Research article summary (published 13 Oct 2009):

Usefulness of two-dimensional strain echocardiography to predict segmental viability following acute myocardial infarction and optimization using bayesian logistic spatial modeling.

Full Abstract

Viability assessment after acute myocardial infarction (MI) is important to guide revascularization. Two-dimensional strain echocardiography was shown to predict viability, but the method assumed that strain in each segment is independent of contiguous segments. The aim of this study was to test the hypotheses that segmental strain after MI is spatially correlated and that using a Bayesian approach improves the prediction of nonviable myocardium. Twenty-one subjects (mean age 58 +/- 12 years, 6 women) with MI >or=2 weeks before recruitment underwent 2-dimensional strain echocardiography and late gadolinium enhancement (LGE) cardiac magnetic resonance imaging within 48 hours of each other. The heart was divided into 16 segments, and longitudinal, radial, and circumferential strains were measured using software. Using similar segmentation, LGE was measured, and segments with >50% LGE were considered nonviable. Spearman's analyses were used to assess the spatial correlation of strain, and receiver-operating characteristic curve analysis was used to determine the prediction of nonviable myocardium without and with a Bayesian logistic spatial conditionally autoregressive (CAR) model. There was a significant spatial correlation in strain and LGE among segments, especially in the apex. Longitudinal strain was the best predictor of nonviability and was impaired in nonviable myocardium (-12.1 +/- 0.6%, -8.0 +/- 0.6%, and -4.6 +/- 1% for 0%, 1% to 50%, and >50% LGE, respectively, p <0.001). Use of the CAR model improved the area under the curve for the detection of nonviable myocardium (from 0.7 to 0.94). A CAR probabilistic score of 0.17 had 88% sensitivity and 86% specificity for detecting nonviable myocardium. In conclusion, longitudinal strain from 2-dimensional strain echocardiography can predict myocardial viability after MI, and exploiting spatial correlations in segmental strain using Bayesian CAR modeling enhances the ability of 2-dimensional strain to predict nonviable myocardium.

Author information

Author/s: Migrino, Raymond Q (RQ); Ahn, Kwang Woo (KW); Brahmbhatt, Tejas (T); Harmann, Leanne (L); Jurva, Jason (J); Pajewski, Nicholas M (NM);

Affiliation: Cardiovascular Division, Medical College of Wisconsin, Milwaukee, Wisconsin, USA. rmigrino(-atsign-)mcw.edu

Grants: M01-RR00058 (Agency:NCRR NIH HHS) ; T32 HL072757 (Agency:NHLBI NIH HHS)

Journal and publication information

Publication Type: Comparative Study; Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't

Journal: The American journal of cardiology (Am J Cardiol), published in United States. (Language: eng)

Reference: 2009-Oct; vol 104 (issue 8) : pp 1023-9

Dates: Created 2009/10/05; Completed 2009/10/20;

PMID: 19801018, status: MEDLINE (last retrieval date: 10/20/2009, IMS Date: )

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MESH Headings shown below.

Bayes Theorem Female Humans Male Middle Aged Myocardial Contraction - physiology

Myocardial Contraction - physiology Myocardial Infarction - mortality; physiopathology; ultrasonography Predictive Value of Tests Reproducibility of Results Sensitivity and Specificity Ventricular Function, Left - physiology

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