Medical image-based simulation of abdominal aortic aneurysm growth

Advances in theoretical modeling of biological tissue growth and remodeling (G&R) and computational biomechanics have been helpful to capture salient features of vascular remodeling during the progression of vascular diseases. Nevertheless, application of such advances to individualized diagnosis and clinical treatment of diseases such as abdominal aortic aneurysm (AAA) remains challenging. As a step toward that goal, in this paper, we present a computational framework necessary towards patient-specific modeling of AAA growth. Prior to AAA simulations, using an inverse optimization method, initial material parameters are identified for a healthy aorta such that a homeostatic condition is satisfied for the given medical image-based geometrical model under physiological conditions. Various shapes of AAAs are then computationally created by inducing elastin degradation with different spatio-temporal distributions. The simulation results emphasize the role of extent of elastin damage, geometric complexity of an enlarged AAA, and sensitivity of stress-mediated collagen turnover on the wall stress distribution and the rate of expansion. The results also show that the distributions of stress and local expansion initially correspond to the extent of elastin damage, but change via stress-mediated tissue G&R depending on the aneurysm shape. Finally, we suggest that the current framework can be utilized along with medical images from an individual patient to predict the AAA shape and mechanical properties in the near future via an inverse scheme.

► We present a computational framework for medical image-based abdominal aortic aneurysm (AAA) simulation as an important step towards individual patient-based clinical application.
► Computational simulation suggests that the stress increases in inflection regions although they were not the regions of the maximum elastin degradation.
► We emphasize that a broader inverse framework is ultimately needed to be developed in conjunction with medical images of AAAs to regenerate patient-specific simulation cases.