Optimal B-Spline Mapping of Flow Imaging Data for Imposing Patient-Specific Velocity Profiles in Computational Hemodynamics

• Published in: IEEE transactions on biomedical engineering Vol. 66; no. 7; pp. 1872 - 1883
• Main Authors: Gomez, Alberto, Marcan, Marija, Arthurs, Christopher J., Wright, Robert, Youssefi, Pouya, Jahangiri, Marjan, Figueroa, C. Alberto
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aortic valve; Blood; Blood flow; CFD; Computational fluid dynamics; Computational modeling; Computer applications; Computer programs; Computer simulation; Contours; Data models; Deformation; Doppler effect; Doppler ultrasound; Flow mapping; flow profile; Flow velocity; Fluid dynamics; Hemodynamics; Hydrodynamics; Magnetic resonance imaging; Mapping; patient-specific modelling; Preservation; Shape; Software; Source code; Three dimensional flow; Three dimensional models; Three-dimensional displays; Tricuspid valve; Two dimensional flow; Two dimensional models; Ultrasound; Valves; Velocity; Velocity distribution
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2018.2880606

Objective: We propose a novel method to map patient-specific blood velocity profiles (obtained from imaging data such as two-dimensional flow MRI or three-dimensional color Doppler ultrasound) to geometric vascular models suitable to perform computational fluid dynamics simulations of haemodynamics. We describe the implementation and utilization of the method within an open-source computational hemodynamics simulation software (CRIMSON). Methods: The proposed method establishes pointwise correspondences between the contour of a fixed geometric model and time-varying contours containing the velocity image data, from which a continuous, smooth, and cyclic deformation field is calculated. Our methodology is validated using synthetic data and demonstrated using two different in vivo aortic velocity datasets: a healthy subject with a normal tricuspid valve and a patient with a bicuspid aortic valve. Results: We compare our method with the state-of-the-art Schwarz-Christoffel method in terms of preservation of velocities and execution time. Our method is as accurate as the Schwarz-Christoffel method, while being over eight times faster. Conclusions: Our mapping method can accurately preserve either the flow rate or the velocity field through the surface and can cope with inconsistencies in motion and contour shape. Significance: The proposed method and its integration into the CRIMSON software enable a streamlined approach toward incorporating more patient-specific data in blood flow simulations.