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Information maximizing component analysis of left ventricular remodeling due to myocardial infarction

BACKGROUND: Although adverse left ventricular shape changes (remodeling) after myocardial infarction (MI) are predictive of morbidity and mortality, current clinical assessment is limited to simple mass and volume measures, or dimension ratios such as length to width ratio. We hypothesized that info...

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Autores principales: Zhang, Xingyu, Ambale-Venkatesh, Bharath, Bluemke, David A., Cowan, Brett R., Finn, J. Paul, Kadish, Alan H., Lee, Daniel C., Lima, Joao A. C., Hundley, William G., Suinesiaputra, Avan, Young, Alistair A., Medrano-Gracia, Pau
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4632345/
https://www.ncbi.nlm.nih.gov/pubmed/26531126
http://dx.doi.org/10.1186/s12967-015-0709-4
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author Zhang, Xingyu
Ambale-Venkatesh, Bharath
Bluemke, David A.
Cowan, Brett R.
Finn, J. Paul
Kadish, Alan H.
Lee, Daniel C.
Lima, Joao A. C.
Hundley, William G.
Suinesiaputra, Avan
Young, Alistair A.
Medrano-Gracia, Pau
author_facet Zhang, Xingyu
Ambale-Venkatesh, Bharath
Bluemke, David A.
Cowan, Brett R.
Finn, J. Paul
Kadish, Alan H.
Lee, Daniel C.
Lima, Joao A. C.
Hundley, William G.
Suinesiaputra, Avan
Young, Alistair A.
Medrano-Gracia, Pau
author_sort Zhang, Xingyu
collection PubMed
description BACKGROUND: Although adverse left ventricular shape changes (remodeling) after myocardial infarction (MI) are predictive of morbidity and mortality, current clinical assessment is limited to simple mass and volume measures, or dimension ratios such as length to width ratio. We hypothesized that information maximizing component analysis (IMCA), a supervised feature extraction method, can provide more efficient and sensitive indices of overall remodeling. METHODS: IMCA was compared to linear discriminant analysis (LDA), both supervised methods, to extract the most discriminatory global shape changes associated with remodeling after MI. Finite element shape models from 300 patients with myocardial infarction from the DETERMINE study (age 31–86, mean age 63, 20 % women) were compared with 1991 asymptomatic cases from the MESA study (age 44–84, mean age 62, 52 % women) available from the Cardiac Atlas Project. IMCA and LDA were each used to identify a single mode of global remodeling best discriminating the two groups. Logistic regression was employed to determine the association between the remodeling index and MI. Goodness-of-fit results were compared against a baseline logistic model comprising standard clinical indices. RESULTS: A single IMCA mode simultaneously describing end-diastolic and end-systolic shapes achieved best results (lowest Deviance, Akaike information criterion and Bayesian information criterion, and the largest area under the receiver-operating-characteristic curve). This mode provided a continuous scale where remodeling can be quantified and visualized, showing that MI patients tend to present larger size and more spherical shape, more bulging of the apex, and thinner wall thickness. CONCLUSIONS: IMCA enables better characterization of global remodeling than LDA, and can be used to quantify progression of disease and the effect of treatment. These data and results are available from the Cardiac Atlas Project (http://www.cardiacatlas.org).
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spelling pubmed-46323452015-11-05 Information maximizing component analysis of left ventricular remodeling due to myocardial infarction Zhang, Xingyu Ambale-Venkatesh, Bharath Bluemke, David A. Cowan, Brett R. Finn, J. Paul Kadish, Alan H. Lee, Daniel C. Lima, Joao A. C. Hundley, William G. Suinesiaputra, Avan Young, Alistair A. Medrano-Gracia, Pau J Transl Med Research BACKGROUND: Although adverse left ventricular shape changes (remodeling) after myocardial infarction (MI) are predictive of morbidity and mortality, current clinical assessment is limited to simple mass and volume measures, or dimension ratios such as length to width ratio. We hypothesized that information maximizing component analysis (IMCA), a supervised feature extraction method, can provide more efficient and sensitive indices of overall remodeling. METHODS: IMCA was compared to linear discriminant analysis (LDA), both supervised methods, to extract the most discriminatory global shape changes associated with remodeling after MI. Finite element shape models from 300 patients with myocardial infarction from the DETERMINE study (age 31–86, mean age 63, 20 % women) were compared with 1991 asymptomatic cases from the MESA study (age 44–84, mean age 62, 52 % women) available from the Cardiac Atlas Project. IMCA and LDA were each used to identify a single mode of global remodeling best discriminating the two groups. Logistic regression was employed to determine the association between the remodeling index and MI. Goodness-of-fit results were compared against a baseline logistic model comprising standard clinical indices. RESULTS: A single IMCA mode simultaneously describing end-diastolic and end-systolic shapes achieved best results (lowest Deviance, Akaike information criterion and Bayesian information criterion, and the largest area under the receiver-operating-characteristic curve). This mode provided a continuous scale where remodeling can be quantified and visualized, showing that MI patients tend to present larger size and more spherical shape, more bulging of the apex, and thinner wall thickness. CONCLUSIONS: IMCA enables better characterization of global remodeling than LDA, and can be used to quantify progression of disease and the effect of treatment. These data and results are available from the Cardiac Atlas Project (http://www.cardiacatlas.org). BioMed Central 2015-11-03 /pmc/articles/PMC4632345/ /pubmed/26531126 http://dx.doi.org/10.1186/s12967-015-0709-4 Text en © Zhang et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhang, Xingyu
Ambale-Venkatesh, Bharath
Bluemke, David A.
Cowan, Brett R.
Finn, J. Paul
Kadish, Alan H.
Lee, Daniel C.
Lima, Joao A. C.
Hundley, William G.
Suinesiaputra, Avan
Young, Alistair A.
Medrano-Gracia, Pau
Information maximizing component analysis of left ventricular remodeling due to myocardial infarction
title Information maximizing component analysis of left ventricular remodeling due to myocardial infarction
title_full Information maximizing component analysis of left ventricular remodeling due to myocardial infarction
title_fullStr Information maximizing component analysis of left ventricular remodeling due to myocardial infarction
title_full_unstemmed Information maximizing component analysis of left ventricular remodeling due to myocardial infarction
title_short Information maximizing component analysis of left ventricular remodeling due to myocardial infarction
title_sort information maximizing component analysis of left ventricular remodeling due to myocardial infarction
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4632345/
https://www.ncbi.nlm.nih.gov/pubmed/26531126
http://dx.doi.org/10.1186/s12967-015-0709-4
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