Validation of Multi-contrast, High-resolution Cardiac Magnetic Resonance Imaging (CARDIO IRM)
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Cardiac Disease
- Sponsor
- University Hospital, Bordeaux
- Enrollment
- 200
- Locations
- 1
- Primary Endpoint
- Imaging integration success
- Status
- Recruiting
- Last Updated
- last year
Overview
Brief Summary
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 heart's 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 CARDIO-IRM 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.
Detailed Description
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 heart's 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 this 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 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).
Investigators
Eligibility Criteria
Inclusion Criteria
- •Adult patient (over 18 years of age) requiring an MRI scan as part of their care.
- •Male or female.
- •Affiliated or beneficiary of a social security scheme
- •Having given his/her oral no objection after having read the information note
Exclusion Criteria
- •Patient unable to give oral consent (guardianship, non-French speaker, etc.)
- •Patient deprived of liberty
- •Patient who does not meet the specific eligibility criteria for an MRI examination: pregnant women, known pathology that may interfere with acquisition (e.g. Parkinson's disease), absolute or relative contraindication to an MRI examination
- •Patient participating in a therapeutic interventional trial or in a period of relative exclusion in relation to another protocol
Outcomes
Primary Outcomes
Imaging integration success
Time Frame: 60 months
Measure of image quality according to signal-to-noise ratio
Secondary Outcomes
- CMR feature extracellular volume fraction (ECV)(60 months)
- Integration of the collected images in an internal database to develop new reconstruction and image processing algorithms specific to this application (e.g. using artificial intelligence)(60 months)
- Cardiac MRI feature: location and size of myocardial scars/fibrosis(60 months)
- Cardiac MRI feature native parameter values (T1, T2, T1-rho, T2*)(60 months)
- CMR feature ejection fraction(60 months)