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BackgroundLeft 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.ResultsSix 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.ConclusionsThe 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.

BackgroundAlthough 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.MethodsIMCA 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.ResultsA 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.ConclusionsIMCA 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 ).

BackgroundAlthough left ventricular cardiac geometric indices such as size and sphericity characterize adverse remodeling and have prognostic value in symptomatic patients, little is known of shape distributions in subclinical populations. We sought to quantify shape variation across a large number of asymptomatic volunteers, and examine differences among sub-cohorts.MethodsAn atlas was constructed comprising 1,991 cardiovascular magnetic resonance (CMR) cases contributed from the Multi-Ethnic Study of Atherosclerosis baseline examination. A mathematical model describing regional wall motion and shape was used to establish a coordinate map registered to the cardiac anatomy. The model was automatically customized to left ventricular contours and anatomical landmarks, corrected for breath-hold mis-registration between image slices. Mathematical techniques were used to characterize global shape distributions, after removal of translations, rotations, and scale due to height. Differences were quantified among ethnicity, sex, smoking, hypertension and diabetes sub-cohorts.ResultsThe atlas construction process yielded accurate representations of global shape (errors between manual and automatic surface points in 244 validation cases were less than the image pixel size). After correction for height, the dominant shape component was associated with heart size, explaining 32% of the total shape variance at end-diastole and 29% at end-systole. After size, the second dominant shape component was sphericity at end-diastole (13%), and concentricity at end-systole (10%). The resulting shape components distinguished differences due to ethnicity and risk factors with greater statistical power than traditional mass and volume indices.ConclusionsWe have quantified the dominant components of global shape variation in the adult asymptomatic population. The data and results are available at cardiacatlas.org. Shape distributions were principally explained by size, sphericity and concentricity, which are known correlates of adverse outcomes. Atlas-based global shape analysis provides a powerful method for quantifying left ventricular shape differences in asymptomatic populations.Trial registrationClinicalTrials.gov NCT00005487.

Myocardial infarction leads to changes in the geometry (remodeling) of the left ventricle (LV) of the heart. The degree and type of remodeling provides important diagnostic information for the therapeutic management of ischemic heart disease. In this paper, we present a novel analysis framework for characterizing remodeling after myocardial infarction, using LV shape descriptors derived from atlas-based shape models. Cardiac magnetic resonance images from 300 patients with myocardial infarction and 1991 asymptomatic volunteers were obtained from the Cardiac Atlas Project. Finite element models were customized to the spatio-temporal shape and function of each case using guide-point modeling. Principal component analysis was applied to the shape models to derive modes of shape variation across all cases. A logistic regression analysis was performed to determine the modes of shape variation most associated with myocardial infarction. Goodness of fit results obtained from end-diastolic and end-systolic shapes were compared against the traditional clinical indices of remodeling: end-diastolic volume, end-systolic volume and LV mass. The combination of end-diastolic and end-systolic shape parameter analysis achieved the lowest deviance, Akaike information criterion and Bayesian information criterion, and the highest area under the receiver operating characteristic curve. Therefore, our framework quantitatively characterized remodeling features associated with myocardial infarction, better than current measures. These features enable quantification of the amount of remodeling, the progression of disease over time, and the effect of treatments designed to reverse remodeling effects.

Abstract Background Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. Methods A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Results Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Conclusions Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

MotivationIntegrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups.ResultsThree main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt).Availabilityhttp://www.cardiacatlas.orgContacta.young@auckland.ac.nzSupplementary informationSupplementary data are available at Bioinformatics online.

Heart shape and function are major determinants of disease severity and predictors of future morbidity and mortality. Many studies now rely on non-invasive cardiac imaging techniques to quantify structural and functional changes. Statistical anatomical modeling of heart shape and motion provides a new tool for the quantification and evaluation of heart disease. This review surveys recent progress in the evaluation of statistical shape measures across populations and sub-cohorts, and highlights collaborative efforts to facilitate data sharing and atlas-based shape analysis. [ABSTRACT FROM AUTHOR]

We aimed to compare child body mass index (BMI) in prediction of hypertension in early adulthood with 4 other adiposity indices (waist circumference [WC], waist circumference-to-height ratio [WHtR], waist-to-hip ratio [WHR], and triceps skinfold [TSF]). The cohort from the China Health and Nutrition Survey 1993-2011 consisted of 1444 adults aged 18-36 years who were examined in childhood and early adulthood. Child adiposity indices and adult blood pressure (BP) were transformed into age-, sex-, and survey year-specific Z-scores. Adult hypertension was defined as BP ≥130/80 mm Hg as per the 2017 American College of Cardiology/American Heart Association guidelines. Adult hypertension prevalence was 32.9% during a mean follow-up of 10.1 years. Childhood BMI showed stronger correlation with adult BP than WHR and TSF (P S for difference <.05). Child BMI showed the better prediction of adult hypertension compared with WHtR, WHR, and TSF using area under the receiver operating characteristic curves (P S for difference <.05). Per SD change in the predictor, child BMI (relative risk [95% confidence interval], 1.11 [1.04-1.18]) and WC (1.12 [1.05-1.20]) were significantly associated with adult hypertension using covariate-adjusted Poisson models with robust standard errors. Child BMI performed equally or better compared with 4 other adiposity indices in predicting adult hypertension., (© 2019 Wiley Periodicals, Inc.)

Statistical shape modeling is a powerful tool for visualizing and quantifying geometric and functional patterns of the heart. After myocardial infarction (MI), the left ventricle typically remodels in response to physiological challenges. Several methods have been proposed in the literature to describe statistical shape changes. Which method best characterizes left ventricular remodeling after MI is an open research question. A better descriptor of remodeling is expected to provide a more accurate evaluation of disease status in MI patients. We therefore designed a challenge to test shape characterization in MI given a set of three-dimensional left ventricular surface points. The training set comprised 100 MI patients, and 100 asymptomatic volunteers (AV). The challenge was initiated in 2015 at the Statistical Atlases and Computational Models of the Heart workshop, in conjunction with the MICCAI conference. The training set with labels was provided to participants, who were asked to submit the likelihood of MI from a different (validation) set of 200 cases (100 AV and 100 MI). Sensitivity, specificity, accuracy and area under the receiver operating characteristic curve were used as the outcome measures. The goals of this challenge were to (1) establish a common dataset for evaluating statistical shape modeling algorithms in MI, and (2) test whether statistical shape modeling provides additional information characterizing MI patients over standard clinical measures. Eleven groups with a wide variety of classification and feature extraction approaches participated in this challenge. All methods achieved excellent classification results with accuracy ranges from 0.83 to 0.98. The areas under the receiver operating characteristic curves were all above 0.90. Four methods showed significantly higher performance than standard clinical measures. The dataset and software for evaluation are available from the Cardiac Atlas Project website1.

This is a consensus document from the European Bifurcation Club concerning bench testing in coronary artery bifurcations. It is intended to provide guidelines for bench assessment of stents and other strategies in coronary bifurcation treatment where the United States Food and Drug Administration (FDA) or International Organization for Standardization (ISO) guidelines are limited or absent. These recommendations provide guidelines rather than a step-by-step manual. We provide data on the anatomy of bifurcations and elastic response of coronary arteries to aid model construction. We discuss testing apparatus, bench testing endpoints and bifurcation nomenclature.

