The MeDiTATe project will be present at the 18th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE 2023). The event will take place on 3 – 5 May 2023 in Paris, France. Read More
A new paper HPC+ in the medical field: Overview and current examples has been published in the Technology and Health Care Journal .The paper was written by several authors including Federica Galbiati ESR 07 of the MeDiTATe project as well as Simona Celi & Emanuele Vignali (BioCardioLab FTGM). Read More
We had a small talk with Dr. Simona Celi, a member of the Board of the MeDiTATe project. She is a Senior scientist at Fondazione Toscana G. Monasterio (FTGM) and co-founder of the BioCardioLab. In her experience, she participated to several National and International research projects and currently she is the technical Project Investigator (PI) and sub-unit PI of three national research grants. During the project, she will be supervising ESR09, ESR10 and ESR14.
The MeDiTATe project, a research proposal funded by the European Commission in the framework of Horizon 2020 programme. Can you tell us about FTGM and its role in the project? Read More
The Fondazione Toscana G. Monasterio hosted the MeDiTATe project Winter School “Big Data Analytics, from engineering to clinical”. The event took place from 20th to 24th February 2023 at Pisa, Italy.
The Early Stage Researchers of the MeDiTATe project had the opportunity to follow several courses regarding both the clinical and genetic view of aneurysms and the application of AI and big data to hemodynamics studies.
The Winter School was also an opportunity to strengthen the collaboration among the Early-Stage Researchers and to present their own results.
A new paper Uncertainty Quantification in the In Vivo Image-Based Estimation of Local Elastic Properties of Vascular Walls has been published in the MDPI Journal of Cardiovascular Development and Disease in collaboration with the MeDiTATe project.
The paper was written by Benigno Marco Fanni (BioCardioLab FTGM), Maria Nicole Antonuccio, ESR 14 of the MeDiTATe project, Simona Celi (BioCardioLab FTGM), Alessandra Pizzuto and Giuseppe Santoro (Pediatric Cardiology Unit, FTGM), Sergio Berti (Adult Cardiology Unit, FTGM).
Here follows the paper’s abstract:
Introduction: Patient-specific computational models are a powerful tool for planning cardiovascular interventions. However, the in vivo patient-specific mechanical properties of vessels represent a major source of uncertainty. In this study, we investigated the effect of uncertainty in the elastic module (E) on a Fluid–Structure Interaction (FSI) model of a patient-specific aorta. Methods: The image-based χ-method was used to compute the initial E value of the vascular wall. The uncertainty quantification was carried out using the generalized Polynomial Chaos (gPC) expansion technique. The stochastic analysis was based on four deterministic simulations considering four quadrature points. A deviation of about ±20% on the estimation of the E value was assumed. Results: The influence of the uncertain E parameter was evaluated along the cardiac cycle on area and flow variations extracted from five cross-sections of the aortic FSI model. Results of stochastic analysis showed the impact of E in the ascending aorta while an insignificant effect was observed in the descending tract. Conclusions: This study demonstrated the importance of the image-based methodology for inferring E, highlighting the feasibility of retrieving useful additional data and enhancing the reliability of in silico models in clinical practice.
Leonardo Geronzi, ESR 02 of the MeDiTATe project, published the paper Assessment of shape-based features ability to predict the ascending aortic aneurysm growth in the Frontiers in Physiology journal.
This work involved the collaboration of several universities, research centres and three French hospitals: the University Hospital of Rennes, the University Hospital of Dijon and the University Hospital of Toulouse.
The full paper is available at this link on the Frontiers journal website. Antonio Martinez Pascual, ESR 01 of the MeDiTATe project, also participated in this work.
This publication shows the importance of considering the shape of the ascending aorta in predicting the risk of aneurysm growth. In fact, the work aims at explaining how to compute some shape features on the ascending tract and how to use machine learning classifiers to assess the risk of growth. The results provide a clear indication that a set of shape features could be selected to identify patients at high risk of growth more accurately than the maximum diameter alone.
Fondazione Toscana G. Monasterio will host the MeDiTATe Winter School: “Big Data Analytics, from engineering to clinical” from February 20th to 24th, 2023.
Our Early Stage Researchers will have the opportunity to follow several lessons, with different topics within the event’s five days:
This Winter School will also include two specific training events scheduled in the MeDiTATe program:
A new paper An image-based approach for the estimation of arterial local stiffness in vivo has been published in the Frontiers in Bioengineering and Biotechnology journal in collaboration with the MeDiTATe project.
The paper was written by Simona Celi, Emanuele Gasparotti, Katia Capellini and Emanuele Vignali from BioCardioLab (Fondazione Toscana G. Monasterio), Francesco Bardi (ESR 10), Martino Andrea Scarpolini (ESR 09), Carlo Cavaliere (IRCCS SynLab SDN) e Filippo Cademartiri (Dipartimento Immagini, Fondazione Toscana Gabriele Monasterio).
Here follows the paper’s abstract:
The analysis of mechanobiology of arterial tissues remains an important topic of research for cardiovascular pathologies evaluation. In the current state of the art, the gold standard to characterize the tissue mechanical behavior is represented by experimental tests, requiring the harvesting of ex-vivo specimens. In recent years though, image-based techniques for the in vivo estimation of arterial tissue stiffness were presented. The aim of this study is to define a new approach to provide local distribution of arterial stiffness, estimated as the linearized Young’s Modulus, based on the knowledge of in vivo patient-specific imaging data. In particular, the strain and stress are estimated with sectional contour length ratios and a Laplace hypothesis/inverse engineering approach, respectively, and then used to calculate the Young’s Modulus. After describing the method, this was validated by using a set of Finite Element simulations as input. In particular, idealized cylinder and elbow shapes plus a single patient-specific geometry were simulated. Different stiffness distributions were tested for the simulated patient-specific case. After the validation from Finite Element data, the method was then applied to patient-specific ECG-gated Computed Tomography data by also introducing a mesh morphing approach to map the aortic surface along the cardiac phases. The validation process revealed satisfactory results. In the simulated patient-specific case, root mean square percentage errors below 10% for the homogeneous distribution and below 20% for proximal/distal distribution of stiffness. The method was then successfully used on the three ECG-gated patient-specific cases. The resulting distributions of stiffness exhibited significant heterogeneity, nevertheless the resulting Young’s moduli were always contained within the 1–3 MPa range, which is in line with literature.
Last September 2022, the University of Sydney, one of the partners of the MeDiTATe project, hosted a workshop on heart valve replacements.
Prof. Marco Evangelos Biancolini, Principal Investigator of the MeDiTATe project, was one of the international guests, giving a speech on Digital Twins & Medicine 4.0.
Full recording of the speech is now available on the University of Sydney website, at the following link.
