Automated mitral valve vortex ring extraction from 4D‐flow MRI

Figures

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  Figure 1. Visual analysis of the presence/absence of an MV vortex ring in one sample frame of a healthy subject. The 3D streamlines (upper panel) and multiplanar reconstructed 2D vector fields (lower panel) are color‐coded by velocity. An MV vortex ring was identified if swirling flow was present in at least four of six regions in the vicinity of the mitral valve (white arrows) in cardiac long‐axis views

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  Figure 2. Pipeline of the proposed automated MV vortex ring extraction algorithm

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  Figure 3. Maximum Q throughout the cardiac cycle for identification of vortex candidates. The locations of all Q maxima (A) allow calculation of a Q threshold in each frame that will reveal the strongest vortices in the LV. The maximum Q time‐curve (B) allows identification of diastolic to early systolic “vortex frames” (blue). Abbreviations: LA, left atrium; LVOT, left ventricular outflow tract

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  Figure 4. Possible MV vortex ring shapes defining the stop criteria of the predictor‐corrector algorithm. The predictor‐corrector method is applied to each vortex candidate independently, elongating the vortex core first in the forward and then in the backward direction. Stop criteria for forward elongation are arriving back at the start point, thereby forming a closed vortex ring, getting stuck or reaching a voxel where Q ≤ 0. In the latter two cases, the vortex core is elongated in the backward direction until a closed vortex ring is formed (by fusing with the forward core line or arriving at the start point) or the core line gets stuck or reaches a voxel with Q ≤ 0. If no closed core line is formed, the forward and backward core lines are merged and tested for having a U‐shape. If there are two vortex candidates and neither of them yields a torus‐shape or U‐shape, the option that together they form a bracket‐shape is assessed

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  Figure 5. Reference condition and different segmentation approaches for MV vortex ring extraction and analysis experiments. In the reference condition (A), manual segmentation was performed on short‐axis images throughout the entire cardiac cycle. The slice distance was increased (B) and the segmentation mask at end‐diastole was applied to all cardiac frames (C) to simulate segmentation speed‐up. The segmentation masks of all frames were eroded (D) and dilated (E) to simulate segmentation variability

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  Figure 6. Temporal evolution of early and late diastolic MV vortex rings of a healthy subject. In each frame, the MV vortex ring is represented with Q isosurfaces that are color‐coded by MV vortex ring mean vorticity. For better orientation, the vortex rings are overlaid on a phase‐contrast MRA volume (notice the descending aorta on the right). The viewer position is at the apex looking upward. The diagram at the lower right shows the maximum forward velocity measured at the level of the mitral annulus

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  Figure 7. Error plots of early and late diastolic peak values of the MV vortex ring parameters volume, maximum vorticity, mean vorticity, absolute kinetic energy, and relative kinetic energy for different segmentation masks. Average errors are marked by ×, and a statistically significant difference to the reference condition is indicated by *