期刊
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
卷 66, 期 7, 页码 1872-1883出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2018.2880606
关键词
CFD; patient-specific modelling; flow profile; magnetic resonance imaging; Doppler ultrasound
资金
- iFIND project-Wellcome Trust IEH Award [102431]
- National Institute for Health Research (NIHR) Biomedical Research Centre at Guy's and St Thomas' NHS Foundation Trust
- King's College London
- Wellcome/Engineering and Physical Sciences Research Council Centre for Medical Engineering at King's College London [WT 203148/Z/16/Z]
- European Research Council under the European Union's Seventh Framework Program (FP)/ERC [307532]
- Edward B. Diethrich M.D. research Professorship
- United States National Institutes of Health [U01HL135842]
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.
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