Girolamo Mastronuzzi
Estimating coronary hemodynamics with a Deep Learning-based approach.
Rel. Umberto Morbiducci, Maurizio Lodi Rizzini, Bianca Griffo, Diego Gallo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2023
Abstract
Atherosclerosis is the primary pathology impacting the coronary arteries, generating stenosis which constrict blood flow. It is a chronic disease characterized by the thickening of the coronary wall from fat buildup. In coronary arteries atherosclerosis leads to coronary artery disease (CAD) with myocardial infarction as deadliest complication. CAD is responsible for 30% of fatalities in individuals aged 35 and older. Evaluating the severity of coronary lesions is crucial in identifying the appropriate treatment. Therefore, the physiological assessment of CAD has gained increasing importance in clinical and research settings. In clinical practice, the traditional technique for CAD diagnosis, coronary angiography imaging, has been complemented by flow-based and pressure-based functional quantities.
However, such quantities only moderately predict the risk associated with the presence of non-obstructive lesions
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