set to be 1.5 ms.

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Fig. 4

Stereoscopic PIV velocity data of both AAA models (a) without and (b) with ILT. Velocity fields on each measurement plane are shown in x (the first row), y (the second row), and z (the third row) directions. Unit of color bars: m/s.

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Fig. 5

Comparison of flow patterns between AAA models with and without ILT. A vortex was observed in the middle plane near the aneurysm bulge region of the AAA model without ILT as evidenced by (a) Vz contour map overlaid with 2D streamtraces at three measurement planes and (c) 2D velocity vectors overlapped with raw PIV image. No vortex was found in the same region of the AAA model with ILT as evidenced by (b) and (d).

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Fig. 6

Wall shear stress distribution for both AAA models. Unit of the color bar: Pa.

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Fig. 7

(a) Out-of-plane velocity data comparison of patient-specific AAA model without ILT using stereoscopic PIV, Fluent, and in-house CFD methods. Left panel: Out-of-plane velocity contour maps; right panel: quantitative velocity profile comparison. Data were extracted from each A-B line (50 mm) of contour plots (left panel). Correlation coefficients between stereoscopic PIV and Fluent, stereoscopic PIV and in-house CFD, and Fluent and in-house CFD are 0.92, 0.85, and 0.96, respectively. Unit of the color bar: m/s.

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