Sciences & Société
Soutenance de thèse : Gerardo Kenny RUMINDO
Predictive cardiac modelling for the study of myocardial injuries
Doctorant : Gerardo Kenny RUMINDO
Laboratoire INSA : CREATIS
Ecole doctorale : ED160 E.E.A
Ischemic heart disease is initiated by the constriction of the coronary arteries, causing myocardial infarction and the formation of myocardial scar tissue or infarct. The underlying mechanism of how the whole myocardium remodels and the mechanical interactions between the infarct and the healthy tissue are still not well understood. In order to better understand the mechanics of the heart under normal and pathological conditions, computational models are being increasingly used, since they are able to provide physicians with information that cannot be measured with the current clinical tools. This information can then be used to improve the diagnosis and subsequently, the treatment course of each specific patient.
The main goal of this PhD project is to develop and evaluate a model-based approach to extract novel biomechanical indices that characterize myocardial stiffness and contractility. These indices would serve to improve the assessment of the regional myocardial functional status and viability, as well as the prognosis of the functional recovery of ischemic myocardium. In this PhD report, we firstly introduced an approach to retrieve the biomechanical indices from normal healthy volunteer data obtained from routine cardiac cine magnetic resonance acquisitions. Secondly, we investigated the prognostic value of the retrieved indices on a magnetic resonance-based longitudinal study of clinical patients with ischemic heart disease. Lastly, we tested the feasibility of a novel proposed pipeline to estimate biomechanical indices of pathological cases by combining learning-based infarct localization algorithm and inverse dynamics finite element modelling.
Amphithéâtre Emilie du Châtelet - Bibliothèque Marie Curie - INSA Lyon