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.

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

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.)

ReproMech (2019)

The Molecular Mechanisms of Cell Fate Reprogramming in Vertebrate Eggs

Read More  

NSTree (2020)

Understanding substrate delivery for cell wall biosynthesis in plants

Read More  

BB-SLM (2020)

Polychromatic digital optics for structured light

Read More