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Manifesto

Dettaglio Insegnamento

Contesto
Anno Accademico 2021/2022
Corso di Studi Dott. - MI (1373) Bioingegneria / Bioengineering
Anno di Corso 1

Scheda Insegnamento
Codice Identificativo 057876
Denominazione Insegnamento FROM IN VIVO IMAGING, HAEMODYNAMICS, BIG DATA TO AI
Tipo Insegnamento MONODISCIPLINARE
Crediti Formativi Universitari (CFU) 5.0
Programma sintetico Atherosclerosis the first cause of death and disability in the world. Most of ischaemic stroke and heart attack are due to the rupture of an atherosclerotic plaque. Degree of luminal stenosis, the current validated risk assessment criterion, cannot reliably identify high risk patients. Studies suggest that lesion morphological and compositional features and inflammatory burden are more relevant with clinical events. Various imaging techniques have been developed to characterise these features, including mini invasive, e.g., intravascular ultrasound (IVUS) and optical coherence tomography (OCT), and non-invasive techniques, e.g., high-resolution multi-contrast magnetic resonance imaging (hrMRI), computed tomography (CT) and positron emission tomography (PET). Moreover, under physiological conditions, atherosclerotic plaque is subject to mechanical loading due to blood pressure and flow, which has been shown to affect plaque development and rupture. Clinical studies have demonstrated the incremental value of biomechanical analysis in differentiating patients with different clinical presentation and predicting subsequent ischaemic events over luminal stenosis. The physiological and pathological basis of vascular diseases will be introduced in this course as well as various imaging techniques. The segmentation algorithm and techniques used to reconstruct the lesion geometry will be introduced. Finite element method will be used to calculate local haemodynamic parameters, including vessel structural stress (VSS) and wall shear stress (WSS). The biological function of these stresses will be discussed. Finally, the experience of translation and clinical pathway of this novel approach will be shared.
Settori Scientifico Disciplinari (SSD)
Codice SSD Descrizione SSD CFU
ING-IND/34 BIOINGEGNERIA INDUSTRIALE 5.0

Dettaglio
Scaglione Docente Programma dettagliato
Da (compreso) A (escluso)
A ZZZZ Rodriguez Matas Jose Felix, Teng Zhongzhao
manifestidott v. 1.7.0 / 1.7.0
Area Servizi ICT
12/08/2022