Assessing left main bifurcation anatomy and haemodynamics as a potential surrogate for disease risk in suspected coronary artery disease without stenosis - R. Gharleghi; M. Zhang; C. Shen; M. Webster; C. Ellis; S. Beier (Scientific Reports)
Abstract Coronary anatomy governs local haemodynamics associated with atherosclerotic development, progression and ultimately adverse clinical outcomes. However, lack of large sample size studies and methods to link adverse haemodynamics to anatomical information has hindered meaningful insights to date. The Left Main coronary bifurcations of 127 patients with suspected coronary artery disease in the absence of significant stenosis were segmented from CTCA images before computing the local haemodynamics. We correlated 11 coronary anatomical characteristics with the normalised lumen area exposed to adverse haemodynamics linked with atherosclerotic processes. These include mean curvatures and diameters of branches, bifurcation and inflow angles, and Finet’s ratio as the anatomical parameters, and low Time-Averaged Endothelial Shear Stress ( $$\hbox {lowTAESS}\,<\,{0.5}$$ lowTAESS < 0.5  Pa), high Oscillatory Shear Index (highOSI >  0.1), high Relative Residence Time (highRRT >  4.17 Pa−1), and mean Topological Shear Variation Index for the haemodynamics consideration. We separately tested if the geometric measures and haemodynamics indicators differed between subgroups (sex, smokers, and those with hypertension). We then use a step-down multiple linear regression model to find the best model for predicting lowTAESS, highOSI, highRRT and meanTSVI. Finet’s Ratio (FR) significantly correlated to lowTAESS ( $$\hbox {p}\,<\, 0.001$$ p < 0.001 ). Vessel diameters and curvature correlated to highOSI (both p $$\,<\,$$ < 0.001) as well as meanTSVI (p $$\,<\,$$ < 0.05). Finet’s ratio, vessel diameters and daughter branch curvature independently correlated to RRT (all p $$\,<\,$$ < 0.01). Our results indicate that specific anatomical vessel characteristics may be used as a surrogate of adverse haemodynamics environment associated with clinically adverse mechanisms of disease. This is especially powerful with the latest computing resources and may unlock clinical integration via standard imaging modalities as biomarkers without further computationally expensive simulations.