title: Robust and objective decomposition and mapping of bifurcating vessels.
abstract: Computational modeling of human arteries has been broadly employed to investigate the relationships between geometry, hemodynamics and vascular disease. Recent developments in modeling techniques have made it possible to perform such analyses on realistic geometries acquired noninvasively and, thus, have opened up the possibility to extend the investigation to populations of subjects. However, for this to be feasible, novel methods for the comparison of the data obtained from large numbers of realistic models in the presence of anatomic variability must be developed. In this paper, we present an automatic technique for the objective comparison of distributions of geometric and hemodynamic quantities over the surface of bifurcating vessels. The method is based on centerlines and consists of robustly decomposing the surface into its constituent branches and mapping each branch onto a template parametric plane. The application of the technique to realistic data demonstrates how similar results are obtained over similar geometries, allowing for proper model-to-model comparison. Thanks to the computational and differential geometry criteria adopted, the method does not depend on user-defined parameters or user interaction, it is flexible with respect to the bifurcation geometry and it is readily extendible to more complex configurations of interconnecting vessels.
authors.affiliation: Imaging Research Labs, Robarts Research Institute and Bioengineering Department, Mario Negri Institute for Pharmacological Research, London, ON N6A 5K8, Canada.
authors.forename: Luca
authors.initials: L
authors.lastname: Antiga
authors.forename: David A
authors.initials: DA
authors.lastname: Steinman
mesh_terms: D000465:Algorithms; D001158:Arteries / Q000033:anatomy & histology*; D016893:Carotid Stenosis / Q000473:pathology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008953:Models, Anatomic; D008955:Models, Cardiovascular; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity