Abstract
Thin-cap fibroatheroma (TCFA) is an atherosclerotic plaque type most vulnerable to rupture, which is the leading cause of death in coronary heart disease. Atherosclerosis is initiated by endothelial cell dysfunction and it has long been recognized that the hemodynamic environment, typically quantified via shear stress, may play an important role in promoting a pro-atherogenic cell phenotype. Despite numerous studies, there is no consensus on the relationship between disturbed flow and markers of atherogenesis or specific advanced plaque morphologies such as TCFA. To study this relationship in greater detail, we have developed custom software that accurately co-registers in vivo images with histological data in 3-D (called 3-D histology). Computational fluid dynamics is then performed on vessel geometries derived from the in vivo images to compute established and new shear stress metrics of disturbed flow. The overlap is then computed between these shear metrics and histopathological markers of atherosclerosis at a high spatial resolution. We applied this framework to a hypercholesterolemic mouse carotid and pig coronary model of atherosclerosis, wherein, for each, an instrument was surgically introduced that perturbed the vessel hemodynamics and induced TCFA formation. We found that TCFA consistently formed within local regions of low shear stress, which we quantified with a new metric called the low shear index. Future work will use this framework to isolate dysfunctional endothelial cells from local regions exhibiting a high magnitude of low shear index to better understand the altered genomics that underlies the patho-mechanobiology of TCFA.
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