Stratifying thrombosis risk in Kawasaki Disease using hemodynamic analysis beyond the z-score - Project Summary/Abstract Coronary artery aneurysms (CAA) and ectasia (CAE) describe abnormal local dilatations of the coronary artery that typically exceed 1.5 times the neighboring artery diameter. The pathogenesis of CAA and CAE is not well understood; however, several factors come into play such as certain vasculitic and connective tissue diseases such as Kawasaki disease (KD), a pediatric acquired heart disease. CAA and CAE are usually found incidentally, sometimes without symptoms and other times accompanied by acute coronary syndrome. Clinical symptoms can appear due to the presence of local thrombosis among others causes, leading to angina and myocardial infarction, which carries a substantial health and economic burden. Currently, anticoagulation therapy is the recommended approach used in CAA and CAE despite several conflicting studies. The thrombotic risk of CAA and CAE in KD, and recommended anticoagulation therapy, are currently defined by ONLY the largest diameter (through the z-score metric), without taking other morphologic features into consideration. However, studies including our preliminary data showed that for the same z-score, flow patterns and indices related to thrombosis were different. Literature has shown that blood flow stagnation and sluggish flow are correlated with thrombosis. The occurrence of blood flow stagnation and therefore thrombosis risk is correlated with low velocities, low time averaged wall shear stress (TAWSS), high oscillatory shear index (OSI), and elevated relative residence time (RRT). Several patient-specific computational fluid dynamics (CFD) and experimental investigations to analyze the flow and risk level of CAA cases in KD based on hemodynamic indices were performed and studies showed that for the same z-score, flow patterns were different. So how can we complement the z-score with flow indices and other geometrical factors beyond just the diameter and without running extensive and time-consuming computational simulations to facilitate the decision-making process for cardiologists? The goal of this proposal is to address this question through developing simple predictive hemodynamic indices that can be used to refine the z-score metric so in addition to the dilation diameter, more geometrical parameters and hemodynamic parameters can be included to obtain a more robust stratification of thrombosis risk and determination of anticoagulation therapy in KD. This will be done through using patient-specific datasets of Kawasaki Disease (KD) patients from the Nationwide Children’s Hospital (Columbus, OH) and Chicago Lurie’s Children’s Hospital registries. These datasets include patients with documented magnetic resonance imaging (MRI), computed tomography (CT) and echocardiographic data.
