Information maximizing component analysis (IMCA) of combined end-diastolic and end-systolic shapes discriminated myocardial infarction patients from asymptomatic volunteers with an AUC of 99.99%, significantly outperforming linear discriminant analysis.
Observational (n=2,291)
Yes
Does information maximizing component analysis (IMCA) improve the characterization and discrimination of left ventricular remodeling in patients with myocardial infarction compared to linear discriminant analysis (LDA) and standard clinical indices?
Information maximizing component analysis (IMCA) of CMR images provides a highly sensitive, single continuous index for quantifying global left ventricular remodeling after myocardial infarction.
Absolute Event Rate: 99.99% vs 99.77%
p-value: p=<0.05
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 ).
Zhang et al. (Tue,) conducted a observational in Myocardial infarction (Left ventricular remodeling) (n=2,291). Information maximizing component analysis (IMCA) vs. Linear discriminant analysis (LDA) was evaluated on Area under the receiver-operating-characteristic curve (AUC) for discriminating MI patients from asymptomatic volunteers (p=<0.05). Information maximizing component analysis (IMCA) of combined end-diastolic and end-systolic shapes discriminated myocardial infarction patients from asymptomatic volunteers with an AUC of 99.99%, significantly outperforming linear discriminant analysis.