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Multiscale Modeling of Endothelium Derived Wall Shear Stress Regulation in Common Carotid Artery

Published online by Cambridge University Press:  16 July 2019

Saeed Siri ,
Malikeh Nabaei  and
Nasser Fatouraee
Saeed Siri
Affiliation:
M.Sc. Biomedical Engineering department AmirKabir University of TechnologyTehran, Iran
Malikeh Nabaei*
Affiliation:
Assistant Professor Biomedical Engineering department AmirKabir University of TechnologyTehran, Iran
Nasser Fatouraee
Affiliation:
Associate Professor Biomedical Engineering department AmirKabir University of Technology
*
*Corresponding author (m_nabaei@aut.ac.ir, Amirkabir University of Technology, 424 Hafez Ave, Tehran, Iran, Tel: +98 (21) 64545575, P.O. Box: 15875-4413)
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Abstract

Shear induced autoregulation is the natural ability of organs to maintain the local hemodynamic stresses in a stable condition in spite of altering perfusion rate. Endothelium cells are shear sensitive mechanoreceptors that are responsible for regulating the arterial wall architecture and mechanical properties in order to maintain homeostasis. This occurs by means of vasoactive mediators, which cause vasodilation or vasoconstriction. In this paper we presented a multiscale model of local flow regulation. First, a lumped parameter model of the whole cardiovascular system was implemented. Then a 3D numerical model of human common carotid artery was constructed considering fluid-structure interaction. The CCA inflow waveform obtained from the extended 0D model was applied to the 3D model as the boundary condition. After applying the Head-Up Tilt test, the local hemodynamics were disturbed. By considering the wall shear stress as the regulation criterion, then altering the arterial mechanical properties and the following vasodilation, shear forces exerted on the inner lining of the vessel were regulated and returned to the normal range. The resulting 0D/3D model can be considered as a plat-form for a more complete model containing local and systemic cardiovascular control mechanisms and patient-specific geometries which can be used for clinical purposes.

Keywords

Multiscale modelAutoregulationFluid-structure interactionWall shear stress
Type
Research Article
Information
Journal of Mechanics , Volume 35 , Issue 6 , December 2019 , pp. 901 - 914
Copyright
© The Society of Theoretical and Applied Mechanics 2019 

