Wall Shear Stress (WSS) Analysis in Atherosclerosis in Partial Ligated Apolipoprotein E Knockout Mouse Model through Computational Fluid Dynamics (CFD)

Abstract

Atherosclerosis involves an inflammatory response due to plaque formation within the arteries, which can lead to ischemic stroke and heart disease. It is one of the leading causes of death worldwide, with various contributing factors such as hyperlipidemia, hypertension, obesity, diabetes, and smoking. Wall shear stress (WSS) is also known as a contributing factor of the formation of atherosclerotic plaques. Since the causes of atherosclerosis cannot be attributed to a single factor, clearly understanding the mechanisms and causes of its occurrence is crucial for preventing the disease and developing effective treatment strategies. To better understand atherosclerosis and define the correlation between various contributing factors, computational fluid dynamics (CFD) analysis is primarily used. CFD simulates WSS, the frictional force caused by blood flow on the vessel wall with various hemodynamic changes. Using apolipoprotein E knockout (ApoE-KO) mice subjected to partial ligation and a high-fat diet at 1-week, 2-week, and 4-week intervals as an atherosclerosis model, CFD analysis was conducted along with the reconstruction of carotid artery blood flow via magnetic resonance imaging (MRI) and compared to the inflammatory factors and pathological staining. In this experiment, a comparative analysis of the effects of high WSS and low WSS was conducted by comparing the standard deviation of time-averaged wall shear stress (TAWSS) at each point within the vessel wall. As a novel approach, the standard deviation of TAWSS within the vessel was analyzed with the staining results and pathological features. Since the onset of atherosclerosis cannot be explained by a single factor, the aim was to find the correlation between the thickness of atherosclerotic plaques and inflammatory factors through standard deviation analysis. As a result, the gap between low WSS and high WSS widened as the interval between weeks in the atherosclerosis mouse model increased. This finding not only linked the occurrence of atherosclerosis to WSS differences but also provided a connection to the causes of vulnerable plaques.

Keywords: ApoE-KO mice; atherosclerosis; computational fluid dynamics (CFD); plaque formation; standard deviation; wall shear stress (WSS).

Figure 1

Scheme of WSS evaluation acquisition of ApoE-KO mice atherosclerosis model. (A) Partially ligated ApoE-KO mice fed a high-fat diet were developed as an atherosclerosis model. To confirm disrupted blood flow, (B) MRI images were acquired, along with (C) H&E, Movat staining, and IF staining images. Based on these results, (D) a 3D reconstruction of the carotid artery was performed to evaluate WSS.

Figure 2

Blood flow disrupt confirmation through MRI TOF mode and histological staining of carotid artery. (A) Cross-sectioned MRI image and lateral MRI image of 1- and 4-week partial ligated ApoE-KO mice. Partial ligated LCA are indicated as white arrows in MRI images. (B) The excised sample of 4-week mice and H&E and MOVAT staining images of the cross-sectioned tissue at the partial ligation site (bifurcation), the midpoint, and the RCA without partial ligation as control. (C) H&E staining results of 1-, 2-, and 4-week LCA. Pathological features are marked in the image.

Figure 3

IF performed on the bifurcation part of the LCA. The samples were double-stained with VCAM-1 and NF-κB as one set, and CD31 and α-SMA as another set. (A–C) represent the 1-, 2-, and 4-week IF staining results for VCAM-1 (green) and NF-κB (red) in the LCA bifurcation. (D–F) show the staining results for CD31 (red) and α-SMA (green) in the LCA bifurcation, respectively. The arrows and dotted lines in the magnified images of each figure indicate the fluorescence biomarker. The arrows in Figures (A–C) represent NF-κB (red). The arrows in the magnified images of Figures (D–F) represent CD31 (red). For VCAM-1 (green), no significant observations were made, and α-SMA (green) was well visualized in Figures (D–F).

Figure 4

A 3D construction of the left carotid artery from the midpoint of LCA to bifurcation of the partial ligation part with WSS evaluation. (A) 3D image of LCA with WSS distribution; the red part refers to high WSS, where the blue part refers to low WSS. (B–E) are maximum WSS graphs for 1-, 2-, and 4-week mice in all groups, respectively.

Figure 5

Summary of (A) standard deviation of TAWSS, (B) area, (C) maximum WSS, and (D) fluorescence intensity for LCA and RCA (p value < 0.01 ** and <0.05 *).