Preliminary establishment and validation of the inversion method for growth and remodeling parameters of patient-specific abdominal aortic aneurysms

Abstract

Background Traditional medical imaging studies and biomechanical researches have limitations in analyzing the long-term evolution process of AAA (Abdominal Aortic Aneurysm, AAA). The HCMT (Homogenized Constrained Mixture Theory, HCMT) allows for quantitative analysis of the changes of the three-dimensional morphology and composition of AAA. However, the accuracy of HCMT still requires further clinical verification. Objective This study aims to establish a patient-specific AAA growth model based on HCMT, simulate the long-term G&R (Growth and Remodeling G&R) process of AAA, and validate the feasibility and accuracy of the method using two additional AAA cases with 5 follow-up data. Methods The media and adventitia of the aorta were modeled as mixtures composed of elastin, collagen fibers, and SMC (smooth muscle cells, SMC). The strain energy function was used to describe the continuously generation and degradation of the mixture during the AAA G&R process. Multiple sets of growth parameters were applied to finite element simulations, and the simulation results were compared with the follow-up data for gradually selecting the optimal growth parameters. Two additional AAA patients with different growth rates were used for validating the method, the optimal growth parameters were obtained using the first two follow-up imaging data, and the growth model was applied to simulate the subsequent four time points. The differences between the simulated diameters and the follow-up diameters of AAA were compared to validate the accuracy of the growth model. Results The growth parameters, especially the stress-mediated substance deposition gain factor Kσi, is highly related to the AAA G&R process. When setting the optimal growth parameters to simulate AAA growth, the proportion of simulation results within the distance of less than 0.5 mm from the follow-up model is above 80%. For the validating cases, during the 5 follow-up processes, the mean difference rates between the simulated diameter and the real-world diameter are within 2.5%, which basically meets the clinical demand for quantitatively predicting the AAA growth in maximum diameters. Conclusion This study simulated the growth process of AAA, and validated the accuracy of this growth model. This method was proved to be used to predict the G&R process of AAA caused by dynamic changes in the mixtures of the AAA vessel wall at a long-term time scale, assisting accurately and quantitatively predicting the multi-dimensional morphological development and mixtures evolution process of AAA in clinic.