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Design and Computational Validation of a Novel Bioreactor for Conditioning Vascular Tissue to Time-Varying Multidirectional Fluid Shear Stress

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Abstract

Purpose

The cardiovascular endothelium experiences pulsatile and multidirectional fluid wall shear stress (WSS). While the effects of non-physiologic WSS magnitude and pulsatility on cardiovascular function have been studied extensively, the impact of directional abnormalities remains unknown due to the challenge to replicate this characteristic in vitro. To address this gap, this study aimed at designing a bioreactor capable of subjecting cardiovascular tissue to time-varying WSS magnitude and directionality.

Methods

The device consisted of a modified cone-and-plate bioreactor. The cone rotation generates a fluid flow subjecting tissue to desired WSS magnitude, while WSS directionality is achieved by altering the alignment of the tissue relative to the flow at each instant of time. Computational fluid dynamics was used to verify the device ability to replicate the native WSS of the proximal aorta. Cone and tissue mount velocities were determined using an iterative optimization procedure.

Results

Using conditions derived from cone-and-plate theory, the initial simulations yielded root-mean-square errors of 22.8 and 8.4% in WSS magnitude and angle, respectively, between the predicted and the target signals over one cycle, relative to the time-averaged target values. The conditions obtained after two optimization iterations reduced those errors to 3.5 and 0.5%, respectively, and generated 0.2% and 0.01% difference in time-averaged WSS magnitude and angle, respectively, relative to the target waveforms.

Conclusions

A bioreactor capable of generating simultaneously desired time-varying WSS magnitude and directionality was designed and validated computationally. The ability to subject tissue to in vivo-like WSS will provide new insights into cardiovascular mechanobiology and disease.

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References

  1. Atkins, S., K. Cao, N. M. Rajamannan, and P. Sucosky. Bicuspid aortic valve hemodynamics induces abnormal medial remodeling in the convexity of porcine ascending aortas. Biomech. Model. Mechanobiol. 13:1209–1225, 2014.

    Article  Google Scholar 

  2. Atkins, S. K., A. McNally, and P. Sucosky. Mechanobiology in cardiovascular disease management: potential strategies and current needs. Front. Bioeng. Biotechnol. 4:79, 2016.

    Article  Google Scholar 

  3. Atkins, S. K., A. Moore, and P. Sucosky. Bicuspid aortic valve hemodynamics does not promote remodeling in porcine aortic wall concavity. World J. Cardiol. 8:89–97, 2016.

    Article  Google Scholar 

  4. Atkins, S. K., and P. Sucosky. The etiology of bicuspid aortic valve disease: focus on hemodynamics. World J. Cardiol. 12:1227–1233, 2014.

    Article  Google Scholar 

  5. Bissell, M. M., A. T. Hess, L. Biasiolli, S. J. Glaze, M. Loudon, A. Pitcher, A. Davis, B. Prendergast, M. Markl, A. J. Barker, S. Neubauer, G. Saul, and S. G. Myerson. Aortic dilation in bicuspid aortic valve disease: flow pattern is a major contributor and differs with valve fusion type. Circ. Cardiovasc. Imaging 6:499–507, 2013.

    Article  Google Scholar 

  6. Buschmann, M. H., P. Dieterich, N. A. Adams, and H.-J. Schnittler. Analysis of flow in cone-and-plate apparatus with respect to spatial and temporal effects on endothelial cells. Biotechnol. Bioeng. 89:493–502, 2005.

    Article  Google Scholar 

  7. Cao, K., S. K. Atkins, A. McNally, J. Liu, and P. Sucosky. Simulations of morphotype-dependent hemodynamics in non-dilated bicuspid aortic valve aortas. J. Biomech. 50:63–70, 2017.

    Article  Google Scholar 

  8. Cao, K., and P. Sucosky. Effect of bicuspid aortic valve cusp fusion on aorta wall shear stress: preliminary computational assessment and implication for aortic dilation. World J. Cardiovasc. Dis. 5:129–140, 2015.

    Article  Google Scholar 

  9. Cao, K., and P. Sucosky. Computational comparison of regional stress and deformation characteristics in tricuspid and bicuspid aortic valve leaflets. Int. J. Numer. Method. Biomed. Eng. 33:e02798, 2017.

    Article  Google Scholar 

  10. Caro, C. G., T. J. Pedley, R. C. Schroter, and W. A. Seed. The Mechanics of the Circulation. Oxford: Oxford University Press, 1978.

    MATH  Google Scholar 

  11. Cecchi, E., C. Giglioli, S. Valente, C. Lazzeri, G. F. Gensini, R. Abbate, and L. Mannini. Role of hemodynamic shear stress in cardiovascular disease. Atherosclerosis 214:249–256, 2011.

    Article  Google Scholar 

  12. Chakraborty, A., S. Chakraborty, V. R. Jala, B. Haribabu, M. K. Sharp, and R. E. Berson. Effects of biaxial oscillatory shear stress on endothelial cell proliferation and morphology. Biotechnol. Bioeng. 109:695–707, 2012.

