Synopsis

We investigate the feasibility of using 2-D self-navigation for respiratory gating for free-breathing whole-heart 3-D CINE imaging, where respiration-induced cardiac motion may be more easily detected than in commonly used 1-D self-navigation methods. We compare self-navigation images, derived gating signals and resulting 3-D CINE images of the 1-D and 2-D methods and find that respiratory motion can be well visualized with the 2-D method; both methods show a good overlap of gating signals and little difference in resulting image quality. 2-D self-gating may thus be considered a promising alternative to 1-D self-navigation as it allows easier detection of respiratory motion.

Introduction

Methods

For 1-D self-navigation, only a single central k-space line needs to be acquired periodically during the imaging process, e.g., once in each heartbeat. For 2-D self-navigation, we use one cardiac phase of the 3-D CINE acquisition in each heartbeat to capture undersampled self-navigation data for sagittal 2-D projection images (see Figure 1). Fully-sampled 2-D navigators have been previously proposed for coronary MRA³. We perform full sampling of a small central k-space region followed by stratified sampling⁴ with one random sample per stratum in the k-space periphery. The remaining data for 3-D CINE imaging is acquired as previously described². Note that this acquisition strategy allows a comparison to the 1-D method within the same dataset as the central k-space line is also acquired in each heartbeat.

Figure 2 shows a flow chart of the image reconstruction pipeline. The compressed sensing reconstructions for both the intermediate self-navigation images and the final 3-D CINE image were performed as previously described⁵.

Motion detection in self-navigation images is restricted to a manually selected region of interest over the heart. Pair-wise image registration⁶ of all self-navigation images to a common reference frame is performed to obtain deformation fields $$$\vec{d}_{k}(x, y)$$$ between the reference frame (manually selected in end-expiration) and the $$$k^\text{th}$$$ self-navigation image. The data of a heartbeat is accepted for the final 3-D CINE reconstruction if the mean magnitude of the deformation field corresponding to its self-navigation image is below a threshold $$$ε$$$: $$\frac{1}{N}\sum_x^{}\sum_y^{}\parallel\vec{d}_{k}(x, y)\parallel_{2} <ε,$$ where $$$N$$$ is the number of pixels in the self-navigation image.

To demonstrate the feasibility of this approach, 3-D CINE imaging was performed in a volunteer (female, age 27) on a 1.5 T clinical MR scanner (MAGNETOM Aera, Siemens Healthcare, Erlangen, Germany). A volume-selective, ECG-gated bSSFP prototype imaging sequence with the following parameters was used: TR=2.8 ms, TE=1.2 ms, FOV=340x209x209 mm³, voxel size (1.9 mm)³, temporal resolution 42 ms, fixed acceleration factor of 2.6 compared to the fully-sampled matrix (before respiratory gating) for the undersampling of 3-D CINE data, and acceleration factor of 8 for the self-navigation data. For signal reception, 18+12 elements of an anterior+posterior local coil matrix were used.

For evaluation, we compared the 1-D and 2-D self-navigation signals and derived gating results as well as a qualitative comparison of the resulting 3-D CINE images.

Results and Discussion

Figure 3 shows the self-navigation images of the 1-D and proposed 2-D approach. The derived gating signals of both methods can be seen in Figure 4 and have an overlap of 81%. A qualitative comparison of the resulting 3-D CINE images is given in Figure 5.

Respiratory motion is clearly observable in the 2-D self-navigation images. Their advantage is that respiration-induced cardiac motion can be easily separated from other moving structures, e.g., the chest wall, whereas they are mixed together in the 1-D signal. The 1-D signal was manually selected from the choice of 30 receiver coils as the one where respiratory motion is seen most clearly, which requires an experienced operator. This is not required for the presented 2-D method. Both methods show a reasonable overlap in derived gating signals, and the qualitative comparison shows little difference in image quality. We expect that the 2-D approach can outperform the 1-D method in cases of complex breathing patterns with uncorrelated respiratory motion in directions orthogonal to the SI direction. Future work will be the automation of manual steps and full scanner integration.

Conclusion

Acknowledgements

References

[1] D. Piccini et al. "Respiratory self-navigation for whole-heart bright-blood coronary MRI: methods for robust isolation and automatic segmentation of the blood pool". Magn. Reson. Med. 68(2):571-9, 2012.

[2] Wetzl, Jens, et al. "Free-Breathing, Self-Navigated Isotropic 3-D CINE Imaging of the Whole Heart Using Cartesian Sampling."

[3] M. Hennigsson et al. "Prospective respiratory motion correction for coronary MR angiography using a 2D image navigator". Magn. Reson. Med. 69(2):486-94, 2013.

[4] C. Särndal et al. “Stratified Sampling”. Springer Publishing, 2003. ISBN 0-387-40620-4.

[5] J. Wetzl et al. "Isotropic 3-D CINE Imaging with Sub-2mm Resolution in a Single Breath-Hold". Proc. ISMRM #1011, 2015.

[6] H. Xue et al. “Motion Compensated Magnetic Resonance Reconstruction Using Inverse-Consistent Deformable Registration: Application to Real-Time Cine Imaging”. MICCAI 2011, pp. 564-572.