Robust self-navigated body MRI using dense coil arrays.

PURPOSE: To develop a robust motion estimation method for free-breathing body MRI using dense coil arrays.
METHODS: Self-navigating pulse sequences can measure subject motion without using external motion monitoring devices. With dense coil arrays, individual coil elements can provide localized motion estimates. An averaged motion estimate over all coils is often used for motion compensation. However, this motion estimate may not accurately represent the dominant motion within the imaging volume. In this work, a coil clustering method is proposed to automatically determine the dominant motion for dense coil arrays. The feasibility of the proposed method is investigated in free-breathing abdominal MRI and cardiac MRI, and compared with manual motion estimate selection for respiratory motion estimation and electrocardiography for cardiac motion estimation.
RESULTS: Automated motion estimation achieved similar respiratory motion estimation compared to manual selection (averaged correlation coefficient 0.989 and 0.988 for abdominal MRI and cardiac MRI, respectively), and accurate cardiac triggering compared to electrocardiography (averaged temporal variability 17.5 ms).
CONCLUSION: The proposed method can provide accurate automated motion estimation for body MRI using dense coil arrays. It can enable self-navigated free-breathing abdominal and cardiac MRI without the need for external motion monitoring devices. Magn Reson Med 76:197-205, 2016.