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| Funder | European Commission |
|---|---|
| Recipient Organization | Universite de Bordeaux |
| Country | France |
| Start Date | Sep 01, 2023 |
| End Date | Aug 31, 2028 |
| Duration | 1,826 days |
| Number of Grantees | 2 |
| Roles | Coordinator; Third Party |
| Data Source | European Commission |
| Grant ID | 101076351 |
Cardiovascular disease (CVD) causes at least 1.8 million European deaths annually, exceeding fatalities from cancer, chronic respiratory disease, and diabetes.
Consequently, the fight against CVD has become the main priority of the World Health Organization.In the pursuit of understanding and treating CVD, cardiac magnetic resonance imaging (CMR) has remained the only modality capable of providing a comprehensive assessment of the hearts function and structure without harmful radiation.
Unfortunately, current CMR systems remain too slow, too complex, require highly trained specialists and, as such, have presented a barrier to a wider adoption of CMR.The aim of my ERC project is to unleash the full potential of CMR to transform patient trajectories by introducing a fast, one-click, fully automated, and comprehensive imaging pipeline applicable to diagnosis, prognosis, and therapy selection in cardiology.This aim will be achieved by (i) creating a novel imaging technology that collects CMR data in a single continuous free-breathing scan, taking into account post-processing requirements at the very origin of CMR sequence design; (ii) exploiting the unique contrasts generated by this technology to automatically extract quantitative markers on cardiac anatomy, function, and tissue characteristics; and (iii) translating this transformative technology from a pre-clinical to a clinical setting.This will be the first-ever integrated cardiac imaging pipeline in which CMR images are acquired in a single click, jointly represented in a single volume, and automatically analysed.
This will unlock obstacles for broader acceptance of CMR and unleash the full potential of CMR to maximize its impact on patient trajectories.
The results of this project will pave the way towards robust image-based strategies for personalized patient care (diagnosis, risk stratification, therapy selection, monitoring, and image-guided interventions).
Universite de Bordeaux; Chu Hopitaux de Bordeaux
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