Evaluation of tissue at-risk for remodeling after aortic root or valve repair in bicuspid aortic valve

Bicuspid aortic valve (BAV) is the most common congenital cardiac anomaly and affects up to 2% of the general population. It is associated with aortic disease which can manifest as aneurysm or dissection. Thus, the early detection of BAV-associated aortopathy is crucial for patient management and outcome. Current guidelines for its assessment and surgical planning are based on simple diameter measurements. However, to date, mechanisms involved in aortic wall disease pathogenesis in BAV are not fully understood and consensus regarding the extent of aortic tissue to be repaired or resected is still lacking. Evidence suggests that local blood flow hemodynamics may have an influence on the progression of aortic wall degeneration. Our group recently developed non-invasive maps of the wall shear stress (WSS), which is the viscous force exerted parallel to the vessel wall, throughout the aorta, using advanced 4D flow MRI data analysis methods. Such technique allowed to exhibit significantly abnormal aortic WSS patterns in BAV patients, which correlated with histological biomarkers of aortic wall degradation. Our objective is to design maps of further aortic hemodynamics indices from 4D flow MRI data, to provide a better understanding on aortic blood flow patterns changes and evolution of aortic tissue prone to disease progression after surgery in BAV. Our second goal is to validate such indices both against histopathology in BAV patients undergoing surgery and against experiments on in vitro phantom data. Finally, in a longitudinal clinical study including BAV patients who undergo surgery as well as both pre- and post-surgery 4D flow MRI, we will investigate the association between the newly proposed aortic hemodynamic indices at baseline and clinical outcome at follow-up, such as aortic growth, aneurysm formation, rupture or reoperation. We hypothesize that such non-invasive biomarkers could ultimately help identify at-risk aortic regions and thus plan patient-specific surgical strategies to limit the use of unnecessary aggressive interventions as well as their associated higher risk.