The Impact of the Right Coronary Artery Geometric Parameters on Hemodynamic Performance
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Coronary artery geometry can have a significant impact in the hemodynamic behavior of coronary blood flow, influencing atherosclerotic plaque formation. The present work focuses on, through a statistical study, the connection between several geometric parameters of the right coronary artery—ostium cross-sectional area, angles between the common trunk and the side-branches, tortuosity, curvature and cross-sectional area in each side-branch—and their influence on hemodynamic descriptors. Parameters such as low wall shear stress and local disturbed flow, which are associated with atherosclerosis formation, were analysed.
Computed tomography images of ten healthy individuals were selected to reconstruct in vivo three-dimensional models of right coronary arteries. Blood flow was simulated through a compliant model with realistic boundary conditions. Calculated hemodynamic descriptors values were correlated with the geometric parameters using the Pearson correlation coefficient (r) and the p value.
The strongest correlations were found in the middle and distal segments of the right coronary artery. A decrease in the ostium area promotes a decrease in the WSS magnitude from the proximal to the distal segment (r = 0.82). Very strong correlations (r > 0.90) were achieved between geometric parameters (cross-sectional area, angle, tortuosity) of the right-ventricular branch and the wall shear stress magnitude in the middle and distal segments.
Low values of tortuosity, smaller cross-sectional area and higher angle of the right-ventricular branch leads to a hemodynamic behavior more propitious to atherosclerosis formation, within the study cases. The right-ventricular branch seems to have the highest influence in the hemodynamic behavior of the right coronary artery.
KeywordsAtherosclerosis Right coronary artery Geometric parameters Statistics Fluid–structure interaction Wall shear stress-based descriptors
Authors gratefully acknowledge the financial support of the Foundation for Science and Technology (FCT), Portugal, the Engineering Faculty of University of Porto (FEUP), the Institute of Science and Innovation in Mechanical and Industrial Engineering (LAETA-INEGI), the Cardiovascular R&D Unit of the Medicine Faculty of University of Porto (FMUP) and the Cardiology Department of Gaia/Espinho Hospital Centre.
Conflict of interest
Authors declare that they have not any actual or potential conflict of interest.
All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5).
Informed consent was obtained from all patients for being included in the study.
- 1.Ansys® Academic Research 15.0. ANSYS Fluent Tutorial Guide., 2013.Google Scholar
- 6.Evans, J. D. Straightforward Statistics for the Behavioral Science. Boston: Brooks/Cole, 1995.Google Scholar
- 7.Feher, J. Vascular Function: Hemodynamics BT—Quantitative Human Physiology (2nd ed.). Boston: Academic Press, pp. 568–577, 2012. https://doi.org/10.1016/B978-0-12-800883-6.00054-9.Google Scholar
- 8.Gallo, D., G. Isu, D. Massai, F. Pennella, M. A. Deriu, R. Ponzini, C. Bignardi, A. Audenino, G. Rizzo, and U. Morbiducci. A survey of quantitative descriptors of arterial flows BT. In: Visualization and Simulation of Complex Flows in Biomedical Engineering, edited by R. Lima, Y. Imai, T. Ishikawa, and M. S. N. Oliveira. Dordrecht: Springer, 2014, pp. 1–24.Google Scholar
- 20.Knight, J., U. Olgac, S. C. Saur, D. Poulikakos, W. Marshall, P. C. Cattin, H. Alkadhi, and V. Kurtcuoglu. Choosing the optimal wall shear parameter for the prediction of plaque location—A patient-specific computational study in human right coronary arteries. Atherosclerosis 211:445–450, 2010.CrossRefGoogle Scholar
- 24.Malvè, M., A. M. Gharib, S. K. Yazdani, G. Finet, M. A. Martínez, R. Pettigrew, and J. Ohayon. Tortuosity of coronary bifurcation as a potential local risk factor for atherosclerosis: CFD steady state study based on in vivo dynamic CT measurements. Ann. Biomed. Eng. 43:82–93, 2014.CrossRefGoogle Scholar
- 26.Pinho, N., M. Bento, L. C. Sousa, S. Pinto, C. F. Castro, C. C. António, and E. Azevedo. Patient-Specific Study of a Stenosed Carotid Artery Bifurcation Using Fluid–Structure Interactive Simulation BT—VipIMAGE 2017: Proceedings of the VI ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing Porto, Portugal, Octob. edited by J. M. R. S. Tavares, and R. M. Natal Jorge. Cham: Springer International Publishing, 2018, pp. 495–503. https://doi.org/10.1007/978-3-319-68195-5_54.
- 27.Pinho, N., C. F. Castro, C. C. António, N. Bettencourt, L. C. Sousa, and S. I. S. Pinto. Correlation between geometric parameters of the left coronary artery and hemodynamic descriptors of atherosclerosis: FSI and statistical study. Med. Biol. Eng. Comput. 2018. https://doi.org/10.1007/s11517-018-1904-2.Google Scholar
- 30.Siogkas, P. K., M. I. Papafaklis, A. I. Sakellarios, K. A. Stefanou, C. V. Bourantas, L. S. Athanasiou, T. P. Exarchos, K. K. Naka, L. K. Michalis, O. Parodi, and D. I. Fotiadis. Patient-specific simulation of coronary artery pressure measurements: An in vivo three-dimensional validation study in humans. Biomed Res. Int. 2015, 2015.Google Scholar
- 31.Soulis, J. V., and D. K. Fytanidis. Oscillating shear index, wall shear stress and low density lipoprotein accumulation in human RCAs. Acad. Sci. USA 32:867–877, 2010.Google Scholar
- 32.Sousa, L. C., C. F. Castro, C. C. António, A. M. F. Santos, R. M. dos Santos, P. M. A. C. Castro, E. Azevedo, and J. M. R. S. Tavares. Toward hemodynamic diagnosis of carotid artery stenosis based on ultrasound image data and computational modeling. Med. Biol. Eng. Comput. 52:971–983, 2014.CrossRefGoogle Scholar
- 35.Torii, R., N. B. Wood, N. Hadjiloizou, A. W. Dowsey, A. R. Wright, A. D. Hughes, J. Davies, D. P. Francis, J. Mayet, G.-Z. Yang, S. A. M. Thom, and X. Y. Xu. Fluid–structure interaction analysis of a patient-specific right coronary artery with physiological velocity and pressure waveforms. Commun. Numer. Methods Eng. 25:565–580, 2009.MathSciNetCrossRefzbMATHGoogle Scholar
- 37.WHO. The Atlas of Heart Disease and Stroke. Geneva: WHO, 2010.Google Scholar