Non-invasive evaluation of blood flow through a healthy and stenosed coronary artery

Authors

  • Mohammed Ghalib Al-Azawy Doctor, Mechanical Eng.Dept - Wasit University
  • Zahraa Ahmed Hamza
  • Alaa Ahmed Alkinani

DOI:

https://doi.org/10.31185/ejuow.Vol10.Iss3.369

Keywords:

Coronary stenosis, hemodynamic impacts, stenosis severity, computational fluid dynamics, non-Newtonian fluid flow, turbulent flow

Abstract

The current numerical analysis was utilised to compare the hemodynamic effects caused by flow disruptions in coronary arteries with and without stenosis in order to evaluate the hemodynamic importance of patient-specific coronary stenosis using Computational Fluid Dynamics (CFD) to provide information to the public, particularly surgeons, and assist them in reducing the risk of stenosis. Assuming the flow is turbulent and non-Newtonian viscosity, the Carreau model is incorporated by utilizing STAR-CCM+ 2021.2.1. The test model is a patient-specific coronary stenosis with area stenosis (60%). The velocity, shear stress, and strain rate were evaluated and revealed that the stenosed artery experiences more hemodynamic impacts as the flow rate increases compared to the normal artery. The turbulent kinetic energy and turbulent viscosity ratio findings showed that the TKE and TVR are almost the same downstream of the stenoses, with the TKE and TVR being somewhat higher with the stenosed artery model than the unstenosed artery model, and it increases as the flow increases. Moreover, to determine the stenosis severity, the coefficient of pressure drop (CDP) and lesion flow coefficient (LFC) were used and showed that the CDP value be higher in stenosed artery (107pa) compared to a normal artery (5.2pa) but it was less when the flow increased (84.4pa), (2.5pa) respectively. whereas the LFC value in the stenoses artery is higher (0.61) and rises as flow increases (0.69). 

References

Carvalho, V., Rodrigues, N., Lima, R. A., & Teixeira, S. (2020). Numerical simulation of blood pulsatile flow in stenotic coronary arteries: The effect of turbulence modeling and non-Newtonian assumptions. Proceedings - 24th International Conference on Circuits, Systems, Communications and Computers, CSCC 2020, 112–116. https://doi.org/10.1109/CSCC49995.2020.00027 DOI: https://doi.org/10.1109/CSCC49995.2020.00027

Carvalho, V., Pinho, D., Lima, R. A., Teixeira, J. C., & Teixeira, S. (2021). Blood flow modeling in coronary arteries: A review. Fluids, 6(2). https://doi.org/10.3390/fluids6020053 DOI: https://doi.org/10.3390/fluids6020053

Toivari, M., Nygård, Y., Kumpula, E. P., Vehkomäki, M. L., Benčina, M., Valkonen, M., … Wiebe, M. G. (2012). Metabolic engineering of Saccharomyces cerevisiae for bioconversion of d-xylose to d-xylonate. Metabolic Engineering, 14(4), 427–436. https://doi.org/10.1016/j.ymben.2012.03.002 DOI: https://doi.org/10.1016/j.ymben.2012.03.002

Lopes, D., Puga, H., Teixeira, J., & Lima, R. (2020). Blood flow simulations in patient-specific geometries of the carotid artery: A systematic review. Journal of Biomechanics, 111, 110019. https://doi.org/10.1016/j.jbiomech.2020.110019 DOI: https://doi.org/10.1016/j.jbiomech.2020.110019

De Nisco, G., Hoogendoorn, A., Chiastra, C., Gallo, D., Kok, A. M., Morbiducci, U., & Wentzel, J. J. (2020). The impact of helical flow on coronary atherosclerotic plaque development. Atherosclerosis, 300(December 2019), 39–46. https://doi.org/10.1016/j.atherosclerosis.2020.01.027 DOI: https://doi.org/10.1016/j.atherosclerosis.2020.01.027

Moreno, C., & Bhaganagar, K. (2013). Modeling of stenotic coronary artery and implications of plaque morphology on blood flow. Modelling and Simulation in Engineering, 2013. https://doi.org/10.1155/2013/390213 DOI: https://doi.org/10.1155/2013/390213

Mahalingam, A., Gawandalkar, U. U., Kini, G., Buradi, A., Araki, T., Ikeda, N., … Suri, J. S. (2016). Numerical analysis of the effect of turbulence transition on the hemodynamic parameters in human coronary arteries. Cardiovascular Diagnosis and Therapy, 6(3), 208–220. https://doi.org/10.21037/cdt.2016.03.08 DOI: https://doi.org/10.21037/cdt.2016.03.08

