Incremental prognostic value of aortic stiffness in addition to myocardial ischemia by cardiac magnetic resonance imaging

Abstract

© 2020 The Author(s). Background: Aortic stiffness is an independent predictor of cardiovascular (CV) events and mortality. However, no data exists for the prognosis of combined aortic stiffness and myocardial ischemia. Using cardiac magnetic resonance (CMR) imaging, we assessed the association of aortic stiffness by pulse wave velocity (PWV), myocardial ischemia, and CV events in patients with known or suspected coronary artery disease (CAD). Methods: Velocity-encoded CMR was performed in 520 patients who had undergone adenosine stress CMR. The PWV was determined between the mid-ascending and mid-descending thoracic aorta. Patients were divided into 4 groups by PWV (higher or lower PWV) and myocardial ischemia (positive or negative ischemia). Combined CV events including mortality, acute coronary syndrome, heart failure, coronary revascularization, and stroke were analyzed among the 4 groups. Results: The median follow-up period was 46.5 months, and the median PWV was 10.54 m/sec. Myocardial ischemia was positive in 199 patients (38.3%). The group with a higher PWV and positive ischemia had the most CV events (hazard ratio 8.94, p < 0.001). The group with a higher PWV and negative ischemia also was significantly associated with CV events (HR 2.19, p = 0.02). Groups with a lower PWV-positive ischemia and a higher PWV-negative ischemia showed no difference in terms of CV events (HR 0.60, p = 0.08). Patients with myocardial ischemia who had higher PWV demonstrated significantly higher event rates than those who had lower PWV (HR 2.41, p < 0.001). Multivariate analysis demonstrated that myocardial ischemia and PWV were independent predictors for combined CV events (HR 2.71, p < 0.001 and HR 2.42, p < 0.001, respectively). Conclusions: Stress perfusion CMR provided prognostic utility in patients with known or suspected CAD. Adding aortic stiffness to stress perfusion CMR could improve risk assessment and prediction for future CV events.