Predictive value of global and territorial longitudinal strain imaging in detecting significant coronary artery disease in patients with myocardial infarction without persistent ST-segment elevation.

Abstract

Two-dimensional (2D) speckle-tracking echocardiographic (STE) imaging is frequently performed in the assessment of cardiovascular diseases. We aim to investigate the role of the global and territorial longitudinal strain (GLS and TLS) values assessed via 2D STE imaging to detect significant coronary artery disease (CAD) in non-ST-segment elevation myocardial infarction (NSTEMI) patients without wall-motion abnormalities. This study enrolled 150 patients with the diagnosis of NSTEMI. Patients who had typical chest pain with unstable angina characteristics within the last 24hours were 18-80years of age and had a typical rise and/or fall of cardiac biomarkers were included. Myocardial functions were assessed via myocardial deformation analyses of 2D STE images. The mean age of the CAD group was 52.91±9.11, vs 50.31±8.32 in the control group. In the CAD group, 56 patients were male (65%), whereas 21 were male (60%) in control group. GLS and TLS assessments demonstrated a statistically significant difference between CAD and control groups, with GLS values of -16.27±1.91 and -18.74±1.93 (P<0.001), TLS-LAD values of -15.67±1.83 and -18.54±1.97 (P<0.001), TLS-RCA values of -17.04±1.81 and -19.20±1.86 (P<0.001), and TLS-Cx values of -17.40±2.08 and -18.34±2.18 (P=0.028), respectively. Correlation analyses revealed that as high-sensitivity troponin (hsTnT) values increased, GLS decreased significantly, and further, an increase in severity of CAD resulted in decreased TLS-LAD, -CX and -RCA (TLS-LAD: P<0.001, r=-0.743; TLS-CX: P<0.001, r=-0.449; TLS-RCA: P<0.001, r=-0.737). Multivariate analyses indicated that GLS and GRACE ACS risk scores are independent predictors of CAD in patients with NSTEMI (GLS: OR=0.514, P<0.001; GRACE score: OR=0.938, P=0.007). Global longitudinal strain (GLS) assessed with 2D STE is a promising, easy to perform and quick imaging method to predict CAD in patients with NSTEMI.