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Cardiovascular Engineering and Technology

, Volume 6, Issue 3, pp 281–293 | Cite as

Quantitative Assessment of Turbulence and Flow Eccentricity in an Aortic Coarctation: Impact of Virtual Interventions

  • Magnus AnderssonEmail author
  • Jonas Lantz
  • Tino Ebbers
  • Matts Karlsson
Article

Abstract

Turbulence and flow eccentricity can be measured by magnetic resonance imaging (MRI) and may play an important role in the pathogenesis of numerous cardiovascular diseases. In the present study, we propose quantitative techniques to assess turbulent kinetic energy (TKE) and flow eccentricity that could assist in the evaluation and treatment of stenotic severities. These hemodynamic parameters were studied in a pre-treated aortic coarctation (CoA) and after several virtual interventions using computational fluid dynamics (CFD), to demonstrate the effect of different dilatation options on the flow field. Patient-specific geometry and flow conditions were derived from MRI data. The unsteady pulsatile flow was resolved by large eddy simulation including non-Newtonian blood rheology. Results showed an inverse asymptotic relationship between the total amount of TKE and degree of dilatation of the stenosis, where turbulent flow proximal the constriction limits the possible improvement by treating the CoA alone. Spatiotemporal maps of TKE and flow eccentricity could be linked to the characteristics of the jet, where improved flow conditions were favored by an eccentric dilatation of the CoA. By including these flow markers into a combined MRI–CFD intervention framework, CoA therapy has not only the possibility to produce predictions via simulation, but can also be validated pre- and immediate post treatment, as well as during follow-up studies.

Keywords

Computational fluid dynamics Large eddy simulation Turbulent kinetic energy Flow displacement Non-Newtonian Carreau Virtual treatment Magnetic resonance imaging 

Notes

Acknowledgments

This research was supported by grants from the Swedish Research Council and the Center for Industrial Information Technology (CENIIT). We also like to acknowledge the Center of Medical Image Science and Visualization (CMIV, http://www.cmiv.liu.se/) for providing necessary MRI data and the National Supercomputer Centre (NSC) for the computational resources via grants from the Swedish National Infrastructure for Computing (SNIC).

Conflict of interest

M. Karlsson received non-financial support from the Swedish National Infrastructure for Computing, T. Ebbers grants from the Center for Industrial Information Technology at Linköping University, the Swedish Research Council and the Swedish e-Science Research Center.

Statement of human studies

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all patients for being included in the study.

Statement of animal studies

No animal studies were carried out by the authors for this article.

Supplementary material

13239_2015_218_MOESM1_ESM.pdf (32.5 mb)
Supplementary material 1 (PDF 33324 kb)

Supplementary material 2 (MPG 9509 kb)

Supplementary material 3 (MPG 1009 kb)

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Copyright information

© Biomedical Engineering Society 2015

Authors and Affiliations

  • Magnus Andersson
    • 1
    • 5
    Email author
  • Jonas Lantz
    • 2
    • 5
  • Tino Ebbers
    • 2
    • 3
    • 4
    • 5
  • Matts Karlsson
    • 1
    • 4
    • 5
  1. 1.Department of Management and Engineering (IEI)Linköping UniversityLinköpingSweden
  2. 2.Department of Science and TechnologyLinköping UniversityLinköpingSweden
  3. 3.Department of Medical and Health SciencesLinköping UniversityLinköpingSweden
  4. 4.Center for Medical Image Science and Visualization (CMIV)Linköping UniversityLinköpingSweden
  5. 5.Swedish e-Science Research Center (SeRC)StockholmSweden

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