Accurate fully automated assessment of left ventricle, left atrium, and left atrial appendage function from computed tomography using deep learning

Figures

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  Figure 1. Ground truth creation schematic. (A) Semi-automatic segmentation of the peak-diastolic timeframe in ITK-Snap using the ‘active contour’ method for a subset of patients (n = 8) followed by atlas-based segmentation of the remaining peak-diastolic volumes (n = 31). The peak-diastolic timeframes were used for atlas-based segmentation of the peak-systolic timeframes in each patient separately. All segmentations for the peak-diastolic and peak-systolic timeframe were manually corrected. (B) Automatic atlas-based segmentation for the remaining timeframes based on the previously segmented peak-systolic and peak-diastolic timeframe for each patient separately.

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  Figure 2. Rendering of segmentation result from three representative patients (rows) from the test set at peak diastole and peak systole. The patients were selected based on average DSS across time points. The average DSS for ‘best’ is 0.9392 for nnU-Net and 0.9226 for 3D TransUNet. The average DSS for ‘median’ is 0.9132 for nnU-Net and 0.8988 for 3D TransUNet. The average DSS for ‘worst’ is 0.8826 for nnU-Net and 0.8713 for 3D TransUNet. Blue: LV; orange: LA; red: LAA; green: AA; purple: PVs.

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  Figure 3. Regional volume across the cardiac cycle. Average volume for patients in the test set calculated for the LV, LA, and LAA across the cardiac cycle. Volumes for all regions are calculated based on the largest connected component for that region in the segmentation.

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  Figure 4. Bland–Altman plots for region volumes calculated using the ground truth and nnU-Net predictions for the LV, LA, and LAA. Plots contain bias (red dashed line) and limits of agreement (±1.96 SD, green dashed lines).

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  Figure 5. Bland–Altman plots for cardiac function parameters calculated using the ground truth and nnU-Net predictions. Plots contain bias (red dashed line) and limits of agreement (±1.96 SD, green dashed lines).