Kim Minsuok, Bordas Rafel, Vos Wim, Hartley Ruth A, Brightling Chris E, Kay David, Grau Vicente, Burrowes Kelly S
Department of Computer Science, University of Oxford, Oxford, UK.
FluidDA, Groeningenlei 132, Kontich, 2550, Belgium.
Int J Numer Method Biomed Eng. 2015 Dec;31(12). doi: 10.1002/cnm.2730. Epub 2015 Jun 25.
Complex flow patterns exist within the asymmetric branching airway network in the lungs. These flow patterns are known to become increasingly heterogeneous during disease as a result of various mechanisms such as bronchoconstriction or alterations in lung tissue compliance. Here, we present a coupled model of tissue deformation and network airflow enabling predictions of dynamic flow properties, including temporal flow rate, pressure distribution, and the occurrence of reverse flows. We created two patient-specific airway geometries, one for a healthy subject and one for a severe asthmatic subject, derived using a combination of high-resolution CT data and a volume-filling branching algorithm. In addition, we created virtually constricted airway geometry by reducing the airway radii of the healthy subject model. The flow model was applied to these three different geometries to solve the pressure and flow distribution over a breathing cycle. The differences in wave phase of the flows in parallel airways induced by asymmetric airway geometry and bidirectional interaction between intra-acinar and airway network pressures were small in central airways but were more evident in peripheral airways. The asthmatic model showed elevated ventilation heterogeneity and significant flow disturbance. The reverse flows in the asthmatic model not only altered the local flow characteristics but also affected total lung resistance. The clinical significance of temporal flow disturbance on lung ventilation in normal airway model is obscure. However, increased flow disturbance and ventilation heterogeneity observed in the asthmatic model suggests that reverse flow may be an important factor for asthmatic lung function.
肺部不对称分支气道网络中存在复杂的流动模式。众所周知,由于支气管收缩或肺组织顺应性改变等各种机制,这些流动模式在疾病期间会变得越来越不均匀。在此,我们提出了一种组织变形与网络气流的耦合模型,能够预测动态流动特性,包括瞬时流速、压力分布以及逆流的发生。我们创建了两种针对特定患者的气道几何模型,一个用于健康受试者,另一个用于重度哮喘患者,通过结合高分辨率CT数据和容积填充分支算法得出。此外,我们通过减小健康受试者模型的气道半径创建了虚拟狭窄气道几何模型。将流动模型应用于这三种不同的几何模型,以求解一个呼吸周期内的压力和流量分布。由不对称气道几何形状引起的平行气道中气流的波相位差异以及腺泡内与气道网络压力之间的双向相互作用,在中央气道中较小,但在周边气道中更为明显。哮喘模型显示通气不均匀性增加且存在明显的气流紊乱。哮喘模型中的逆流不仅改变了局部流动特性,还影响了总肺阻力。正常气道模型中瞬时气流紊乱对肺通气的临床意义尚不清楚。然而,在哮喘模型中观察到的气流紊乱增加和通气不均匀性表明,逆流可能是哮喘肺功能的一个重要因素。