Multiparametric exercise stress cardiovascular magnetic resonance in the diagnosis of coronary artery disease: the EMPIRE trial
Thu‐Thao Le, Briana Ang, Jennifer Bryant, Chee Yang Chin, Khung Keong Yeo, Philip Wong, Kay Woon Ho, Jack Wei Chieh Tan, Phong Teck Lee, Calvin Chin, Stuart A. Cook
Abstract
Stress cardiovascular magnetic resonance (CMR) offers assessment of ventricular function, myocardial perfusion and viability in a single examination to detect coronary artery disease (CAD). We developed an in-scanner exercise stress CMR (ExCMR) protocol using supine cycle ergometer and aimed to examine the diagnostic value of a multiparametric approach in patients with suspected CAD, compared with invasive fractional flow reserve (FFR) as the reference gold standard. In this single-centre prospective study, patients who had symptoms of angina and at least one cardiovascular disease risk factor underwent both ExCMR and invasive angiography with FFR. Rest-based left ventricular function (ejection fraction, regional wall motion abnormalities), tissue characteristics and exercise stress-derived (perfusion defects, inducible regional wall motion abnormalities and peak exercise cardiac index percentile-rank) CMR parameters were evaluated in the study. In the 60 recruited patients with intermediate CAD risk, 50% had haemodynamically significant CAD based on FFR. Of all the CMR parameters assessed, the late gadolinium enhancement, stress-inducible regional wall motion abnormalities, perfusion defects and peak exercise cardiac index percentile-rank were independently associated with FFR-positive CAD. Indeed, this multiparametric approach offered the highest incremental diagnostic value compared to a clinical risk model (χ2 for the diagnosis of FFR-positive increased from 7.6 to 55.9; P < 0.001) and excellent performance [c-statistic area under the curve 0.97 (95% CI: 0.94–1.00)] in discriminating between FFR-normal and FFR-positive patients. The study demonstrates the clinical potential of using in-scanner multiparametric ExCMR to accurately diagnose CAD. Trial registration: ClinicalTrials.gov, NCT03217227, Registered 11 July 2017–Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03217227?id=NCT03217227&draw=2&rank=1&load=cart