ArticleJournal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance2014
Population-based studies of myocardial hypertrophy: high resolution cardiovascular magnetic resonance atlases improve statistical power.
Article in Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Deep Learning-Based Estimation of Myocardial Material Parameters from Cardiac MRI.Bioengineering (Basel, Switzerland) · 2025Article
- Motion correction and super-resolution for multi-slice cardiac magnetic resonance imaging via an end-to-end deep learning approach.Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society · 2024Article
- Translating principles of quality control to cardiovascular magnetic resonance: assessing quantitative parameters of the left ventricle in a large cohort.Scientific reports · 2023Article
- Article
- A completely automated pipeline for 3D reconstruction of human heart from 2D cine magnetic resonance slices.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2021Article
- Sex and regional differences in myocardial plasticity in aortic stenosis are revealed by 3D model machine learning.European heart journal. Cardiovascular Imaging · 2020Article
- Paradoxical Higher Myocardial Wall Stress and Increased Cardiac Remodeling Despite Lower Mass in Females.Journal of the American Heart Association · 2020Article
- Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.IEEE transactions on medical imaging · 2019Article
- Evaluating reinforcement learning agents for anatomical landmark detection.Medical image analysis · 2019Article
- Identifying the optimal regional predictor of right ventricular global function: a high-resolution three-dimensional cardiac magnetic resonance study.Anaesthesia · 2019Article
- Artificial Intelligence for Cardiac Imaging-Genetics Research.Frontiers in cardiovascular medicine · 2019Review
- Novel Index of Maladaptive Myocardial Remodeling in Hypertension.Circulation. Cardiovascular imaging · 2017Article
- Machine Learning of Three-dimensional Right Ventricular Motion Enables Outcome Prediction in Pulmonary Hypertension: A Cardiac MR Imaging Study.Radiology · 2017Article
- Titin-truncating variants affect heart function in disease cohorts and the general population.Nature genetics · 2017Article
- Review of Journal of Cardiovascular Magnetic Resonance 2015.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2016Review
- Pulmonary Artery Stiffness Is Independently Associated with Right Ventricular Mass and Function: A Cardiac MR Imaging Study.Radiology · 2016Observational
- Relationship between body composition and left ventricular geometry using three dimensional cardiovascular magnetic resonance.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2016Observational
- Review of Journal of Cardiovascular Magnetic Resonance 2014.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2015Review
- Precursors of Hypertensive Heart Phenotype Develop in Healthy Adults: A High-Resolution 3D MRI Study.JACC. Cardiovascular imaging · 2015Article
- Review
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11 authors.
Funding
Abstract
backgroundCardiac phenotypes, such as left ventricular (LV) mass, demonstrate high heritability although most genes associated with these complex traits remain unidentified. Genome-wide association studies (GWAS) have relied on conventional 2D cardiovascular magnetic resonance (CMR) as the gold-standard for phenotyping. However this technique is insensitive to the regional variations in wall thickness which are often associated with left ventricular hypertrophy and require large cohorts to reach significance. Here we test whether automated cardiac phenotyping using high spatial resolution CMR atlases can achieve improved precision for mapping wall thickness in healthy populations and whether smaller sample sizes are required compared to conventional methods.
methodsLV short-axis cine images were acquired in 138 healthy volunteers using standard 2D imaging and 3D high spatial resolution CMR. A multi-atlas technique was used to segment and co-register each image. The agreement between methods for end-diastolic volume and mass was made using Bland-Altman analysis in 20 subjects. The 3D and 2D segmentations of the LV were compared to manual labeling by the proportion of concordant voxels (Dice coefficient) and the distances separating corresponding points. Parametric and nonparametric data were analysed with paired t-tests and Wilcoxon signed-rank test respectively. Voxelwise power calculations used the interstudy variances of wall thickness.
resultsThe 3D volumetric measurements showed no bias compared to 2D imaging. The segmented 3D images were more accurate than 2D images for defining the epicardium (Dice: 0.95 vs 0.93, P<0.001; mean error 1.3 mm vs 2.2 mm, P<0.001) and endocardium (Dice 0.95 vs 0.93, P<0.001; mean error 1.1 mm vs 2.0 mm, P<0.001). The 3D technique resulted in significant differences in wall thickness assessment at the base, septum and apex of the LV compared to 2D (P<0.001). Fewer subjects were required for 3D imaging to detect a 1 mm difference in wall thickness (72 vs 56, P<0.001).
conclusionsHigh spatial resolution CMR with automated phenotyping provides greater power for mapping wall thickness than conventional 2D imaging and enables a reduction in the sample size required for studies of environmental and genetic determinants of LV wall thickness.
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