Computational Modeling of Right Ventricular Intracardiac Flow in Tetralogy of Fallot

法洛四联症是最常见的紫绀型心脏病，通常在早期手术矫正。 2婴儿期然而，大多数法洛四联症（rTOF）修复后的幸存者将遭受长期的 3例肺功能不全，右心室（RV）扩大，需行肺动脉瓣置换术（PVR） 4作为青少年或年轻人。手术的时间历来由心脏决定。 5磁共振成像（cMRI）。然而，PVR的时间是有争议的，因为有可变的CMR PVR的6个标准，瓣膜置换术的耐久性有限，并且没有方法确定 7 PVR的血流动力学益处。计算流体动力学（CFD）模拟是解决这一难题的关键， 8被用于模拟和指导其他形式的先天性心脏病手术。 9.拟议研究的总体目标是使用以下方法模拟rTOF患者的异常血流： 10例cMRI数据。我们假设我们可以在PVR之前检测到rTOF患者的重要血流异常， 11通过我们独特的CFD求解器使用cMRI数据。与其他形式的CFD相比，我们的方法 12独特，因为它模拟了移动RV内的流动，并且仅依赖于cMRI数据。我们计划解决 使用cMRI数据创建50例rTOF患者的综合模拟。 14本申请的具体目标包括：1）使用cMRI数据重建RV室壁运动，2） 15模拟rTOF患者队列中的RV心内血流，3）使用体内cMRI验证CFD求解器结果 以三维速度编码相位对比（4D流）的形式进行16次测量。 17这项工作的结果将验证我们完全开发的rTOF中RV流的综合CFD求解器 18个病人未来的工作将利用此求解器开发PVR的预测模型。随着越来越多地使用 19 PVR和不断增长的rTOF成人人口，这项工作将对他们的整体护理产生重大影响， 20名临床医生的血流生物标志物可预测PVR的获益并指导治疗。

1 Tetralogy of Fallot is the most common form of cyanotic heart disease, typically surgically corrected in early 2 infancy. However, a majority of survivors with repaired Tetralogy of Fallot (rTOF) will suffer from long-standing 3 pulmonary insufficiency, right ventricular (RV) enlargement, and require pulmonary valve replacement (PVR) 4 as a teenager or young adult. The timing of the procedure has been historically determined by cardiac 5 magnetic resonance imaging (cMRI). However, the timing of PVR is controversial, as there are variable CMR 6 criteria for PVR, valve replacements have limited durability, and there is no method to determine the 7 hemodynamic benefit of PVR. Computational fluid dynamics (CFD) simulation is key to this dilemma, as CFD 8 been used to simulate and guide other forms of congenital heart surgery. 9 The overall objective of the proposed research is to create a simulation of abnormal flow in rTOF patients using 10 cMRI data. We hypothesize that we can detect important flow abnormalities in rTOF patients, prior to PVR, 11 through our unique CFD solver using cMRI data. When compared to other forms of CFD, our method is 12 unique as it simulates flow inside a moving RV and relies only on cMRI data. We plan on addressing our 13 hypothesis by using cMRI data to create comprehensive simulations of 50 rTOF patients. 14 The specific objectives of this application include: 1) To reconstruct RV wall motion with cMRI data, 2) To 15 simulate RV intracardiac flow in a cohort of rTOF patients, 3) To validate CFD solver results with in-vivo cMRI 16 measurements in the form of three-dimensional velocity-encoded phase contrast (4D flow). 17 The results from this work will validate our fully developed, comprehensive CFD solver of RV flow in rTOF 18 patients. Future work would utilize this solver to develop a prediction model for PVR. With the increasing use of 19 PVR and growing adult population of rTOF, this work will have significant impact on their overall care, providing 20 clinicians with flow biomarkers that may predict the benefit of PVR and guide therapy.