Accuracy of Computational Hemodynamics in Complex Arterial Geometries Reconstructed from Magnetic Resonance Imaging

AbstractPurpose: Combining computational blood flow modeling with three-dimensional medical imaging provides a new approach for studying links between hemodynamic factors and arterial disease. Although this provides patient-specific hemodynamic information, it is subject to several potential errors. This study quantifies some of these errors and identifies optimal reconstruction methodologies. Methods: A carotid artery bifurcation phantom of known geometry was imaged using a commercial magnetic resonance (MR) imager. Three-dimensional models were reconstructed from the images using several reconstruction techniques, and steady and unsteady blood flow simulations were performed. The carotid bifurcation from a healthy, human volunteer was then imaged in vivo, and geometric models were reconstructed. Results: Reconstructed models of the phantom showed good agreement with the gold standard geometry, with a mean error of approximately 15% between the computed wall shear stress fields. Reconstructed models of the in vivo carotid bifurcation were unacceptably noisy, unless lumenal profile smoothing and approximating surface splines were used. Conclusions: All reconstruction methods gave acceptable results for the phantom model, but in vivo models appear to require smoothing. If proper attention is paid to smoothing and geometric fidelity issues, models reconstructed from MR images appear to be suitable for use in computational studies of in vivo hemodynamics. © 1999 Biomedical Engineering Society. PAC99: 8719Uv, 8761-c, 0705Pj, 8710+e

[1]  D D Duncan,et al.  Effects of arterial compliance and non-Newtonian rheology on correlations between intimal thickness and wall shear. , 1992, Journal of biomechanical engineering.

[2]  B. Rutt,et al.  Hemodynamics of human carotid artery bifurcations: computational studies with models reconstructed from magnetic resonance imaging of normal subjects. , 1998, Journal of vascular surgery.

[3]  R. F. Smith,et al.  Geometric characterization of stenosed human carotid arteries. , 1996, Academic radiology.

[4]  Richard A. Robb Three-Dimensional Biomedical Imaging: Principles and Practice , 1995 .

[5]  D. Ku,et al.  Pulsatile Flow and Atherosclerosis in the Human Carotid Bifurcation: Positive Correlation between Plaque Location and Low and Oscillating Shear Stress , 1985, Arteriosclerosis.

[6]  D A Steinman,et al.  Computational blood flow modelling: errors associated with reconstructing finite element models from magnetic resonance images. , 1997, Journal of biomechanics.

[7]  Thomas J. R. Hughes,et al.  Computational investigations in vascular disease , 1996 .

[8]  Jennifer Anne Moore,et al.  Accuracy Assessment of Computational Blood Flow Modelling in Realistic Arterial Geometries , 1998, Advances in Bioengineering.

[9]  Petra Schmalbrock,et al.  Measurement of the geometric parameters of the aortic bifurcation from magnetic resonance images , 1994, Annals of Biomedical Engineering.

[10]  D. Ku,et al.  Pulsatile flow visualization in the abdominal aorta under differing physiologic conditions: implications for increased susceptibility to atherosclerosis. , 1992, Journal of biomechanical engineering.