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Research Papers

Computational Modeling of LDL and Albumin Transport in an In Vivo CT Image-Based Human Right Coronary Artery

[+] Author and Article Information
Nanfeng Sun, Ryo Torii, Nigel B. Wood

Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK

Alun D. Hughes, Simon A. Thom

National Heart and Lung Institute, International Centre for Circulatory Health, Imperial College London, St. Mary’s Hospital, London W2 1LA, UK

X. Yun Xu1

Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UKyun.xu@imperial.ac.uk

1

Corresponding author.

J Biomech Eng 131(2), 021003 (Dec 10, 2008) (9 pages) doi:10.1115/1.3005161 History: Received December 12, 2007; Revised July 21, 2008; Published December 10, 2008

Low wall shear stress (WSS) is implicated in endothelial dysfunction and atherogenesis. The accumulation of macromolecules is also considered as an important factor contributing to the development of atherosclerosis. In the present study, a fluid-wall single-layered model incorporated with shear-dependent transport parameters was used to investigate albumin and low-density lipoprotein (LDL) transport in an in vivo computed tomographic image-based human right coronary artery (RCA). In the fluid-wall model, the bulk blood flow was modeled by the Navier–Stokes equations, Darcy’s law was employed to model the transmural flow in the arterial wall, mass balance of albumin and LDL was governed by the convection-diffusion mechanism with an additional reaction term in the wall, and the Kedem–Katchalsky equations were applied at the endothelium as the interface condition between the lumen and wall. Shear-dependent models for hydraulic conductivity and albumin permeability were derived from experimental data in literature to investigate the influence of WSS on macromolecular accumulation in the arterial wall. A previously developed so-called lumen-free time-averaged scheme was used to approximate macromolecular transport under pulsatile flow conditions. LDL and albumin accumulations in the subendothelial layer were found to be colocalized with low WSS. Two distinct mechanisms responsible for the localized accumulation were identified: one was insufficient efflux from the subendothelial layer to outer wall layers caused by a weaker transmural flow; the other was excessive influx to the subendothelial layer from the lumen caused by a higher permeability of the endothelium. The comparison between steady flow and pulsatile flow results showed that the dynamic behavior of the pulsatile flow could induce a wider and more diffuse macromolecular accumulation pattern through the nonlinear shear-dependent transport properties. Therefore, it is vital to consider blood pulsatility when modeling the shear-dependent macromolecular transport in large arteries. In the present study, LDL and albumin accumulations were observed in the low WSS regions of a human RCA using a fluid-wall mass transport model. It was also found that steady flow simulation could overestimate the magnitude and underestimate the area of accumulations. The association between low WSS and accumulation of macromolecules leading to atherosclerosis may be mediated through effects on transport properties and mass transport and is also influenced by flow pulsatility.

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Figures

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Figure 1

Computational geometry of a human RCA reconstructed from CT images. 5D extensions (extensions not shown in the illustration) were added at both inlet and outlet of the artery to accommodate blood flow simulations.

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Figure 2

Normalized shear-dependent hydraulic conductivity (a) and albumin permeability (b) of the endothelium. The analytical model for shear-dependent hydraulic conductivity (Lp) was derived using experimental data reported by Sill (33), while shear-dependent albumin permeability was derived from experimental data reported by Kudo (37).

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Figure 3

A physiologically realistic coronary flow waveform (acquired from a different patient) used in the present study. The mean Reynolds number Re=184.

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Figure 4

Distribution of WSS magnitude calculated from the steady flow simulation (a) and pulsatile flow simulation (b) shown on the epicardial and pericardial sides of the human RCA. Three main low WSS regions can be identified: downstream of the main stenosis in the proximal part, downstream of a second stenosis in the middle of the RCA, and in the expansion at the distal end of the RCA.

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Figure 5

Distribution of transmural velocity (Δpw=120mmHg) calculated from the steady flow simulation (a) and pulsatile flow simulation (b) shown on the epicardial and pericardial sides of the human RCA

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Figure 6

Distribution of transmural velocity (Δpw=70mmHg) calculated from the steady flow simulation (a) and pulsatile flow simulation (b) shown on the epicardial and pericardial sides of the human RCA

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Figure 7

Distribution of LDL concentration on the lumenal surface calculated from the steady flow simulation shown on the epicardial and pericardial sides of the human RCA (Δpw=120mmHg)

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Figure 8

Distribution of subendothelial LDL concentration calculated from the steady flow simulation (a) and pulsatile flow simulation (b) shown on the epicardial and pericardial sides of the human RCA (Δpw=120mmHg)

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Figure 9

Distribution of albumin concentration on the lumenal surface calculated from the steady flow simulation shown on the epicardial and pericardial sides of the human RCA (Δpw=70mmHg)

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Figure 10

Distribution of transendothelial albumin flux calculated from the steady flow simulation (a) and pulsatile flow simulation (b) shown on the epicardial and pericardial sides of the human RCA. Flux was normalized by a reference flux N0=1×10−11m∕s(Δpw=70mmHg).

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Figure 11

Distribution of subendothelial albumin concentration calculated from the steady flow simulation (a) and pulsatile flow simulation (b) shown on the epicardial and pericardial sides of the human RCA (Δpw=70mmHg)

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