Analyses of individual atherosclerotic plaques are mostly descriptive, relying - for example - on histological classification by spectral analysis of ultrasound waves or staining and observing particular cellular components. Such passive methods have proved useful for characterizing the structure and vulnerability of plaques but have little quantitative predictive power. Our aim is to introduce and discuss a computational framework to provide insight to clinicians and help them visualize internal plaque dynamics. We use Partial Differential Equations (PDEs) with macrophages, necrotic cells, oxidized lipids, oxygen concentration and PDGF (Platelet Derived Growth Factor) as primary variables coupled to a biomechanical model to describe vessel growth. The model is deterministic, providing mechanical, morphological, and histological characteristics of an atherosclerotic vessel at any desired future time point. We use our model to create computer-generated animations of a plaque evolution that are in qualitative agreement with published serial ultrasound images and hypothesize possible atherogenic mechanisms. A systems-biology model consisting of 5 differential equations is able to capture the morphology of necrotic cores residing within vulnerable atherosclerotic plaque. In the context of the model, the distribution of Ox-LDL particles, endothelial inflammation, plaque oxygenation (via the presence of vasa vasora) and intimal oxygenation are four important factors that drive changes in core morphology.

中文翻译：

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模拟易损动脉粥样硬化斑块的综合方法。


对单个动脉粥样硬化斑块的分析大多是描述性的，例如，依赖于通过超声波光谱分析或染色和观察特定细胞成分进行的组织学分类。事实证明，这种被动方法对于表征斑块的结构和脆弱性很有用，但定量预测能力很小。我们的目标是介绍和讨论一个计算框架，为临床医生提供见解并帮助他们可视化内部斑块动态。我们使用偏微分方程 (PDE)，以巨噬细胞、坏死细胞、氧化脂质、氧浓度和 PDGF（血小板衍生生长因子）作为主要变量，与生物力学模型相结合来描述血管生长。该模型是确定性的，可提供动脉粥样硬化血管在任何所需的未来时间点的机械、形态和组织学特征。我们使用我们的模型创建计算机生成的斑块演变动画，该动画与已发布的连续超声图像定性一致，并假设可能的动脉粥样硬化机制。由 5 个微分方程组成的系统生物学模型能够捕获易损动脉粥样硬化斑块内坏死核心的形态。在该模型中，Ox-LDL 颗粒的分布、内皮炎症、斑块氧合（通过血管血管的存在）和内膜氧合是驱动核心形态变化的四个重要因素。