Kabinejadian, F., Ghista, D. N., Su, B., Kaabi Nezhadian, M., Chua, L. P., Yeo, J. H., & Leo, H. L. (2014). In vitro measurements of velocity and wall shear stress in a novel sequential anastomotic graft design model under pulsatile flow conditions. Medical Engineering and Physics, 36(10), 1233–1245. https://doi.org/10.1016/j.medengphy.2014.06.024 DOI: https://doi.org/10.1016/j.medengphy.2014.06.024

Friedman, M. H., & Giddens, D. P. (2005). Blood flow in major blood vessels - Modeling and experiments. Annals of Biomedical Engineering, 33(12 SPEC. ISS.), 1710–1713. https://doi.org/10.1007/s10439-005-8773-1 DOI: https://doi.org/10.1007/s10439-005-8773-1

Fatahian, E., Kordani, N., & Fatahian, H. (2018). The application of computational fluid dynamics (CFD) method and several rheological models of blood flow: A review. Gazi University Journal of Science, 31(4), 1213–1227.

Zakaria, M. S., Zainudin, S. H., Abdullah, H., Yuan, C. S., Latif, M. J. A., & Osman, K. (2019). CFD Simulation of Non-Newtonian Effect on Hemodynamics Characteristics of Blood Flow through Benchmark Nozzle. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 64(1), 117–125.

Young, D. F. (1968). Effect of a time-dependent stenosis on flow through a tube. Journal of Manufacturing Science and Engineering, Transactions of the ASME, 90(2), 248–254. https://doi.org/10.1115/1.3604621 DOI: https://doi.org/10.1115/1.3604621

Jahangiri, M., Saghafian, M., & Sadeghi, M. R. (2015). Numerical simulation of hemodynamic parameters of turbulent and pulsatile blood flow in flexible artery with single and double stenoses. Journal of Mechanical Science and Technology, 29(8), 3549–3560. https://doi.org/10.1007/s12206-015-0752-3 DOI: https://doi.org/10.1007/s12206-015-0752-3

Doost, S. N., Zhong, L., Su, B., & Morsi, Y. S. (2016). The numerical analysis of non-Newtonian blood flow in human patient-specific left ventricle. Computer Methods and Programs in Biomedicine, 127, 232–247. https://doi.org/10.1016/j.cmpb.2015.12.020 DOI: https://doi.org/10.1016/j.cmpb.2015.12.020

Apostolidis, A. J., Moyer, A. P., & Beris, A. N. (2016). Non-Newtonian effects in simulations of coronary arterial blood flow. Journal of Non-Newtonian Fluid Mechanics, 233, 155–165. https://doi.org/10.1016/j.jnnfm.2016.03.008 DOI: https://doi.org/10.1016/j.jnnfm.2016.03.008

Abbasian, M., Shams, M., Valizadeh, Z., Moshfegh, A., Javadzadegan, A., & Cheng, S. (2020). Effects of different non-Newtonian models on unsteady blood flow hemodynamics in patient-specific arterial models with in-vivo validation. Computer Methods and Programs in Biomedicine, 186, 105185. https://doi.org/10.1016/j.cmpb.2019.105185 DOI: https://doi.org/10.1016/j.cmpb.2019.105185

Amir Hossain Golshirazi, Etemad, S. G., & Javanbakht, V. (2020). Three-Dimensional Numerical Investigation of Steady State and Physiologically Realistic Pulsatile Flow through the Left Coronary Curved Artery with Stenosis. Theoretical Foundations of Chemical Engineering, 54(3), 489–499. https://doi.org/10.1134/S0040579520030045 DOI: https://doi.org/10.1134/S0040579520030045

Razavi, A., Shirani, E., & Sadeghi, M. R. (2011). Numerical simulation of blood pulsatile flow in a stenosed carotid artery using different rheological models. Journal of Biomechanics, 44(11), 2021–2030. https://doi.org/10.1016/j.jbiomech.2011.04.023 DOI: https://doi.org/10.1016/j.jbiomech.2011.04.023

Chaichana, T., Sun, Z., & Jewkes, J. (2012). Computational fluid dynamics analysis of the effect of plaques in the left coronary artery. Computational and Mathematical Methods in Medicine, 2012, 1–9. https://doi.org/10.1155/2012/504367 DOI: https://doi.org/10.1155/2012/504367

