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Annals of Biomedical Engineering

, Volume 44, Issue 11, pp 3346–3358 | Cite as

Image-Based Simulations Show Important Flow Fluctuations in a Normal Left Ventricle: What Could be the Implications?

  • C. ChnafaEmail author
  • S. Mendez
  • F. Nicoud
Article

Abstract

Intra-cardiac flow has been explored for decades but there is still no consensus on whether or not healthy left ventricles (LV) may harbour turbulent-like flow despite its potential physiological and clinical relevance. The purpose of this study is to elucidate if a healthy LV could harbour flow instabilities, using image-based computational fluid dynamics (CFD). 35 cardiac cycles were simulated in a patient-specific left heart model obtained from cardiovascular magnetic resonance (CMR). The model includes the valves, atrium, ventricle, papillary muscles and ascending aorta. We computed phase-averaged flow patterns, fluctuating kinetic energy (FKE) and associated frequency components. The LV harbours disturbed flow during diastole with cycle-to-cycle variations. However, phase-averaged velocity fields much resemble those of CMR measurements and usually reported CFD results. The peak FKE value occurs during the E wave deceleration and reaches 25% of the maximum phase-averaged flow kinetic energy. Highest FKE values are predominantly located in the basal region and their frequency content reach more than 200 Hz. This study suggests that high-frequency flow fluctuations in normal LV may be common, implying deficiencies in the hypothesis usually made when computing cardiac flows and highlighting biases when deriving quantities from velocity fields measured with CMR.

Keywords

Left heart Turbulence LES Turbulent kinetic energy Atrium Third sound 

Notes

Acknowledgments

The authors would like to express their gratitude to MD Dr. D. Coisne for many fruitful discussions. Dr. R. Moreno from the Rangueil University Hospital, Toulouse (France) is acknowledged for the CMR exams. Dr. V. Moureau and Dr. G. Lartigue from the CORIA lab, and the SUCCESS scientific group are acknowledged for providing the YALES2 code, which served as a basis for the development of YALES2BIO. This work was performed using HPC resources from GENCI-CINES (Grants 2014- and 2015-c2014037194).

Supplementary material

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Supplementary material 1 (AVI 1562 kb)
10439_2016_1614_MOESM2_ESM.pdf (1.2 mb)
Supplementary material 2 (PDF 1223 kb)

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Copyright information

© Biomedical Engineering Society 2016

Authors and Affiliations

  1. 1.Université de Montpellier - IMAG CNRS UMR 5149Montpellier Cedex 5France
  2. 2.Biomedical Simulation Laboratory, University of Toronto - Mechanical and Industrial EngineeringTorontoCanada

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