Smart Cardiac Magnetic Resonance Delivering One-Click and Comprehensive Assessment of Cardiovascular Diseases

Projektbeschreibung

Fortgeschrittene Bildgebung für die Diagnose von Herz-Kreislauf-Erkrankungen

Herz-Kreislauf-Erkrankungen stellen weltweit eine der häufigsten Todesursachen und eine große gesundheitliche Herausforderung dar, die Aufmerksamkeit und innovative Ansätze für Prävention, Diagnose und Behandlung erfordert. Die derzeitigen Methoden zur Beurteilung der Funktion und Struktur des Herzens, wie z. B. die kardiale Magnetresonanztomographie, weisen jedoch Einschränkungen auf, die einer breiten Anwendung entgegenstehen. Ziel des vom Europäischen Forschungsrat finanzierten Projekts SMHEART ist es, die kardiale Magnetresonanztomographie durch die Entwicklung einer schnellen, automatisierten Bildgebungspipeline zu revolutionieren, die eine umfassende und effiziente Diagnose, Prognose und Therapieauswahl in der Kardiologie unterstützt. Mit dieser transformativen Technologie soll die Wirkung der kardialen Magnetresonanztomographie zu maximieren und ihre Anwendung zu rationalisieren, um den Weg für eine individuelle Patientenversorgung im Bereich der kardiovaskulären Gesundheit zu ebnen.

Ziel

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).