Gaudio, L. T., Caruso, M. V., De Rosa, S., Indolfi, C., & Fragomeni, G. (2018). Different Blood Flow Models in Coronary Artery Diseases: Effects on hemodynamic parameters. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2018-July, 3185–3188. https://doi.org/10.1109/EMBC.2018.8512917 DOI: https://doi.org/10.1109/EMBC.2018.8512917

Pandey, R., Kumar, M., & Srivastav, V. K. (2020). Numerical computation of blood hemodynamic through constricted human left coronary artery: Pulsatile simulations. Computer Methods and Programs in Biomedicine, 197, 105661. https://doi.org/10.1016/j.cmpb.2020.105661 DOI: https://doi.org/10.1016/j.cmpb.2020.105661

Mittal, R., Simmons, S. P., & Udaykumar, H. S. (2001). Application of large-eddy simulation to the study of pulsatile flow in a modeled arterial stenosis. Journal of Biomechanical Engineering, 123(4), 325–332. https://doi.org/10.1115/1.1385840 DOI: https://doi.org/10.1115/1.1385840

Zhang, J., Zhang, P., Fraser, K. H., Griffith, B. P., & Wu, Z. J. (2013). Comparison and Experimental Validation of Fluid Dynamic Numerical Models for a Clinical Ventricular Assist Device. Artificial Organs, 37(4), 380–389. https://doi.org/10.1111/j.1525-1594.2012.01576.x DOI: https://doi.org/10.1111/j.1525-1594.2012.01576.x

Lee, T. S., Liao, W., & Low, H. T. (2003). Numerical simulation of turbulent flow through series stenoses. International Journal for Numerical Methods in Fluids, 42(7), 717–740. https://doi.org/10.1002/fld.550 DOI: https://doi.org/10.1002/fld.550

Lee, T. S., Liao, W., & Low, H. T. (2004). Numerical study of physiological turbulent flows through series arterial stenoses. International Journal for Numerical Methods in Fluids, 46(3), 315–344. https://doi.org/10.1002/fld.755 DOI: https://doi.org/10.1002/fld.755

Molla, M. M., Paul, M. C., & Roditi, G. (2010). LES of additive and non-additive pulsatile flows in a model arterial stenosis. Computer Methods in Biomechanics and Biomedical Engineering, 13(1), 105–120. https://doi.org/10.1080/10255840903062545 DOI: https://doi.org/10.1080/10255840903062545

Ziervogel, G., Cartwright, A., Tas, A., Adejuwon, J., Zermoglio, F., Shale, M., & Smith, B. (2008). Climate change and adaptation in African agriculture. Training, 4179, 53. https://doi.org/10.1002/cnm

Mynard, J. P., Wasserman, B. A., & Steinman, D. A. (2013). Errors in the estimation of wall shear stress by maximum Doppler velocity. Atherosclerosis, 227(2), 259–266. https://doi.org/10.1016/j.atherosclerosis.2013.01.026 DOI: https://doi.org/10.1016/j.atherosclerosis.2013.01.026

Kolli, K. K., Helmy, T. A., Peelukhana, S. V., Arif, I., Leesar, M. A., Back, L. H., … Effat, M. A. (2014). Functional diagnosis of coronary stenoses using pressure drop coefficient: A pilot study in humans. Catheterization and Cardiovascular Interventions, 83(3), 377–385. https://doi.org/10.1002/ccd.25085 DOI: https://doi.org/10.1002/ccd.25085

Peelukhana, S. V., Back, L. H., & Banerjee, R. K. (2009). Influence of coronary collateral flow on coronary diagnostic parameters: An in vitro study. Journal of Biomechanics, 42(16), 2753–2759. https://doi.org/10.1016/j.jbiomech.2009.08.013 DOI: https://doi.org/10.1016/j.jbiomech.2009.08.013

Konala, B. C., Das, A., & Banerjee, R. K. (2011). Influence of arterial wall-stenosis compliance on the coronary diagnostic parameters. Journal of Biomechanics, 44(5), 842–847. https://doi.org/10.1016/j.jbiomech.2010.12.011 DOI: https://doi.org/10.1016/j.jbiomech.2010.12.011

Peelukhana, S. V., Banerjee, R. K., van de Hoef, T. P., Kolli, K. K., Effat, M., Helmy, T., … Arif, I. (2018). Evaluation of lesion flow coefficient for the detection of coronary artery disease in patient groups from two academic medical centers. Cardiovascular Revascularization Medicine, 19(3), 348–354. https://doi.org/10.1016/j.carrev.2017.08.018 DOI: https://doi.org/10.1016/j.carrev.2017.08.018

