The Left Atrial Area Derived Cardiovascular Magnetic Resonance Left Ventricular Filling Pressure Equation Shows Superiority over Integrated Echocardiography

Background and objectives: Evaluating left ventricular filling pressure (LVFP) plays a crucial role in diagnosing and managing heart failure (HF). While traditional assessment methods involve multi-parametric transthoracic echocardiography (TTE) or right heart catheterisation (RHC), cardiovascular magnetic resonance (CMR) has emerged as a valuable diagnostic tool in HF. This study aimed to assess a simple CMR-derived model to estimate pulmonary capillary wedge pressure (PCWP) in a cohort of patients with suspected or proven heart failure and to investigate its performance in risk-stratifying patients. Materials and methods: A total of 835 patients with breathlessness were evaluated using RHC and CMR and split into derivation (85%) and validation cohorts (15%). Uni-variate and multi-variate linear regression analyses were used to derive a model for PCWP estimation using CMR. The model's performance was evaluated by comparing CMR-derived PCWP with PCWP obtained from RHC. Results: A CMR-derived PCWP incorporating left ventricular mass and the left atrial area (LAA) demonstrated good diagnostic accuracy. The model correctly reclassified 66% of participants whose TTE was 'indeterminate' or 'incorrect' in identifying raised filling pressures. On survival analysis, the CMR-derived PCWP model was predictive for mortality (HR 1.15, 95% CI 1.04-1.28, p = 0.005), which was not the case for PCWP obtained using RHC or TTE. Conclusions: The simplified CMR-derived PCWP model provides an accurate and practical tool for estimating PCWP in patients with suspected or proven heart failure. Its predictive value for mortality suggests the ability to play a valuable adjunctive role in echocardiography, especially in cases with unclear echocardiographic assessment.

Automated summary

This study aimed to evaluate a simple CMR-derived model for estimating pulmonary capillary wedge pressure (PCWP) in patients with heart failure. The results showed that the model had good diagnostic accuracy and predictive value for mortality.