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BACKGROUND: In the conventional paradigm of the progression of left ventricular hypertrophy, a thick-walled left ventricle (LV) ultimately transitions to a dilated cardiomyopathy. There are scant data in humans demonstrating whether this transition occurs commonly without an interval myocardial infarction. METHODS AND RESULTS: Participants (n=1282) from the Dallas Heart Study underwent serial cardiac magnetic resonance ≈7 years apart. Those with interval cardiovascular events and a dilated LV (increased LV end-diastolic volume [EDV] indexed to body surface area) at baseline were excluded. Multivariable linear regression models tested the association of concentric hypertrophy (increased LV mass and LV mass/volume0.67) with change in LVEDV. The study cohort had a median age of 44 years, 57% women, 43% black, and 11% (n=142) baseline concentric hypertrophy. The change in LVEDV in those with versus without concentric hypertrophy was 1 mL (-9 to 12) versus -2 mL (-11 to 7), respectively, P<0.01. In multivariable linear regression models, concentric hypertrophy was associated with larger follow-up LVEDV (P≤0.01). The progression to a dilated LV was uncommon (2%, n=25). CONCLUSIONS: In the absence of interval myocardial infarction, concentric hypertrophy was associated with a small, but signifcantly greater, increase in LVEDV after 7-year follow-up. However, the degree of LV enlargement was minimal, and few participants developed a dilated LV. These data suggest that if concentric hypertrophy does progress to a dilated cardiomyopathy, such a transition would occur over a much longer timeframe (eg, decades) and may be less common than previously thought. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifer: NCT00344903. [ABSTRACT FROM AUTHOR]

The article presents a study which introduces the 4-tiered classification of left ventricular hypertrophy (LVH) to monitor the LV concentricity and LV end-diastolic volume (LVEDV). It states that the study was made on 2803 subjects of the Dallas Heart Study, wherein they underwent cardiac magnetic resonance imaging (MRI). It reveals that subjects with eccentric LVH can be classified into two groups such as with dilated hypertrophy and the large group with no thick of dilated hypertrophy.

To elucidate mechanisms by which left ventricular (LV) hypertrophy (LVH) increases the risk of atherosclerotic heart disease, we sought to determine whether LVH is independently associated with coronary artery calcium (CAC) and serum C-reactive protein (CRP) levels in the general population. The Dallas Heart Study is a population-based sample in which 2633 individuals underwent cardiac MRI to measure LV structure, electron beam CT to measure CAC, and measurement of plasma CRP. We used univariate and multivariable analyses to determine whether LV mass and markers of concentric LV hypertrophy or dilation were associated with CAC and CRP. Increasing quartiles of LV mass indexed to fat-free mass, LV wall thickness, and concentricity, but not LV volume, were associated with CAC in both men and women (P<0.001). After adjustment for traditional cardiovascular risk factors and statin use, LV wall thickness and concentricity remained associated with CAC in linear regression (P<0.001 for each). These associations were particularly robust in blacks. LV wall thickness and concentricity were also associated with elevated CRP levels (P=0.001 for both) in gender-stratified univariate analyses, although these associations did not persist in multivariable analysis. In conclusion, concentric LVH is an independent risk factor for subclinical atherosclerosis. LVH is also associated with an inflammatory state as reflected in elevated CRP levels, although this relationship appears to be mediated by comorbid conditions. These data likely explain in part why individuals with LVH are at increased risk for myocardial infarction. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text. Background: Coronary artery calcium scoring only represents a small fraction of all information available in noncontrast cardiac computed tomography (CAC-CT). We hypothesized that an automated pipeline using radiomics and machine learning could identify phenotypic information about high-risk left ventricular hypertrophy (LVH) embedded in CAC-CT. Methods: This was a retrospective analysis of 1982 participants from the DHS (Dallas Heart Study) who underwent CAC-CT and cardiac magnetic resonance. Two hundred twenty-four participants with high-risk LVH were identified by cardiac magnetic resonance. We developed an automated adaptive atlas algorithm to segment the left ventricle on CAC-CT, extracting 107 radiomics features from the volume of interest. Four logistic regression models using different feature selection methods were built to predict high-risk LVH based on CAC-CT radiomics, sex, height, and body surface area in a random training subset of 1587 participants. Results: The respective areas under the receiver operating characteristics curves for the cluster-based model, the logistic regression model after exclusion of highly correlated features, and the penalized logistic regression models using least absolute shrinkage and selection operators with minimum or one SE λ values were 0.74 (95% CI, 0.67–0.82), 0.74 (95% CI, 0.67–0.81), 0.76 (95% CI, 0.69–0.83), and 0.73 (95% CI, 0.66–0.80) for detecting high-risk LVH in a distinct validation subset of 395 participants. Conclusions: Ventricular segmentation, radiomics features extraction, and machine learning can be used in a pipeline to automatically detect high-risk phenotypes of LVH in participants undergoing CAC-CT, without the need for additional imaging or radiation exposure. Registration: URL http://www.clinicaltrials.gov. Unique identifier: NCT00344903. [ABSTRACT FROM AUTHOR]