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PIC SIGNED

Personalised In-Silico Cardiology

Total Cost €

0

EC-Contrib. €

0

Partnership

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 PIC project word cloud

Explore the words cloud of the PIC project. It provides you a very rough idea of what is the project "PIC" about.

companies    healthcare    simulation    rendering    optimization    ideas    safety    choices    articulate    articulating    industrial    experts    talent    cohort    animal    deaths    pic    therapies    medical    tools    instrumentation    delivered    diagnostic    cultural    solutions    technologies    cardiac    biomarkers    fluent    society    improving    morbidity    protocols    barriers    silico    fellows    drugs    diseases    annually    materialise    data    predictive    leaders    shift    innovation    vision    cardiovascular    pooling    sensing    beneficiaries    models    disease    capacity    42    personalised    training    mandates    acquisition    computational    compliance    preventive    mortality    intervention    originated    packages    15    meet    itn    169    total    inter    disciplines    dialogue    expertise    disciplinary    practical    model    device    sectors    engineers    detection    exposed    structural    generation    clinical    huge    responsible    translation    imaging    academic    clinicians    train    actual    million    billion    cardiology    regulation    unparalleled   

Project "PIC" data sheet

The following table provides information about the project.

Coordinator
KING'S COLLEGE LONDON 

Organization address
address: STRAND
city: LONDON
postcode: WC2R 2LS
website: www.kcl.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website https://picnet.eu/
 Total cost 4˙000˙569 €
 EC max contribution 4˙000˙569 € (100%)
 Programme 1. H2020-EU.1.3.1. (Fostering new skills by means of excellent initial training of researchers)
 Code Call H2020-MSCA-ITN-2017
 Funding Scheme MSCA-ITN-ETN
 Starting year 2017
 Duration (year-month-day) from 2017-09-01   to  2021-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    KING'S COLLEGE LONDON UK (LONDON) coordinator 819˙863.00
2    OSLO UNIVERSITETSSYKEHUS HF NO (OSLO) participant 572˙550.00
3    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) participant 546˙575.00
4    UNIVERSITEIT MAASTRICHT NL (MAASTRICHT) participant 510˙748.00
5    GE VINGMED ULTRASOUND AS NO (HORTEN) participant 286˙275.00
6    UNIVERSITE DE BORDEAUX FR (BORDEAUX) participant 262˙875.00
7    MEDTRONIC BAKKEN RESEARCH CENTER B.V. NL (MAASTRICHT) participant 255˙374.00
8    FEOPS NV BE (GENT) participant 250˙560.00
9    CONSORCI INSTITUT D'INVESTIGACIONS BIOMEDIQUES AUGUST PI I SUNYER ES (BARCELONA) participant 247˙872.00
10    UNIVERSIDAD DE ZARAGOZA ES (ZARAGOZA) participant 247˙872.00
11    Agency for Health Quality & Assessment of Catalonia ES (Barcelona) partner 0.00
12    CARDIACCS AS NO (Oslo) partner 0.00
13    Food & Drug Administration US (Silver Spring) partner 0.00
14    IBM US (Armonk) partner 0.00
15    JANSSEN PHARMACEUTICA NV BE (BEERSE) partner 0.00
16    John Radcliffe Hospital UK (Oxford) partner 0.00
17    MS Start CH (Zurich) partner 0.00
18    Said Business School UK (Oxford) partner 0.00
19    VPH-Institute BE (Leuven) partner 0.00

Map

 Project objective

Improving healthcare systems mandates a shift towards personalised and preventive management of disease. Specifically, the management of cardiovascular diseases has a huge impact on European society in terms of mortality, morbidity and healthcare costs, being responsible for 1.9 million deaths in the EU annually (42% of all deaths) with a total cost of €169 billion. Advances in computational and simulation technologies now provide us with unparalleled capacity to analyse clinical data in-silico, rendering the vision of an early detection of disease through model-based diagnostic biomarkers, and the design of personalised therapies through predictive models. In-silico methodologies enable the optimization of clinical protocols, from data acquisition to device parameters and intervention choices. In-silico tools also enable the reduction of animal use in the development of novel cardiac therapies and drugs. PIC is the European ITN that will train the cohort of 15 of the future innovation leaders able to articulate and materialise the vision of a Personalised In-silico Cardiology (PIC). It will address specific challenges originated by cultural and structural barriers between sectors and disciplines, articulating a fluent dialogue and work between clinicians and engineers. Fellows will be exposed to the generation of novel academic ideas, the design of practical solutions that meet actual clinical needs, the translation into industrial products, and the compliance with safety and regulation requirements. This will be achieved by pooling the expertise of leading experts from 4 academic, 3 industrial and 3 clinical beneficiaries. A highly inter-disciplinary program will be delivered in 4 research work packages, with companies leading two of them. New talent and innovation will be produced through the training in the disciplines of computational cardiac modelling, medical imaging & sensing, and clinical devices & instrumentation.

