Abstract
Purpose
Accurately reproducing physiological and time-varying variables in cardiac bioreactors is a difficult task for conventional control methods. This paper presents a new controller based on a genetic algorithm for the control of a cardiac bioreactor dedicated to the study and conditioning of heart valve substitutes.
Methods
A multi-objective genetic algorithm was designed to obtain an accurate simultaneous reproduction of physiological periodic time functions of the three most relevant variables characterizing the blood flow in the aortic valve. These three controlled variables are the flow rate and the pressures upstream and downstream of the aortic valve.
Results
Experimental results obtained with this new algorithm showed an accurate dynamic reproduction of these three controlled variables. Moreover, the controller can react and adapt continuously to changes happening over time in the cardiac bioreactor, which is a major advantage when working with living biological valve substitutes.
Conclusion
The strong non-linear interaction that exists between the three controlled variables makes it difficult to obtain a precise control of any of these, let alone all three simultaneously. However, the results showed that this new control algorithm can efficiently overcome such difficulties. In the particular field of bioreactors reproducing the cardiovascular environment, such a flexible, versatile and accurate reproduction of these three interdependent controlled variables is unprecedented.
Similar content being viewed by others
References
Arjunon, S., S. Rathan, H. Jo, and A. P. Yoganathan. Aortic valve: mechanical environment and mechanobiology. Ann. Biomed. Eng. 41(7):1331–1346, 2013.
Beelen, M. J., P. E. Neerincx, and M. J. G. van de Molengraft. Control of an air pressure actuated disposable bioreactor for cultivating heart valves. Mechatronics 21(8):1288–1297, 2011.
Bégin-Drolet, A., S. Collin, J. Gosselin, and J. Ruel. A new robust controller for non-linear periodic single-input/single-output systems using genetic algorithms. J. Process Control 61:23–35, 2018.
Benjamin, E. J., et al. Heart disease and stroke statistics—2017 update: a report from the american heart association. Circulation 135(10):e146, 2017.
Berry, J. L., J. A. Steen, J. Koudy-Williams, J. E. Jordan, A. Atala, and J. J. Yoo. Bioreactors for development of tissue engineered heart valves. Ann. Biomed. Eng. 38(11):3272–3279, 2010.
Butcher, J. T., C. A. Simmons, and J. N. Warnock. Review: mechanobiology of the aortic heart valve. J. Heart Valve Dis. 17(1):62–73, 2008.
Coello, C. A. C., G. B. Lamont, and D. A. Van Veldhuizen. Evolutionary Algorithms for Solving Multi-Objective Problems. New-York: Springer, 2007.
Driessen-Mol, G. Functional Tissue Engineering of Human Heart Valve Leaflets. Technische Universiteit Eindhoven, 2005.
Duan, B., L. A. Hockaday, K. H. Kang, and J. T. Butcher. Aortic heart valve tissue regeneration. In: Tissue and Organ Regeneration: Advances in Micro and Nanotechnology, edited by L. G. Zhang, A. Khademhosseini, and T. Webster. Jenny Stanford Publishing, 2014, pp. 645–694.
Eiben, Á. E., C. H. M. van Kemenade, and J. N. Kok. Orgy in the computer: multi-parent reproduction in genetic algorithms. In: Advances in Artificial Life, edited by F. Morán, A. Moreno, J. J. Merelo, and P. Chacón. Berlin, Heidelberg: Springer, 1995, pp. 934–945.
Hildebrand, D. K., Z. J. Wu, J. E. Mayer, and M. S. Sacks. Design and hydrodynamic evaluation of a novel pulsatile bioreactor for biologically active heart valves. Ann. Biomed. Eng. 32(8):1039–1049, 2004.
Lachance, G. Conception d’un bioréacteur dédié à la culture de valves aortiques cardiaques produites par génie tissulaire. Université Laval, 2010.
Laterreur, V. Développement d’outils pour le conditionnement mécanique de substituts valvulaires et vasculaires produits par génie tissulaire. Université Laval, 2015.
LOEX. Génie tissulaire et médecine régénératrice. Laboratoire D’Organogénèse Expérimentale, 2018. http://www.loex.qc.ca. Accessed 08 May 2018.
MacNeil, S. Biomaterials for tissue engineering of skin. Mater. Today 11(5):26–35, 2008.
Mitchell, M. An Introduction to Genetic Algorithms. Cambridge: MIT Press, Massachusetts Institute of Technology, 1998.
Nichol, J. W., and A. Khademhosseini. Modular tissue engineering: engineering biological tissues from the bottom up. Soft Matters 5(7):1312–1319, 2009.
Ruel, J., and G. Lachance. A new bioreactor for the development of tissue-engineered heart valves. Ann. Biomed. Eng. 37(4):674–681, 2009.
Ruel, J., and G. Lachance. Mathematical modeling and experimental testing of three bioreactor configurations based on windkessel models. Heart Int. 5(1):1–6, 2010.
Silbernagl, S., A. Despopoulos, and D. Laurent, Atlas de poche de physiologie. Médecines. 2001.
Soares, J. S., K. R. Feaver, W. Zhang, D. Kamensky, A. Aggarwal, and M. S. Sacks. Biomechanical behavior of bioprosthetic heart valve heterograft tissues: characterization, simulation, and performance. Cardiovasc. Eng. Technol. 7(4):309–351, 2016.
Tondreau, M. Y., et al. Mechanical properties of endothelialized fibroblast-derived vascular scaffolds stimulated in a bioreactor. Acta Biomater. 18:176–185, 2015.
Tremblay, C. Développement de techniques de construction de valves aortiques par génie tissulaire, 2015.
Xinghuo, Y. (ed.). Applied Decision Support with Soft Computing, Vol. 124. New York: Springer, 2003.
Acknowledgments
The authors would like to gratefully acknowledge the Natural Sciences and Engineering Research Council of Canada (NSERC) for the financial support they provided for this research through the NSERC Discovery Grants Program.
Conflict of interest
All authors declare that they have no conflict of interest.
Author information
Authors and Affiliations
Corresponding author
Additional information
Associate Editor Jane Grande-Allen oversaw the review of this article.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Gosselin, J., Bégin-Drolet, A., Maciel, Y. et al. A New Approach Based on a Multiobjective Evolutionary Algorithm for Accurate Control of Flow Rate and Blood Pressure in Cardiac Bioreactors. Cardiovasc Eng Tech 11, 84–95 (2020). https://doi.org/10.1007/s13239-019-00440-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13239-019-00440-3