Computational Fluid Dynamics Modeling of Hemodynamic Parameters in the Human Diseased Aorta: A Systematic Review.

BACKGROUND: The analysis of the correlation between blood flow and aortic pathology through computational fluid dynamics (CFD) shows promise in predicting disease progression, the effect of operative intervention, and guiding patient treatment. However, to date, there has not been a comprehensive systematic review of the published literature describing CFD in aortic diseases and their treatment. METHODS: This review includes 136 published articles which have investigated the application of CFD in all types of aortic disease (aneurysms, dissections, and coarctation). We took into account case studies of both, treated or untreated pathology, investigated with CFD. We also graded all studies using an author-defined Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach based on the validation method used for the CFD results. RESULTS: There are no randomized controlled trials assessing the efficacy of CFD as applied to aortic pathology, treated or untreated. Although a large number of observational studies are available, those using clinical imaging tools as independent validation of the calculated CFD results exist in far smaller numbers. Only 21% of all studies used clinical imaging as a tool to validate the CFD results and these were graded as high-quality studies. CONCLUSIONS: Contemporary evidence shows that CFD can provide additional hemodynamic parameters such as wall shear stress, vorticity, disturbed laminar flow, and recirculation regions in untreated and treated aortic disease. These have the potential to predict the progression of aortic disease, the effect of operative intervention, and ultimately help guide the choice and timing of treatment to the benefit of patients and clinicians alike.