Cardiology

Related publications (30)

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Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

Background: Signal processing tools are required to efficiently analyze data collected in body-surface-potential map (BSPM) recordings. A limited number of such tools exist for studying persistent atrial fibrillation (persAF). We propose two novel, spatiot ...

FRONTIERS MEDIA SA2022

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Riccardo Tenderini, Stefano Pagani

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

2022

POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium

Alfio Quarteroni, Andrea Manzoni

The numerical simulation of multiple scenarios easily becomes computationally prohibitive for cardiac electrophysiology (EP) problems if relying on usual high-fidelity, full order models (FOMs). Likewise, the use of traditional reduced order models (ROMs) ...

FRONTIERS MEDIA SA2021

A 0.4 nJ Excitation Energy Bridge-to-Digital Converter for Implantable Pulmonary Artery Pressure Monitoring

Marco Mattavelli, Catherine Dehollain, Diego Ruben Barrettino, Kerim Türe, Mustafa Besirli

This paper presents an energy-efficient, duty-cycled, and spinning excitation bridge-to-digital converter (BDC) suitable for measuring the pulmonary artery pressure of heart failure patients with an implantable system. The duty-cycled bridge uses resistanc ...

IEEE2021

The effect of left ventricular contractility on arterial hemodynamics: A model-based investigation

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou

Ventricular-arterial coupling is a major determinant of cardiovascular performance, however, there are still inherent difficulties in distinguishing ventricular from vascular effects on arterial pulse phenotypes. In the present study, we employed an extens ...

2021

A Computational Study of the Electrophysiological Substrate in Patients Suffering From Atrial Fibrillation

Alfio Quarteroni, Andrea Manzoni

In the context of cardiac electrophysiology, we propose a novel computational approach to highlight and explain the long-debated mechanisms behind atrial fibrillation (AF) and to reliably numerically predict its induction and sustainment. A key role is pla ...

FRONTIERS MEDIA SA2021

Acute and Long-Term Effects of Aortic Compliance Decrease on Central Hemodynamics: A Modeling Analysis

Nikolaos Stergiopoulos, Georgios Rovas, Vasiliki Bikia, Stamatia Zoi Pagoulatou

Aortic compliance is an important determinant of cardiac afterload and a contributor to cardiovascular morbidity. In the present study, we sought to provide in silico insights into the acute as well as long-term effects of aortic compliance decrease on cen ...

FRONTIERS MEDIA SA2021

ECG-Based Indices to Characterize Persistent Atrial Fibrillation Before and During Stepwise Catheter Ablation

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

Background: Consistently successful patient outcomes following catheter ablation (CA) for treatment of persistent atrial fibrillation (pers-AF) remain elusive. We propose an electrocardiogram (ECG) analysis designed to (1) refine selection of patients most ...

2021

Predicting future myocardial infarction from angiographies with deep learning

Pascal Frossard, Emmanuel Abbé, Ortal Yona Senouf, Olivier Muller, Ntorina Thanou, Thabodhan Mahendiran, Omar Raita, Stéphane Fournier, David Meier, Nicolas Dayer

In patients with stable Coronary Artery Disease (CAD), the identification of lesions which will be responsible of a myocardial infarction (MI) during follow-up remains a daily challenge. In this work, we propose to predict culprit stenosis by applying a de ...

2021

Pulsatile Flow-Induced Fatigue-Resistant Photopolymerizable Hydrogels for the Treatment of Intracranial Aneurysms

Dominique Pioletti, Christophe Moser, Mahmut Selman Sakar, Andreas Schmocker, Oriane Poupart, Lucio Feo Pancaldi-Giubbini

An alternative intracranial aneurysm embolic agent is emerging in the form of hydrogels due to their ability to be injected in liquid phase and solidify in situ. Hydrogels have the ability to fill an aneurysm sac more completely compared to solid implants ...

2021

Page 2 of 3

Novel spatiotemporal processing tools for body-surface potential map signals for the prediction of catheter ablation outcome in persistent atrial fibrillation

Jean-Marc Vesin, Adrian Luca, Etienne Pruvot

FRONTIERS MEDIA SA2022

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Riccardo Tenderini, Stefano Pagani

2022

POD-Enhanced Deep Learning-Based Reduced Order Models for the Real-Time Simulation of Cardiac Electrophysiology in the Left Atrium

Alfio Quarteroni, Andrea Manzoni

FRONTIERS MEDIA SA2021