Faculty Collaboration Database

Usefulness of two-dimensional strain echocardiography to predict segmental viability following acute myocardial infarction and optimization using bayesian logistic spatial modeling. Am J Cardiol 2009 Oct 15;104(8):1023-9

Date

10/06/2009

Pubmed ID

19801018

Pubmed Central ID

PMC2856659

DOI

10.1016/j.amjcard.2009.05.049

Scopus ID

2-s2.0-70349505973 (requires institutional sign-in at Scopus site)   10 Citations

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 List

Migrino RQ, Ahn KW, Brahmbhatt T, Harmann L, Jurva J, Pajewski NM

Author

Kwang Woo Ahn PhD Professor in the Institute for Health and Equity department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Bayes Theorem
Female
Humans
Male
Middle Aged
Myocardial Contraction
Myocardial Infarction
Predictive Value of Tests
Reproducibility of Results
Sensitivity and Specificity
Ultrasonography
Ventricular Function, Left