Continuous advances in imaging technologies enable ever more comprehensive phenotyping of human anatomy and physiology. Concomitant reduction of imaging costs has resulted in widespread use of imaging in large clinical trials and population imaging studies. Magnetic Resonance Imaging (MRI), in particular, offers one-stop-shop multidimensional biomarkers of cardiovascular physiology and pathology. A wide range of analysis methods offer sophisticated cardiac image assessment and quantification for clinical and research studies. However, most methods have only been evaluated on relatively small databases often not accessible for open and fair benchmarking. Consequently, published performance indices are not directly comparable across studies and their translation and scalability to large clinical trials or population imaging cohorts is uncertain. Most existing techniques still rely on considerable manual intervention for the initialization and quality control of the segmentation process, becoming prohibitive when dealing with thousands of images. The contributions of this paper are three-fold. First, we propose a fully automatic method for initializing cardiac MRI segmentation, by using image features and random forests regression to predict an initial position of the heart and key anatomical landmarks in an MRI volume. In processing a full imaging database, the technique predicts the optimal corrective displacements and positions in relation to the initial rough intersections of the long and short axis images. Second, we introduce for the first time a quality control measure capable of identifying incorrect cardiac segmentations with no visual assessment. The method uses statistical, pattern and fractal descriptors in a random forest classifier to detect failures to be corrected or removed from subsequent statistical analysis. Finally, we validate these new techniques within a full pipeline for cardiac segmentation applicable to large-scale cardiac MRI databases. The results obtained based on over 1200 cases from the Cardiac Atlas Project show the promise of fully automatic initialization and quality control for population studies., (Copyright © 2017 Elsevier B.V. All rights reserved.)

We characterized motion attributes arising from LV spatio-temporal analysis of motion distributions in myocardial infarction. Time-varying 3D finite element shape models were obtained in 300 Controls and 300 patients with myocardial infarction. Inter-individual left ventricular shape differences were eliminated using parallel transport to the grand mean of all cases. The first three principal component (PC) scores were used to characterize trajectory attributes. Scores were tested with ANOVA/MANOVA using patient disease status (Infarcts vs. Controls) as a factor. Infarcted patients had significantly different magnitude, orientation and shape of left ventricular trajectories in comparison to Controls. Significant differences were found for the angle between PC scores 1 and 2 in the endocardium, and PC scores 1 and 3 in the epicardium. The largest differences were found in the magnitude of endocardial motion. Endocardial PC scores in shape space showed the highest classification power using support vector machine, with higher total accuracy in comparison to previous methods. Shape space performed better than size-and-shape space for both epicardial and endocardial features. In conclusion, LV spatio-temporal motion attributes accurately characterize the presence of infarction. This approach is easily generalizable to different pathologies, enabling more precise study of the pathophysiological consequences of a wide spectrum of cardiac diseases.

Purpose: To examine the feasibility of combining computational fluid dynamics (CFD) and dynamically scaled phantom phase-contrast magnetic resonance imaging (PC-MRI) for coronary flow assessment., Materials and Methods: Left main coronary bifurcations segmented from computed tomography with bifurcation angles of 33°, 68°, and 117° were scaled-up ∼7× and 3D printed. Steady coronary flow was reproduced in these phantoms using the principle of dynamic similarity to preserve the true-scale Reynolds number, using blood analog fluid and a pump circuit in a 3T MRI scanner. After PC-MRI acquisition, the data were segmented and coregistered to CFD simulations of identical, but true-scale geometries. Velocities at the inlet region were extracted from the PC-MRI to define the CFD inlet boundary condition., Results: The PC-MRI and CFD flow data agreed well, and comparison showed: 1) small velocity magnitude discrepancies (2-8%); 2) with a Spearman's rank correlation ≥0.72; and 3) a velocity vector correlation (including direction) of r(2) ≥ 0.82. The highest agreement was achieved for high velocity regions with discrepancies being located in slow or recirculating zones with low MRI signal-to-noise ratio (SNRv ) in tortuous segments and large bifurcating vessels., Conclusion: Characterization of coronary flow using a dynamically scaled PC-MRI phantom flow is feasible and provides higher resolution than current in vivo or true-scale in vitro methods, and may be used to provide boundary conditions for true-scale CFD simulations. J. MAGN. RESON. IMAGING 2016;44:983-992., (© 2016 International Society for Magnetic Resonance in Medicine.)

