Cardiovascular Fluid Dynamic Analysis with MRI Velocimetry and MRI-based Computational Simulation

Magnetic resonance imaging (MRI) velocimetry and computational fluid dynamics (CFD) are both methods that offer advantages when used for cardiovascular fluid dynamic analysis. However, each of these methods has its own set of unique limitations. MRI velocimetry offers patient-specific analysis of real fluid flow. However, MRI has some limitations in quantitative and predictive cardiovascular analysis when used as a stand-alone method due to resolution limits and errors that result from manipulation of magnetic field. Fortunately, computational methods may be used to address some of these limitations. CFD provides high resolution data, and relies on boundary conditions that can be manipulated to match physiological or surgical variations of interest. However, standalone CFD can also be limited due to its high dependence on patient-specific boundary conditions, and its need for appropriate validation with physical blood flow. This work was aimed at utilizing the best of both MRI and CFD for cardiovascular fluid dynamic analysis by leveraging the advantages of one method to fill the inherent gaps of the other. This is shown through a number of examples, such as using 4D flow MRI velocimetry to analyze blood flow dynamics in congenital heart disease patients, simulating hepatic blood flow with image-based computational simulation, and coupling imaging, computational simulation, and machine learning methods to improve patient-specific blood flow quantification.