Orthogonal decomposition of left ventricular remodeling in myocardial infarction

• Published in: Gigascience Vol. 6; no. 3; pp. 1 - 15
• Main Authors: Zhang, Xingyu, Medrano-Gracia, Pau, Ambale-Venkatesh, Bharath, Bluemke, David A., Cowan, Brett R, Finn, J. Paul, Kadish, Alan H., Lee, Daniel C., Lima, Joao A. C., Young, Alistair A., Suinesiaputra, Avan
• Format: Journal Article
• Language: English
• Published: United States Oxford University Press 01.03.2017
• Subjects: Adult; Aged; Aged, 80 and over; Algorithms; Asymptomatic; Asymptomatic Diseases; Cardiovascular diseases; Computer Simulation; Decoupling; Female; Heart attacks; Humans; Magnetic resonance imaging; Male; Middle Aged; Models, Cardiovascular; Models, Statistical; Myocardial infarction; Myocardial Infarction - diagnosis; Myocardial Infarction - pathology; Myocardial Infarction - physiopathology; Patients; Principal components analysis; Regression analysis; Reproducibility of Results; Risk Factors; ROC Curve; Shape; Stroke Volume; Ventricle; Ventricular Function, Left; Ventricular Remodeling; Cardiac remodeling; Partial least squares regression; Magnetic resonance imaging; Shape components
• ISSN: 2047-217X; 2047-217X
• DOI: 10.1093/gigascience/gix005

Left ventricular size and shape are important for quantifying cardiac remodeling in response to cardiovascular disease. Geometric remodeling indices have been shown to have prognostic value in predicting adverse events in the clinical literature, but these often describe interrelated shape changes. We developed a novel method for deriving orthogonal remodeling components directly from any (moderately independent) set of clinical remodeling indices. Results: Six clinical remodeling indices (end-diastolic volume index, sphericity, relative wall thickness, ejection fraction, apical conicity, and longitudinal shortening) were evaluated using cardiac magnetic resonance images of 300 patients with myocardial infarction, and 1991 asymptomatic subjects, obtained from the Cardiac Atlas Project. Partial least squares (PLS) regression of left ventricular shape models resulted in remodeling components that were optimally associated with each remodeling index. A Gram–Schmidt orthogonalization process, by which remodeling components were successively removed from the shape space in the order of shape variance explained, resulted in a set of orthonormal remodeling components. Remodeling scores could then be calculated that quantify the amount of each remodeling component present in each case. A one-factor PLS regression led to more decoupling between scores from the different remodeling components across the entire cohort, and zero correlation between clinical indices and subsequent scores. Conclusions: The PLS orthogonal remodeling components had similar power to describe differences between myocardial infarction patients and asymptomatic subjects as principal component analysis, but were better associated with well-understood clinical indices of cardiac remodeling. The data and analyses are available from www.cardiacatlas.org.