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PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers

Martí-Bonmatí, Luis; Alberich-Bayarri, Ángel; Ladenstein, Ruth; Blanquer, Ignacio; Segrelles, J. Damian; Cerdá-Alberich, Leonor; Gkontra, Polyxeni; Hero, Barbara; García-Aznar, J. M.; Keim, Daniel; Jentner, Wolfgang; Seymour, Karine; Jiménez-Pastor, Ana; González-Valverde, Ismael; Martínez de las Heras, Blanca; Essiaf, Samira; Walker, Dawn; Rochette, Michel; Bubak, Marian; Mestres, Jordi; Viceconti, Marco; Martí-Besa, Gracia; Cañete, Adela; Richmond, Paul; Wertheim, Kenneth Y.; Gubala, Tomasz; Kasztelnik, Marek; Meizner, Jan; Nowakowski, Piotr; Gilpérez, Salvador; Suárez, Amelia; Aznar, Mario; Restante, Giuliana; Neri, Emanuele

Authors

Luis Martí-Bonmatí

Ángel Alberich-Bayarri

Ruth Ladenstein

Ignacio Blanquer

J. Damian Segrelles

Leonor Cerdá-Alberich

Polyxeni Gkontra

Barbara Hero

J. M. García-Aznar

Daniel Keim

Wolfgang Jentner

Karine Seymour

Ana Jiménez-Pastor

Ismael González-Valverde

Blanca Martínez de las Heras

Samira Essiaf

Dawn Walker

Michel Rochette

Marian Bubak

Jordi Mestres

Marco Viceconti

Gracia Martí-Besa

Adela Cañete

Paul Richmond

Tomasz Gubala

Marek Kasztelnik

Jan Meizner

Piotr Nowakowski

Salvador Gilpérez

Amelia Suárez

Mario Aznar

Giuliana Restante

Emanuele Neri



Abstract

PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consortium, including the European Society for Paediatric Oncology, two imaging biobanks, and three prominent European paediatric oncology units. The project is constructed as an observational in silico study involving high-quality anonymised datasets (imaging, clinical, molecular, and genetics) for the training and validation of machine learning and multiscale algorithms. The open cloud-based platform will offer precise clinical assistance for phenotyping (diagnosis), treatment allocation (prediction), and patient endpoints (prognosis), based on the use of imaging biomarkers, tumour growth simulation, advanced visualisation of confidence scores, and machine-learning approaches. The decision support prototype will be constructed and validated on two paediatric cancers: neuroblastoma and diffuse intrinsic pontine glioma. External validation will be performed on data recruited from independent collaborative centres. Final results will be available for the scientific community at the end of the project, and ready for translation to other malignant solid tumours.

Citation

Martí-Bonmatí, L., Alberich-Bayarri, Á., Ladenstein, R., Blanquer, I., Segrelles, J. D., Cerdá-Alberich, L., …Neri, E. (2020). PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers. European Radiology Experimental, 4(1), https://doi.org/10.1186/s41747-020-00150-9

Journal Article Type Article
Publication Date Dec 1, 2020
Deposit Date Jan 23, 2023
Publicly Available Date Jan 24, 2023
Journal European Radiology Experimental
Electronic ISSN 2509-9280
Publisher SpringerOpen
Peer Reviewed Peer Reviewed
Volume 4
Issue 1
DOI https://doi.org/10.1186/s41747-020-00150-9
Public URL https://hull-repository.worktribe.com/output/4186836

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© The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License,
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