Development of a computer-generated model for the coronary arterial tree based on multislice CT and morphometric data


Journal Article

A detailed four-dimensional model of the coronary artery tree has great potential in a wide variety of applications especially in biomedical imaging. We developed a computer generated three-dimensional model for the coronary arterial tree based on two datasets: (1) gated multi-slice computed tomography (MSCT) angiographic data obtained from a normal human subject and (2) statistical morphometric data obtained from porcine hearts. The main coronary arteries and heart structures were segmented from the MSCT data to define the initial segments of the vasculature and geometrical details of the boundaries. An iterative rule-based computer generation algorithm was then developed to extend the coronary artery tree beyond the initial segmented branches. The algorithm was governed by the following factors: (1) the statistical morphometric measurements of the connectivities, lengths, and diameters of the arterial segments, (2) repelling forces from other segments and boundaries, and (3) optimality principles to minimize the drag force at each bifurcation in the generated tree. Using this algorithm, the segmented coronary artery tree from the MSCT data was optimally extended to create a 3D computational model of the largest six orders of the coronary arterial tree. The new method for generating the 3D model is effective in imposing the constraints of anatomical and physiological characteristics of coronary vasculature. When combined with the 4D NCAT phantom, a computer model for the human anatomy and cardiac and respiratory motions, the new model will provide a unique tool to study cardiovascular characteristics and diseases through direct and medical imaging simulation studies.

Full Text

Duke Authors

Cited Authors

  • Fung, GSK; Segars, WP; Taguchi, K; Fishman, EK; Tsui, BMW

Published Date

  • June 30, 2006

Published In

Volume / Issue

  • 6142 II /

International Standard Serial Number (ISSN)

  • 1605-7422

Digital Object Identifier (DOI)

  • 10.1117/12.653491

Citation Source

  • Scopus