P5.7 A Database of Virtual Healthy Subjects as a New Tool to Assess Physiological Indexes and Algorithms Based on Wave Propagation

Many physiological indexes and algorithms based on pulse wave analysis have been suggested in order to better understand the physiology of arterial hemodynamics (e.g. pulse wave velocity, transfer functions for central blood pressure derivation). Because these tools are most often computed from hemo...

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Published inArtery research Vol. 12; no. 1; p. 22
Main Authors Willemet, Marie, Chowienczyk, Phil, Vennin, Samuel, Alastruey, Jordi
Format Journal Article
LanguageEnglish
Published Dordrecht Springer Netherlands 01.12.2015
Springer Nature B.V
BMC
Subjects
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ISSN1872-9312
1876-4401
1876-4401
DOI10.1016/j.artres.2015.10.272

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Summary:Many physiological indexes and algorithms based on pulse wave analysis have been suggested in order to better understand the physiology of arterial hemodynamics (e.g. pulse wave velocity, transfer functions for central blood pressure derivation). Because these tools are most often computed from hemodynamic measurements, their validation is time-consuming and biased by measurement errors. We present a new methodology to assess theoretically these computed tools. We create a database of virtual healthy subjects using a numerical 1D–0D model of the arterial hemodynamics, which parameters are varied to cover a physiological healthy range. The generated set of simulations encloses a wide selection of possible cases that could be encountered in a clinical study. We illustrate this new concept by assessing the efficiency of indexes estimating aortic stiffness, such as central and peripheral foot-to-foot pulse wave velocities computed with different methods (foot-to-foot, sum of squares), the stiffness index and the augmentation index. We also apply our methodology to a new algorithm that estimates the central aortic pressure from peripheral measurements. We show that the results of our analysis confirm clinical observations. Our database of virtual subjects could become a new tool for the clinician: it provides insight into the physical mechanisms that are important when designing large cohort clinical studies, analyzing their results, and explaining the correlations observed in clinical practice.
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ISSN:1872-9312
1876-4401
1876-4401
DOI:10.1016/j.artres.2015.10.272