Vessel structural stress mediates aortic media degeneration in bicuspid aortopathy: New insights based on patient-specific fluid-structure interaction analysis.


This study aimed to assess the relationship between local mechanical stimuli and regional aortic tissue degeneration using fluid-structure interaction (FSI) analysis in patients with bicuspid aortic valve (BAV) disease. Nine patients underwent ascending aortic replacement were recruited. Tissues were collected to evaluate the pathology features in four regions, greater curvature (GC-region), posterior (P-region), anterior (A-region), and lesser curvature (LC-region). FSI analysis was performed to quantify vessel structural stress (VSS) and flow-induced parameters, including wall shear stress (WSS), oscillatory shear index (OSI), and particle relative residence time (RRT). The correlation between these biomechanical metrics and tissue degeneration was analyzed. Elastin in the medial layer and media thickness were thinnest and the gap between fibers was biggest in the GC-region, followed by the P-region and A-region, while the elastin and media thickness were thickest and the gap smallest in the LC-region. The collagen deposition followed a pattern with the biggest in the GC-region and least in the LC-region. There is a strong negative correlation between mean or peak VSS and elastin thickness in the arterial wall in the GC-region (r = -0.917; p = 0.001 and r = -0.899; p = 0.001), A-region (r = -0.748; p = 0.020 and r = -0.700; p = 0.036) and P-region (r = -0.773; p = 0.014 and r = -0.769; p = 0.015), and between mean VSS and fiber distance in the A-region (r = -0.702, p = 0.035). Moreover, strong negative correlation between mean or peak VSS and media thickness was also observed. No correlation was found between WSS, OSI, and RRT and aortic tissue degeneration in these four regions. These findings indicate that increased VSS correlated with local elastin degradation and aortic media degeneration, implying that it could be a potential biomechanical parameter for a refined risk stratification for patients with BAV.