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Empowering cancer research in Europe: the EUCAIM cancer imaging infrastructure

  • Luis Martí-Bonmatí*
  • , Ignacio Blanquer
  • , the EUCAIM Consortium
  • , European Society of Radiology (ESR)
  • , Manolis Tsiknakis
  • , Gianna Tsakou
  • , Ricard Martinez
  • , Salvador Capella-Gutierrez
  • , Sara Zullino
  • , Janos Meszaros
  • , Esther E. Bron
  • , Jose Luis Gelpi
  • , Katrine Riklund
  • , Linda Chaabane
  • , Heinz Peter Schlemmer
  • , Mario Aznar
  • , Patricia Serrano Candelas
  • , Peter Gordebeke
  • , Monika Hierath
  • , Serena Scollen
  • Fernando Martin-Sanchez, Oscar Gil García, Nils Sandberg, Tobias Penzkofer, Annabel Seebohm, Patrycja Gazinska, Johannes Haybaeck, Matteo Pallocca, Isabelle Huys, Zdenka Dudova, Petr Holub, Manuela França, José Miguel Rosell Tejada, Olivier Humbert, Carles Hernandez-Ferrer, Maciej Bobowicz, Patrick Fuhrmann, Cátia Sousa Pinto, Wim Vos, Bengt Persson, Gernot Marx, Philippe Lambin, Emanuele Neri, Daniel Rückert, Marc Van den Bulcke, Bram van Ginneken, Angel Alberich-Bayarri, Harald Heese, Regina Beets-Tan, Carlo Catalano, Laure Saint-Aubert, Joel Hedlund
*Corresponding author for this work
  • Instituto de Investigación Sanitaria, Fundación Jiménez Díaz
  • Polytechnic University of Valencia
  • Foundation for Research and Technology-Hellas
  • Maggioli S.P.A.
  • University of Valencia
  • Barcelona Supercomputing Center (BSC)
  • EATRIS ERIC
  • KU Leuven
  • University of Barcelona
  • Umeå University
  • Institute of Legal Informatics and Judicial Systems (IGSiG-CNR)
  • German Cancer Research Center
  • Matical Innovation
  • EIBIR Gemeinnutzige Gmbh Zur Forderung Der Erforschung Der Biomedizinischen Bildgebung
  • ELIXIR Hub
  • Escuela Nacional de Sanidad
  • IQVIA Inc.
  • Region Västerbotten
  • Charité – Universitätsmedizin Berlin
  • Comite Europeen de Coordination des Industries Radiologiques Electromedicales et de Informatique
  • PORT Polish Center for Technology Development
  • Innsbruck Medical University
  • IRCCS Istituti fisioterapici ospitalieri - Istituto Regina Elena
  • Masaryk University
  • Biobanking and BioMolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC)
  • University Hospital Center of Santo António
  • S2 Grupo
  • French Institute for Research in Computer Science and Automation (INRIA)
  • Medical University of Gdańsk
  • EGI Foundation
  • Shared Services of the Ministry of Health (SPMS)
  • Uppsala University
  • Universitätsklinikum Aachen
  • Maastricht University
  • University of Pisa
  • Technical University of Munich
  • Belgian Cancer Centre
  • Radboud University Medical Center
  • QUIBIM SL
  • Phillips Research
  • Netherlands Cancer Institute
  • University of Rome La Sapienza
  • Medexprim
  • Linköping University

Research output: Contribution to journalArticleAcademicpeer-review

13 Citations (Scopus)
61 Downloads (Pure)

Abstract

Artificial intelligence (AI) is a powerful technology with the potential to disrupt cancer detection, diagnosis and treatment. However, the development of new AI algorithms requires access to large and complex real-world datasets. Although such datasets are constantly being generated, access to them is limited by data fragmentation across numerous repositories and sites, heterogeneity, lack of annotations, and potential privacy issues. The European Cancer Imaging Initiative is a flagship of Europe’s Beating Cancer Plan, aiming to unlock the power of AI for cancer patients, clinicians, and researchers by establishing a federated European infrastructure for cancer images through the EU-funded EUropean Federation for CAncer IMages (EUCAIM) project. This infrastructure, called Cancer Image Europe, builds on the AI for Health Imaging network (AI4HI), established European Research Infrastructures (Euro-BioImaging, BBMRI-ERIC, EATRIS, ECRIN, and ELIXIR), and numerous related partners providing access to research tools, images, and related clinical, pathology and molecular data. The infrastructure targets clinicians, researchers, and innovators by providing the means to develop and validate data-intensive AI-based and other IT-enabled clinical decision-making systems supporting precision medicine. Common data models, including a linking hyperontology, quality standards, compliance with the FAIR (Findability, Accessibility, Interoperability and Reusability) principles, data annotation, curation and anonymization services are provided to ensure data quality and interoperability, consistency and privacy. In summer 2024, the EUCAIM project released the first prototype of an EU-wide infrastructure, with a comprehensive dashboard integrating applications for dataset discovery, federated search, data access request, metadata harvesting, annotation, secure processing environments and federated processing. Critical relevance statement: EUCAIM’s federated infrastructure for cancer image data advances medical research and related AI development in Europe. It addresses the current fragmentation and heterogeneity of data repositories is legally compliant, and facilitates collaboration among clinicians, researchers, and innovators. Key Points: AI solutions to advance cancer care rely on large, high-quality real-world datasets. EUCAIM’s federated infrastructure for cancer image data empowers cancer research in Europe. It provides access to research tools, images, and related clinical, pathology and molecular data.

Original languageEnglish
Article number47
JournalInsights into Imaging
Volume16
Issue number1
DOIs
Publication statusPublished - 24 Feb 2025

Bibliographical note

Publisher Copyright:
© The Author(s) 2025.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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