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.

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

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.)

NSTree (2020)

Understanding substrate delivery for cell wall biosynthesis in plants

Read More  

MetEpiC (2020)

P53-dependent Metabolic and Epigenetic Reprogramming in Carcinogenesis

Read More  

CREDit (2020)

Chronological REference Datasets and Sites (CREDit) towards improved accuracy and precision in luminescence-based chronologies

Read More