Extraction of morphometry and branching angles of porcine coronary arterial tree from CT images

Thomas Wischgoll, Jenny S. Choy, Ghassan S. Kassab
2009 American Journal of Physiology. Heart and Circulatory Physiology  
Wischgoll T, Choy JS, Kassab GS. Extraction of morphometry and branching angles of porcine coronary arterial tree from CT images. The morphometry (diameters, length, and angles) of coronary arteries is related to their function. A simple, easy, and accurate image-based method to seamlessly extract the morphometry for coronary arteries is of significant value for understanding the structure-function relation. Here, the morphometry of large (Ն1 mm in diameter) coronary arteries was extracted from
more » ... computed tomography (CT) images using a recently validated segmentation algorithm. The coronary arteries of seven pigs were filled with Microfil, and the cast hearts were imaged with CT. The centerlines of the extracted vessels, the vessel radii, and the vessel lengths were identified for over 700 vessel segments. The extraction algorithm was based on a topological analysis of a vector field generated by normal vectors of the extracted vessel wall. The diameters, lengths, and angles of the right coronary artery, left anterior descending coronary artery, and left circumflex artery of all vessels Ն1 mm in diameter were tabulated for the respective orders. It was found that bifurcations at orders 9 -11 are planar (ϳ90%). The relations between volume and length and area and length were also examined and found to scale as power laws. Furthermore, the bifurcation angles follow the minimum energy hypothesis but with significant scatter. Some of the applications of the semiautomated extraction of morphometric data in applications to coronary physiology and pathophysiology are highlighted. image analysis; computed tomography; segmentation; coronary arteries THE LOCAL FLOW PATTERNS in large epicardial coronary arteries have significant clinical relevance because of their predilection to atherosclerosis in regions of bifurcations and curvature (4). A detailed understanding of local flow patterns must be based on an accurate reconstruction of the anatomy of the coronary vasculature (6, 7). Accordingly, a three-dimensional (3-D) reconstruction of the epicardial coronary arteries with accurate measurements of diameters, lengths, and branching angles is necessary for the accurate simulation of the local flow field. To date, we are unaware of any validated method or algorithm that addresses this need. Recent studies that segment and reconstruct the geometric structure of vascular trees from volumetric imagery focus on vessel radii but do not extract other quantitive morphological data (e.g., lengths, volumes, and angles). A study by Nordsletten et al. (17) analyzed the renal vasculature in microcomputed tomography (micro-CT) scans, confirming Murray's law, which describes the relation between the radii of parent and daughter vessels. In a related study, Lee et al. (14) segmented a coronary micro-CT scan from a rat to determine vessel radii based on a seeded active countour algorithm. The methodology was validated using an artificial data set with an error of 0.5 voxels. There is clearly a need for a more diverse algorithm that can generate not only the diameters but also other morphological parameters necessary for hemodynamics analysis. Furthermore, there is a need for a higher-resolution extraction method with a lower voxel error. The significance of accuracy for the determination of vessel diameter is apparent based on Poiseuille's relation, which relates the fourth power of diameter to flow resistance (11), i.e., a 10% error in diameter can result in a 44% error in resistance to flow. A recently validated software tool by our group (22) was used for measurements of radii and lengths of trunks of major coronary arteries from volumetric imagery of porcine coronary CT images (15). The method was validated on a series of CT scans with a resolution of 0.6 ϫ 0.6 ϫ 1.0 mm 3 , providing a root mean square (RMS) error of 0.27 voxels (22). The method identifies the vessels and determines the centerlines of those vessels, i.e., it reduces the entire vasculature to a curve skeleton. The major focus was on the validation of diameter and length measurements for the trunks of the major coronary arteries. The objective of this study was to extend the previous algorithm to the entire coronary arterial tree visible under CT (vessels Ն 1 mm in diameter). Specifically, we intended to incorporate the following new features: 1) an algorithm for 3-D angle measurements (four angles) to completely characterize the bifurcation angles, 2) an ordering scheme for classifying various vessels and hence determining the relation between order number and diameters and lengths, and 3) an algorithm to determine tree properties (area, lengths, and volume). These novel elements will further validate the algorithm in the following ways: 1) the relation between order number and diameters and lengths, 2) the relation between diameter ratios and branching angles, and 3) the scaling laws between crown length-volume and length-area. These further validations will provide greater confidence in this algorithm to be used as a standard labor-saving tool for the reconstruction of the large coronary arterial tree to test various scientific hypotheses and for potential clinical utility. METHODS Existing data. We have recently validated a segmentation algorithm for CTs of porcine coronary arteries (22) , which analyzed five hearts with a focus on the main trunks of the right coronary artery (RCA), left anterior descending coronary artery (LAD), and left circumflex artery (LCx). For this publication, two additional hearts were prepared and analyzed for the entire arterial tree under CT resolution.
doi:10.1152/ajpheart.00093.2009 pmid:19749169 pmcid:PMC2781359 fatcat:p2y4lfz7erdzxjkvjy43ao5whq