Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries

Abstract Numerical simulations of coupled hemodynamics and leukocyte transport and adhesion inside coronary arteries have been performed. Realistic artery geometries have been obtained for a set of four patients from intravascular ultrasound and angiography images. The numerical model computes unste...

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Autores principales:	Umberto Ciri, Ruth L. Bennett, Rita Bhui, David S. Molony, Habib Samady, Clark A. Meyer, Heather N. Hayenga, Stefano Leonardi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/efed1c87cc924ad89fac5867eafe5a42
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spelling	oai:doaj.org-article:efed1c87cc924ad89fac5867eafe5a422021-12-02T17:40:48ZAssessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries10.1038/s41598-021-92084-42045-2322https://doaj.org/article/efed1c87cc924ad89fac5867eafe5a422021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92084-4https://doaj.org/toc/2045-2322Abstract Numerical simulations of coupled hemodynamics and leukocyte transport and adhesion inside coronary arteries have been performed. Realistic artery geometries have been obtained for a set of four patients from intravascular ultrasound and angiography images. The numerical model computes unsteady three-dimensional blood hemodynamics and leukocyte concentration in the blood. Wall-shear stress dependent leukocyte adhesion is also computed through agent-based modeling rules, fully coupled to the hemodynamics and leukocyte transport. Numerical results have a good correlation with clinical data. Regions where high adhesion is predicted by the simulations coincide to a good approximation with artery segments presenting plaque increase, as documented by clinical data from baseline and six-month follow-up exam of the same artery. In addition, it is observed that the artery geometry and, in particular, the tortuosity of the centerline are a primary factor in determining the spatial distribution of wall-shear stress, and of the resulting leukocyte adhesion patterns. Although further work is required to overcome the limitations of the present model and ultimately quantify plaque growth in the simulations, these results are encouraging towards establishing a predictive methodology for atherosclerosis progress.Umberto CiriRuth L. BennettRita BhuiDavid S. MolonyHabib SamadyClark A. MeyerHeather N. HayengaStefano LeonardiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Umberto Ciri Ruth L. Bennett Rita Bhui David S. Molony Habib Samady Clark A. Meyer Heather N. Hayenga Stefano Leonardi Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
description	Abstract Numerical simulations of coupled hemodynamics and leukocyte transport and adhesion inside coronary arteries have been performed. Realistic artery geometries have been obtained for a set of four patients from intravascular ultrasound and angiography images. The numerical model computes unsteady three-dimensional blood hemodynamics and leukocyte concentration in the blood. Wall-shear stress dependent leukocyte adhesion is also computed through agent-based modeling rules, fully coupled to the hemodynamics and leukocyte transport. Numerical results have a good correlation with clinical data. Regions where high adhesion is predicted by the simulations coincide to a good approximation with artery segments presenting plaque increase, as documented by clinical data from baseline and six-month follow-up exam of the same artery. In addition, it is observed that the artery geometry and, in particular, the tortuosity of the centerline are a primary factor in determining the spatial distribution of wall-shear stress, and of the resulting leukocyte adhesion patterns. Although further work is required to overcome the limitations of the present model and ultimately quantify plaque growth in the simulations, these results are encouraging towards establishing a predictive methodology for atherosclerosis progress.
format	article
author	Umberto Ciri Ruth L. Bennett Rita Bhui David S. Molony Habib Samady Clark A. Meyer Heather N. Hayenga Stefano Leonardi
author_facet	Umberto Ciri Ruth L. Bennett Rita Bhui David S. Molony Habib Samady Clark A. Meyer Heather N. Hayenga Stefano Leonardi
author_sort	Umberto Ciri
title	Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
title_short	Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
title_full	Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
title_fullStr	Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
title_full_unstemmed	Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
title_sort	assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/efed1c87cc924ad89fac5867eafe5a42
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Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries

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