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Atlas-based quantification of cardiac remodeling due to myocardial infarction.

Zhang X, Cowan BR, Bluemke DA, Finn JP, Fonseca CG, Kadish AH, Lee DC, Lima JA, Suinesiaputra A, Young AA, Medrano-Gracia P - PLoS ONE (2014)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand.

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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ROC curve for the logistic regression classification for each model.
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pone-0110243-g007: ROC curve for the logistic regression classification for each model.

Mentions: The goodness of fit was compared between the five models with the indices of Deviance, AIC, BIC and AUC of each model, which are listed in Table 7. Overall, all the PCA mode models as well as the mass-volume model showed good performance. The ED&ES PCA model achieved the best performance in terms of Deviance, AIC, SC, and AUC values, followed closely by the ES PCA model and the ED PCA model. All PCA models better characterized patients from non-patients than traditional mass and volume measures. The ROC curves are shown in Fig. 7.


Atlas-based quantification of cardiac remodeling due to myocardial infarction.

Zhang X, Cowan BR, Bluemke DA, Finn JP, Fonseca CG, Kadish AH, Lee DC, Lima JA, Suinesiaputra A, Young AA, Medrano-Gracia P - PLoS ONE (2014)

ROC curve for the logistic regression classification for each model.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4215861&req=5

pone-0110243-g007: ROC curve for the logistic regression classification for each model.
Mentions: The goodness of fit was compared between the five models with the indices of Deviance, AIC, BIC and AUC of each model, which are listed in Table 7. Overall, all the PCA mode models as well as the mass-volume model showed good performance. The ED&ES PCA model achieved the best performance in terms of Deviance, AIC, SC, and AUC values, followed closely by the ES PCA model and the ED PCA model. All PCA models better characterized patients from non-patients than traditional mass and volume measures. The ROC curves are shown in Fig. 7.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand.

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.

Show MeSH
Related in: MedlinePlus