 Deliverables

List of deliverables.
Guidelines for Supervision Quality Documents, reports 2019-06-17 13:50:29

Take a look to the deliverables list in detail:  detailed list of PIC deliverables.

 Publications

year authors and title journal last update
List of publications.
2020 Jorge Corral Acero, Ernesto Zacur, Hao Xu, JE Scheneider, Alfonso Bueno-Orovio, Pablo Lamata, Vicente Grau
Left Ventricle Quantification with Cardiac MRI: Deep Learning Meets Statistical Models of Deformation
published pages: , ISSN: , DOI:
STACOM 2019 the 10th Workshop on Statistical Atlases and Computational Modelling of the Heart 2019-11-18
2019 Loncaric F, Marciniak M, Nunno L, Fernandes JF, Mimbrero M, Tirapu L, Fabijanovic D, Sanchis L, Doltra A, Cikes M, Lamata P, Bijnens B, Sitges M
Myocardial work in hypertension and mitral regurgitation- insights from non-invasive assessment of left ventricular pressure-strain relations
published pages: , ISSN: , DOI:
European Heart Journal Cardiovascular Imaging 2019-11-12
2018 Loncaric F, Nunno L, Mimbrero M, Sanchis L, Montserrat S, Weidemann F, Bijnens B, Sitges M
A septal bulge depicts more advanced cardiac impairment in patients with hypertension: the case of atrial remodelling
published pages: , ISSN: , DOI:
European Heart Journal Cardiovascular Imaging 2019-11-12
2019 F Loncaric, M Marciniak, J F Fernandes, L Nunno, M Mimbrero, L Tirapu, L Sanchis, A Doltra, D Fabijanovic, M Cikes, P Lamata, B Bijnens, M Sitges
P3836Myocardial work distribution in hypertensive patients with basal septal hypertrophy - a non-invasive assessment with left ventricular pressure-strain relations
published pages: , ISSN: 0195-668X, DOI: 10.1093/eurheartj/ehz745.0677
European Heart Journal 40/Supplement_1 2019-11-12
2019 F Loncaric, A Regueiro, L Sanchis, M Sousa, A Doltra, S Prat, M Sabate, P Lamata, P Mortier, M Sitges
P3695Predicting adverse outcomes after TAVI procedure - a comparison of two CoreValve generations using real-life outcomes and patient-specific computer simulations
published pages: , ISSN: 0195-668X, DOI: 10.1093/eurheartj/ehz745.0549
European Heart Journal 40/Supplement_1 2019-11-12
2018 Filip Loncaric, Bart Bijnens, Marta Stiges
Added value of cardiac deformation imaging in differential diagnosis of left ventricular hypertrophy
published pages: , ISSN: 2305-7823, DOI: 10.21542/gcsp.2018.21
Global Cardiology Science and Practice 2018/3 2019-11-12
2018 Filip Lončarić, Maciej Marciniak, Joao Filipe Fernandes, Loredana Nunno, Laura Sanchis, Bart Bijnens, Marta Sitges
Basal septal hypertrophy in patients with hypertension: a non-invasive assessment of segmental myocardial work with left ventricular pressure-strain relations
published pages: 411-412, ISSN: 1848-543X, DOI: 10.15836/ccar2018.411
Cardiologia Croatica 13/11-12 2019-11-12
2019 Loncaric F, Marciniak M, Fernandes JF, Nunno L, Mimbrero M, Tirapu L, Sanchis L, Doltra A, Fabijanovic D, Cikes M, Bijnens B, Lamata P, Sitges M.
Segmental septal curvature - a novel, semi-automated parameter for recognizing basal septal hypertrophy in arterial hypertension
published pages: , ISSN: , DOI:
European Heart Journal Cardiovascular Imaging 2019-11-12
2019 JC Acero, H Xu, E Zacur, J Schneider, P Lamata, A Bueno-Orovio, V Grau
Left Ventricle Quantification with Cardiac MRI : Deep Learning Meets Statistical Models of Deformation
published pages: , ISSN: , DOI:
Lecture Notes in Computer Science (LNCS) 2019-11-07
2019 Joao Filipe Fernandes, Alessandro Faraci, Saul Myerson, David Alexander Nordsletten, Pablo Lamata.
“Enhanced non-invasive pressure drop and flow inefficiencies quantification via 4D-flow MRI”
published pages: , ISSN: , DOI:
Proc. of 27th ISMRM conference 2019-11-07