    Article  Google Scholar 

  13. Chien, S. Mechanotransduction and endothelial cell homeostasis: the wisdom of the cell. Am. J. Physiol. Heart Circ. Physiol. 292:H1209–H1224, 2007.

    Article  Google Scholar 

  14. Chung, C. A., M. R. Tzou, and R. W. Ho. Oscillatory flow in a cone-and-plate bioreactor. J. Biomech. Eng. 127:601–610, 2005.

    Article  Google Scholar 

  15. Dai, G., S. Natarajan, Y. Zhang, S. Vaughn, B. R. Blackman, R. D. Kamm, G. Garcia-Cardena, and M. A. Gimbrone, Jr. Distinct endothelial phenotypes evoked by arterial waveforms derived from atherosclerosis-susceptible and -resistant regions of human vasculature. Proc. Natl. Acad. Sci. 101:14871–14876, 2004.

    Article  Google Scholar 

  16. Davies, P. F. Hemodynamic shear stress and the endothelium in cardiovascular pathophysiology. Nat. Clin. Pract. Cardiovasc. Med. 6:16–26, 2009.

    Article  Google Scholar 

  17. Dewey, Jr, C. F., S. R. Bussolari, M. A. Gimbrone, and P. F. Davies. The dynamic response of vascular endothelial cells to fluid shear stress. J. Biomech. Eng. 103:177–185, 1981.

    Article  Google Scholar 

  18. Dolan, J. M., H. Meng, S. Singh, R. A. Paluch, and J. Kolega. High fluid shear stress and spatial shear stress gradients affect endothelial proliferation, survival, and alignment. Ann. Biomed. Eng. 35:1252–1260, 2011.

    Google Scholar 

  19. Fernández Esmerats, J., J. Heath, and H. Jo. Shear-sensitive genes in aortic valve endothelium. Antioxid. Redox Signal. 25:401–414, 2016.

    Article  Google Scholar 

  20. Fewell, M. E., and J. D. Hellums. The secondary flow of Newtonian fluids in cone-and-plate viscometers. Trans. Soc. Rheol. 21:535–565, 1977.

    Article  Google Scholar 

  21. Gonzalez, C. F., Y. I. Cho, H. V. Ortega, and J. Moret. Intracranial aneurysms: flow analysis of their origin and progression. Am. J. Neuroradiol. 13:181–188, 1992.

    Google Scholar 

  22. Harloff, A., A. Nußbaumer, S. Bauer, A. F. Stalder, A. Frydrychowicz, C. Weiller, J. Hennig, and M. Markl. In vivo assessment of wall shear stress in the atherosclerotic aorta using flow-sensitive 4D MRI. Magn. Reson. Med. 63:1529–1536, 2010.

    Article  Google Scholar 

  23. Hoehn, D., L. Sun, and P. Sucosky. Role of pathologic shear stress alterations in aortic valve endothelial activation. Cardiovasc. Eng. Technol. 1:165–178, 2010.

    Article  Google Scholar 

  24. Hope, T. A., M. Markl, L. Wigström, M. T. Alley, D. C. Miller, and R. J. Herfkens. Comparison of flow patterns in ascending aortic aneurysms and volunteers using four-dimensional magnetic resonance velocity mapping. J. Magn. Reson. Imaging 26:1471–1479, 2007.

    Article  Google Scholar 

  25. Huang, T.-C., C.-K. Chang, C.-H. Liao, and Y.-J. Ho. Quantification of blood flow in internal cerebral artery by optical flow method on digital subtraction angiography in comparison with time-of-flight magnetic resonance angiography. PLoS ONE 8:e54678, 2013.

    Article  Google Scholar 

  26. Humphrey, J. D. D., and C. A. A. Taylor. Intracranial and abdominal aortic aneurysms: similarities, differences, and need for a new class of computational models. Annu. Rev. Biomed. Eng. 10:221–246, 2008.

    Article  Google Scholar 

  27. Kilner, P. J., G. Z. Yang, R. H. Mohiaddin, D. N. Firmin, and D. B. Longmore. Helical and retrograde secondary flow patterns in the aortic arch studied by three-directional magnetic resonance velocity mapping. Circulation 88:2235–2247, 1993.

    Article  Google Scholar 

  28. Kilner, P. J., G. Z. Yang, A. J. Wilkes, R. H. Mohiaddin, D. N. Firmin, and M. H. Yacoub. Asymmetric redirection of flow through the heart. Nature 404:759–761, 2000.

    Article  Google Scholar 

  29. Lehoux, S., Y. Castier, and A. Tedgui. Molecular mechanisms of the vascular responses to haemodynamic forces. J. Intern. Med. 259:381–392, 2006.

    Article  Google Scholar 

  30. Lehoux, S., and A. Tedgui. Cellular mechanics and gene expression in blood vessels. J. Biomech. 36:631–643, 2003.

    Article  Google Scholar 

  31. Levesque, M. J., E. A. Sprague, C. J. Schwartz, and R. M. Nerem. The influence of shear stress on cultured vascular endothelial cells: the stress response of an anchorage dependent mammalian cell. Biotechnol. Prog. 5:1, 1989.

