| Literature DB >> 25485418 |
Pau Medrano-Gracia, John Ormiston, Mark Webster, Susann Beier, Chris Ellis, Chunliang Wang, Alistair A Young, Brett R Cowan.
Abstract
Describing the detailed statistical anatomy of the coronary artery tree is important for determining the aetiology of heart disease. A number of studies have investigated geometrical features and have found that these correlate with clinical outcomes, e.g. bifurcation angle with major adverse cardiac events. These methodologies were mainly two-dimensional, manual and prone to inter-observer variability, and the data commonly relates to cases already with pathology. We propose a hybrid atlasing methodology to build a population of computational models of the coronary arteries to comprehensively and accurately assess anatomy including 3D size, geometry and shape descriptors. A random sample of 122 cardiac CT scans with a calcium score of zero was segmented and analysed using a standardised protocol. The resulting atlas includes, but is not limited to, the distributions of the coronary tree in terms of angles, diameters, centrelines, principal component shape analysis and cross-sectional contours. This novel resource will facilitate the improvement of stent design and provide a reference for hemodynamic simulations, and provides a basis for large normal and pathological databases.Entities:
Mesh:
Year: 2014 PMID: 25485418 DOI: 10.1007/978-3-319-10470-6_64
Source DB: PubMed Journal: Med Image Comput Comput Assist Interv