Population-based studies of myocardial hypertrophy: high resolution cardiovascular magnetic resonance atlases improve statistical power

Abstract

Background: Cardiac 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.

Methods: LV 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.

Results: The 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).

Conclusions: High 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.

Figure 1

The automated cardiac segmentation method looked for similarities between cubic "patches" in the manually-labeled pool of atlases and each new target image. Correspondences with two atlases are shown in the diagram, but up to 20 high spatial resolution atlases were simultaneously used for accurate segmentation in the study.

Figure 2

The accuracy of cardiac segmentation, measured with the Dice coefficient, improved as a larger number of 3D atlases were included in the analysis.

Figure 3

Left ventricular long axis reconstruction of short-axis cine MR images at end-diastole in a healthy volunteer. Automated segmentation of the myocardium is shown in green and the cavity in red. Data from a conventional 2D LVSA is shown in A) compared to a high-spatial resolution 3DLVSA in B).

Figure 4

Segmentations of the myocardium in a healthy volunteer with wall thickness shown as a color-scale. Data from 2D (A) and 3D (B) LVSA cine images are presented with the right ventricle depicted as a mesh. Step artefact due to lower spatial resolution of 2D imaging is visible at the base and apex of the left ventricle (arrows).

Figure 5

Comparison of the automated 3D LVSA segmentations to their respective manually labeled cardiac atlas in 20 volunteers demonstrating no bias for calculating LVEDI (A) or LVMI (B).

Figure 6

Comparison of the automated 3D LVSA segmentations to manual volumetry of the corresponding 2D LVSA images in 20 volunteers demonstrating no bias for calculating LVEDI (A) or LVMI (B).

Figure 7

The reduction in sample size required for 3D LVSA segmentations to detect a 1mm difference in left ventricular wall thickness compared to 2D LVSA segmentations is shown using reproducibility data from 20 healthy subjects. The right ventricle is depicted as a mesh. The hot colors show where 3D imaging has the largest effect on reducing sample size which is predominantly at the basal and apical regions. (Values of ±90% are shown).

Figure 8

Voxelwise comparisons between LV wall thickness on 2D and 3D LVSA myocardial segmentations in 100 healthy volunteers is shown. The right ventricle is depicted as a mesh. A significance level of 5% corresponds to a value of 12.7 on the scale. Differences in wall thickness between the imaging techniques are apparent at highly curved regions of the base, interventricular septum and apex.