Thekkethil Namshad, Gao Hao, Hill Nicholas A, Luo Xiaoyu
School of Mathematics and Statistics, University of Glasgow, Glasgow, UK.
Int J Numer Method Biomed Eng. 2025 Sep;41(9):e70091. doi: 10.1002/cnm.70091.
Blood perfusion in cardiac tissues involves intricate interactions among vascular networks and tissue mechanics. Perfusion deficit is one of the leading causes of cardiac diseases, and modeling certain cardiac conditions that are clinically infeasible, invasive, or costly can provide valuable supplementary insights to aid clinicians. However, existing homogeneous perfusion models lack the complexity required for patient-specific simulations. In this study, we develop a computational framework for modeling perfusion using a multicompartment Darcy flow model with heterogeneous anisotropic perfusion that incorporates the nonlinear deformation and compliance of blood vessels with poroelastic parameters derived from realistic vascular data. Through numerical simulations and a comparison of pore pressure results obtained from the proposed model and the Poiseuille flow approach in a benchmark problem, we demonstrate that the heterogeneous anisotropic model outperforms homogeneous models in predicting perfusion, particularly by accurately capturing the spatial heterogeneity of the poroelastic parameters and the permeability transitions from large vessels to microvessels. Additionally, the proposed model successfully simulates patient-specific conditions, such as vessel blockages, highlighting its potential for personalized medical applications.
心脏组织中的血液灌注涉及血管网络与组织力学之间复杂的相互作用。灌注不足是心脏病的主要病因之一，对某些临床上不可行、具有侵入性或成本高昂的心脏状况进行建模，可以为临床医生提供有价值的补充见解。然而，现有的均匀灌注模型缺乏针对患者特异性模拟所需的复杂性。在本研究中，我们开发了一个计算框架，用于使用多隔室达西流模型对灌注进行建模，该模型具有非均匀各向异性灌注，结合了血管的非线性变形和顺应性以及从实际血管数据得出的多孔弹性参数。通过数值模拟以及在一个基准问题中对所提出模型与泊肃叶流方法获得的孔隙压力结果进行比较，我们证明非均匀各向异性模型在预测灌注方面优于均匀模型，特别是通过准确捕捉多孔弹性参数的空间非均匀性以及从大血管到微血管的渗透率转变。此外，所提出的模型成功模拟了患者特异性状况，如血管堵塞，突出了其在个性化医疗应用中的潜力。
