The MeDiTATe project was present at the 18th International Symposium on Computer Methods in Biomechanics and Biomedical Engineering (CMBBE 2023). The event took place on 3 – 5 May 2023 in Paris, France.
In this occasion four Early-Stage Researchers (ESRs) had the opportunity to present their research findings and share them with colleagues from around the world: Read More
The MeDiTATe project will be participating to the MASH’s congress. The event will take place on 4 – 6 May 2023 at the University of Corsica in Bastia, France. In this occasion two Early-Stage Researchers (ESRs), ESR 01 Antonio Martinez Pascual and ESR 02 Leonardo Geronzi will be presenting the results of their activities with a joint talk whose title is “Ascending aortic aneurysm growth prediction based on shape and fluid-dynamics biomarkers”. Read More
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:
