Department of Mathematics, North Carolina State University, Raleigh, NC, USA.
Kitware, Inc., Carrboro, NC, USA.
Proc Inst Mech Eng H. 2020 Nov;234(11):1312-1329. doi: 10.1177/0954411920944110. Epub 2020 Jul 28.
Detection and monitoring of patients with pulmonary hypertension, defined as a mean blood pressure in the main pulmonary artery above 25 mmHg, requires a combination of imaging and hemodynamic measurements. This study demonstrates how to combine imaging data from microcomputed tomography images with hemodynamic pressure and flow waveforms from control and hypertensive mice. Specific attention is devoted to developing a tool that processes computed tomography images, generating subject-specific arterial networks in which one-dimensional fluid dynamics modeling is used to predict blood pressure and flow. Each arterial network is modeled as a directed graph representing vessels along the principal pathway to ensure perfusion of all lobes. The one-dimensional model couples these networks with structured tree boundary conditions representing the small arteries and arterioles. Fluid dynamics equations are solved in this network and compared to measurements of pressure in the main pulmonary artery. Analysis of microcomputed tomography images reveals that the branching ratio is the same in the control and hypertensive animals, but that the vessel length-to-radius ratio is significantly lower in the hypertensive animals. Fluid dynamics predictions show that in addition to changed network geometry, vessel stiffness is higher in the hypertensive animal models than in the control models.
肺动脉高压患者的检测和监测,定义为肺动脉主干内平均血压高于 25mmHg,需要影像学和血流动力学测量的结合。本研究展示了如何将微计算机断层扫描图像的影像学数据与对照和高血压小鼠的血流动力学压力和流量波形相结合。特别关注开发一种处理计算机断层扫描图像的工具,生成特定于主体的动脉网络,其中使用一维流体动力学模型来预测血压和流量。每个动脉网络都被建模为一个有向图,代表沿主通路的血管,以确保所有叶的灌注。一维模型将这些网络与代表小动脉和小动脉的结构化树边界条件耦合。在该网络中求解流体动力学方程,并与主肺动脉中的压力测量值进行比较。微计算机断层扫描图像的分析表明,在对照和高血压动物中,分支比相同,但在高血压动物中,血管长度与半径比显著降低。流体动力学预测表明,除了网络几何形状的改变外,高血压动物模型中的血管刚性也高于对照模型。