Bicuspid Aortic valve (BAV) is the most common congenital heart defect affecting up to 2% of the population and responsible for more deaths and complications than all other congenital heart defects combined. Nevertheless, the development of BAV complications remains poorly understood, and considerable debate exists regarding predictive metrics for patient management. Recent 4D Flow MRI findings provide strong evidence that BAV aortopathy is influenced by a complex interaction between the valve and aortic blood flow. However, the degree to which interactions between disease of the aortic valve and changes in blood flow in the aorta can impact the risk for BAV complications remains unidentified. To address these limitations, we have recently developed novel non-invasive virtual Catheter (vCath) technique that uses mathematical modeling to mimic the well-established invasive catheter in quantifying aortic flow and pressure gradients. Our objective is to leverage our uniquely large 4D flow MRI database (800+ BAV patients; N=200 with follow-up) to improve the vCath development to simultaneously evaluate transvalvular pressure gradient and various 3D aortic flow indices and their diagnostic value in BAV outcome prediction. This may help identify novel aortopathy biomarkers and could support establishing optimized intervention strategies.
|Effective start/end date||1/1/19 → 8/31/20|
- Northwestern Memorial Hospital (NMH Agmt #16 Exhibit B.6)
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