Transitional flow in XXXX and the computation of haemodynamic parameters.

@entity439 @entity1642 @entity1028 @entity438
Haemodynamic forces appear to play an influential role in the evolution of @entity439 . This has led to numerous studies, usually based on computational fluid dynamics. Their focus is predominantly on the @entity1642 ( @entity1642 ) and associated derived parameters, attempting to find correlations between particular patterns of haemodynamic indices and regions subjected to disease formation and progression. The indices are generally determined by integration of flow properties over a single cardiac cycle. In this study, we illustrate that in some cases the transitional flow in @entity439 can lead to significantly different @entity1642 distributions in consecutive cardiac cycles. Accurate determination of time-averaged haemodynamic indices may thus require simulation of a large number of cycles, which contrasts with the common approach to determine parameters using data from a single cycle. To demonstrate the role of transitional flow, two exemplary cases are considered: flow in an @entity1028 and in an @entity438 . The key differences that are observed between these cases are explained in terms of the integral timescale of the transitional flows in comparison with the cardiac cycle duration: for relatively small geometries, transients will decay before the next cardiac cycle. In larger geometries, transients are still present when the systolic phase produces new instabilities. These residual fluctuations serve as random initial conditions and thus seed different flow patterns in each cycle. To judge whether statistics are converged, the derived indices from at least two successive cardiac cycles should be compared.
