Systematic Review of the Application of Computational Fluid Dynamics for Adult Aortic Diseases.

BACKGROUND

Computational fluid dynamics (CFD) is a new medical method combining medicine and science. The aim of this study is to summarize and analyze the application of CFD in adult aortic diseases.

METHODS

This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A search in the PubMed, Cochrane Library and Chinese databases identified 47 highly relevant articles. Studies were included if they assessed biomechanical markers and their potential association with progression or rupture of aortic aneurysms or dissections.

RESULTS

There are no randomized controlled trials to examine the direct relationship between all biomechanical parameters and aortic disease progression or rupture. Wall stress and peak wall rupture risk can predict the risk of aortic aneurysm rupture using biomechanics, which is more accurate than the prediction based on "diameter" alone. Areas with lower time averaged wall shear stress (TAWSS) and higher oscillatory shear index (OSI) are at risk for further aortic expansion or dissection. Higher relative residence time (RRT) area can predict platelet activation and thrombosis. In addition, pressure, flow field and other indicators can also roughly predict the risk of aortic disease progression.

CONCLUSIONS

Contemporary evidence suggests that CFD can provide additional hemodynamic parameters, which have the potential to predict the progression of aortic lesions, the effect of surgical intervention, and prognosis.