Aortic aneurysm is a cardiovascular disease related to the alteration of the aortic tissue. It is an important cause of death in developed countries, especially for older patients. The diagnosis and treatment of such pathology is performed according to guidelines, which suggest surgical or interventional (stenting) procedures for aneurysms with a maximum diameter above a critical threshold. Although conservative, this clinical approach is also not able to predict the risk of acute complications for every patient. In the last decade, there has been growing interest towards the development of advanced in silico aortic models, which may assist in clinical diagnosis, surgical procedure planning or the design and validation of medical devices. This paper details a comprehensive review of computational modelling and simulations of blood vessel interaction in aortic aneurysms and dissection, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). In particular, the following questions are addressed: “What mathematical models were applied to simulate the biomechanical behaviour of healthy and diseased aortas?” and “Why are these models not clinically implemented?”. Contemporary evidence proves that computational models are able to provide clinicians with additional, otherwise unavailable in vivo data and potentially identify patients who may benefit from earlier treatment. Notwithstanding the above, these tools are still not widely implemented, primarily due to low accuracy, an extensive reporting time and lack of numerical validation.

Ascending Thoracic Aortic Aneurysm (ATAA) is a permanent dilatation of the aorta which is usually related to tissue degeneration, hemodynamic conditions, lifestyle, environmental and genetic factors. As the mechanical conditions can become critical in a dilated aorta, a patient-specific computational model can be very useful to assist clinical decisions in the management of ATAAs. In this article, we model the biomechanical conditions of ATAA by performing Fluid–Structure Interaction (FSI) simulations in the SimVascular open-source software package. The patient-specific geometric model is reconstructed from Computed Tomography scan (CT). The numerical implementation takes into account patient-specific outlet conditions and a temporal flow variation at the model inlet. We performed a mesh convergence analysis on a new mesh reconstruction method in SimVascular and showed that it can significantly reduce the computational cost without impacting the accuracy.

Computational fluid dynamics (CFD) can be seen as complementary tool alongside the visualization capabilities of cardiovascular magnetic resonance (CMR) and computed tomography (CT) imaging for decision-making. In this research CT images of three cases (i.e., a healthy heart pilot project and two patients with complex aortic disease) are used to validate and analyse the corresponding computational results. Three 3D domains of the thoracic aorta were tested under hemodynamic conditions. Under normal conditions, the flow inside the thoracic aorta is more streamlined. In the presence of ascending aortic aneurysm, large areas of blue separation zones (i.e., low velocities) are identified, as well as an internal geometry deformation of the aortic wall, respectively. This flow separation is characterized by the reversal of flow and sudden drop of the wall shear stress (WSS) in the aorta. Moreover, the aortic aneurysm simulations adversely affect the flow by increasing the pressure drop and flow inefficiency, due to the anatomical configuration of the ascending aorta. Altered hemodynamics led to a vortex formation and locally reversed the flow that eventually induced a low flow velocity and oscillating WSS in the thoracic aorta. Significant changes in the hemodynamic characteristics affect the normal blood circulation with strong turbulence occurrence, damaging the aortic wall, leading ultimately to the need of surgical intervention to avoid fatal events.

Experimental protocols are fundamental for quantifying the mechanical behaviour of soft tissue. These data are crucial for advancing the understanding of soft tissue mechanics, developing and calibrating constitutive models, and informing the development of more accurate and predictive computational simulations and artificial intelligence tools. This paper offers a comprehensive review of experimental tests conducted on soft aortic tissues, employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, based on the Scopus, Web of Science, IEEE, Google Scholar and PubMed databases. This study includes a detailed overview of the test method protocols, providing insights into practical methodologies, specimen preparation and full-field measurements. The review also briefly discusses the post-processing methods applied to extract material parameters from experimental data. In particular, the results are analysed and discussed providing representative domains of stress–strain curves for both uniaxial and biaxial tests on human aortic tissue.

Modelling patient-specific aortic biomechanics with advanced computational techniques, such as Fluid-Structure Interaction (FSI), can be crucial to provide effective decision-making indices to enhance current clinical practices. To effectively simulate Ascending Thoracic Aortic Aneurysms (ATAA), the stress-free configuration must be defined. The Zero Pressure Geometry (ZPG) and the Prestress Tensor (PT) are two of the main approaches to tackle this issue. However, their impact on the numerical results is yet to be analysed. Computed Tomography Angiography (CTA) and Magnetic Resonance Imaging (MRI) data were used to develop patient-specific 2-way FSI frameworks. Three models were developed considering different tissue prestressing approaches to account for the reference configuration and their numerical results were compared. The selected approaches were: (i) ZPG, (ii) PT and (iii) a combination of the PT approach with a regional mapping of material properties (PTCAL). The pressure fields estimated by all models were equivalent. The estimation of Wall Shear Stress (WSS) based metrics revealed good correspondence between all models except the Relative Residence Time (RRT). Regarding ATAA wall mechanics, the proposed extension to the PT approach presented a closer agreement with the ZPG model than its counterpart. Additionally, the PT and PTCAL approaches required around 60% fewer iterations to achieve cycle-to-cycle convergence than the ZPG algorithm. Using a regional mapping of material properties in combination with the PT method presented a better correspondence with the ZPG approach. The outcomes of this study can pave the way for advancing the accuracy and convergence of ATAA numerical models using the PT methodology.