title: Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors.
abstract: Atherosclerosis is a systemic disease with local manifestations. Low-density lipoprotein (LDL) accumulation in the subendothelial layer is one of the hallmarks of atherosclerosis onset and ignites plaque development and progression. Blood flow-induced endothelial shear stress (ESS) is causally related to the heterogenic distribution of atherosclerotic lesions and critically affects LDL deposition in the vessel wall. In this work we modeled blood flow and LDL transport in the coronary arterial wall and investigated the influence of several hemodynamic and biological factors that may regulate LDL accumulation. We used a three-dimensional model of a stenosed right coronary artery reconstructed from angiographic and intravascular ultrasound patient data. We also reconstructed a second model after restoring the patency of the stenosed lumen to its nondiseased state to assess the effect of the stenosis on LDL accumulation. Furthermore, we implemented a new model for LDL penetration across the endothelial membrane, assuming that endothelial permeability depends on the local lumen LDL concentration. The results showed that the presence of the stenosis had a dramatic effect on the local ESS distribution and LDL accumulation along the artery, and areas of increased LDL accumulation were observed in the downstream region where flow recirculation and low ESS were present. Of the studied factors influencing LDL accumulation, 1) hypertension, 2) increased endothelial permeability (a surrogate of endothelial dysfunction), and 3) increased serum LDL levels, especially when the new model of variable endothelial permeability was applied, had the largest effects, thereby supporting their role as major cardiovascular risk factors.
authors.affiliation: Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
authors.forename: Antonis I
authors.initials: AI
authors.lastname: Sakellarios
authors.forename: Michail I
authors.initials: MI
authors.lastname: Papafaklis
authors.forename: Panagiotis
authors.initials: P
authors.lastname: Siogkas
authors.forename: Lambros S
authors.initials: LS
authors.lastname: Athanasiou
authors.forename: Themistoklis P
authors.initials: TP
authors.lastname: Exarchos
authors.forename: Konstantinos
authors.initials: K
authors.lastname: Stefanou
authors.forename: Christos V
authors.initials: CV
authors.lastname: Bourantas
authors.forename: Katerina K
authors.initials: KK
authors.lastname: Naka
authors.forename: Lampros K
authors.initials: LK
authors.lastname: Michalis
authors.forename: Oberdan
authors.initials: O
authors.lastname: Parodi
authors.forename: Dimitrios I
authors.initials: DI
authors.lastname: Fotiadis
mesh_terms: D000368:Aged; D000465:Algorithms; D050197:Atherosclerosis / Q000473:pathology; D001809:Blood Viscosity; D002199:Capillary Permeability / Q000502:physiology; D002318:Cardiovascular Diseases / Q000453:epidemiology; D003198:Computer Simulation; D017023:Coronary Angiography; D023921:Coronary Stenosis / Q000378:metabolism*; D003331:Coronary Vessels / Q000378:metabolism*; D004730:Endothelium, Vascular / Q000378:metabolism*; D006339:Heart Rate / Q000502:physiology; D006439:Hemodynamics / Q000502:physiology; D006801:Humans; D006973:Hypertension / Q000503:physiopathology; D007091:Image Processing, Computer-Assisted; D008077:Lipoproteins, LDL / Q000097:blood / Q000378:metabolism*; D018810:Magnetic Resonance Angiography; D008297:Male; D008954:Models, Biological; D018570:Risk Assessment
chemical_list: D008077:Lipoproteins, LDL
keywords: atherosclerosis; endothelial permeability; low-density lipoprotein transport; patient-specific simulations; risk factors; shear stress