Computational Modeling of Right Ventricular Intracardiac Flow in Tetralogy of Fallot

法洛四联症是青紫型心脏病最常见的形式，通常在早期通过手术矫正

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.