Kamangar, S., Kalimuthu, G., Anjum Badruddin, I., Badarudin, A., Salman Ahmed, N. J., & Khan, T. M. Y. (2014). Numerical investigation of the effect of stenosis geometry on the coronary diagnostic parameters. Scientific World Journal, 2014. https://doi.org/10.1155/2014/354946 DOI: https://doi.org/10.1155/2014/354946

Abhijit Sinha Roy, Lloyd H. Back, R. K. B. (2006). Guidewire flow obstruction effect on pressure drop-flow relationship in moderate coronary artery stenosis. DOI: https://doi.org/10.1016/j.jbiomech.2005.01.020

STAR-CCM+. (2020). STAR-CCM+ Documentation Theory Guide, Turbulence. Siemens,GER.

Levy, S. W. (1959). Use of Madribon in Dermatological Conditions, With Special Reference To Acne. Annals of the New York Academy of Sciences (Vol. 82). https://doi.org/10.1111/j.1749-6632.1959.tb44882.x DOI: https://doi.org/10.1111/j.1749-6632.1959.tb44882.x

Al-Azawy, M. G., Kadhim, S. K., & Hameed, A. S. (2020). Newtonian and non-newtonian blood rheology inside a model of stenosis. CFD Letters, 12(11), 27–36. https://doi.org/10.37934/cfdl.12.11.2736 DOI: https://doi.org/10.37934/cfdl.12.11.2736

Johnston, B. M., Johnston, P. R., Corney, S., & Kilpatrick, D. (2004). Non-Newtonian blood flow in human right coronary arteries: steady state simulations. Journal of biomechanics, 37(5), 709–720. https://doi.org/10.1016/j.jbiomech.2003.09.016 DOI: https://doi.org/10.1016/j.jbiomech.2003.09.016

Kadhim, S. K., Al-Azawy, M. G., Ali, S. A., & Kadhim, M. Q. (2021). The influence of non-Newtonian model on properties of blood flow through a left coronary artery with presence of different double stenosis. International Journal of Heat and Technology, 39(3), 895–905. https://doi.org/10.18280/ijht.390324 DOI: https://doi.org/10.18280/ijht.390324

Manceau, R., & Hanjalić, K. (2002). Elliptic blending model: A new near-wall Reynolds-stress turbulence closure. Physics of Fluids, 14(2), 744–754. https://doi.org/10.1063/1.1432693 DOI: https://doi.org/10.1063/1.1432693

Lardeau, S., Manceau, R., Lardeau, S., & Manceau, R. (2016). Computations of canonical and complex flow configurations using a robust formulation of the elliptic-blending Reynolds-Stress model To cite this version : HAL Id : hal-01051799 U SING A M ODIFIED E LLIPTIC - BLENDING R EYNOLDS - STRESS M ODEL.

Al-Azawy, M. G., Turan, A., & Revell, A. (2016). Assessment of turbulence models for pulsatile flow inside a heart pump. Computer methods in biomechanics and biomedical engineering, 19(3), 271–285. https://doi.org/10.1080/10255842.2015.1015527 DOI: https://doi.org/10.1080/10255842.2015.1015527

Li, S., Chin, C., Thondapu, V., Poon, E. K. W., Monty, J. P., Li, Y., … Barlis, P. (2017). Numerical and experimental investigations of the flow–pressure relation in multiple sequential stenoses coronary artery. International Journal of Cardiovascular Imaging, 33(7), 1083–1088. https://doi.org/10.1007/s10554-017-1093-3 DOI: https://doi.org/10.1007/s10554-017-1093-3

Hariharan, P., Giarra, M., Reddy, V., Day, S. W., Manning, K. B., Deutsch, S., … Malinauskas, R. A. (2011). Multilaboratory particle image velocimetry analysis of the FDA benchmark nozzle model to support validation of computational fluid dynamics simulations. Journal of Biomechanical Engineering, 133(4), 1–14. https://doi.org/10.1115/1.4003440 DOI: https://doi.org/10.1115/1.4003440

Downloads

Published

2023-02-21

Issue

Section

Mechanical Engineering

How to Cite

Al-Azawy, M. G., Zahraa Ahmed Hamza, & Alkinani, A. A. (2023). Non-invasive evaluation of blood flow through a healthy and stenosed coronary artery. Wasit Journal of Engineering Sciences, 10(3), 58-74. https://doi.org/10.31185/ejuow.Vol10.Iss3.369