Bicuspid aortic valve (BAV) is the most common congenital anomaly with an incidence of 1-2% in the general population. It is associated with severe complications of both the aortic valve (stenosis, regurgitation) and aorta (aneurysm, dissection). Dilatation of any or all segments of the proximal aorta, known as bicuspid aortopathy, is present in ~50% of individuals with congenital BAV and severe aneurysms will develop at a frequency of 1 in 100 BAV patients per year. The associated aortopathy often requires prophylactic surgery to remove the progressively enlarging aorta to prevent lethal complications. However, contemporary guidelines for surgical intervention rely on empirical data and expert opinion but lack clear evidence. It remains unclear as to whether BAV aortopathy is primarily the result of an inherent defect in the aortic wall (i.e. genetic predisposition) or if valve-mediated changes in ascending aortic blood flow induces maladaptive aortic wall remodeling downstream (i.e. acquired etiology). The axiom of care is centered on the genetic hypothesis and has prompted aggressive surgical resection strategies (early and extensive) to remove aortic tissue considered at risk of future complications. Conversely, accumulating evidence indicates that valve-related changes in blood flow may also contribute to disease progression. As such, clinical practices are highly variable between clinicians and centers. A better understanding of the influence of altered blood flow in BAV on aortic wall integrity and aortopathy is thus urgently needed to enable the development of evidence-based clinical guidelines with improved and targeted surgical resection strategies. Therefore, the goal of this proposal is to use non-invasive imaging (4D flow MRI) to directly assess the impact of valve-mediated 3D blood flow and wall shear stress (WSS) on structural (histopathology) and functional (protein expression, biomechanics) tissue degeneration in BAV aortopathy. Ultimately, we aim to test the hypothesis that quantitative hemodynamic biomarkers as assessed by 4D-flow MRI will correlate with tissue metrics of aortopathy via the following activities: (1) development of an MRI protocol to comprehensively assess aortic valve morphology, thoracic aorta geometry, and time-resolved transvalvular 3D blood outflow patterns. Physiologic hemodynamic biomarker values will be tabulated to identify abnormal hemodynamics at the aorta wall in patients; (2) characterization and constitutive modeling of tissue aortopathy in 150 BAV and 150 trileaflet aortic valve (TAV) patients undergoing aortic resection via identification of extracellular matrix (ECM) molecular dysregulation, histopathology for medial ECM architecture, and tissue biomechanics (strength and anisotropy); (3) correlation analysis of tissue aortopathy with hemodynamic imaging biomarkers. This proposal will advance the current knowledge regarding the role of hemodynamics on aorta tissue function in the presence of the TAV and BAV, thereby informing future efforts to determine the best treatment strategies.

Public Health Relevance

Bicuspid aortic valve (BAV) is the most common congenital anomaly with an incidence of 1-2% in the general population. Dilatation of any or all segments of the proximal aorta, known as bicuspid aortopathy, is present in 50% of individuals with congenital BAV, which increases the risk of catastrophic clinical consequences. As a result, this application seeks to ascertain the role of valve-mediated hemodynamics on tissue metrics of BAV aortopathy and to construct a constitutive model of the underlying tissue mechanical properties.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL133504-04
Application #
9676978
Study Section
Bioengineering, Technology and Surgical Sciences Study Section (BTSS)
Program Officer
Evans, Frank
Project Start
2017-05-01
Project End
2022-04-30
Budget Start
2019-05-01
Budget End
2020-04-30
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Colorado Denver
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
041096314
City
Aurora
State
CO
Country
United States
Zip Code
80045
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