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Erschienen in: Medical & Biological Engineering & Computing 11/2016

01.11.2016 | Original Article

Fluid–structure interaction modeling of calcific aortic valve disease using patient-specific three-dimensional calcification scans

verfasst von: Rotem Halevi, Ashraf Hamdan, Gil Marom, Karin Lavon, Sagit Ben-Zekry, Ehud Raanani, Danny Bluestein, Rami Haj-Ali

Erschienen in: Medical & Biological Engineering & Computing | Ausgabe 11/2016

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Abstract

Calcific aortic valve disease (CAVD) is characterized by calcification accumulation and thickening of the aortic valve cusps, leading to stenosis. The importance of fluid flow shear stress in the initiation and regulation of CAVD progression is well known and has been studied recently using fluid–structure interaction (FSI) models. While cusp calcifications are three-dimensional (3D) masses, previously published FSI models have represented them as either stiffened or thickened two-dimensional (2D) cusps. This study investigates the hemodynamic effect of these calcifications employing FSI models using 3D patient-specific calcification masses. A new reverse calcification technique (RCT) is used for modeling different stages of calcification growth based on the spatial distribution of calcification density. The RCT is applied to generate the 3D calcification deposits reconstructed from a patient-specific CT scans. Our results showed that consideration of 3D calcification deposits led to both higher fluid shear stresses and unique fluid shear stress distribution on the aortic side of the cusps that may have an impact on the calcification growth rate. However, the flow did not seem to affect the geometry of the calcification during the growth phase.

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Metadaten
Titel
Fluid–structure interaction modeling of calcific aortic valve disease using patient-specific three-dimensional calcification scans
verfasst von
Rotem Halevi
Ashraf Hamdan
Gil Marom
Karin Lavon
Sagit Ben-Zekry
Ehud Raanani
Danny Bluestein
Rami Haj-Ali
Publikationsdatum
01.11.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Medical & Biological Engineering & Computing / Ausgabe 11/2016
Print ISSN: 0140-0118
Elektronische ISSN: 1741-0444
DOI
https://doi.org/10.1007/s11517-016-1458-0

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