Respiratory motion-resolved, self-gated 4D-MRI using rotating cartesian k-space (ROCK)

Purpose: To propose and validate a respiratory motion resolved, self-gated (SG) 4D-MRI technique to assess patient-specific breathing motion of abdominal organs for radiation treatment planning. Methods: The proposed 4D-MRI technique was based on the balanced steady-state free-precession (bSSFP) technique and 3D k-space encoding. A novel rotating cartesian k-space (ROCK) reordering method was designed which incorporates repeatedly sampled k-space centerline as the SG motion surrogate and allows for retrospective k-space data binning into different respiratory positions based on the amplitude of the surrogate. The multiple respiratory-resolved 3D k-space data were subsequently reconstructed using a joint parallel imaging and compressed sensing method with spatial and temporal regularization. The proposed 4D-MRI technique was validated using a custom-made dynamic motion phantom and was tested in six healthy volunteers, in whom quantitative diaphragm and kidney motion measurements based on 4D-MRI images were compared with those based on 2D-CINE images. Results: The 5-minute 4D-MRI scan offers high-quality volumetric images in 1.2 x 1.2 x 1.6 mm(3) and eight respiratory positions, with good soft-tissue contrast. In phantom experiments with triangular motion waveform, the motion amplitude measurements based on 4D-MRI were 11.89% smaller than the ground truth, whereas a -12.5% difference was expected due to data binning effects. In healthy volunteers, the difference between the measurements based on 4D-MRI and the ones based on 2D-CINE were 6.2 4.5% for the diaphragm, 8.2 +/- 4.9% and 8.9 +/- 5.1% for the right and left kidney. Conclusion: The proposed 4D-MRI technique could provide high-resolution, high-quality, respiratory motion-resolved 4D images with good soft-tissue contrast and are free of the stitching artifacts usually seen on 4D-CT and 4D-MRI based on resorting 2D-CINE. It could be used to visualize and quantify abdominal organ motion for MRI-based radiation treatment planning. (C) 2017 American Association of Physicists in Medicine.