    Article  Google Scholar 

  32. Liu, J., J. A. Shar, and P. Sucosky. Wall shear stress directional abnormalities in BAV aortas: toward a new hemodynamic predictor of aortopathy? Front. Physiol. 9:993, 2018.

    Article  Google Scholar 

  33. McNally, A., A. Madan, and P. Sucosky. Morphotype-dependent flow characteristics in bicuspid aortic valve ascending aortas: a benchtop particle image velocimetry study. Front. Physiol. 8:44, 2017.

    Article  Google Scholar 

  34. Mooney M, Ewart RH. The conicylindrical viscometer. Physics 5:350–354, 350, 1934.

  35. Nerem, R. M. Hemodynamics and the vascular endothelium. ASME J. Biomech. Eng. 115:510, 1993.

    Article  Google Scholar 

  36. Peiffer, V., S. J. Sherwin, and P. D. Weinberg. Computation in the rabbit aorta of a new metric—the transverse wall shear stress—to quantify the multidirectional character of disturbed blood flow. J. Biomech. 46:2651–2658, 2013.

    Article  Google Scholar 

  37. Pelech, I., and A. H. Shapiro. Flexible disk rotating on a gas film next to a wall. J. Appl. Mech. 31:577–584, 1964.

    Article  MATH  Google Scholar 

  38. Sdougos, H. P., S. R. Bussolari, and C. F. Dewey. Secondary flow and turbulence in a cone-and-plate device. J. Fluid Mech. 138:379–404, 1984.

    Article  Google Scholar 

  39. Sucosky, P., K. Balachandran, A. Elhammali, H. Jo, and A. P. Yoganathan. Altered shear stress stimulates upregulation of endothelial VCAM-1 and ICAM-1 in a BMP-4- and TGF-β1-dependent pathway. Arterioscler. Thromb. Vasc. Biol. 29:254–260, 2009.

    Article  Google Scholar 

  40. Sucosky, P., M. Padala, A. Elhammali, K. Balachandran, H. Jo, and A. P. Yoganathan. Design of an ex vivo culture system to investigate the effects of shear stress on cardiovascular tissue. J. Biomech. Eng. 130:35001–35008, 2008.

    Article  Google Scholar 

  41. Sun, L., S. Chandra, and P. Sucosky. Ex vivo evidence for the contribution of hemodynamic shear stress abnormalities to the early pathogenesis of calcific bicuspid aortic valve disease. PLoS ONE 7:e48843, 2012.

    Article  Google Scholar 

  42. Sun, L., N. M. Rajamannan, and P. Sucosky. Design and validation of a novel bioreactor to subject aortic valve leaflets to side-specific shear stress. Ann. Biomed. Eng. 39:2174–2185, 2011.

    Article  Google Scholar 

  43. Sun, L., N. M. Rajamannan, and P. Sucosky. Defining the role of fluid shear stress in the expression of early signaling markers for calcific aortic valve disease. PLoS ONE 8:e84433, 2013.

    Article  Google Scholar 

  44. Sun, L., and P. Sucosky. Bone morphogenetic protein-4 and transforming growth factor-beta1 mechanisms in acute valvular response to supra-physiologic hemodynamic stresses. World J. Cardiol. 7:331–343, 2015.

    Article  Google Scholar 

  45. Suo, J., J. N. Oshinski, and D. P. Giddens. Blood flow patterns in the proximal human coronary arteries: relationship to atherosclerotic plaque occurrence. Mol. Cell. Biomech. 5:9–18, 2008.

    MATH  Google Scholar 

  46. Vincent, P. E., A. M. Plata, A. A. E. Hunt, P. D. Weinberg, and S. J. Sherwin. Blood flow in the rabbit aortic arch and descending thoracic aorta. J. R. Soc. Interface 8:1708–1719, 2011.

    Article  Google Scholar 

  47. Wang, C., B. M. Baker, C. S. Chen, and M. A. Schwartz. Endothelial cell sensing of flow direction. Arterioscler. Thromb. Vasc. Biol. 33:2130–2136, 2013.

    Article  Google Scholar 

  48. Wang, C., H. Lu, and M. A. Schwartz. A novel in vitro flow system for changing flow direction on endothelial cells. J. Biomech. 45:1212–1218, 2012.

    Article  Google Scholar 

  49. Yang, Z., H. Yu, G. P. Huang, R. Schwieterman, and B. Ludwig. Computational fluid dynamics simulation of intracranial aneurysms—comparing size and shape. J. Coast. Life Med. 3:245–252, 2015.

    Google Scholar 

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Acknowledgments

This work was partially funded by the American Heart Association (Grant-in-Aid 17GRNT33350028), the National Science Foundation (CAREER award 1550144), and the Department of Mechanical and Materials Engineering at Wright State University.

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The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Correspondence to Philippe Sucosky.

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Associate Editor Ajit P. Yoganathan and Hanjoong Jo oversaw the review of this article.

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Liu, J., Cornelius, K., Graham, M. et al. Design and Computational Validation of a Novel Bioreactor for Conditioning Vascular Tissue to Time-Varying Multidirectional Fluid Shear Stress. Cardiovasc Eng Tech 10, 531–542 (2019). https://doi.org/10.1007/s13239-019-00426-1

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