Progression of Coronary Artery Calcium and Incident Heart Failure: The Multi-Ethnic Study of Atherosclerosis.

BackgroundAlthough the association between coronary artery calcium (CAC) and future heart failure (HF) has been shown previously, the value of CAC progression in the prediction of HF has not been investigated. In this study, we investigated the association of CAC progression with subclinical left ventricular (LV) dysfunction and incident HF in the Multi-Ethnic Study of Atherosclerosis.Methods and resultsThe Multi-Ethnic Study of Atherosclerosis is a population-based study consisting of 6814 men and women aged 45 to 84, free of overt cardiovascular disease at enrollment, who were recruited from 4 ethnicities. We included 5644 Multi-Ethnic Study of Atherosclerosis participants who had baseline and follow-up cardiac computed tomography and were free of HF and coronary heart disease before the second cardiac computed tomography. Mean (±SD) age was 61.7±10.2 years and 47.2% were male. The Cox proportional hazard models and multivariable linear regression models were deployed to determine the association of CAC progression with incident HF and subclinical LV dysfunction, respectively. Over a median follow-up of 9.6 (interquartile range: 8.8-10.6) years, 182 participants developed incident HF. CAC progression of 10 units per year was associated with 3% of increased risk of HF independent of overt coronary heart disease (P=0.008). In 2818 participants with available cardiac magnetic resonance images, CAC progression was associated with increased LV end diastolic volume (β=0.16; P=0.03) and LV end systolic volume (β=0.12; P=0.006) after excluding participants with any coronary heart disease.ConclusionsCAC progression was associated with incident HF and modestly increased LV end diastolic volume and LV end systolic volume at follow-up exam independent of overt coronary heart disease

Orthogonal Decomposition of Left Ventricular Remodeling in Myocardial Infarction

BACKGROUND: 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

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 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)

Subclinical myocardial disease by cardiac magnetic resonance imaging and spectroscopy in healthy HIV/Hepatitis C virus-coinfected persons.

Objective The contribution of hepatitis C virus (HCV) infection to the risk of heart failure in human immunodeficiency virus (HIV)-coinfected persons is unknown. The objective was to characterize cardiac function and morphology in HIV-treated coinfected persons. Methods In a cross-sectional study, HIV-infected patients virologically suppressed on antiretroviral therapy without known cardiovascular disease or diabetes mellitus underwent cardiac magnetic resonance imaging and spectroscopy for measures of cardiac function, myocardial fibrosis, and steatosis. Results The study included 18 male patients with a median age of 44 years. Of these, 10 had untreated HCV coinfection and eight had HIV monoinfection. Global systolic and diastolic function in the cohort were normal, and median myocardial fat content was 0.48% (interquartile range 0.35-1.54). Left ventricular (LV) mass index and LV mass/volume ratio were significantly greater in the HIV/HCV-coinfected group compared with the HIV-monoinfected group. In the HIV-monoinfected group, there was more myocardial fibrosis as measured by extracellular volume fraction. Conclusions There were differences between HIV/HCV-coinfected and HIV-monoinfected patients in cardiac structure and morphology. Larger studies are needed to examine whether HIV and HCV independently contribute to mechanisms of heart failure

Resting Heart Rate as Predictor for Left Ventricular Dysfunction and Heart Failure MESA (Multi-Ethnic Study of Atherosclerosis)

ObjectivesThe objective of this study was to investigate the relationship between baseline resting heart rate and incidence of heart failure (HF) and global and regional left ventricular (LV) dysfunction.BackgroundThe association of resting heart rate to HF and LV function has not been well described in an asymptomatic multi-ethnic population.MethodsResting heart rate was measured in participants in the MESA (Multi-Ethnic Study of Atherosclerosis) trial at inclusion. Incident HF was registered (n = 176) during follow-up (median 7 years) in those who underwent cardiac magnetic resonance imaging (n = 5,000). Changes in ejection fraction (ΔEF) and peak circumferential strain (Δεcc) were measured as markers of developing global and regional LV dysfunction in 1,056 participants imaged at baseline and 5 years later. Time to HF (Cox model) and Δεcc and ΔEF (multiple linear regression models) were adjusted for demographics, traditional cardiovascular risk factors, calcium score, LV end-diastolic volume, and mass in addition to resting heart rate.ResultsCox analysis demonstrated that for 1 beat/min increase in resting heart rate, there was a 4% greater adjusted relative risk for incident HF (hazard ratio: 1.04; 95% CI: 1.02 to 1.06; p < 0.001). Adjusted multiple regression models demonstrated that resting heart rate was positively associated with deteriorating εcc and decrease in EF, even when all coronary heart disease events were excluded from the model.ConclusionsElevated resting heart rate was associated with increased risk for incident HF in asymptomatic participants in the MESA trial. Higher heart rate was related to development of regional and global LV dysfunction independent of subclinical atherosclerosis and coronary heart disease. (Multi-Ethnic Study of Atherosclerosis [MESA]; NCT00005487

Deep Learning-based Automated Aortic Area and Distensibility Assessment: The Multi-Ethnic Study of Atherosclerosis (MESA)

