Blood flow patterns in the human left ventricle (LV) have shown relation to cardiac health. However, most studies in the literature are limited to a few patients and results are hard to generalize. This study aims to provide a new framework to generate more generalized insights into LV blood flow as a function of changes in anatomy and wall motion. In this framework, we studied the four-dimensional blood flow in LV via computational fluid dynamics (CFD) in conjunction with a statistical shape model (SSM), built from segmented LV shapes of 150 subjects. We validated results in an in-vitro dynamic phantom via time-resolved optical particle image velocimetry (PIV) measurements. This combination of CFD and the SSM may be useful for systematically assessing blood flow patterns in the LV as a function of varying anatomy and has the potential to provide valuable data for diagnosis of LV functionality.

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Keywords Cardiac blood flow, Computational fluid dynamics, Left ventricle, Statistical shape modelling
Persistent URL dx.doi.org/10.1016/j.jbiomech.2018.04.030, hdl.handle.net/1765/106378
Journal Journal of Biomechanics
Citation
Khalafvand, S.S. (S. S.), Voorneveld, J.D, Muralidharan, A. (A.), Gijsen, F.J.H, Bosch, J.G, van Walsum, T.W, … Kenjeres, S. (S.). (2018). Assessment of human left ventricle flow using statistical shape modelling and computational fluid dynamics. Journal of Biomechanics. doi:10.1016/j.jbiomech.2018.04.030