AI-Enhanced CV MRI Predicts Heart Failure Risk, Study Finds Fivefold Increased Risk with High Heart Pressure
UK: Research published on August 12 in the journal European Society of Cardiology Heart Failure reveals that combining cardiovascular MRI with an AI model can effectively predict heart failure (HF) risk in the general population by estimating heart pressure.
The study, led by Ross Thomson from Queen Mary University of London and senior author Pankaj Garg, MD, from the University of East Anglia in Norwich, found that individuals with elevated heart pressure, as measured by MRI, faced a fivefold increased risk of developing heart failure within six years.
Garg highlighted in a statement from the University of East Anglia that a key finding of the study is the ability of MRI-derived pressure measurements to accurately predict the likelihood of developing heart failure.
The group explained that the rising prevalence of HF is partly attributed to an aging population. A common indicator of this condition is elevated left ventricular filling pressure, which is typically assessed through pulmonary capillary wedge pressure (PCWP) via cardiac catheterization. Cardiovascular magnetic resonance (CMR) imaging holds potential for non-invasive estimation of PCWP. However, its prognostic value at the population level is still uncertain. Additionally, the connection between CMR-modelled PCWP and well-established cardiovascular risk factors has yet to be thoroughly defined.
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