Title

Numerical Modeling Of Pulse Wave Propagation In A Stenosed Artery Using Two-Way Coupled Fluid Structure Interaction (Fsi)

Keywords

CFD; FSI; Pulse Wave Velocity (PWV); Stenosis

Abstract

As the heart beats, it creates fluctuation in blood pressure leading to a pulse wave that propagates by displacing the arterial wall. These waves travel through the arterial tree and carry information about the medium that they propagate through as well as information of the geometry of the arterial tree. Pulse wave velocity (PWV) can be used as a non-invasive diagnostic tool to study the functioning of cardiovascular system. A stenosis in an artery can dampen the pulse wave leading to changes in the propagating pulse. Hence, PWV analysis can be performed to detect a stenosed region in arteries. This paper presents a numerical study of pulse wave propagation in a stenosed artery by means of two-way coupled fluid structure interaction (FSI). The computational model was validated by the comparison of the simulated PWV results with theoretical values for a healthy artery. Propagation of the pulse waves in the stenosed artery was compared with healthy case using spatiotemporal maps of wall displacements. The analysis for PWV showed significance differences between the healthy and stenosed arteries including damping of propagating waves and generation of high wall displacements downstream the stenosis caused by flow instabilities. This approach can be used to develop patient-specific models that are capable of predicting PWV signatures associated with stenosis changes. The knowledge gained from these models may increase utility of this approach for managing patients at risk of stenosis occurrence.

Publication Date

1-1-2018

Publication Title

Proceedings of the Thermal and Fluids Engineering Summer Conference

Volume

2018-March

Number of Pages

1117-1125

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1615/TFEC2018.bio.021647

Socpus ID

85056184400 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85056184400

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