Objective: We created a finite element model to predict the probability of dissection based on imaging-derived aortic stiffness and investigated the link between stiffness and wall tensile stress using our model.
Methods: Transthoracic echocardiogram measurements were used to calculate aortic diameter change over the cardiac cycle. Aortic stiffness index was subsequently calculated based on diameter change and blood pressure. A series of logistic models were developed to predict the binary outcome of aortic dissection using 1 or more series of predictor parameters such as aortic stiffness index or patient characteristics. Finite element analysis was performed on a subset of diameter-matched patients exhibiting patient-specific material properties.
Results: Transthoracic echocardiogram scans of patients with type A aortic dissection (n = 22) exhibited elevated baseline aortic stiffness index when compared with aneurysmal patients' scans with tricuspid aortic valve (n = 83, P < .001) and bicuspid aortic valve (n = 80, P < .001). Aortic stiffness index proved an excellent discriminator for a future dissection event (area under the curve, 0.9337, odds ratio, 2.896). From the parametric finite element study, we found a correlation between peak longitudinal wall tensile stress and stiffness index (ρ = .6268, P < .001, n = 28 pooled).
Conclusions: Noninvasive transthoracic echocardiogram-derived aortic stiffness measurements may serve as an impactful metric toward predicting aortic dissection or quantifying dissection risk. A correlation between longitudinal stress and stiffness establishes an evidence-based link between a noninvasive stiffness parameter and stress state of the aorta with clinically apparent dissection events.
Keywords: aneurysm pathophysiology; aortic dissection; aortic wall stiffness; aortic wall tensile stress; computational modeling; dissection risk prediction; stress analysis.
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