Key result
Computational fluid dynamics predictions of 3D velocity fields in a carotid bifurcation phantom showed fair agreement with MRI measurements, with average correlation factors of 0.939 and 0.876.
CFD modeling provides velocity field predictions that are in fair agreement with MRI measurements in a carotid bifurcation phantom, validating its potential utility in hemodynamic assessment.
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Encourages CFD refinement for carotid flow analysis; leaves open clinical translation pending in vivo studies.
Steady flow of a blood mimicking fluid in a physiologically realistic model of the human carotid bifurcation was studied using both magnetic resonance imaging (MRI) and computational fluid dynamics (CFD) modelling techniques. Quantitative comparisons of the 3D velocity field in the bifurcation phantom were made between phase contrast MRI measurements and CFD predictions. The geometry for the CFD model was reconstructed from T(1) weighted MR imaging of the test phantom. It was found that the predicted velocity fields were in fair agreement with MR measured velocities. In both the internal and external carotid arteries, the agreement between CFD predictions and MRI measurements was better along the inner-outer wall axis with a correlation factor C>0.897 (average 0.939) where the velocity profiles were skewed, than along the anterior-posterior axis (average correlation factor 0.876) where the velocity profiles were in M-shape.
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Long et al. (2002) studied Carotid bifurcation phantom. Computational fluid dynamics (CFD) modelling vs. Phase contrast MRI measurements was evaluated on 3D velocity field agreement (average correlation factor 0.939 (inner-outer wall axis) and 0.876 (anterior-posterior axis)). Computational fluid dynamics predictions of 3D velocity fields in a carotid bifurcation phantom showed fair agreement with MRI measurements, with average correlation factors of 0.939 and 0.876.
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