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| Name | Class |
|---|---|
| Grant Agreement ERC SMHEART | UNKNOWN |
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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.
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).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Cardiac MRI acquisition | Other | 200 patients with a clinical indication for cardiac magnetic resonance imaging |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Cardiac MRI acquisition | Device | All patients will have additional images collected during the magnetic resonance imaging (MRI) examination. These are high-resolution multi-contrast cardiac MRI sequences in gradient echo or in balanced steady state free precession with synchronization on the electrocardiogram. The acquisitions last between 1 minute and 10 minutes. This duration depends on the patient's heart rate and breathing rate. The imaging protocol will last approximately 50 minutes. MRI examinations will be performed on a 1.5 Tesla clinical system with specific cardiac imaging coils. |
| Measure | Description | Time Frame |
|---|---|---|
| Imaging integration success | Measure of image quality according to signal-to-noise ratio | 60 months |
| Measure | Description | Time Frame |
|---|---|---|
| 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) | Measure of training time and training loss function | 60 months |
| Cardiac MRI feature: location and size of myocardial scars/fibrosis |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| BUSTIN Aurelien, PHD | Contact | +33 6 16 29 05 91 | aurelien.bustin@ihu-liryc.fr | |
| COCHET Hubert, MD, PHD | Contact | +33 5 57 65 65 42 | hubert.cochet@chu-bordeaux.fr |
| Name | Affiliation | Role |
|---|---|---|
| BUSTIN Aurelien, PHD | University Hospital, Bordeaux | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Chu de Bordeaux | Recruiting | Pessac | 33600 | France |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36638777 | Background | Bustin A, Stuber M, Sermesant M, Cochet H. Smart cardiac magnetic resonance delivering one-click and comprehensive assessment of cardiovascular disease. Eur Heart J. 2023 Feb 21;44(8):636-637. doi: 10.1093/eurheartj/ehac814. No abstract available. |
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| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| ID | Term |
|---|---|
| D002318 | Cardiovascular Diseases |
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|
Measured in mL on late gadolinium enhancement images |
| 60 months |
| Cardiac MRI feature native parameter values (T1, T2, T1-rho, T2*) | Measured in milliseconds | 60 months |
| CMR feature extracellular volume fraction (ECV) | Measured in mL/m2 | 60 months |
| CMR feature ejection fraction | Measured in percentage | 60 months |