Multiscale image-based assessment of cardiovascular pressure gradients – a paradigm shift in hemodynamic risk prediction

What will be done?

The aim of this proposal is to provide a framework for non-invasive, image-based assessment of pressure gradients throughout the cardiovascular system, where critical limitations of spatial, temporal, and flow scales are overcome in a unique multiscale approach.How will it be done?

Combining full-field magnetic resonance imaging (4D Flow MRI) with physics-informed, neural network-based image analysis, a set of specific aims will allow for pressure gradient assessment across spatial (big/small vessels), temporal (fast/slow flows), and flow (laminar/turbulent flows) scales.

Being trained and validated across dedicated in-silico, in-vitro, and in-vivo cohorts, the framework will be ready for direct clinical use, enabling imaging of pressure gradients across previously inaccessible cardiovascular scales (heart/aorta/brain).Why is this important?

Estimation of cardiovascular pressure gradients is critical for diagnosis and treatment of many cardiovascular diseases.

Still, for a large number of conditions, routine assessment is hindered by complex 3D flow, poor spatiotemporal image resolution, or turbulence-driven flow.Why us? The PI is a recognised expert in quantitative translational flow imaging.

Now returning from a fellowship at the Massachusetts Institute of Technology, this 4-year project will establish this unique line of research in Sweden, gathering a dedicated set of collaborators from technical and clinical fields to ensure feasibility and impact.