title: Three-dimensional simulations in Glenn patients: clinically based boundary conditions, hemodynamic results and sensitivity to input data.
abstract: While many congenital heart defects can be treated without significant long term sequelae, some achieve successful palliation as their definitive endpoints. The single-ventricle defect is one such defect and leaves the child with only one operational ventricle, requiring the systemic and the pulmonary circulations to be placed in series through several operations performed during early childhood. Numerical simulations may be used to investigate these hemodynamic conditions and their relation to post-operative sequelae; however, they rely heavily on boundary condition prescription. In this study, we investigate the impact of hemodynamic input data uncertainties on simulation results. Imaged-based patient-specific models of the multi-branched pulmonary arteries and superior vena cava were built for five cavopulmonary connection (i.e. Glenn) patients. Magnetic resonance imaging and catheterization data were acquired for each patient prior to their Fontan surgery. Inflow and outflow boundary conditions were constructed to match available clinical data and resulted in the development of a framework to incorporate these types of clinical data into patient-specific simulations. Three-dimensional computational fluid dynamics simulations were run and hemodynamic indicators were computed. Power loss was low (and efficiency very high) and a linear correlation was found between power loss and cardiac index among the five patients. Other indicators such as low wall shear stress were considered to better characterize these patients. Flow was complex and oscillatory near the anastomosis, and laminar in the smaller branches. While common trends were seen among patients, results showed differences among patients, especially in the 3D maps, strengthening the importance of patient-specific simulations. A sensitivity analysis was performed to investigate the impact of input data (clinical and modeling) to construct boundary conditions on several indicators. Overall, the sensitivity of the output indicators to the input data was small but non-negligible. The sensitivity of commonly used hemodynamic indicators to compare patients is discussed in this context. Power efficiency was much more sensitive to pressure variation than power loss. To increase the precision of such indicators, mean flow split between right and left lungs needs to be measured with more accuracy with higher priority than refining the model of how the flow is distributed on average among the smaller branches. Although ± 10% flow split imprecision seemed reasonable in terms of patient comparison, this study suggests that the common practice of imposing a right pulmonary artery/left pulmonary artery flow split of 55%/45% when performing patient specific simulations should be avoided. This study constitutes a first step towards understanding the hemodynamic differences between pre- and post Fontan surgery, predicting these differences, and evaluating surgical outcomes based on preoperative data.
authors.affiliation: Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, USA.
authors.forename: G
authors.initials: G
authors.lastname: Troianowski
authors.forename: C A
authors.initials: CA
authors.lastname: Taylor
authors.forename: J A
authors.initials: JA
authors.lastname: Feinstein
authors.forename: I E
authors.initials: IE
authors.lastname: Vignon-Clementel
mesh_terms: D001696:Biomechanical Phenomena; D002675:Child, Preschool; D003198:Computer Simulation; D018729:Fontan Procedure / Q000706:statistics & numerical data*; D006330:Heart Defects, Congenital / Q000473:pathology / Q000503:physiopathology* / Q000601:surgery*; D006439:Hemodynamics; D006801:Humans; D021621:Imaging, Three-Dimensional; D008953:Models, Anatomic; D008955:Models, Cardiovascular; D011651:Pulmonary Artery / Q000473:pathology / Q000503:physiopathology / Q000601:surgery; D014683:Vena Cava, Superior / Q000473:pathology / Q000503:physiopathology / Q000601:surgery