From Magnetic Resonance Imaging to Molecular Signatures: Generative AI for Virtual Biopsy in Gliomasbroad
GLIOGEN-X · Horizon Europe grant · 2026-10-01–2030-09-30
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-EIC-2025-PATHFINDERCHALLENGES-01 · scheme HORIZON-EIC · topic HORIZON-EIC-2025-PATHFINDERCHALLENGES-01-02. CORDIS record →
Objective
GLIOGEN-X pioneers a new paradigm in neuro-oncology. It is a novel generative AI modality designed to test whether brain MRI truly encodes recoverable molecular information about gliomas. While current radiogenomic approaches assume that deep networks can implicitly learn tumour biology from images, this project transforms that assumption into a falsifiable hypothesis, experimentally probing the informational limits of MRI and its capacity to support virtual biopsy.The project builds on three synergistic, high-risk/high-gain pillars. First, generative experimentation will use controlled diffusion models to synthesise realistic, biomarker-aware glioma MRIs, testing whether molecular conditioning injects measurable and reproducible phenotypic structure. Second, interpretable and uncertainty-aware prediction will translate these generative insights into transparent virtual-biopsy models, capable of identifying key molecular signatures from imaging alone.Third, a federated research infrastructure will ensure privacy-preserving, GDPR-compliant collaboration across hospitals, enabling robust validation without data sharing and fostering reproducibility.Beyond its scientific objectives, GLIOGEN-X establishes the methodological and ethical foundations for AI Act–ready medical AI: explainable, auditable, and human-centred by design.Its outputs, a pathology-aware generative engine, hybrid datasets, interpretable predictors and an experimental research platform, will form a reusable European asset for trustworthy AI in healthcare.Whether confirming or refuting the central hypothesis, GLIOGEN-X will deliver transformative knowledge by defining how far imaging can reveal tumour biology and paving the way for non-invasive, personalised oncology guided by trustworthy artificial intelligence.
Beneficiaries (5)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| Siena Imaging s.r.l. | IT | coordinator | €2,201,826 | Yes |
| FONDAZIONE TOSCANA LIFE SCIENCES | IT | participant | €709,625 | |
| THE UNIVERSITY OF MANCHESTER | UK | participant | €646,650 | |
| FUNDACIO PER A LA UNIVERSITAT OBERTA DE CATALUNYA | ES | participant | €437,942 | |
| NORTHERN CARE ALLIANCE NHS FOUNDATION TRUST | UK | thirdParty | €0 |
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