Department of Convergence Medicine, Brain Korea 21 Project, College of Medicine, University of Ulsan, Seoul 05505, Republic of Korea.
Biomedical Engineering Research Center, Asan Institute for Life Science, Asan Medical Center, Seoul 05505, Republic of Korea.
Int J Mol Sci. 2024 Sep 12;25(18):9877. doi: 10.3390/ijms25189877.
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.
动脉粥样硬化涉及动脉内斑块形成引起的炎症反应，可导致缺血性中风和心脏病。它是全球主要的死亡原因之一，有多种致病因素，如高血脂、高血压、肥胖、糖尿病和吸烟等。壁面切应力（WSS）也是动脉粥样斑块形成的一个致病因素。由于动脉粥样硬化的病因不能归因于单一因素，因此，清楚地了解其发生的机制和原因对于预防该疾病和开发有效的治疗策略至关重要。为了更好地理解动脉粥样硬化并定义各种致病因素之间的相关性，主要使用计算流体动力学（CFD）分析。CFD 模拟 WSS，即血流对血管壁的摩擦力，伴随着各种血液动力学变化。使用载脂蛋白 E 敲除（ApoE-KO）小鼠，通过部分结扎和高脂肪饮食在 1 周、2 周和 4 周的间隔时间，建立动脉粥样硬化模型，通过磁共振成像（MRI）对颈动脉血流进行重建，并与炎症因子和病理染色进行 CFD 分析。在该实验中，通过比较血管壁内各点的时间平均壁面切应力（TAWSS）标准差，对高 WSS 和低 WSS 的影响进行了对比分析。作为一种新方法，还分析了血管内 TAWSS 标准差与染色结果和病理特征之间的相关性。由于动脉粥样硬化的发病不能用单一因素来解释，因此，本研究旨在通过标准差分析，找到动脉粥样硬化斑块厚度与炎症因子之间的相关性。结果表明，随着动脉粥样硬化小鼠模型中周数的增加，低 WSS 和高 WSS 之间的差距扩大。这一发现不仅将动脉粥样硬化的发生与 WSS 差异联系起来，还为易损斑块的病因提供了联系。
