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Patient-Specific Simulations Reveal Significant Differences in Mechanical Stimuli in Venous and Arterial Coronary Grafts

  • Abhay B. Ramachandra
  • Andrew M. Kahn
  • Alison L. MarsdenEmail author
Original Article

Abstract

Mechanical stimuli are key to understanding disease progression and clinically observed differences in failure rates between arterial and venous grafts following coronary artery bypass graft surgery. We quantify biologically relevant mechanical stimuli, not available from standard imaging, in patient-specific simulations incorporating non-invasive clinical data. We couple CFD with closed-loop circulatory physiology models to quantify biologically relevant indices, including wall shear, oscillatory shear, and wall strain. We account for vessel-specific material properties in simulating vessel wall deformation. Wall shear was significantly lower (p = 0.014*) and atheroprone area significantly higher (p = 0.040*) in venous compared to arterial grafts. Wall strain in venous grafts was significantly lower (p = 0.003*) than in arterial grafts while no significant difference was observed in oscillatory shear index. Simulations demonstrate significant differences in mechanical stimuli acting on venous vs. arterial grafts, in line with clinically observed graft failure rates, offering a promising avenue for stratifying patients at risk for graft failure.

Keywords

Coronary bypass Vein graft Computational fluid dynamics Wall shear Mammary artery Multiscale model Risk stratification Hemodynamics Patient-specific modeling 

Abbreviation

CABG

Coronary artery bypass graft

CAD

Coronary artery disease

CFD

Computational fluid dynamics

CT

Computed tomography

GSI1

Green Strain Invariant1

IMA

Internal mammary artery

LPN

Lumped parameter network

OSI

Oscillatory shear index

SVG

Saphenous vein graft

WSS

Wall shear stress

Notes

Acknowledgments

The authors wish to thank Weiguang Yang, PhD, for his help with variable wall property code, Christopher Chu for his help with patient model construction from CT scans, and Wendy Davila for her help with data collection.

Compliance with Ethical Standards

Funding

This work was supported by NIH grant (NIH R01-RHL123689A), NSF CAREER Award OCI-1150184 to A. L. M., and a Burroughs Wellcome Fund Career Award at the Scientific Interface to A. L. M. Computational resources were provided by a grant to A. L. M (TG-CTS130034) through the Extreme Science and Engineering Discovery Environment (XSEDE).

Conflict of Interest

Author A. B. R. declares that he has no conflict of interest. Author A. K. declares that he has no conflict of interest. Author A.L.M. declares that she has no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. Patient recruitment and access to non-invasive clinical data (computer tomographic (CT) images, echocardiography data) was carried out according to protocols approved by the University of California and Stanford University institutional review boards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Abhay B. Ramachandra
    • 1
    • 2
  • Andrew M. Kahn
    • 3
  • Alison L. Marsden
    • 4
    Email author
  1. 1.Department of Mechanical and Aerospace EngineeringUniversity of California San DiegoLa Jolla, CA 92093USA
  2. 2.Departments of Pediatrics and Bioengineering, Institute for Computational and Mathematical EngineeringStanford UniversityStanfordUSA
  3. 3.Department of MedicineUniversity of California San DiegoLa Jolla, CA 92093USA
  4. 4.Departments of Pediatrics and Bioengineering, Institute for Computational and Mathematical EngineeringStanford UniversityStanford,USA

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