MRI-based analysis of structural-functional relationships in HFpEF

HFpeF is a heterogeneous syndrome associated with increased myocardial stiffness, fibrosis, fat accumulation, microvascular dysfunction, abnormal ventricular-aortic coupling and dysregulation of cardiac energy metabolism. These phenotypes of cardiac remodelling may depend on predisposition, the intensity and duration of the underlying triggers. Cardiovascular magnetic resonance imaging (CMR) is currently the gold standard for assessing heart size and function, as well as changes in cardiac muscle tissue such as fibrosis, inflammatory response and fat infiltration.

New CMR approaches enable the quantification of luminal blood flow, microvascular perfusion and blood oxygenation, as well as the quantification of epicardial and myocardial fat and functional reserve through the performance of an MR-compatible physiological stress test. Whilst conventional analysis methods utilise only a fraction of the data provided by CMR, image analyses based on artificial intelligence (AI) allow for a more comprehensive consideration of complementary CMR sequences and the parallel assessment of other organ systems (kidney, lung). Our central hypothesis is that innovative CMR applications, in combination with AI, enable imaging-based differentiation of the predominant HFpEF cardiac pathologies.