Estimation of regional myocardial mass at risk based on distal arterial lumen volume and length using 3D micro-CT images

Abstract

The determination of regional myocardial mass at risk distal to a coronary occlusion provides valuable prognostic information for a patient with coronary artery disease. The coronary arterial system follows a design rule which allows for the use of arterial branch length and lumen volume to estimate regional myocardial mass at risk. Image processing techniques, such as segmentation, skeletonization, and arterial network tracking, are presented for extracting anatomical details of the coronary arterial system using micro-computed tomography (CT). Moreover, a method of assigning tissue voxels to their corresponding arterial branches is presented to determine the dependent myocardial region. The proposed micro-CT technique was utilized to investigate the relationship between the sum of the distal coronary arterial branch lengths and volumes to the dependent regional myocardial mass using a polymer cast of a porcine heart. The correlations of the logarithm of the total distal arterial lengths (L) to the logarithm of the regional myocardial mass (M) for the left anterior descending (LAD), left circumflex (LCX) and right coronary (RCA) arteries were log(L) = 0.73log (M)+ 0.09 (R= 0.78), log(L) = 0.82log(M)+ 0.05 (R= 0.77), and log(L) = 0.85log(M)+ 0.05 (R= 0.87) s, respectively. The correlation of the logarithm of the total distal arterial lumen volumes (V) to the logarithm of the regional myocardial mass for the LAD, LCX and RCA were log(V) = 0.93log(M)− 1.65 (R= 0.81), log(V) = 1.02log(M) −1.79 (R= 0.78), and log(V) = 1.17log(M)− 2.10 (R= 0.82), respectively. These morphological relations did not change appreciably for diameter truncations of 600 to 1400 µm. The results indicate that the image processing procedures successfully extracted information from a large 3D dataset of the coronary arterial tree to provide prognostic indications in the form of arterial tree parameters and anatomical area at risk.

Myocardial Segmentation of Area at Risk Based on Coronary Computed Tomography Angiography and Voronoi Diagram in Comparison with Magnetic Resonance Perfusion Imaging

“…Some researchers have reported clinical application of Voronoi diagrams in cardiovascular imaging [24] [25] [26]. Termeer et al [25] utilized the Voronoi algorithm for estimating the MAAR on a 2D bull's eye map of the 17-segment model.…”

Allometric scaling in the coronary arterial system

“…A detailed description of the techniques has been reported previously [13]. Briefly, the process began with differentiating voxels belonging to the myocardium versus those belonging to the arterial branches.…”

Influence of segmented vessel size due to limited imaging resolution on coronary hyperemic flow prediction from arterial crown volume

“…Meaningful application of this relation for FFR prediction requires reliable values for ␣ and ␤. Several studies have been performed to provide such estimates, based on comparison with measured flow (31), or using scaling laws applied to coronary vascular trees extracted from microcomputed tomography images (6). However, the proposed values deviate to an extent that hampers their use in deriving hyperemic flow from image-based arterial tree volumes.…”

“…This requires passing of a guide wire with a pressure sensor through the stenosis. Despite the reliability of this method, risks of vessel and plaque rupture, procedure time, and costs have inspired the search for new less-invasive alternatives for assessing FFR (18), based on computational methods applied to arterial models obtained from angiography (27) or CT (6). By using experimentally established form-function relationships, coronary flow can be calculated from image-derived morphological data.…”