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Atlas-based quantification of cardiac remodeling due to myocardial infarction

Research output: Contribution to journalArticlepeer-review

Xingyu Zhang, Brett R. Cowan, David A Bluemke, J. Paul Finn, Carissa G. Fonseca, Alan H. Kadish, Daniel C Lee, Joao A. C Lima, Avan Suinesiaputra, Alistair A. Young, Pau Medrano-Gracia

Original languageEnglish
Article numbere110243
JournalPloS one
Volume9
Issue number10
Early online date31 Oct 2014
DOIs
Accepted/In press12 Sep 2014
E-pub ahead of print31 Oct 2014
Published2014

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Abstract

Myocardial infarction leads to changes in the geometry (remodeling) of the left ventricle (LV) of the heart. The degree and type of remodeling provides important diagnostic information for the therapeutic management of ischemic heart disease. In this paper, we present a novel analysis framework for characterizing remodeling after myocardial infarction, using LV shape descriptors derived from atlas-based shape models. Cardiac magnetic resonance images from 300 patients with myocardial infarction and 1991 asymptomatic volunteers were obtained from the Cardiac Atlas Project. Finite element models were customized to the spatio-temporal shape and function of each case using guide-point modeling. Principal component analysis was applied to the shape models to derive modes of shape variation across all cases. A logistic regression analysis was performed to determine the modes of shape variation most associated with myocardial infarction. Goodness of fit results obtained from end-diastolic and end-systolic shapes were compared against the traditional clinical indices of remodeling: end-diastolic volume, end-systolic volume and LV mass. The combination of end-diastolic and end-systolic shape parameter analysis achieved the lowest deviance, Akaike information criterion and Bayesian information criterion, and the highest area under the receiver operating characteristic curve. Therefore, our framework quantitatively characterized remodeling features associated with myocardial infarction, better than current measures. These features enable quantification of the amount of remodeling, the progression of disease over time, and the effect of treatments designed to reverse remodeling effects.

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