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

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

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. This will be 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.

Cyfronet tasks

The Cyfronet team will be involved directly in development, integration and support for high-performance execution environment for large-scale multi-model simulations. This solution will be provisioned by our team to the consortium members using the PLGrid Infrastructure for e-Science, and specifically, the Prometheus supercomputer. We will assist our partners in efficient usage of computational power and disk storage, and we will perform integration of Cyfronet tools and solutions with these provided by other technology providers within the project.

PRIMAGE Partners

  • Instituto de Investigación Sanitaria La Fe
  • Quibim SL
  • Medexprim
  • Konstanz University
  • Universita di Pisa
  • Universidad de Zaragoza
  • The University of Sheffield
  • Ansys France
  • Matical Innovation SL
  • St. Anna Kinderkrebsforschung e.V.
  • Children´s Cancer Research Institute
  • Uniklinik Koeln
  • The European Society for Paediatric Oncology
  • Institute for instrumentation on molecular imaging UPV-CSIC
  • ACC Cyfronet AGH
  • Chemotargets SL
  • University of Bologna

PRIMAGE Papers

5 members of DICE Team are co-authors of a paper on the PRIMAGE project published in the European Radiology Experimental journal: Martí-Bonmatí, L., Alberich-Bayarri, Á., Ladenstein, R. et al.: PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers. Eur Radiol Exp 4, 22 (2020). https://doi.org/10.1186/s41747-020-00150-9

PRIMAGE Presentations

First PRIMAGE Working Session, 28-30 April 2020

PRIMAGE Kick-off, Valencia, 19-20 December 2018

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