This study applies convolutional neural network (CNN)-based automatic segmentation and distensibility measurement of the ascending and descending aorta from 2D phase-contrast cine magnetic resonance imaging (PC-cine MRI) within the large MESA cohort with subsequent assessment on an external cohort of thoracic aortic aneurysm (TAA) patients. 2D PC-cine MRI images of the ascending and descending aorta at the pulmonary artery bifurcation from the MESA study were included. Train, validation, and internal test sets consisted of 1123 studies (24282 images), 374 studies (8067 images), and 375 studies (8069 images), respectively. An external test set of TAAs consisted of 37 studies (3224 images). A U-Net based CNN was constructed, and performance was evaluated utilizing dice coefficient (for segmentation) and concordance correlation coefficients (CCC) of aortic geometric parameters by comparing to manual segmentation and parameter estimation. Dice coefficients for aorta segmentation were 97.6% (CI: 97.5%-97.6%) and 93.6% (84.6%-96.7%) on the internal and external test of TAAs, respectively. CCC for comparison of manual and CNN maximum and minimum ascending aortic areas were 0.97 and 0.95, respectively, on the internal test set and 0.997 and 0.995, respectively, for the external test. CCCs for maximum and minimum descending aortic areas were 0.96 and 0. 98, respectively, on the internal test set and 0.93 and 0.93, respectively, on the external test set. We successfully developed and validated a U-Net based ascending and descending aortic segmentation and distensibility quantification model in a large multi-ethnic database and in an external cohort of TAA patients.Comment: 25 pages, 5 figure

Deep Learning Analysis of Cardiac MRI in Legacy Datasets:Multi-Ethnic Study of Atherosclerosis

The shape and motion of the heart provide essential clues to understanding the mechanisms of cardiovascular disease. With the advent of large-scale cardiac imaging data, statistical atlases become a powerful tool to provide automated and precise quantification of the status of patient-specific heart geometry with respect to reference populations. The Multi-Ethnic Study of Atherosclerosis (MESA), begun in 2000, was the first large cohort study to incorporate cardiovascular MRI in over 5000 participants, and there is now a wealth of follow-up data over 20 years. Building a machine learning based automated analysis is necessary to extract the additional imaging information necessary for expanding original manual analyses. However, machine learning tools trained on MRI datasets with different pulse sequences fail on such legacy datasets. Here, we describe an automated atlas construction pipeline using deep learning methods applied to the legacy cardiac MRI data in MESA. For detection of anatomical cardiac landmark points, a modified VGGNet convolutional neural network architecture was used in conjunction with a transfer learning sequence between two-chamber, four-chamber, and short-axis MRI views. A U-Net architecture was used for detection of the endocardial and epicardial boundaries in short axis images. Both network architectures resulted in good segmentation and landmark detection accuracies compared with inter-observer variations. Statistical relationships with common risk factors were similar between atlases derived from automated vs manual annotations. The automated atlas can be employed in future studies to examine the relationships between cardiac morphology and future events

Assessment of left atrial systolic dyssynchrony in paroxysmal atrial fibrillation and heart failure using cardiac magnetic resonance imaging: MESA study

Background: Left atrial (LA) remodeling in response to cardiovascular and hemodynamic stress may precede atrial fibrillation (AF) and heart failure (HF). We hypothesized that LA systolic synchronous contraction as a functional measure of LA remodeling is deranged in patients with paroxysmal AF and HF. Methods: We performed a nested case-control analysis with 1:2 matching for 39 cases of paroxysmal AF (n=28, in sinus rhythm during cardiac magnetic resonance (CMR)) and HF (n=14, AF+HF; n=3) and 78 controls with similar demographic and clinical characteristics at the baseline (Table 1). LA circumferential (short axis) and longitudinal strain rate (horizontal long axis) were measured using Multi-modality Tissue Tracking (Toshiba, Japan) from short and long-axis cine CMR images. Circumferential LA systolic dyssynchrony among 18 LA segments (6 segments x 3 slices) was evaluated as; Standard Deviation (SD) of time to pre atrial contraction Strain rate (PreA Src) and Peak systolic strain rate (Peak Srac) (Figure 1). Similarly, longitudinal LA dyssynchrony parameters (among 6 segments) were: SD-Time to pre-atrial contraction strain rate (PreA SrL) and SD-Time to peak systolic strain rate (Peak-SraL). Wilcoxon-rank sum test (non-parametric) or two sample t-test (parametric) were used for comparison between the groups. Results: In participants during MESA exam 5 (age 74±8 years, 51.4% men), systolic circumferential dyssynchrony (SD-TP-PreA Src, msec) was significantly higher in the cases compared to controls (45.06 vs. 28.73, p<0.010). Similarly, case group had greater longitudinal dyssynchrony than controls; SD-TP PreA SrL (51.62 vs. 36.43, p=0.001) and SD-TP-Peak SraL (45.23 vs. 35.92, p=0.027) (Table 1). Conclusions: Patients with paroxysmal atrial fibrillation and heart failure have significantly higher LA circumferential and longitudinal systolic dyssynchrony compared to normal controls