Non-Newtonian Endothelial Shear Stress Simulation: Does It Matter?

Frontiers in Cardiovascular Medicine, vol. 9, pp. 835270

Abstract

Patient-specific coronary endothelial shear stress (ESS) calculations using Newtonian and non-Newtonian rheological models were performed to assess whether the common assumption of Newtonian blood behavior offers similar results to a more realistic but computationally expensive non-Newtonian model. 16 coronary arteries (from 16 patients) were reconstructed from optical coherence tomographic (OCT) imaging. Pulsatile CFD simulations using Newtonian and the Quemada non-Newtonian model were performed. Endothelial shear stress (ESS) and other indices were compared. Exploratory indices including local blood viscosity (LBV) were calculated from non-Newtonian simulation data. Compared to the Newtonian results, the non-Newtonian model estimates significantly higher time-averaged ESS (1.69 (IQR 1.36)Pa versus 1.28 (1.16)Pa, p < 0.001) and ESS gradient (0.90 (1.20)Pa/mm versus 0.74 (1.03)Pa/mm, p < 0.001) throughout the cardiac cycle, under-estimating the low ESS (<1Pa) area (37.20 ± 13.57% versus 50.43 ± 14.16%, 95% CI 11.28–15.18, p < 0.001). Similar results were also found in the idealized artery simulations with non-Newtonian median ESS being higher than the Newtonian median ESS (healthy segments: 0.8238Pa versus 0.6618Pa, p < 0.001 proximal; 0.8179Pa versus 0.6610Pa, p < 0.001 distal; stenotic segments: 0.8196Pa versus 0.6611Pa, p < 0.001 proximal; 0.2546Pa versus 0.2245Pa, p < 0.001 distal) On average, the non-Newtonian model has a LBV of 1.45 times above the Newtonian model with an average peak LBV of 40-fold. Non-Newtonian blood model estimates higher quantitative ESS values than the Newtonian model. Incorporation of non-Newtonian blood behavior may improve the accuracy of ESS measurements. The non-Newtonian model also allows calculation of exploratory viscosity-based hemodynamic indices, such as local blood viscosity, which may offer additional information to detect underlying atherosclerosis.

Authors 10

1. Vikas Thondapu

   The University of Melbourne · Yale University

   Affiliation as printed

   Department of Mechanical Engineering, Melbourne School of Engineering, University of Melbourne, Parkville, VIC, Australia

   Department of Medicine, Faculty of Medicine, Melbourne Medical School, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia

   Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, United States

2. Daisuke Shishikura

   Osaka Medical and Pharmaceutical University

   Affiliation as printed

   Department of Cardiology, Osaka Medical and Pharmaceutical University, Osaka, Japan

3. Jouke Dijkstra Aachen Department of Radiology Division of Image Processing (LKEB)

   Leiden University Medical Center

   Affiliation as printed

   Department of Radiology, Division of Image Processing, Leiden University Medical Center, Leiden, Netherlands

4. Shuang Jie Zhu

   The University of Melbourne

   Affiliation as printed

   Department of Mechanical Engineering, Melbourne School of Engineering, University of Melbourne, Parkville, VIC, Australia

5. Eve Revalor

   The University of Melbourne

   Affiliation as printed

   Department of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Parkville, VIC, Australia

   Department of Medicine, Faculty of Medicine, Melbourne Medical School, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia

6. Patrick W.J.C. Serruys

   Ollscoil na Gaillimhe – University of Galway · Imperial College London

   Affiliation as printed

   Department of Cardiology, National University of Ireland Galway (NUIG), Galway, Ireland

   National Heart and Lung Institute, Imperial College London, London, United Kingdom

7. William Joseph van Gaal

   The University of Melbourne · Northern Hospital

   Affiliation as printed

   Department of Cardiology, Northern Hospital, Epping, NSW, Australia

   Department of Medicine, Faculty of Medicine, Melbourne Medical School, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia

8. Eric Poon

   The University of Melbourne

   Affiliation as printed

   Department of Medicine, Faculty of Medicine, Melbourne Medical School, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia

9. Andrew S. H. Ooi

   The University of Melbourne

   Affiliation as printed

   Department of Mechanical Engineering, Melbourne School of Engineering, University of Melbourne, Parkville, VIC, Australia

10. Peter Barlis corresponding

    The University of Melbourne

    Affiliation as printed

    Department of Medicine, Faculty of Medicine, Melbourne Medical School, Dentistry and Health Sciences, University of Melbourne, Parkville, VIC, Australia