An optimal control approach to determine resistance-type boundary conditions from in-vivo data for cardiovascular simulations

• Main Authors: Ballarin, F. (Author), Fevola, E. (Author), Fremes, S. (Author), Grivet-Talocia, S. (Author), Jiménez-Juan, L. (Author), Rozza, G. (Author), Triverio, P. (Author)
• Format: Article
• Language: English
• Published: John Wiley and Sons Inc 2021
• Subjects: Aorta, Thoracic; Automated estimation; Automated procedures; biological model; blood flow velocity; Blood Flow Velocity; Boundary conditions; cardiovascular modeling; Cardiovascular simulations; Cardiovascular system; Computational fluid dynamics; Computational fluid dynamics simulations; Control variable; data assimilation; haemodynamics modeling; hemodynamics; Hemodynamics; human; Humans; hydrodynamics; Hydrodynamics; mechanical stress; Models, Cardiovascular; Murray's law; optimal control; Optimal controls; Outlet boundary condition; patient-specific simulations; Shear flow; Shear stress; Stress, Mechanical; thoracic aorta; Wall shear stress
• Online Access: View Fulltext in Publisher

 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. © 2021 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.