Key result
An optimal control approach for automated estimation of outlet boundary conditions assimilated 4D-Flow MRI data more accurately than Murray's law and Ohm's law in four patient-specific aortic arches.
Why the study?
Common CFD boundary condition techniques do not automatically assimilate patient-specific data, relying instead on expensive and time-consuming manual tuning procedures.
An optimal control approach for estimating resistive boundary conditions in cardiovascular CFD simulations can assimilate patient-specific 4D-Flow MRI data more accurately than standard methods.
May refine aortic CFD accuracy; leaves open clinical translation without larger validation.
The choice of appropriate boundary conditions is a fundamental step in computational fluid dynamics (CFD) simulations of the cardiovascular system. Boundary conditions, in fact, highly affect the computed pressure and flow rates, and consequently haemodynamic indicators such as wall shear stress (WSS), which are of clinical interest. Devising automated procedures for the selection of boundary conditions is vital to achieve repeatable simulations. However, the most common techniques do not automatically assimilate patient‐specific data, relying instead on expensive and time‐consuming manual tuning procedures. In this work, we propose a technique for the automated estimation of outlet boundary conditions based on optimal control. The values of resistive boundary conditions are set as control variables and optimized to match available patient‐specific data. Experimental results on four aortic arches demonstrate that the proposed framework can assimilate 4D‐Flow MRI data more accurately than two other common techniques based on Murray's law and Ohm's law.
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Fevola et al. (2021) studied Coronary artery disease (patients undergoing coronary bypass graft surgery) (n=4). Optimal control approach for boundary condition estimation vs. Murray's law and Ohm's law was evaluated on Difference between simulated and measured pressure and flow rates. An optimal control approach for automated estimation of outlet boundary conditions assimilated 4D-Flow MRI data more accurately than Murray's law and Ohm's law in four patient-specific aortic arches.
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