Using MRI scans to detect heart failure could change how the condition is diagnosed, according to research from the University of East Anglia and the University of Sheffield.
Until now, the best way of diagnosing heart failure has been an invasive assessment, but it does carry risks for patients. Non-invasive echocardiogram, based on ultrasound, is usually used instead, but is wrong in up to 50% of cases.
A recent study, published in European Heart Journal, shows how magnetic resonance imaging (MRI) is superior to echocardiography for diagnosing heart failure, as well as being a powerful tool to predict patient outcomes, including death.
Lead researcher Dr Pankaj Garg, from the University of East Anglia’s Norwich Medical School, said: “Heart failure is a dreadful condition resulting from rising pressures inside the heart. The best method of diagnosis is by invasive assessment, which is not preferred as it has risks.
“An echocardiogram, or ultrasound of the heart, is usually used to predict the pressure in the heart. However, it is not very accurate. We wanted to find out if MRI scans might offer a better alternative.”
The research team studied 835 patients who received an invasive assessment and a heart MRI on the same day from the ASPIRE registry – a database of patients assessed at the Sheffield Pulmonary Vascular Disease Unit.
Garg said: “We investigated if heart MRI can predict invasively measured left ventricular filling pressure. Once we had identified the key parameters – left atrial volume and left ventricular mass – we created an equation to non-invasively derive the pressure in the heart. This simple equation can be applied in any centre around the world that does heart MRI.
“We also tested the equation in a separate group of patients and demonstrated its reliability. We showed that heart MRI is superior to echocardiography in predicting pressure inside the heart: almost 71% of patients who had wrongly measured pressures by echocardiography had correct pressures by heart MRI.”
These findings would reduce the need for invasive assessment, he said. The method was not only cost-effective but also reduced risks to patients, as a heart MRI scan is a completely non-invasive test.
Senior author Dr Andy Swift, from University of Sheffield and a consultant radiologist, said: “This simple diagnostic equation is very clinically useful and will help doctors predict the pressure in the heart and diagnose heart failure. Testing the use of the equation at other hospitals is the next step to assess the benefit to patients and the reduced need for invasive tests.”
Study details
Cardiac magnetic resonance identifies raised left ventricular filling pressure: prognostic implications.
Pankaj Garg, Rebecca Gosling, Peter Swoboda, Rachel Jones, Alexander Rothman, Jim M Wild, David Kiely, Robin Condliffe, Samer Alabed, Andrew Swift.
Published in European Heart Journal on 4 May 2022
Abstract
Aims
Non-invasive imaging is routinely used to estimate left ventricular (LV) filling pressure (LVFP) in heart failure (HF). Cardiovascular magnetic resonance (CMR) is emerging as an important imaging tool for sub-phenotyping HF. However, currently, LVFP cannot be estimated from CMR. This study sought to investigate (i) if CMR can estimate LVFP in patients with suspected HF and (ii) if CMR-modelled LVFP has prognostic power.
Methods and results
Suspected HF patients underwent right heart catheterisation (RHC), CMR and transthoracic echocardiography (TTE) (validation cohort only) within 24 h of each other. Right heart catheterisation measured pulmonary capillary wedge pressure (PCWP) was used as a reference for LVFP. At follow-up, death was considered as the primary endpoint. We enrolled 835 patients (mean age: 65 ± 13 years, 40% male). In the derivation cohort (n = 708, 85%), two CMR metrics were associated with RHC PCWP:LV mass and left atrial volume. When applied to the validation cohort (n = 127, 15%), the correlation coefficient between RHC PCWP and CMR-modelled PCWP was 0.55 (95% confidence interval: 0.41–0.66, P < 0.0001). Cardiovascular magnetic resonance-modelled PCWP was superior to TTE in classifying patients as normal or raised filling pressures (76 vs. 25%). Cardiovascular magnetic resonance-modelled PCWP was associated with an increased risk of death (hazard ratio: 1.77, P < 0.001). At Kaplan–Meier analysis, CMR-modelled PCWP was comparable to RHC PCWP (≥15 mmHg) to predict survival at 7-year follow-up (35 vs. 37%, χ2 = 0.41, P = 0.52).
Conclusion
A physiological CMR model can estimate LVFP in patients with suspected HF. In addition, CMR-modelled LVFP has a prognostic role.
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