Aims: The aim of this study was to define the shape variations, including diameters and angles, of the major coronary artery bifurcations., Methods and Results: Computed tomographic angiograms from 300 adults with a zero calcium score and no stenoses were segmented for centreline and luminal models. A computational atlas was constructed enabling automatic quantification of 3D angles, diameters and lengths of the coronary tree. The diameter (mean±SD) of the left main coronary was 3.5±0.8 mm and the length 10.5±5.3 mm. The left main bifurcation angle (distal angle or angle B) was 89±21° for cases with, and 75±23° for those without an intermediate artery (p<0.001). Analogous measurements of diameter and angle were tabulated for the other major bifurcations (left anterior descending/diagonal, circumflex/obtuse marginal and right coronary crux). Novel 3D angle definitions are proposed and analysed., Conclusions: A computational atlas of normal coronary artery anatomy provides distributions of diameter, lengths and bifurcation angles as well as more complex shape analysis. These data define normal anatomical variation, facilitating stent design, selection and optimal treatment strategy. These population models are necessary for accurate computational flow dynamics, can be 3D printed for bench testing bifurcation stents and deployment strategies, and can aid in the discussion of different approaches to the treatment of coronary bifurcations.

The majority of patients with angina or heart failure have coronary artery disease. Left main bifurcations are particularly susceptible to pathological narrowing. Flow is a major factor of atheroma development, but limitations in imaging technology such as spatio-temporal resolution, signal-to-noise ratio (SNRv), and imaging artefacts prevent in vivo investigations. Computational fluid dynamics (CFD) modelling is a common numerical approach to study flow, but it requires a cautious and rigorous application for meaningful results. Left main bifurcation angles of 40°, 80° and 110° were found to represent the spread of an atlas based 100 computed tomography angiograms. Three left mains with these bifurcation angles were reconstructed with 1) idealized, 2) stented, and 3) patient-specific geometry. These were then approximately 7× scaled-up and 3D printing as large phantoms. Their flow was reproduced using a blood-analogous, dynamically scaled steady flow circuit, enabling in vitro phase-contrast magnetic resonance (PC-MRI) measurements. After threshold segmentation the image data was registered to true-scale CFD of the same coronary geometry using a coherent point drift algorithm, yielding a small covariance error (σ 2 <;5.8×10 -4 ). Natural-neighbour interpolation of the CFD data onto the PC-MRI grid enabled direct flow field comparison, showing very good agreement in magnitude (error 2-12%) and directional changes (r 2 0.87-0.91), and stent induced flow alternations were measureable for the first time. PC-MRI over-estimated velocities close to the wall, possibly due to partial voluming. Bifurcation shape determined the development of slow flow regions, which created lower SNRv regions and increased discrepancies. These can likely be minimised in future by testing different similarity parameters to reduce acquisition error and improve correlation further. It was demonstrated that in vitro large phantom acquisition correlates to true-scale coronary flow simulations when dynamically scaled, and thus can overcome current PC-MRI's spatio-temporal limitations. This novel method enables experimental assessment of stent induced flow alternations, and in future may elevate CFD coronary flow simulations by providing sophisticated boundary conditions, and enable investigations of stenosis phantoms.

The hemodynamic influence of vessel shape such as bifurcation angle is not fully understood with clinical and quantitative observations being equivocal. The aim of this study is to use computational modeling to study the hemodynamic effect of shape characteristics, in particular bifurcation angle (BA), for non-stented and stented coronary arteries. Nine bifurcations with angles of 40°, 60° and 80°, representative of ±1 SD of 101 asymptomatic computed tomography angiogram cases (average age 54±8 years; 57 females), were generated for (1) a non-stented idealized, (2) stented idealized, and (3) non-stented patient-specific geometry. Only the bifurcation angle was changed while the geometries were constant to eliminate flow effects induced by other vessel shape characteristics. The commercially available Biomatrix stent was used as a template and virtually inserted into each branch, simulating the T-stenting technique. Three patient-specific geometries with additional shape variation and ±2 SD BA variation (33°, 42° and 117°) were also computed. Computational fluid dynamics (CFD) analysis was performed for all 12 geometries to simulate physiological conditions, enabling the quantification of the hemodynamic stress distributions, including a threshold analysis of adversely low and high wall shear stress (WSS), low time-averaged WSS (TAWSS), high spatial WSS gradient (WSSG) and high Oscillatory Shear Index (OSI) area. The bifurcation angle had a minor impact on the areas of adverse hemodynamics in the idealized non-stented geometries, which fully disappeared once stented and was not apparent for patient geometries. High WSS regions were located close to the carina around peak-flow, and WSSG increased significantly after stenting for the idealized bifurcations. Additional shape variations affected the hemodynamic profiles, suggesting that BA alone has little effect on a patient׳s hemodynamic profile. Incoming flow angle, diameter and tortuosity appear to have stronger effects. This suggests that other bifurcation shape characteristics and stent placement/strategy may be more important than bifurcation angle in atherosclerotic disease development, progression, and stent outcome., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Background: The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management., Methods: In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX)., Results: The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model., Conclusion: Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis.

