Unmasking systolic impairment in HFpEF by cardiovascular magnetic resonance derived hemodynamic force assessment: insights from the HFpEF stress trial

Abstract

Abstract Background The diagnosis of heart failure with preserved ejection fraction (HFpEF) remains challenging. Exercise-stress testing is recommended in case of uncertainty; however, this approach is time-consuming and costly. Since preserved EF does not represent normal systolic function, we evaluated cardiovascular magnetic resonance (CMR) comprehensive cardiac hemodynamic forces (HDF) analyses for an in-depth characterisation of cardiac function at rest. Methods The HFpEF Stress Trial (DZHK-17) prospectively recruited 75 patients with exertional dyspnea, preserved EF (≥50%) and signs of diastolic dysfunction (E/e' ≥8) on echocardiography. Patients underwent right heart catheterisation, echocardiography and CMR. 68 patients entered the final study cohort (HFpEF n=34 and non-cardiac dyspnea n=34 according to pulmonary capillary wedge pressure (PCWP)). HDF assessment included left ventricular (LV) longitudinal, systolic peak and impulse, systolic/diastolic transition, E-wave deceleration as well as A-wave acceleration forces. Two patients were lost to 24 months follow-up evaluating cardiovascular mortality and hospitalisation (CVH). Results HDF assessment revealed impairment of LV longitudinal force in HFpEF (15.8 vs. 18.3, p=0.035) attributable to impairment of systolic peak (38.6 vs 51.6, p=0.003) and impulse (20.8 vs. 24.5, p=0.009) forces as well as late diastolic filling (−3.8 vs −5.4, p=0.029). Impairment of early diastolic filling could be observed in HFpEF patients identified at rest only but not stress (7.7 vs. 9.9, p=0.004). Impaired systolic peak was associated to CVH (HR 0.95, p=0.016) and superior for CVH prediction compared to LV global longitudinal strain (AUC 0.76 vs. 0.61, p=0.048). Conclusions Assessment of HDF reveals impairment of LV systolic and diastolic function in HFpEF. The value of systolic HDF assessment exceeded that of conventional deformation imaging for CVH prediction. Funding Acknowledgement Type of funding sources: Public grant(s) – National budget only. Main funding source(s): German Centre for Cardiovascular Research