Opendata, web and dolomites

PICModForPCa SIGNED

Personalised Image-based Computational Modelling Framework to Forecast Prostate Cancer

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 PICModForPCa project word cloud

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

monitored    patient    meeting    actual    mpmri    inverse    life    ageing    treatment    multiparametric    researcher    resonance    limited    priorities    ideal    background    active    written    computational    optimise    issue    evolution    hence    communications    biological    predictive    respectively    differential    compromise    regular    magnetic    survival    skills    personalised    scientific    individualisation    strategy    imaging    directed    previously    models    surveillance    personalise    derive    led    undertreatment    simulation    rely    candidate    proposes    tumour    simulations    diagnosis    closely    clinical    offers    worldwide    network    ing    independent    threatening    equations    pca    prostate    indolent    provides    organ    patients    mechanical    images    date    model    start    men    phenomena    data    voxel    quality    obtain    collaborations    tests    posterior    forecast    medical    techniques    dates    validated    building    wise    scenarios    tumours    wealth    guide    solving    unresolved    unparalleled    run    health    oral    cancer    computationally    mathematical    overtreatment    precise   

Project "PICModForPCa" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITA DEGLI STUDI DI PAVIA 

Organization address
address: STRADA NUOVA 65
city: PAVIA
postcode: 27100
website: www.unipv.it

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 Italy [IT]
 Total cost 251˙002 €
 EC max contribution 251˙002 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2018
 Funding Scheme MSCA-IF-GF
 Starting year 2020
 Duration (year-month-day) from 2020-09-01   to  2023-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITA DEGLI STUDI DI PAVIA IT (PAVIA) coordinator 251˙002.00
2    THE UNIVERSITY OF TEXAS SYSTEM US (AUSTIN) partner 0.00

Map

 Project objective

Prostate cancer (PCa) is a major health problem among ageing men worldwide, especially in Europe. However, the medical management of PCa only offers limited individualisation and has led to significant overtreatment and undertreatment, which may compromise patient quality of life and survival respectively. Active surveillance is a clinical strategy in which patients with life-threatening PCa are directed to treatment while those with indolent tumours remain closely monitored via regular clinical tests and medical imaging. Multiparametric magnetic resonance imaging (mpMRI) provides high-quality data on PCa and is increasingly used in its diagnosis and surveillance, but computationally exploiting the wealth of data in these images to obtain precise information on tumour evolution to guide clinical management is an unresolved challenge. To address this timely issue, this project proposes to derive a personalised predictive mathematical model of PCa based on mpMRI to run organ-scale simulations that improve diagnosis and forecast the patient’s tumour evolution. The model will rely on robust biological and mechanical phenomena described via differential equations whose parameters are identified voxel-wise by solving an inverse problem using the patient’s clinical and mpMRI data at two dates. The model will then be validated by comparing simulation and actual data at a posterior date. The resulting predictive technology offers an unparalleled advance to personalise and optimise active surveillance for PCa, hence meeting many European Commission priorities for research in cancer. The candidate has previously developed computational models and methods to study PCa growth in clinical scenarios. Building on this ideal background, this project will provide him with crucial scientific techniques and skills to become a leading independent researcher, produce high-impact oral and written communications, and start an active network of collaborations between the US and Europe.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "PICMODFORPCA" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "PICMODFORPCA" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.3.2.)

RipGEESE (2020)

Identifying the ripples of gene regulation evolution in the evolution of gene sequences to determine when animal nervous systems evolved

Read More  

5G-ACE (2019)

Beyond 5G: 3D Network Modelling for THz-based Ultra-Fast Small Cells

Read More  

CIRICC (2019)

Complicity: Individual Responsibility in Collective Contexts

Read More