title: Computational study of blood flow in an aorto-coronary bypass model using single versus sequential grafting technique.
abstract: Coronary artery bypass grafting (CABG) is performed to obtain myocardial reperfusion downstream from severe coronary stenoses. When a single artery is blocked the routine CABG is performed while more than one artery are blocked, say the branches of the coronary vessels are stenosed, sequential grafting technique is adopted. However even though the advantage of using sequential bypass grafting over single bypass grafts are not fully known, the hemodynamics of the surgically reconstructed coronary bed is strongly dependent on the bypass configuration. Hence an attempt is made to analyse the blood flow in a three-dimensional aorto-coronary bypass graft model (which has the proximal portion of the branches of the left circumflex artery, namely the obtuse marginals 1 and 2 to be 90% and 80% occluded) using single grafts and sequential bypass graft. The finite volume technique was employed to model the 3-D blood flow pattern to determine the distribution of wall shear stress (WSS) and their spatial gradients (WSSG) in the bypassed regions for two specific instances of the cardiac cycle namely, t=0.15 s the mid-ejection phase and t=0.57 s the mid-diastole phase Results confirm that WSSG distribution is much higher while using single bypass grafts. Hence it is suggested that when two or more branches of the coronary vessels are occluded, sequential bypass grafting technique would be more efficient thereby contributing to the long-term graft patency.
authors.affiliation: Media Division, Institute for Infocomm Research, Singapore. meena@i2r.a-star.edu.sg
authors.forename: S
authors.initials: S
authors.lastname: Meena
authors.forename: Chen
authors.initials: C
authors.lastname: Xiang
mesh_terms: D003198:Computer Simulation; D001026:Coronary Artery Bypass; D003326:Coronary Circulation / Q000502:physiology*; D003331:Coronary Vessels / Q000502:physiology*; D006801:Humans; D008954:Models, Biological