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B. Hametner, S. Wassertheurer, T. Weber:
"Vascular Impedance Calculation using a new Blood Flow Mode";
Poster: ASIM-TCSE Workshop 2012, TU Wien; 2012-02-13 - 2012-02-14; in: "ARGESIM Report", S. Tauböck, F. Breitenecker (ed.); Argesim / Asim, 37 (2012), 11 - 12.

Introduction.
Cardiovascular diseases are the major cause of death in many developed countries, and the World Health Organization (WHO) predicts a worldwide increase for the next centuries. Within the concept of pulse
wave analysis, arterial pressure and flow curves over a whole cardiac cycle are analyzed. A possibility to
characterize the arterial system is to relate pressure
and flow via a linear time-invariant transfer function. The transfer function can be expressed as the ratio of output to
input in the frequency domain. This ratio of pressure to
flow is called impedance. The characteristic impedance (Z
c) is obtained when pressure and flow waves are not
influenced by wave reflection. This situation will never
occur in the arterial tree,therefore the characteristic
impedance can be approximated only, usually with the help of a calculated input impedance.
Methods.
Since the measurement of blood flow
in the aorta is cumbersome, models are used to generate flow
curves for the determination of vascular impedance.
The aim of this work is to evaluate the effects of a new blood
flow model on the determination of the characteristic impedance compared to flow curves gained from ultrasound
measurements. This recently developed blood flow model is based on Windkessel theory (ARCSolver flow). By
optimizing the left ventricular work using the calculus of variations a personalized flow curve can be obtained.
In a study population of 148 patients, pressure and flow curves were measured non-invasively using tonometric
and ultrasound techniques. For the evaluation of the different models the input impedance and subsequently the
characteristic impedance will be calculated in the freque
ncy domain. For a fair comparison for both methods the
flow curves are scaled in such a way that the maxima
l value is at the level of 100 arbitrary units (AU).
Results.
The mean characteristic impedance using flow curves
from ultrasound images is 0.22 (0.08 SD) AU. For
the ARCSolver flow a mean difference of 0.016 (0.039 SD)
AU compared to the ultrasound flow is obtained. The
correlation between the two methods is R=0.88. In a Bland-Altman analysis small trends of underestimation for higher values can be noticed, see the figure below for a scatter plot and a Bland-Altman plot.
Conclusion.
These results indicate that calculations using the ARCSolver flow model provide good estimates for characteristic impedance. Since these impedance values have a sufficient accuracy compared to those gained from ultrasound measurements, this new model offers an easy way to perform pulse wave separation and furthermore to calculate pulse wave velocity based on information from a single blood pressure measurement, where characteristic impedance is an important parameter for the calculations