LAD_data
Description
A Nomogram for Predicting Heterogeneous Etiology of Atherosclerosis in the Left Anterior Descending Coronary Artery Using Geometric Morphological Parameters.
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The 3D geometric reconstruction of the LAD was performed based on the segmentation of end-diastolic images from CCTA (version 20.0, Mimics Research). The range of density attenuation was set between 200-600 HU, with subsequent smoothing applied to the vessels. After obtaining the full-length 3D model of the LAD, further segmentation was conducted to isolate the vessel from the ostium up to 80 mm, which served as the 3D models for the proximal and mid (PM) segments of the LAD. The two sets of models were then imported into the open-source Vascular Modeling Toolkit (version 1.4.0, VMTK) to extract the vascular centerlines. We developed an application using Python to provide standardized data measurement, ensuring the repeatability of geometric parameter acquisition. Based on a variable number of consecutive points along the vascular centerline, the curvature and torsion at each point were obtained (Figure 3). Curvature is used to describe the bending of the vascular centerline and is defined as the reciprocal of the radius of the inscribed sphere at the corresponding point on the centerline. Torsion describes to what extent the centeline twists out of the plane of the curvature for each centerline point. The torsion value can be positive or negative, indicating the direction of twist. We processed the torsion values at each point by taking their absolute values. The tortuosity index (TI) is a conventional method for assessing the degree of tortuosity in a spatial curve, defined as the ratio of the length of the vascular centerline to the spatial linear distance between the two ends of the centerline. The length of the centerline is the sum of all individual distances between consecutive points along the centerline [13]. The extraction of parameters such as maximum curvature (MC), average curvature (AC), maximum torsion (MT), average torsion (AT), and TI was implemented in Matlab 2023.