PURPOSE: To examine the feasibility of combining computational fluid dynamics (CFD) and dynamically scaled phantom phase-contrast magnetic resonance imaging (PC-MRI) for coronary flow assessment. MATERIALS AND METHODS: Left main coronary bifurcations segmented from computed tomography with bifurcation angles of 33°, 68°, and 117° were scaled-up ∼7× and 3D printed. Steady coronary flow was reproduced in these phantoms using the principle of dynamic similarity to preserve the true-scale Reynolds number, using blood analog fluid and a pump circuit in a 3T MRI scanner. After PC-MRI acquisition, the data were segmented and coregistered to CFD simulations of identical, but true-scale geometries. Velocities at the inlet region were extracted from the PC-MRI to define the CFD inlet boundary condition. RESULTS: The PC-MRI and CFD flow data agreed well, and comparison showed: 1) small velocity magnitude discrepancies (2-8%); 2) with a Spearman's rank correlation ≥0.72; and 3) a velocity vector correlation (including direction) of r(2) ≥ 0.82. The highest agreement was achieved for high velocity regions with discrepancies being located in slow or recirculating zones with low MRI signal-to-noise ratio (SNRv ) in tortuous segments and large bifurcating vessels. CONCLUSION: Characterization of coronary flow using a dynamically scaled PC-MRI phantom flow is feasible and provides higher resolution than current in vivo or true-scale in vitro methods, and may be used to provide boundary conditions for true-scale CFD simulations. J. MAGN. RESON. IMAGING 2016;44:983-992.
PURPOSE: To examine the feasibility of combining computational fluid dynamics (CFD) and dynamically scaled phantom phase-contrast magnetic resonance imaging (PC-MRI) for coronary flow assessment. MATERIALS AND METHODS: Left main coronary bifurcations segmented from computed tomography with bifurcation angles of 33°, 68°, and 117° were scaled-up ∼7× and 3D printed. Steady coronary flow was reproduced in these phantoms using the principle of dynamic similarity to preserve the true-scale Reynolds number, using blood analog fluid and a pump circuit in a 3T MRI scanner. After PC-MRI acquisition, the data were segmented and coregistered to CFD simulations of identical, but true-scale geometries. Velocities at the inlet region were extracted from the PC-MRI to define the CFD inlet boundary condition. RESULTS: The PC-MRI and CFD flow data agreed well, and comparison showed: 1) small velocity magnitude discrepancies (2-8%); 2) with a Spearman's rank correlation ≥0.72; and 3) a velocity vector correlation (including direction) of r(2) ≥ 0.82. The highest agreement was achieved for high velocity regions with discrepancies being located in slow or recirculating zones with low MRI signal-to-noise ratio (SNRv ) in tortuous segments and large bifurcating vessels. CONCLUSION: Characterization of coronary flow using a dynamically scaled PC-MRI phantom flow is feasible and provides higher resolution than current in vivo or true-scale in vitro methods, and may be used to provide boundary conditions for true-scale CFD simulations. J. MAGN. RESON. IMAGING 2016;44:983-992.
Authors: Andreas A Giannopoulos; Dimitris Mitsouras; Shi-Joon Yoo; Peter P Liu; Yiannis S Chatzizisis; Frank J Rybicki Journal: Nat Rev Cardiol Date: 2016-10-27 Impact factor: 32.419
Authors: Ramtin Gharleghi; Claire A Dessalles; Ronil Lal; Sinead McCraith; Kiran Sarathy; Nigel Jepson; James Otton; Abdul I Barakat; Susann Beier Journal: Ann Biomed Eng Date: 2021-05-17 Impact factor: 3.934
Authors: M Kelm; L Goubergrits; J Bruening; P Yevtushenko; J F Fernandes; S H Sündermann; F Berger; V Falk; T Kuehne; S Nordmeyer Journal: Sci Rep Date: 2017-08-29 Impact factor: 4.379