Kawasaki disease (KD) is a serious childhood disease that can result in permanent damage to the cardiovascular system if left untreated. Without prompt treatment with high dose intravenous gamma globulin, 25% of children develop potential life-threatening coronary artery aneurysms. These aneurysms can thrombose and cause sudden, unpredictable cardiovascular events. Currently, there are no clear guidelines for the timing of revascularization for these patients, and no tools to predict which patients may be at the highest risk for thrombosis and myocardial infarction. As a result, clinicians are left with a difficult choice to either subject an otherwise normal, healthy young adult to the risks associated with angioplasty, stent placement, or coronary bypass surgery, or to wait and watch, knowing that if a myocardial infarction occurs, it will likely be a devastating event. The vasculopathy of KD in young adults is different and distinct from atherosclerotic disease, so management guidelines for traditional coronary artery disease do not apply. To generate models that will assist clinicians in performing risk assessment in KD patients with aneurysms, we will develop the first quantitative computational tools for risk stratification in KD patients using sophisticated computer simulations of blood flow. This research will build upon on our extensive experience with patient- specific blood flow simulations for children with congenital heart disease. These tools will allow us to quantitatively assess hemodynamics in aneurysms resulting from KD, including detailed information about three-dimensional, time-varying wall shear stress and particle residence time. The project will consist of the following aims. First, we will enhance current simulation capabilities to include uncertainty analysis, fluid structure interaction, and physiologic data. With these tools we will demonstrate the potential for simulations to produce detailed hemodynamic data. Second, we will validate simulation data against in vitro data using particle image velocimetry experiments and rapid prototyped patient-specific models. Third, we will test the hypothesis that there are large differences in flow conditions, including shear stress, flow stasis, and particle residence time, among KD patients depending on the shape of the aneurysm. Lastly, we will use data from cardiac MRI studies to create simulations from multiple KD patients to develop a risk stratification that will offer initial predictions of the risk of thrombus based on multiple biomechanical factors. With these tools, we will lay a foundation for future animal and in vitro cell experiments that will validate our findings. The proposed project brings together a unique team including a pediatrician expert in KD, an adult cardiologist MRI imaging specialist, and an engineer with expertise in cardiovascular biomechanics, with the goal of bringing computational tools one step closer to the bedside and optimizing the clinical care of KD patients with coronary aneurysms.
Kawasaki disease is the leading cause of acquired heart disease in children, affecting more than 4,000 children annually in the US. This project applies computer simulations of blood flow incorporating MRI imaging and clinical data to perform detailed analysis of the hemodynamics in coronary artery aneurysms caused by KD. Improvements in simulation techniques resulting from this work will provide previously unavailable insights into flow characteristics and will result in the first quantitative thrombotic risk assessment tool for KD patients.
