Application of a meta-analysis of aortic geometry to the generation of a compliant phantom for use in particle image velocimetry experimentation

Larissa Huetter, Patrick H. Geoghegan, Paul D. Docherty, Milad Soltanipour Lazarjan, Don Clucas, Mark C. Jermy

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Abstract

The evolution of pressure-flow geometry in the aortic arch is increasingly understood as a key element in the treatment of hemodynamic dysfunction in patients. However, little is known about the properties of the flow across the aortic geometry and thus the sensitivity of sensor placement is also unknown. Compliant models of the aortic path can be built to allow techniques such as particle image velocimetry to measure the velocity fields. This paper presents the justification and production methodology used to generate a compliant model of the aortic arch that represents the geometry and compliance of typical hemodynamics patients. The information from twenty papers was synthesized to generate a single model of the aortic arch. The model incorporates the three branching arteries at an apex of a tapering aortic path experimental that has been manufactured as a flexible thin-walled silicon model. Calculations were undertaken to ensure that the model matches the in vivo compliance of the arteries. The experimental setup uses the compliant silicone model of the aorta with variable flow pump to mimic the cardiac cycle, and a variable extramural pressure to mimic changes in intrathoracic pressure. This research was necessary for the development of an accurate experimental setup that would enable results that are immediately applicable to the research of cardiovascular therapy optimization.

Original languageEnglish
Pages (from-to)407-412
Number of pages6
JournalIFAC-PapersOnLine
Volume48
Issue number20
DOIs
Publication statusPublished - 1 Sep 2015

Bibliographical note

© 2015, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/

Keywords

  • Aortic arch
  • Blood flow
  • Compliant vessels
  • Particle image velocimetry (PIV)
  • Windkessel model

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    Docherty, P. D., Geoghegan, P. H., Huetter, L., Jermy, M. & Sellier, M., 1 Feb 2017, In : Biomedical Signal Processing and Control. 32, p. 143-149 7 p.

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