患有单心室心脏病的儿童通常需要一系列的三个手术,(1)诺伍德,(2)格伦,和(3)Fontan,这最终导致肺和全身回路的完全分离,以改善肺/体循环。在最后阶段,丰坦行动,下腔静脉(IVC)连接到肺动脉(PA),允许剩余的脱氧血液被动地流到肺回路。假设优化Fontan解剖结构将导致功率损失减少和更平衡的肝血流分布。优化几何形状的一种方法是创建患者特定的数字孪生模型,以模拟Fontan导管的各种配置,这需要近端PA解剖结构和阻力的计算模型,以及远端肺血管阻力(PVR),在Glenn阶段.为此,使用3D计算流体动力学(CFD)和0D集总参数(LP)模拟开发了一个优化管道,通过最小化与患者心脏磁共振(CMR)和导管插入(CATH)数据相关的模拟流量和压力误差,迭代地细化每个肺的PVR.虽然PVR也可以通过从CATH和CMR数据计算压力梯度和流量的比率来直接估计,计算方法可以分别识别沿着Glenn途径的PVR的不同成分,允许更详细地描述格伦脉管系统。结果表明,CFD和LP模型的优化PVR之间具有良好的相关性(n=16),左肺和右肺的组内相关系数(ICC)为0.998(p=0.976)和0.991(p=0.943),分别。此外,与CMR流量和CATH压力数据相比,优化的PVR估计值导致平均出口流量和压力误差小于5%。优化的PVR估计值也与从CATH压力和CMR流量计算的PVR估计值非常吻合。产生小于4%的平均差。
Children with single ventricle heart disease typically require a series of three operations, (1) Norwood, (2) Glenn, and (3) Fontan, which ultimately results in complete separation of the pulmonary and systemic circuits to improve pulmonary/systemic circulation. In the last stage, the Fontan operation, the inferior vena cava (IVC) is connected to the pulmonary arteries (PAs), allowing the remainder of deoxygenated blood to passively flow to the pulmonary circuit. It is hypothesized that optimizing the Fontan anatomy would lead to decreased power loss and more balanced hepatic flow distribution. One approach to optimizing the geometry is to create a patient-specific digital twin to simulate various configurations of the Fontan conduit, which requires a computational model of the proximal PA anatomy and resistance, as well as the distal Pulmonary Vascular Resistance (PVR), at the Glenn stage. To that end, an optimization pipeline was developed using 3D computational fluid dynamics (CFD) and 0D lumped parameter (LP) simulations to iteratively refine the PVR of each lung by minimizing the simulated flow and pressure error relative to patients\' cardiac magnetic resonance (CMR) and catheterization (CATH) data. While the PVR can also be estimated directly by computing the ratio of pressure gradients and flow from CATH and CMR data, the computational approach can separately identify the different components of PVR along the Glenn pathway, allowing for a more detailed depiction of the Glenn vasculature. Results indicate good correlation between the optimized PVR of the CFD and LP models (n = 16), with an intraclass correlation coefficient (ICC) of 0.998 (p = 0.976) and 0.991 (p = 0.943) for the left and right lung, respectively. Furthermore, compared to CMR flow and CATH pressure data, the optimized PVR estimates result in mean outlet flow and pressure errors of less than 5%. The optimized PVR estimates also agree well with the computed PVR estimates from CATH pressure and CMR flow for both lungs, yielding a mean difference of less than 4%.