The burden of heart disease is rapidly worsening due to the increasing prevalence of obesity and diabetes. Data sharing and open database resources for heart health informatics are important for advancing our understanding of cardiovascular function, disease progression and therapeutics. Data sharing enables valuable information, often obtained at considerable expense and effort, to be reused beyond the specific objectives of the original study. Many government funding agencies and journal publishers are requiring data reuse, and are providing mechanisms for data curation and archival. Tools and infrastructure are available to archive anonymous data from a wide range of studies, from descriptive epidemiological data to gigabytes of imaging data. Meta-analyses can be performed to combine raw data from disparate studies to obtain unique comparisons or to enhance statistical power. Open benchmark datasets are invaluable for validating data analysis algorithms and objectively comparing results. This review provides a rationale for increased data sharing and surveys recent progress in the cardiovascular domain. We also highlight the potential of recent large cardiovascular epidemiological studies enabling collaborative efforts to facilitate data sharing, algorithms benchmarking, disease modeling and statistical atlases.

Describing the detailed statistical anatomy of the coronary artery tree is important for determining the aetiology of heart disease. A number of studies have investigated geometrical features and have found that these correlate with clinical outcomes, e.g. bifurcation angle with major adverse cardiac events. These methodologies were mainly two-dimensional, manual and prone to inter-observer variability, and the data commonly relates to cases already with pathology. We propose a hybrid atlasing methodology to build a population of computational models of the coronary arteries to comprehensively and accurately assess anatomy including 3D size, geometry and shape descriptors. A random sample of 122 cardiac CT scans with a calcium score of zero was segmented and analysed using a standardised protocol. The resulting atlas includes, but is not limited to, the distributions of the coronary tree in terms of angles, diameters, centrelines, principal component shape analysis and cross-sectional contours. This novel resource will facilitate the improvement of stent design and provide a reference for hemodynamic simulations, and provides a basis for large normal and pathological databases.

A collaborative framework was initiated to establish a community resource of ground truth segmentations from cardiac MRI. Multi-site, multi-vendor cardiac MRI datasets comprising 95 patients (73 men, 22 women; mean age 62.73±11.24years) with coronary artery disease and prior myocardial infarction, were randomly selected from data made available by the Cardiac Atlas Project (Fonseca et al., 2011). Three semi- and two fully-automated raters segmented the left ventricular myocardium from short-axis cardiac MR images as part of a challenge introduced at the STACOM 2011 MICCAI workshop (Suinesiaputra et al., 2012). Consensus myocardium images were generated based on the Expectation-Maximization principle implemented by the STAPLE algorithm (Warfield et al., 2004). The mean sensitivity, specificity, positive predictive and negative predictive values ranged between 0.63 and 0.85, 0.60 and 0.98, 0.56 and 0.94, and 0.83 and 0.92, respectively, against the STAPLE consensus. Spatial and temporal agreement varied in different amounts for each rater. STAPLE produced high quality consensus images if the region of interest was limited to the area of discrepancy between raters. To maintain the quality of the consensus, an objective measure based on the candidate automated rater performance distribution is proposed. The consensus segmentation based on a combination of manual and automated raters were more consistent than any particular rater, even those with manual input. The consensus is expected to improve with the addition of new automated contributions. This resource is open for future contributions, and is available as a test bed for the evaluation of new segmentation algorithms, through the Cardiac Atlas Project (www.cardiacatlas.org)., (Copyright © 2013 Elsevier B.V. All rights reserved.)