BACKGROUND: Early prediction of infarct size directs therapy in patients with acute myocardial infarction (AMI). Global strain by echocardiography describes myocardial deformation and correlates with infarct size. However, peak strain measures deformation at a single time point, whereas ischemia and necrosis influence deformation throughout the heart cycle. It was hypothesized that the measurement of myocardial deformation throughout the heart cycle by mean strain is a more comprehensive expression of myocardial deformation. The aim of this study was to assess the ability of mean strain to predict infarct size and to identify large infarctions at admission and after revascularization in patients with AMI. METHODS: Seventy-six patients with AMI were included. Echocardiographic measurements were performed at admission and after revascularization. Myocardial strain was calculated using speckle-tracking echocardiography. Infarct size was measured using contrast-enhanced magnetic resonance imaging ≥3 months after revascularization. RESULTS: There were significant correlations between infarct size and longitudinal global mean strain, longitudinal global strain, and left ventricular ejection fraction (P < .0001), both at admission and after revascularization. The correlations improved after revascularization. Longitudinal global mean strain had the best correlation with infarct size and the best ability to discriminate between different infarct size categories. At admission, a cutoff value of -7.6 had 89% sensitivity, 88% specificity, and an area under the receiver operating characteristic curve of 0.92 for the identification of large infarctions. Prediction of infarct size improved for all parameters after revascularization. CONCLUSIONS: Longitudinal global mean strain provides improved early prediction of infarct size in patients with AMI compared with longitudinal global strain and left ventricular ejection fraction.
BACKGROUND: Early prediction of infarct size directs therapy in patients with acute myocardial infarction (AMI). Global strain by echocardiography describes myocardial deformation and correlates with infarct size. However, peak strain measures deformation at a single time point, whereas ischemia and necrosis influence deformation throughout the heart cycle. It was hypothesized that the measurement of myocardial deformation throughout the heart cycle by mean strain is a more comprehensive expression of myocardial deformation. The aim of this study was to assess the ability of mean strain to predict infarct size and to identify large infarctions at admission and after revascularization in patients with AMI. METHODS: Seventy-six patients with AMI were included. Echocardiographic measurements were performed at admission and after revascularization. Myocardial strain was calculated using speckle-tracking echocardiography. Infarct size was measured using contrast-enhanced magnetic resonance imaging ≥3 months after revascularization. RESULTS: There were significant correlations between infarct size and longitudinal global mean strain, longitudinal global strain, and left ventricular ejection fraction (P < .0001), both at admission and after revascularization. The correlations improved after revascularization. Longitudinal global mean strain had the best correlation with infarct size and the best ability to discriminate between different infarct size categories. At admission, a cutoff value of -7.6 had 89% sensitivity, 88% specificity, and an area under the receiver operating characteristic curve of 0.92 for the identification of large infarctions. Prediction of infarct size improved for all parameters after revascularization. CONCLUSIONS: Longitudinal global mean strain provides improved early prediction of infarct size in patients with AMI compared with longitudinal global strain and left ventricular ejection fraction.
Authors: Martina Chantal de Knegt; A Fuchs; P Weeke; R Møgelvang; C Hassager; K F Kofoed Journal: Int J Cardiovasc Imaging Date: 2016-08-18 Impact factor: 2.357
Authors: Giuseppe Muscogiuri; Andrea Igoren Guaricci; Nicola Soldato; Riccardo Cau; Luca Saba; Paola Siena; Maria Grazia Tarsitano; Elisa Giannetta; Davide Sala; Paolo Sganzerla; Marco Gatti; Riccardo Faletti; Alberto Senatieri; Gregorio Chierchia; Gianluca Pontone; Paolo Marra; Mark G Rabbat; Sandro Sironi Journal: J Clin Med Date: 2022-09-26 Impact factor: 4.964