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首页> 美国卫生研究院文献>Frontiers in Physiology >Development of a Patient-Specific Multi-Scale Model to Understand Atherosclerosis and Calcification Locations: Comparison with In vivo Data in an Aortic Dissection
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Development of a Patient-Specific Multi-Scale Model to Understand Atherosclerosis and Calcification Locations: Comparison with In vivo Data in an Aortic Dissection

机译：特定患者的多尺度模型的发展以了解动脉粥样硬化和钙化的位置：与主动脉夹层体内数据的比较。

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Vascular calcification results in stiffening of the aorta and is associated with hypertension and atherosclerosis. Atherogenesis is a complex, multifactorial, and systemic process; the result of a number of factors, each operating simultaneously at several spatial and temporal scales. The ability to predict sites of atherogenesis would be of great use to clinicians in order to improve diagnostic and treatment planning. In this paper, we present a mathematical model as a tool to understand why atherosclerotic plaque and calcifications occur in specific locations. This model is then used to analyze vascular calcification and atherosclerotic areas in an aortic dissection patient using a mechanistic, multi-scale modeling approach, coupling patient-specific, fluid-structure interaction simulations with a model of endothelial mechanotransduction. A number of hemodynamic factors based on state-of-the-art literature are used as inputs to the endothelial permeability model, in order to investigate plaque and calcification distributions, which are compared with clinical imaging data. A significantly improved correlation between elevated hydraulic conductivity or volume flux and the presence of calcification and plaques was achieved by using a shear index comprising both mean and oscillatory shear components (HOLMES) and a non-Newtonian viscosity model as inputs, as compared to widely used hemodynamic indicators. The proposed approach shows promise as a predictive tool. The improvements obtained using the combined biomechanical/biochemical modeling approach highlight the benefits of mechanistic modeling as a powerful tool to understand complex phenomena and provides insight into the relative importance of key hemodynamic parameters.
机译：血管钙化导致主动脉硬化，并伴有高血压和动脉粥样硬化。动脉粥样硬化是一个复杂，多因素的系统性过程。许多因素的结果，每个因素同时在几个时空尺度上运作。预测动脉粥样硬化发生部位的能力对于临床医生将很有用，以改善诊断和治疗计划。在本文中，我们提出了一个数学模型作为一种工具，以了解为什么在特定位置会发生动脉粥样硬化斑块和钙化。然后，该模型使用一种机械的，多尺度的建模方法，结合特定于患者的流体结构相互作用模拟与内皮机械传导模型，用于分析主动脉夹层患者的血管钙化和动脉粥样硬化区域。为了研究菌斑和钙化分布，将许多基于最新文献的血液动力学因素用作内皮渗透性模型的输入，并将其与临床影像数据进行比较。与广泛使用的相比，通过使用包括均值和振荡剪切分量（HOLMES）的剪切指数和非牛顿粘度模型作为输入，可以显着改善升高的水力传导率或体积通量与钙化和斑块之间的相关性。血液动力学指标。所提出的方法将希望作为一种预测工具。使用组合的生物力学/生化建模方法获得的改进突出了机械建模作为理解复杂现象的有力工具的好处，并提供了对关键血液动力学参数的相对重要性的见识。

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