Speckle Tracking Echocardiography: Early Predictor of Diagnosis and Prognosis in Coronary Artery Disease

Abstract

Echocardiography represents a first level technique for the evaluation of coronary artery disease (CAD) which supports clinicians in the diagnostic and prognostic workup of these syndromes. However, visual estimation of wall motion abnormalities sometimes fails in detecting less clear or transient myocardial ischemia and in providing accurate differential diagnosis. Speckle tracking echocardiography (STE) is a widely available noninvasive tool that could easily and quickly provide additive information over basic echocardiography, since it is able to identify subtle myocardial damage and to localize ischemic territories in accordance to the coronary lesions, obtaining a clear visualization with a "polar map" useful for differential diagnosis and management. Therefore, it has increasingly been applied in acute and chronic coronary syndromes using rest and stress echocardiography, showing good results in terms of prediction of CAD, clinical outcome, left ventricular remodeling, presence, and quantification of new/residual ischemia. The aim of this review is to illustrate the current available evidence on STE usefulness for the assessment and follow-up of CAD, discussing the main findings on bidimensional and tridimensional strain parameters and their potential application in clinical practice.

Figure 1

Bull's eye polar map representation of regional global longitudinal strain according to specific territories of coronary artery vascularization on a 17-segments model. The “blue” segments represent the ischemic area. ANT: anterior; SEPT: septal; ANT_SEPT: anteroseptal region; CX: circumflex coronary artery; INF: inferior; LAD: left anterior descending coronary artery; LAT: lateral; POST: posterior; RCA: right coronary artery.

Figure 2

Potential integration of speckle tracking echocardiography as additive tool in diagnostic and follow-up algorithms of acute and chronic coronary syndromes. Large prospective studies are needed to validate this algorithm and investigate its impact on clinical outcome.