Heart Diseases Clinical Trial
Official title:
PReserved Ejection Fraction Evaluation and Recognition by Cardiac Magnetic Resonance
Heart failure with preserved ejection fraction (HFpEF) is a common and growing condition with a poor prognosis but the pathophysiology and management are still being investigated. The PREFER-CMR project aims to evaluate and validate the application of novel 4D cardiac magnetic resonance flow dynamic methods to measure left ventricular pressures and validate these measurements with direct pressure measurement by coronary angiography. This is a prospective observational study of patients with HFpEF undergoing clinical evaluation with coronary angiography who will also undergo contemporaneous cardiac MRI. The primary outcome will be the level of agreement between the two methods using angiography as the reference method.
Heart failure with preserved ejection fraction (HFpEF) is prevalent, increasing in incidence and has a poor prognosis. Accurate left ventricular (LV) haemodynamic assessment is needed to diagnose and manage patients with HFpEF. The reference method for assessment is an invasive study using catheters to measure intra-ventricular pressure but this is rarely done due to its invasive nature, high procedural costs and lack of expertise, despite the fact that haemodynamic guided therapy is associated with reduced re-hospitalisation and mortality. Non-invasive methods of LV haemodynamic assessment are inaccurate. The Investigators have developed an accurate four-dimensional flow cardiac magnetic resonance (4D flow CMR) protocol which is non-invasive and addresses the issues with existing practices to evaluate HFpEF. This observational-analytical study aims to assess the utility of a non-invasive 4D flow CMR protocol for haemodynamic assessment of HFpEF, to generate clinical data to support future clinical trials, clinical translation and patient benefit. This research study will involve generating a precise haemodynamic model using invasive and non-invasive data of prospectively recruited patients. This model will be also optimised in clinical patients with arrhythmias. Also, observational data will be collected to test the model's prognostic value. ;
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