Coupling hemodynamics with mechanobiology in patient-specific computational models of ascending thoracic aortic aneurysms

• Published in: Computer methods and programs in biomedicine Vol. 205; p. 106107
• Main Authors: Jamaleddin Mousavi, S., Jayendiran, Raja, Farzaneh, Solmaz, Campisi, Salvatore, Viallon, Magalie, Croisille, Pierre, Avril, Stéphane
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.06.2021; Elsevier
• Subjects: Ascending Thoracic Aortic Aneurysm; Bioengineering; Computational Fluid Dynamics; Constrained mixture theory; Growth and remodeling; Imaging; Life Sciences; Mechanobiology; Growth and remodeling; Ascending Thoracic Aortic Aneurysm; Computational Fluid Dynamics; Constrained mixture theory; Mechanobiology
• ISSN: 0169-2607; 1872-7565; 1872-7565
• DOI: 10.1016/j.cmpb.2021.106107

Highlights*•In this manuscript we establish the first computational framework coupling patient-specific hemodynamics simulations in ascending thoracic aortic aneurysms with a computational mechanobiological model and simulate aneurysm progression for 4 subjects.•We determine computationally the conditions for aneurysm progression. The model shows that the rate of collagen production or cell mechano-sensitivity play the most critical roles.•Our patient-specific computational modeling coupling hemodynamics with mechanobiology is a promising approach to explore ATAA initiation and progression. Background and Objective. The prevention of ascending thoracic aortic aneurysms (ATAAs), which affect thousands of persons every year worldwide, remains a major issue. ATAAs may be caused by anything that weakens the aortic wall. Altered hemodynamics, which concerns a majority of patients with bicuspid aortic valves, has been shown to be related to such weakening and to contribute to ATAA development and progression. However the underlying mechanisms remain unclear and computational modeling in this field could help significantly to elucidate how hemodynamics and mechanobiology interact in ATAAs. Methods. Accordingly, we propose a numerical framework combining computational fluid dynamics and 4D flow magnetic resonance imaging (MRI) coupled with finite element (FE) analyses to simulate growth and remodeling (G&R) occurring in patient-specific aortas in relation with altered hemodynamics. The geometries and the blood velocities obtained from 4D flow MRI are used as boundary conditions for CFD simulations. CFD simulations provide an estimation of the wall shear stress (WSS) and relative residence time (RRT) distribution across the luminal surface of the wall. An initial insult is then applied to the FE model of the aortic wall, assuming that the magnitude of the insult correlates spatially with the normalized RRT distribution obtained from CFD simulations. G&R simulations are then performed. The material behavior of each Gauss point in these FE models is evolved continuously to compensate for the deviation of the actual wall stress distribution from the homeostatic state after the initial insult. The whole approach is illustrated on two healthy and two diseased subjects. The G&R parameters are calibrated against previously established statistical models of ATAA growth rates. Results. Among the variety of results provided by G&R simulations, the analysis focused especially on the evolution of the wall stiffness, which was shown to be a major risk factor for ATAAs. It was shown that the G&R parameters, such as for instance the rate of collagen production or cell mechanosensitivity, play a critical role in ATAA progression and remodeling. Conclusions. These preliminary findings show that patient-specific computational modeling coupling hemodynamics with mechanobiology is a promising approach to explore aneurysm progression.