Statistical analysis for rupture risk prediction of abdominal aortic aneurysms (AAA) based on its morphometry

Abstract

The morphometry of the abdominal aortic aneurysms (AAA) it has been recognized as one of the main factors that may predispose its rupture. The variation of the AAA morphometry, over time, induces modifications in hemodynamic behavior which, in turn, alters the spatial and temporal distribution of hemodynamic stress on the aneurismatic wall, establishing a bidirectional process that can influence the rupture phenomenon. In order to evaluate potential correlations between the main geometric parameters characterizing the AAA and hemodynamic stresses, 13 unrupture AAA patient-specific models were created. To AAA geometric characterization, twelve indices based on lumen center line were defined and determined. The computing of temporal and spatial distributions of hemodynamic stresses was conducted through Computational Fluid Dynamics. Statistical techniques were used to assess the relationships between the hemodynamic parameters and the different geometrical indices of the AAA. Regression analyses were conducted to obtain linear predictor models for hemodynamic stresses using the different indices defined in this paper as predictor variables. The statistical analysis confirmed that the length L, the asymmetry and the saccular index significantly influenced the hemodynamic stresses. The results obtained show the potential of the use of statistical techniques in predicting the rupture risk of patient-specific AAA