| Literature DB >> 30140921 |
David Molony1, Jaekeun Park2, Lei Zhou3, Candace Fleischer4, He-Ying Sun1, Xiaoping Hu5, John Oshinski4, Habib Samady1, Don P Giddens2, Amir Rezvan1.
Abstract
Animal models offer a flexible experimental environment for studying atherosclerosis. The mouse is the most commonly used animal, however, the underlying hemodynamics in larger animals such as the rabbit are far closer to that of humans. The aortic arch is a vessel with complex helical flow and highly heterogeneous shear stress patterns which may influence where atherosclerotic lesions form. A better understanding of intra-species flow variation and the impact of geometry on flow may improve our understanding of where disease forms. In this work we use Magnetic Resonance Angiography (MRA) and 4D Phase contrast magnetic resonance imaging (PC-MRI) to image and measure blood velocity in the rabbit aortic arch. Measured flow rates from the PC-MRI were used as boundary conditions in computational fluid dynamics models of the arches. Helical flow, cross flow index (CFI) and time-averaged wall shear stress (TAWSS) were determined from the simulated flow field. Both traditional geometric metrics and shape modes derived from statistical shape analysis were analyzed with respect to flow helicity. High CFI and low TAWSS were found to co-localize in the ascending aorta and to a lesser extent on the inner curvature of the aortic arch. The Reynolds number was linearly associated with an increase in helical flow intensity (R=0.85, p<.05). Both traditional and statistical shape analysis correlated with increased helical flow symmetry. However, a stronger correlation was obtained from the statistical shape analysis demonstrating its potential for discerning the role of shape in hemodynamic studies.Entities:
Year: 2018 PMID: 30140921 PMCID: PMC6298529 DOI: 10.1115/1.4041222
Source DB: PubMed Journal: J Biomech Eng ISSN: 0148-0731 Impact factor: 2.097