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References

REFERENCES

Carlson, B. E., Arciero, J. C., and Secomb, T. W., “Theoretical model of blood flow autoregulation: roles of myogenic, shear-dependent, and metabolic responses,” American Journal of Physiology-Heart and Circulatory Physiology, 295, pp. H1572–H1579 (2008).CrossRefGoogle ScholarPubMed
Klabunde, R., Cardiovascular physiology concepts, 2ND Edition, Lippincott Williams & Wilkins, Baltimore, USA (2011).Google Scholar
Hall, J. E., Guyton and Hall textbook of medical physiology, 13TH Edition, Elsevier Health Sciences, Philadelphia, USA (2016).Google Scholar
Ferrandez, A., David, T., and Brown, M., “Numerical models of auto-regulation and blood flow in the cerebral circulation,” Computer Methods in Biomechanics & Biomedical Engineering, 5, pp. 7–19 (2002).CrossRefGoogle ScholarPubMed
Rudic, R. D., et al., “Direct evidence for the importance of endothelium-derived nitric oxide in vascular remodeling,” Journal of Clinical Investigation, 101, p. 731 (1998).CrossRefGoogle ScholarPubMed
Wilkinson, I. B., et al., “Nitric oxide regulates local arterial distensibility in vivo,” Circulation, 105, pp. 213–217 (2002).CrossRefGoogle ScholarPubMed
Meng, H., Tutino, V., Xiang, J., and Siddiqui, A., “High WSS or low WSS? Complex interactions of hemodynamics with intracranial aneurysm initiation, growth, and rupture: toward a unifying hypothesis,” American Journal of Neuroradiology, 35, pp. 1254–1262 (2014).CrossRefGoogle ScholarPubMed
Nabaei, M. and Fatouraee, N., “Computational modeling of formation of a cerebral aneurysm under the influence of smooth muscle cell relaxation,” Journal of Mechanics in Medicine and Biology, 12, p. 1250006 (2012).CrossRefGoogle Scholar
Chatziprodromou, I., Tricoli, A., Poulikakos, D., and Ventikos, Y., “Haemodynamics and wall remodelling of a growing cerebral aneurysm: a computational model,” Journal of biomechanics, 40, pp. 412–426 (2007).CrossRefGoogle ScholarPubMed
Kolega, J., et al., “Cellular and molecular responses of the basilar terminus to hemodynamics during intracranial aneurysm initiation in a rabbit model,” Journal of vascular research, 48, pp. 429–442 (2011).CrossRefGoogle Scholar
Shojima, M., et al., “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 (2004).CrossRefGoogle ScholarPubMed
Nabaei, M. and Fatouraee, N., “Microstructural modelling of cerebral aneurysm evolution through effective stress mediated destructive remodelling,” Journal of theoretical biology, 354, pp. 60–71 (2014).CrossRefGoogle ScholarPubMed
Nabaei, M. and Fatouraee, N., “A 3D model for mural-cell-mediated destructive remodeling during early development of a cerebral aneurysm,” Journal of Mechanics in Medicine and Biology, 15, p. 1550034 (2015).CrossRefGoogle Scholar
Alastruey, J., et al., “Reduced modelling of blood flow in the cerebral circulation: coupling 1-D, 0-D and cerebral auto-regulation models,” International journal for numerical methods in fluids, 56, p. 1061 (2008).CrossRefGoogle Scholar
Kaufmann, T. A., Schmitz-Rode, T., and Steinseifer, U., “Implementation of cerebral autoregulation into computational fluid dynamics studies of cardiopulmonary bypass,” Artificial organs, 36, pp. 754–758 (2012).CrossRefGoogle ScholarPubMed
Siri, S., Nabaei, M., Nasiraei-Moghaddam, A., Fatouraee, N., Khodaei, V., “Effect of baroreflex mechanism on pressure wave amplitude in human vascular network,” Proceedings of 23th Annual International Conference on Mechanical Engineering (ISME2015), Iran (2015).Google Scholar
Siri, S., Nabaei, M., Fatouraee, N., “Numerical modeling of cerebral autoregulation in human common carotid artery,” Iranian Journal of Biomedical Engineering, 9, pp. 229–241 (2016).Google Scholar
Keijsers, J., et al., “Influence of local auto-regulation mechanisms on flow during the muscle pump effect: a modeling approach,” CMBE Proceeding, pp. 725–728 (2015).Google Scholar
Arciero, J., Pickrell, A., Siesky, B., and Harris, A., “Theoretical analysis of myogenic and metabolic responses in retinal blood flow autoregulation,” Investigative Ophthalmology & Visual Science, 53, pp. 6847–6847 (2012).Google Scholar
Wen, J., Wang, Q., Wang, Q., Khoshmanesh, K., and Zheng, T., “Numerical analysis of hemodynamics in spastic middle cerebral arteries,” Computer methods in biomechanics and biomedical engineering, 19, pp. 1489–1496 (2016).CrossRefGoogle ScholarPubMed
Mader, G., Olufsen, M., and Mahdi, A., “Modeling cerebral blood flow velocity during orthostatic stress,” Annals of biomedical engineering, 43, pp. 1748–1758 (2015).CrossRefGoogle ScholarPubMed
Valencia, A. and Solis, F., “Blood flow dynamics and arterial wall interaction in a saccular aneurysm model of the basilar artery,” Computers & structures, 84, pp. 1326–1337 (2006).CrossRefGoogle Scholar
Rideout, V. C., Mathematical and computer modeling of physiological systems, Prentice Hall Englewood Cliffs, New Jersey. USA (1991).Google Scholar
Abdolrazaghi, M., Navidbakhsh, M., and Hassani, K., “Mathematical modelling and electrical analog equivalent of the human cardiovascular system,” Cardiovascular Engineering, 10, pp. 45–51 (2010).CrossRefGoogle ScholarPubMed
Wang, J., and Parker, K., “Wave propagation in a model of the arterial circulation,” Journal of biomechanics, 37, pp. 457–470 (2004).CrossRefGoogle Scholar
