Keywords: Flow, Cardiovascular, Catheterization, Computational Fluid Dynamics, Lumped Parameter Model, Pulmonary Vascular Resistance, Glenn Physiology, Simulation of Fontan Surgery
Motivation: Individual pulmonary vascular resistances (PVR) of the left and right lung are needed to perform in-silico virtual cardiac surgery to improve Fontan conduit designs, yielding more balanced blood flow to the lungs.
Goal(s): Predict patient-specific PVR of both lungs using clinical flow and pressure data acquired from cardiovascular magnetic resonance exams and catheterizations.
Approach: Utilize computational fluid dynamics (CFD) and lumped parameter (LP) models to iteratively optimize the PVR of both lungs.
Results: There is excellent correlation between the PVR estimates of the CFD and LP models, and both models fit to clinical outlet flow and pressure with less than 10% error.
Impact: Accurate prediction of individual lung resistances is needed for patient-specific in-silico virtual cardiac surgery to optimize the design of the Fontan conduit. This design could then be implemented by surgeons to provide more balanced pulmonary blood flow in Fontan patients.
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