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- Open Access
A new method to quantify coronary flow conditions using dynamically scaled in vitro phase contrast magnetic resonance imaging
© Beier et al. 2016
- Published: 27 January 2016
- Computational Fluid Dynamic
- Coronary Flow
- Computational Fluid Dynamic Simulation
- Contrast Magnetic Resonance Imaging
- Phase Contrast Magnetic Resonance Imaging
Atherosclerotic coronary artery disease remains a major cause of illness and death, and coronary flow predetermines disease. Limitations in imaging technology prevent coronary flow measurements but computational fluid dynamics (CFD) need sophisticated boundary conditions for accurate flow predictions. MRI has recently been combined with CFD for larger calibre vessels, but small coronary arteries remain inaccessible.
The aim of this study was to assess the feasibility of coronary flow measurement in 3D printed large scale coronary phantoms using phase contrast MRI (PC-MRI).
1) Three patient bifurcation geometries with 33°, 72° and 110° angle (mean and ± 2SD of the first principal mode of variation of 300 asymptomatic patients) were 2) 6:1 printed, and their flow was replicated via a dynamically scaled blood mimicking flow circuit. The PC-MRI measured flow was measured was semi-automatically segmented and co-registered to 3) identical, real scale CFD. Measured velocity inlets profiles were transformed and prescribed as CFD inlet condition. The data was statistically compared using a 3D flow field correlation analysis.
Coronary flow was successfully replicated and measured with dynamically scaled 3D printed phantom PC-MRI, where co-registration (σ<5e-6) resulted in good to strong agreement in magnitude (error 2-12%, ρ ≥0.72), and direction (r2≥0.74).
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.