Suppr超能文献

应用临床数据评估耦合生物-血液动力学数值模型,以预测冠状动脉中的白细胞黏附。

Assessment with clinical data of a coupled bio-hemodynamics numerical model to predict leukocyte adhesion in coronary arteries.

机构信息

Department of Mechanical Engineering, The University of Texas at Dallas, Richardson, TX, 75080, USA.

Department of Bioengineering, The University of Texas at Dallas, Richardson, TX, 75080, USA.

出版信息

Sci Rep. 2021 Jun 16;11(1):12680. doi: 10.1038/s41598-021-92084-4.

Abstract

Numerical simulations of coupled hemodynamics and leukocyte transport and adhesion inside coronary arteries have been performed. Realistic artery geometries have been obtained for a set of four patients from intravascular ultrasound and angiography images. The numerical model computes unsteady three-dimensional blood hemodynamics and leukocyte concentration in the blood. Wall-shear stress dependent leukocyte adhesion is also computed through agent-based modeling rules, fully coupled to the hemodynamics and leukocyte transport. Numerical results have a good correlation with clinical data. Regions where high adhesion is predicted by the simulations coincide to a good approximation with artery segments presenting plaque increase, as documented by clinical data from baseline and six-month follow-up exam of the same artery. In addition, it is observed that the artery geometry and, in particular, the tortuosity of the centerline are a primary factor in determining the spatial distribution of wall-shear stress, and of the resulting leukocyte adhesion patterns. Although further work is required to overcome the limitations of the present model and ultimately quantify plaque growth in the simulations, these results are encouraging towards establishing a predictive methodology for atherosclerosis progress.

摘要

已经对冠状动脉内的血流动力学和白细胞输送及黏附的耦合进行了数值模拟。通过血管内超声和血管造影图像,为 4 位患者中的一组获得了真实的动脉几何形状。该数值模型计算了血液中血液非稳态三维流场和白细胞浓度。通过基于代理的建模规则计算白细胞黏附,该规则与血流动力学和白细胞输送完全耦合。数值结果与临床数据具有良好的相关性。模拟预测的高黏附区域与斑块增加的动脉节段非常吻合,这与同一动脉的基线和 6 个月随访检查的临床数据相符。此外,还观察到动脉几何形状,特别是中心线的弯曲度,是决定壁面切应力和由此产生的白细胞黏附模式的空间分布的主要因素。尽管需要进一步的工作来克服当前模型的限制,并最终在模拟中量化斑块生长,但这些结果令人鼓舞,为动脉粥样硬化进展建立了一种预测方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b75/8208986/d5ef74ae5ab0/41598_2021_92084_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验