2019 Ali Wajdan, Magnus Reinsfelt Krogh, Manuel Villegas-Martinez, Per Steinar Halvorsen, Ole-Johannes Grymyr, Ole Jakob Elle, Espen W. Remme
Monitoring cardiac function by accelerometer –detecting start systole from the acceleration signal makes additional ECG recordings for R-peak detection redundant
published pages: , ISSN: , DOI:
Proc of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019-11-07
2018 Cristóbal Rodero, Marina Strocchi, Pablo Lamata, Gernot Plank, Christopher A Rinaldi, Steven A Niederer.
“In-Silico and clinical based pipeline for the electrode location optimisation in quadripolar left ventricular leads for cardiac resynchronization therapy
published pages: 71, ISSN: , DOI:
Proc. of The heart by numbers Conference 2019-11-07
2019 Francesca Margara, Alfonso Bueno Orovio, Blanca Rodriguez
\"\"\"In-Silico investigation of drug safety and efficacy in human electro-mechanical function”\"
published pages: , ISSN: , DOI:
Proc. of Gordon Research Conference on Cardiac Arrhythmia Mechanisms 2019-11-07
2019 Jorge Corral Acero, Ernesto Zacur, Hao Xu, Rina Ariga, Alfonso Bueno-Orovio, Pablo Lamata, Vicente Grau
SMOD - Data augmentation based on Statistical Models of Deformation to enhance segmentation in 2D cine cardiac MRI
published pages: , ISSN: , DOI:
Lecture Notes in Computer Science (LNCS, volume 11504) 2019-11-07
2018 Joao Filipe Fernandes, Alessandro Faraci, Saul Myerson, David A. Nordsletten and Pablo Lamata
“Inaccuracies of clinical pressure gradient measurements: Quantification of pressure recovery in aortic valve conditions.”
published pages: , ISSN: , DOI:
Proc. of VIRTUAL PHYSIOLOGICAL HUMAN 2018 Conference 2019-11-07
2019 Yingjing Feng, Mirabeau Saha, Mélèze Hocini, Edward Vigmond
Noninvasive One-Year Ablation Outcome Prediction for Paroxysmal Atrial Fibrillation Using Trajectories of Activation From Body Surface Potential Maps
published pages: , ISSN: , DOI:
Computing in Cardiology 2019 Proceeding 2019-11-07
2019 Flavio Palmieri, Pedro Gomis, José Esteban Ruiz, Beatriz Bergasa, Alba Martín-Yebra, Syed Hassaan Ahmed, Esther Pueyo, Juan Pablo Martínez, Julia Ramírez, Pablo Laguna
Transmural ventricular heterogeneities play a major role in determining T-wave morphology at different extracellular potassium levels
published pages: , ISSN: , DOI:
Computing in Cardiology 2019 Proceeding 2019-11-07
2019 J Fernandes, A Faraci, J Sotelo, J Urbina, C Bertoglio, S Uribe, D A Nordsletten, P Lamata
P588Flow profile for a better non-invasive pressure drop in CoA
published pages: , ISSN: 0195-668X, DOI: 10.1093/eurheartj/ehz747.0197
European Heart Journal 40/Supplement_1 2019-11-07
2018 M. Marciniak, L. Toemen, A. King, V. Jaddoe, P. Lamata
An anatomical surrogate of wall compliance in the infant heart
published pages: , ISSN: , DOI:
Proc. of Frontiers of Simulation and Experimentation for Personalised Cardiovascular Management and Treatment conference VPH CaSE Conference. 2019-11-07
2019 Syed Hassaan Ahmed, Flavio Palmieri, Mark Potse, Julia Ramírez, Pablo Laguna, Carlos Sánchez, Esther Pueyo
Transmural ventricular heterogeneities play a major role in determining T-wave morphology at different extracellular potassium levels.
published pages: , ISSN: , DOI:
Computing in Cardiology 2019 Proceeding 2019-11-07
2018 J.F. Fernandes, A. Faraci, S. Myerson, D.A. Nordsletten, P. Lamata
Inaccuracies of clinical pressure drop: Quantification of pressure recovery in bicuspid aortic valve
published pages: , ISSN: , DOI:
Proc. of Frontiers of Simulation and Experimentation for Personalised Cardiovascular Management and Treatment conference VPH CaSE Conference. 2019-11-07

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