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PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers

Project description

DEENESFRITPL

Cloud-based platform for personalised diagnosis of paediatric cancers

For accurate diagnosis and subsequent management of cancer, clinicians are asked to combine diagnostic and clinical information from imaging, pathology, genomics and biochemical analyses. The scope of the EU-funded PRIMAGE project is to further promote the development of in silico tools for a more personalised clinical management of cancer. The work will focus on a decision support system for two types of childhood cancer, neuroblastoma and diffuse intrinsic pontine glioma. Researchers propose to combine all retrospective clinical information, giving particular emphasis on imaging biomarkers and how they can be incorporated into the diagnostic pipeline using AI.

Objective

PRIMAGE proposes a cloud-based platform to support decision making in the clinical management of malignant solid tumours, offering predictive tools to assist diagnosis, prognosis, therapies choice and treatment follow up, based on the use of novel imaging biomarkers, in-silico tumour growth simulation, advanced visualisation of predictions with weighted confidence scores and machine-learning based translation of this knowledge into predictors for the most relevant, disease-specific, Clinical End Points.
PRIMAGE implements a hybrid cloud model, comprising the of use of open public cloud (based on EOSC services) and private clouds, enabling use by the scientific community (facilitating reuse of de-identified clinical curated data in Open Science) and also suitable for future commercial exploitation.
The proposed data infrastructures, imaging biomarkers and models for in-silico medicine research will be validated in the application context of two paediatric cancers, Neuroblastoma (NB, the most frequent solid cancer of early childhood) and the Diffuse Intrinsic Pontine Glioma (DIPG, the leading cause of brain tumour-related death in children). These two paediatric cancers are relevant validation cases given their representativeness of cancer disease, and their high societal impact, as they affect the most vulnerable and loved family members.
The European Society for Paediatric Oncology, two Imaging Biobanks and three of the most prominent European Paediatric oncology units are partners in this project, making retrospective clinical data (imaging, clinical, molecular and genetics) registries accessible to PRIMAGE, for training of machine learning algorithms and testing of the in-silico tools´ performance. Solutions to streamline and secure the data pseudonymisation, extraction, structuring, quality control and storage processes, will be implemented and validated also for use on prospective data, contributing European shared data infrastructures.

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Call for proposal

H2020-SC1-DTH-2018-2020

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Sub call

H2020-SC1-DTH-2018-1

Funding Scheme

RIA - Research and Innovation action

Coordinator

FUNDACION PARA LA INVESTIGACION DEL HOSPITAL UNIVERSITARIO LA FE DE LA COMUNIDAD VALENCIANA
Net EU contribution
€ 1 243 342,07
Address
Av fernando abril martorell 106
46026 Valencia
Spain

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Region
Este Comunitat Valenciana Valencia/València
Activity type
Research Organisations
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Other funding
€ 0,95

Participants (16)

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EC signature date 14 November 2018
Last update: 30 June 2023

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Permalink: https://cordis.europa.eu/project/id/826494

European Union, 2023