Olufsen, M. S. and Nadim, A., “On deriving lumped models for blood flow and pressure in the systemic arteries,” Mathematical Biosciences and Engineering, 1, pp. 61–80 (2004).CrossRefGoogle ScholarPubMed
Rhoades, R. A., Bell, D. R., Medical Physiology: Principles for Clinical Medicine, 5th Edition, Lippincott Williams & Wilkins, Baltimore, USA, pp. 212–226 (2013).Google Scholar
Chen, S. H., “Baroreflex-based physiological control of a left ventricular assist device,” Ph.D. Thesis, University of Pittsburgh (2006).Google Scholar
Mukkamala, R., “A forward model-based analysis of cardiovascular system identification methods,” Ph.D. Thesis, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology (2000).Google Scholar
Santos, J. M. M. G. L., “A Baroreflex Control Model Using Head-Up Tilt Test,” Ph.D. Thesis, Bioengineering Department, Technical University of Lisbon (2008).Google Scholar
Watton, P., et al., “Modelling evolution and the evolving mechanical environment of saccular cerebral aneurysms,” Biomechanics and modeling in mechanobiology, 10, pp. 109–132 (2011).CrossRefGoogle ScholarPubMed
Watton, P. N., Raberger, N. B., Holzapfel, G. A., and Ventikos, Y., “Coupling the hemodynamic environment to the evolution of cerebral aneurysms: computational framework and numerical examples,” Journal of biomechanical engineering, 131, p. 101003 (2009).CrossRefGoogle ScholarPubMed
Riley, W. A., Barnes, R. W., Evans, G., , W., and Burke, G. L., “Ultrasonic measurement of the elastic modulus of the common carotid artery. The Atherosclerosis Risk in Communities (ARIC) Study,” Stroke, 23, pp. 952–956 (1992).CrossRefGoogle ScholarPubMed
Levenson, J., Pessana, F., Gariepy, J., Armentano, R., and Simon, A., “Gender differences in wall shear– mediated brachial artery vasoconstriction and vasodilation,” Journal of the American College of Cardiology, 38, pp. 1668–1674 (2001).CrossRefGoogle ScholarPubMed
Rizzo, D. C., Fundamentals of anatomy and physiology, 3rd Edition, Cengage Learning, New York, USA (2015).Google Scholar
Scheffers, I., et al., “Sustained blood pressure reduction by baroreflex hypertension therapy with a chronically implanted system: 2-year data from the Rheos DEBuT-HT study in patients with resistant hypertension,” Journal of Hypertension, 26, p. S19 (2008).Google Scholar
Bisognano, J., Sloand, J., and Papademetriou, V., “Baroreflex hypertension therapy with a chronically implanted system: early results from the Rheos feasibility trial in patients with resistant hypertension,” The Journal of Clinical Hypertension, 5, p. A43 (2006).Google Scholar
Pitts, G. R., Schiller, J. R., Thompson, J., “Chapter 19 The Cardiovascular System: Blood Vessels. http://slideplayer.com/slide/4889864/,” (2015).Google Scholar
Tortora, G. J. and Grabowski, S. R., Introduction to the human body: the essentials of anatomy and physiology, 6th Edition, John Wiley & Sons, New Jersey, USA (1997).Google Scholar
Ku, D., Giddens, D., Phillips, D., and Strandness, D., “Hemodynamics of the normal human carotid bifurcation: in vitro and in vivo studies,” Ultrasound in medicine & biology, 11, pp. 13–26 (1985).CrossRefGoogle ScholarPubMed
Long, Q., Xu, X.Y., Ariff, B., Thom, S.A., Hughes, A.D. and Stanton, A.V., 2000. Reconstruction of blood flow patterns in a human carotid bifurcation: a combined CFD and MRI study. Journal of Magnetic Resonance Imaging: An Official Journal of the International Society for Magnetic Resonance in Medicine, 11(3), pp.299–311.41.3.0.CO;2-M>CrossRefGoogle Scholar
Taylor, C.A. and Figueroa, C.A., 2009. Patient-specific modeling of cardiovascular mechanics. Annual review of biomedical engineering, 11, pp.109–134.CrossRefGoogle ScholarPubMed
Taylor, C.A. and Draney, M.T., 2004. Experimental and computational methods in cardiovascular fluid mechanics. Annu. Rev. Fluid Mech., 36, pp.197–231.CrossRefGoogle Scholar
Johnston, B.M., Johnston, P.R., Corney, S. and Kilpatrick, D., 2004. Non-Newtonian blood flow in human right coronary arteries: steady state simulations. Journal of biomechanics, 37(5), pp.709–720.CrossRefGoogle ScholarPubMed
Bessonov, N., Sequeira, A., Simakov, S., Vassilevskii, Y. and Volpert, V., 2016. Methods of blood flow modelling. Mathematical modelling of natural phenomena, 11(1), pp.1–25.CrossRefGoogle Scholar
Waite, L. and Fine, J.M., 2007. Applied biofluid mechanics.Google Scholar
García, A., Pena, E., Laborda, A., Lostalé, F., De Gregorio, M.A., Doblaré, M. and Martínez, M.A., 2011. Experimental study and constitutive modelling of the passive mechanical properties of the porcine carotid artery and its relation to histological analysis: Implications in animal cardiovascular device trials. Medical engineering & physics, 33(6), pp.665–676.CrossRefGoogle ScholarPubMed
Masson, I., Beaussier, H., Boutouyrie, P., Laurent, S., Humphrey, J.D. and Zidi, M., 2011. Carotid artery mechanical properties and stresses quantified using in vivo data from normotensive and hypertensive humans. Biomechanics and modeling in mechanobiology, 10(6), pp.867–882.CrossRefGoogle ScholarPubMed
Masson, I., Beaussier, H., Boutouyrie, P., Laurent, S., Humphrey, J.D. and Zidi, M., 2011. Carotid artery mechanical properties and stresses quantified using in vivo data from normotensive and hypertensive humans. Biomechanics and modeling in mechanobiology, 10(6), pp.867–882.CrossRefGoogle ScholarPubMed