Abstract

Background: Speckle-tracking imaging is a novel method for assessing left ventricular (LV) function and ischemic changes. The aim of this study was to predict the presence of coronary artery disease by longitudinal 2D strain analysis using speckle tracking echocardiography in patients with stable or unstable angina with no regional wall motion abnormality at rest. Objectives: Objective of this study is to predict the presence of significant CAD in a patient with no regional wall motion abnormality by longitudinal 2D strain analysis using speckle tracking echocardiography. Methods: This cross-sectional study included a total 66 patients (mean age, 51.92±8.9 years) with suspected CAD without RWMA on resting echocardiography who underwent coronary angiography. Longitudinal 2D strain analysis by STE was performed in all patients before coronary angiography. Global and segmental peak systolic longitudinal strain (PSLS) were recorded & computed by offline dedicated software semi-automatically on bull’s-eye report. The patients were divided into two groups according to the coronary angiographic findings; group- I: significant CAD on coronary angiogram (n=35), group-II: normal coronaries on CAG (n=31).All the baseline characteristics and outcome were then compared between the two groups. Results: PSLSs of all left ventricular segments were obtained successfully in 66 patients. PSLS (both global and segmental) was significantly decreased in patients with significant CAD on CAG group. Receiver operating characteristic (ROC) curve analysis demonstrated that global PSLSs could effectively detect patients with CAD (area under ROC curve = 0.877, 95% CI=0.749–0.960). According to ROC curve analysis, -18.77% appeared to be a good cutoff value for predicting those with significant CAD (specificity 77.4% and sensitivity 82.9%). Conclusion: Global and segmental PSLS using speckle tracking echocardiography at rest was significantly lower in patients with CAD without RWMA, and might be useful for identifying patients with a significant CAD with good degree of sensitivity and specificity.

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