Emiliano Votta

ORCID: 0000-0001-7115-0151
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About
Contact & Profiles
Research Areas
  • Cardiac Valve Diseases and Treatments
  • Cardiovascular Function and Risk Factors
  • Aortic Disease and Treatment Approaches
  • Infective Endocarditis Diagnosis and Management
  • Cardiac Imaging and Diagnostics
  • Aortic aneurysm repair treatments
  • Cardiac Structural Anomalies and Repair
  • Elasticity and Material Modeling
  • Congenital Heart Disease Studies
  • Coronary Interventions and Diagnostics
  • Advanced MRI Techniques and Applications
  • Cardiac Arrhythmias and Treatments
  • Respiratory Support and Mechanisms
  • Cardiac and Coronary Surgery Techniques
  • Soft Robotics and Applications
  • Advanced X-ray and CT Imaging
  • Osteoarthritis Treatment and Mechanisms
  • Cardiac electrophysiology and arrhythmias
  • Cardiovascular Health and Disease Prevention
  • Mechanical Circulatory Support Devices
  • Cardiac Arrest and Resuscitation
  • Cardiac, Anesthesia and Surgical Outcomes
  • Cardiomyopathy and Myosin Studies
  • Neonatal Respiratory Health Research
  • Renal and Vascular Pathologies

Politecnico di Milano
2016-2025

IRCCS Policlinico San Donato
2020-2024

Bioengineering Technology and Systems (Italy)
2017-2021

Mylan (South Africa)
2015

University of Milan
2008-2010

International Flame Research Foundation
2009

Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele
2002

University of Patras
1994

The beating heart-on-a-chip (i) generates 3D cardiac constructs with well-defined geometries from cell-laden hydrogel prepolymers, (ii) provides uniaxial cyclic mechanical stimulation, (iii) allows efficient delivery of drugs and chemicals.

10.1039/c5lc01356a article EN Lab on a Chip 2015-12-22

Objective: Tidal volume (VT) and of gas caused by positive end-expiratory pressure (VPEEP) generate dynamic static lung strains, respectively. Our aim was to clarify whether different combinations resulting in the same large global strain, constantly produce edema. Design: Laboratory investigation. Setting: Animal unit. Subjects: Twenty-eight healthy pigs. Interventions: After computed tomography, 20 animals were ventilated for 54 hours at a strain 2.5, either entirely (VT 100% VPEEP 0%),...

10.1097/ccm.0b013e31827417a6 article EN Critical Care Medicine 2013-02-05

Lungs behave as viscoelastic polymers. Harms of mechanical ventilation could then depend on not only amplitude (strain) but also velocity (strain rate) lung deformation. Herein, we tested this hypothesis.Laboratory investigation.Animal unit.Thirty healthy piglets.Two groups animals were ventilated for 54 hours with matched strains (ratio between tidal volume and functional residual capacity) different strain rates inspiratory time). Individual ranged 0.6 3.5 in both groups. Piglets low had...

10.1097/ccm.0000000000001718 article EN Critical Care Medicine 2016-04-19

High tidal volume can cause ventilator-induced lung injury (VILI), but positive end-expiratory pressure (PEEP) is thought to be protective. We aimed find the volumetric VILI threshold and see whether PEEP protective per se or indirectly. In 76 pigs (22 ± 2 kg), we examined lower upper limits (30.9–59.7 mL/kg) of inspiratory capacity by computed tomography (CT) scan at 45 cmH2O pressure. The underwent a 54-h mechanical ventilation with global strain ((tidal (dynamic) + (static))/functional...

10.1186/s40635-015-0070-1 article EN cc-by Intensive Care Medicine Experimental 2015-12-01

In the current scientific literature, particular attention is dedicated to study of mitral valve and comprehension mechanisms that lead its normal function, as well those trigger possible pathological conditions. One adopted approaches consists computational modelling, which allows quantitative analysis mechanical behaviour by means continuum mechanics theory numerical techniques. However, none currently available models realistically accounts for all aspects characterize function valve....

10.1098/rsta.2008.0095 article EN Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences 2008-07-04

Transcatheter aortic valve implantation (TAVI) can treat symptomatic patients with calcific stenosis. However, the severity and distribution of calcification leaflets impair TAVI efficacy. Here we tackle this issue from a biomechanical standpoint, by finite element simulation widely adopted balloon-expandable in three models representing root different scenarios We developed modeling approach realistically accounting for pressurization complex anatomy, detailed patterns, actual stent...

10.1016/j.jbiomech.2016.03.036 article EN cc-by Journal of Biomechanics 2016-03-26

Bicuspid aortic valve (BAV) is the most common congenital cardiac disease and a foremost risk factor for aortopathies. Despite genetic basis of BAV associated aortopathies, BAV-related alterations in fluid-dynamics, particularly wall shear stresses (WSSs), likely play role progression aortopathy, may contribute to its pathogenesis. To test whether WSS trigger this study we used 4D Flow sequences phase-contrast magnetic resonance imaging (CMR) quantitatively compare vivo fluid dynamics...

10.3389/fphys.2017.00441 article EN cc-by Frontiers in Physiology 2017-06-26

Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology ascending thoratic aortic aneurysms (ATAA). To accurately reproduce in vivo hemodynamics, computational fluid dynamics (CFD) models must employ realistic inflow boundary conditions (BCs). However, limited availability velocity measurements, still makes researchers resort idealized BCs. The aim this study was generate and thoroughly characterize large dataset synthetic 4D profiles sampled on 2D...

10.1016/j.cmpb.2023.107468 article EN cc-by Computer Methods and Programs in Biomedicine 2023-03-07

Accurate planning of transcatheter aortic valve implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation the root (AR), commonly performed through 3D computed tomography (CT) image analysis. Currently, there no standard automated solution for this process. Two convolutional neural networks with U-Net architectures (model 1 model 2) were trained on 310 CT scans AR Model performs segmentation 2 identifies annulus sinotubular junction (STJ) contours. After...

10.1016/j.compbiomed.2023.107147 article EN cc-by Computers in Biology and Medicine 2023-06-07

Abstract Performing automatic and standardized 4D TEE segmentation mitral valve analysis is challenging due to the limitations of echocardiography scarcity manually annotated images. This work proposes a semi-supervised training strategy using pseudo labelling for MV in TEE; it employs Teacher-Student framework ensure reliable pseudo-label generation. 120 recordings from 60 candidates repair are used. The Teacher model, an ensemble three convolutional neural networks, trained on end-systole...

10.1007/s11517-024-03275-w article EN cc-by Medical & Biological Engineering & Computing 2025-01-11
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