The MeDiTATe project will be present at the Summer Biomechanics, Bioengineering, & Biotransport Conference (SB3C). The event will take place on 4 – 8 June 2023 at the Grand Hyatt Vail, Colorado.

In this occasion four Early-Stage Researchers (ESRs) will be presenting the results of their activities:

Leonardo Geronzi – ESR 02: Tuning of the mechanical boundary conditions parameters for a patient-specific thoracic aorta model. This work presents a procedure to tune the parameters controlling the mechanical boundary conditions (BCs) of a thoracic aorta (TA) model in fluid-structure interaction analysis. These parameters specifically account for the displacement caused by the heart at the level of the aortic annulus. The mechanical BCs introduced consist of a group of viscoelastic components that represent the support provided by the soft tissue and replicate the interaction between the aorta and the spine. By exploiting the information derived from 2D cine-MRI sequences, the parameters governing the BCs are calibrated to achieve a better correspondence between the displacement of the simulated model and the displacement derived from the images.

Beatrice Bisighini – ESR 03: Machine Learning-Based Reduced Order Modelling For The Simulation Of Braided Stent Deployment. This work presents a machine learning-based reduced-order model scheme, trained on finite element simulations, to compute the deployed configuration of flow diverters within patient-specific models in real-time. Flow diverters are very dense braided stents used in the endovascular treatment of cerebral aneurysms. Computational tools could be useful in assisting surgeons in the selection of the best device for a patient, especially in complex cases. However, due to the large amount of degrees of freedom and the necessity to solve the contact with the wall, the computational time required by traditional techniques alone, such as finite element modelling, is excessively high. Machine learning-based reduced order modelling can enable real-time prediction while retaining the mechanical realism and predictability of the stent deployed configuration.

Federica Galbiati – ESR 07: Investigating the role of eccentric inlet conditions on hemodynamic results at different stages of aneurysm growth. Ascending thoracic aortic aneurysm (aTAA) is a life-threatening condition whose etiology is still unknown, but the link between altered aortic hemodynamics and aTAA development is widely recognized. In particular, alterations induced by the presence of a bicuspid aortic valve (BAV) with consequent eccentricity of aortic inlet flow seems to play a role in the highest prevalence of aTAA cases in these patients, compared to subjects with a tricuspid aortic valve (TAV). In the state of the art, different groups have focused on the analysis of TAV and BAV influence on aortic hemodynamics by using patient specific geometries and inlet conditions. However, perspective studies that investigate the evolution of hemodynamics patterns in presence of TAV or BAV phenotypes concurrently with aTAA progression are still limited.  Therefore, the main goal of this study is to investigate the role of inlet conditions eccentricity in the hemodynamics results at different stages of aTAA, accounting different configurations of TAV and BAV.

Francesco Bardi – ESR 10: Validation of FSI simulations against a compliant aortic phantom in a Hybrid Mock Circulatory Loop. Computational fluid dynamics (CFD) is a widely used tool in research to improve the understanding of various cardiovascular diseases. Fluid Structure Interaction (FSI) simulations consider the motion of the vessels, providing a more accurate solution for the evaluation of blood velocity and pressure fields. The aim of this work is to perform a rigorous in-vitro validation of the FSI coupled momentum method using a flexible thoracic aortic phantom. A novel Hybrid Mock Circulatory Loop (HMCL) was used to replicate different physiological conditions in the flexible phantoms and the gathered experimental data were compared with the results of the numerical simulations.