Image-based computational assessment of vascular wall mechanics and hemodynamics in pulmonary arterial hypertension patients

基于图像的肺动脉高压患者血管壁力学和血流动力学计算评估

阅读:1

Abstract

Pulmonary arterial hypertension (PAH) is a disease characterized by an elevated pulmonary arterial (PA) pressure. While several computational hemodynamic models of the pulmonary vasculature have been developed to understand PAH, they are lacking in some aspects, such as the vessel wall deformation and its lack of calibration against measurements in humans. Here, we describe a computational modeling framework that addresses these limitations. Specifically, computational models describing the coupling of hemodynamics and vessel wall mechanics in the pulmonary vasculature of a PAH patient and a normal subject were developed. Model parameters, consisting of linearized stiffness E of the large vessels and Windkessel parameters for each outflow branch, were calibrated against in vivo measurements of pressure, flow and vessel wall deformation obtained, respectively, from right-heart catheterization, phase-contrast and cine magnetic resonance images. Calibrated stiffness E of the proximal PA was 2.0 and 0.5 MPa for the PAH and normal models, respectively. Calibrated total compliance C(T) and resistance R(T) of the distal vessels were, respectively, 0.32 ml/mmHg and 11.3 mmHg∗min/l for the PAH model, and 2.93 ml/mmHg and 2.6 mmHg∗min/l for the normal model. These results were consistent with previous findings that the pulmonary vasculature is stiffer with more constricted distal vessels in PAH patients. Individual effects on PA pressure due to remodeling of the distal and proximal compartments of the pulmonary vasculature were also investigated in a sensitivity analysis. The analysis suggests that the remodeling of distal vasculature contributes more to the increase in PA pressure than the remodeling of proximal vasculature.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。