Project description
Smart algorithm to reduce gadolinium dosage in magnetic resonance imaging
The contrast agent gadolinium is commonly used in magnetic resonance imaging to enhance the visibility of internal structures. This improves diagnostic accuracy of pathologies such as metastases. In cranial magnetic resonance tomography, patients receive a full dose of the contrast agent according to body weight. Though usually eliminated through the renal system, gadolinium is toxic and can cause severe side effects, including allergic reactions and kidney complications. To address this, the EU-funded DAICAR project has developed an AI-based algorithm that enables a reduction of gadolinium dosage. Initial data has proven promising, so the project now aims to advance the clinical standard of its smart algorithm.
Objective
In cranial magnetic resonance tomography (cMRT), the administration of contrast agent facilitates diagnosis of various pathologies such as metastases due to contrast agent enhancement. Patients undergoing a medically indicated cMRT receive 100% of the authorized contrast agent dose, i.e. 0.1 mmol of gadolinium per kg body weight. The main component of MRT contrast agent is gadolinium, which is a highly toxic rare-earth element, which has potential health side effects (inter alia allergic reactions and accumulation in the body) as well as environmental side effects (accumulation in the tap water).
Due to the aforementioned issues, the reduction of contrast agent dose in cMRT is highly desirable. To tackle this issue, Katerina Deike-Hofmann from the Clinic for Neuroradiology at the University Hospital Bonn together with colleagues and collaborators from the Institute of Mathematics and Life Sciences developed an artificial intelligence (AI)-based algorithm that allows for contrast agent reduction called SmartContrast. Until today, more than 1.000 prospective data sets were acquired at seven different clinics and SmartContrast showed excellent generalizibility. Thus, Katerina Deike-Hofmann founded the relios.vision GmbH as a spin-off of the University Bonn to commercialize SmartContrast. Her goal is to advance the clinical standard by combining knowledge from the areas of medicine, mathematical image processing, computer vision, and artificial intelligence.
Fields of science (EuroSciVoc)
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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.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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.3.2 - European innovation ecosystems
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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
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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-CSA - HORIZON Coordination and Support Actions
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIE-2022-SCALEUP-02
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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.
53113 BONN
Germany
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