Objective
Smart-MRI (Synthetic Multi-timepoint AI-enhanced Breast MRI) aims to eliminate the need for gadolinium-based contrast agents while preserving the diagnostic accuracy of Dynamic Contrast-Enhanced MRI (DCE-MRI).
Smart-MRI consists of three key phases. The first phase focuses on AI model optimization and external validation. Our deep learning model is trained on a large dataset of paired contrast-enhanced and non-contrast breast MRI scans, designed to capture essential temporal and morphological features for lesion characterization. By reducing imaging complexity and relying only on pre-contrast T1-weighted and DWI sequences, Smart-MRI streamlines imaging protocols, supporting feasibility for widespread clinical adoption.
The second phase involves a multi-center external validation in a screening setting to assess the generalizability and clinical applicability of Smart-MRI across different imaging systems and diverse patient populations. Structured reader studies are conducted with expert radiologists to compare Smart-MRI-generated synthetic contrast-enhanced images with standard DCE-MRI for this purpose. These studies evaluate lesion detectability, image fidelity, and diagnostic confidence.
In the third, and overlapping phase, we assess market potential, and analyse barriers for integration into routine clinical practice, aiming to create an initial prospective integration into existing imaging platforms and workflows and translate the innovation into a usable product in collaboration with our technology transfer office and potential industrial partners.
If successful, Smart-MRI is expected to transform breast cancer imaging by offering a contrast-free alternative to DCE-MRI without compromising diagnostic performance. By eliminating Smart-MRI is an addition to the ERC Consolidator project SAFE-MRI, focussing on the optimisation and validation of a market ready synthetic breast MRI solution, enabling widely accessible contrast-free breast MRI as a screening solution.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- medical and health sciences clinical medicine oncology breast cancer
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2026-POC
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
6525 GA Nijmegen
Netherlands
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