KEYWORDS: Simulation of CCA and DLA aggregates, Hemodynamics, Arteries, Independent component analysis, 3D modeling, Magnetic resonance imaging, 3D image processing, Blood, Magnetic resonance angiography, Optical spheres
Recent work from our group has shown the primacy of the bifurcation area ratio and tortuosity in determining the
amount of disturbed flow at the carotid bifurcation, believed to be a local risk factor for the carotid atherosclerosis. We
have also presented fast and reliable methods of extraction of geometry from routine 3D contrast-enhanced magnetic
resonance angiography, as the necessary step along the way for large-scale trials of such local risk factors. In the present
study, we refine our original geometric variables to better reflect the underlying fluid mechanical principles. Flaring of
the bifurcation, leading to flow separation, is defined by the maximum relative expansion of the common carotid artery
(CCA), proximal to the bifurcation apex. The beneficial effect of curvature on flow inertia, via its suppression of flow
separation, is now characterized by the tortuosity of CCA as it enters the flare region. Based on data from 50 normal
carotid bifurcations, multiple linear regressions of these new independent geometric predictors against the dependent
disturbed flow burden reveals adjusted R2 values approaching 0.5, better than the values closer to 0.3 achieved using the
original variables. The excellent scan-rescan reproducibility demonstrated for our earlier geometric variables is shown to
be preserved for the new definitions. Improved prediction of disturbed flow by robust and reproducible vascular
geometry offers a practical pathway to large-scale studies of local risk factors in atherosclerosis.
KEYWORDS: Arteries, Spatial resolution, Hemodynamics, Image segmentation, Data acquisition, Magnetic resonance imaging, 3D image processing, Image resolution, 3D modeling, Data modeling
Recent work from our group has demonstrated that the amount of disturbed flow at the carotid bifurcation, believed to be a local risk factor for carotid atherosclerosis, can be predicted from luminal geometric factors. The next step along the way to a large-scale retrospective or prospective imaging study of such local risk factors for atherosclerosis is to investigate whether these geometric features are reproducible and accurate from routine 3D contrast-enhanced magnetic resonance angiography (CEMRA) using a fast and practical method of extraction. Motivated by this fact, we examined
the reproducibility of multiple geometric features that are believed important in atherosclerosis risk assessment. We
reconstructed three-dimensional carotid bifurcations from 15 clinical study participants who had previously undergone baseline and repeat CEMRA acquisitions. Certain geometric factors were extracted and compared between the baseline and the repeat scan. As the spatial resolution of the CEMRA data was noticeably coarse and anisotropic, we also investigated whether this might affect the measurement of the same geometric risk factors by simulating the CEMRA acquisition for 15 normal carotid bifurcations previously acquired at high resolution. Our results show that the extracted geometric factors are reproducible and faithful, with intra-subject uncertainties well below inter-subject variabilities.
More importantly, these geometric risk factors can be extracted consistently and quickly for potential use as disturbed
flow predictors.
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