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Patient-Specific Prediction of Coronary Plaque Growth From CTA Angiography: A Multiscale Model for Plaque Formation and Progression

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Patient-Specific Prediction of Coronary Plaque Growth From CTA Angiography: A Multiscale Model for Plaque Formation and Progression

Content Provider	IEEE Xplore Digital Library
Author	Parodi, O. Exarchos, T.P. Marraccini, P. Vozzi, F. Milosevic, Z. Nikolic, D. Sakellarios, A. Siogkas, P.K. Fotiadis, D.I. Filipovic, N.
Copyright Year	1997
Abstract	Computational fluid dynamics methods based on in vivo 3-D vessel reconstructions have recently been identified the influence of wall shear stress on endothelial cells as well as on vascular smooth muscle cells, resulting in different events such as flow mediated vasodilatation, atherosclerosis, and vascular remodeling. Development of image-based modeling technologies for simulating patient-specific local blood flows is introducing a novel approach to risk prediction for coronary plaque growth and progression. In this study, we developed 3-D model of plaque formation and progression that was tested in a set of patients who underwent coronary computed tomography angiography (CTA) for anginal symptoms. The 3-D blood flow is described by the Navier-Stokes equations, together with the continuity equation. Mass transfer within the blood lumen and through the arterial wall is coupled with the blood flow and is modeled by a convection-diffusion equation. The low density lipoprotein (LDL) transports in lumen of the vessel and through the vessel tissue (which has a mass consumption term) are coupled by Kedem-Katchalsky equations. The inflammatory process is modeled using three additional reaction-diffusion partial differential equations. A full 3-D model was created. It includes blood flow and LDL concentration, as well as plaque formation and progression. Furthermore, features potentially affecting plaque growth, such as patient risk score, circulating biomarkers, localization and composition of the initial plaque, and coronary vasodilating capability were also investigated. The proof of concept of the model effectiveness was assessed by repetition of CTA, six months after the baseline evaluation. Besides the low values of local shear stress, plaque characteristics, risk profile, pattern of circulating adhesion molecules, and reduced coronary flow reserve at baseline appeared to affect plaque progression toward flow-limiting lesions at follow-up evaluation. Although preliminary, our multidisciplinary approach to a “personalized” prediction of coronary plaque progression suggests that incorporation in atherosclerotic models of systemic and local hemodynamic features may better predict evolution of plaques in coronary artery disease stable patients.
Sponsorship	IEEE Engineering in Medicine and Biology Society IEEE Computer Society
Page Count	14
File Size	1104228
Starting Page	952
Ending Page	965
File Format	PDF
ISSN	10897771
Volume Number	16
Issue Number	5
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-09-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Arteries Three dimensional displays Lesions Mathematical model Atherosclerosis Angiography Computational modeling plaque progression Blood flow dynamics coronary atherosclerosis multislice computed tomography
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications Biotechnology

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