Collapsed fat navigators for brain 3D rigid body motion.

PURPOSE: To acquire high-resolution 3D multi-slab echo planar imaging data without motion artifacts, using collapsed fat navigators. METHODS: A fat navigator module (collapsed FatNav) was added to a diffusion-weighted 3D multi-slab echo planar imaging (DW 3D-MS EPI) sequence, comprising three orthogonal echo planar imaging readouts to track rigid body head motion in the image domain and performing prospective motion correction. The stability, resolution and accuracy of the navigator were investigated on phantoms and healthy volunteers. RESULTS: The experiments on phantoms and volunteers show that the navigator, depicting projections of the subcutaneous fat in of the head, is capable of correcting for head motion with insignificant bias compared to motion estimates derived from the water-signaling DWI images. Despite that this projection technique implies a non-sparse image appearance, collapsed FatNav data could be highly accelerated with parallel imaging, allowing three orthogonal 2D EPI readouts in about 6ms. CONCLUSION: By utilizing signal from the leading fat saturation RF pulse of the diffusion sequence, only the readout portion of the navigator needs to be added, resulting in a scan time penalty of only about 5%. Motion can be detected and corrected for with a 5-10Hz update frequency when combined with a sequence like the DW 3D-MS EPI.

On the signal-to-noise ratio efficiency and slab-banding artifacts in three-dimensional multislab diffusion-weighted echo-planar imaging.

PURPOSE: Three-dimensional (3D) multislab diffusion-weighted echo-planar imaging (EPI) has been suggested as an alternative for high-resolution diffusion-weighted imaging. In this work, the key components of the sequence are investigated, optimal scan parameter settings suggested, and a signal-to-noise ratio (SNR) analysis, comparing 2D diffusion-weighted EPI and 3D multislab diffusion-weighted EPI, is performed. METHODS: Slab profiles were measured using 3D multislab EPI to investigate slab profile saturation effects with respect to TR, T1 and overlap between slabs. For short TR values, two methods to reduce the slab banding artifacts are proposed. Moreover, the SNR for 2D and 3D multislab (3D-MS) DWI have been simulated for various anatomical coverages and slab thicknesses. RESULTS: Simulated 3D multislab scans were shown to be more SNR-efficient than a corresponding 2D scan, for all investigated anatomical coverages and slab thicknesses. Slab banding artifacts being negligible for long repetition times (TRs) were strong for a TR of 2000 ms, proving that they stem from T1 -saturation effects. This banding was largely reduced by the suggested correction methods. CONCLUSION: In the low TR regime, T1 -saturation effects between adjacent slabs need to be taken in consideration to avoid slab-banding artifacts for multislab sequences. With the proposed correction methods the difference between the SNR-optimal TR and the TR where slab-banding artifacts become acceptable is reduced.

Properties of a 2D fat navigator for prospective image domain correction of nodding motion in brain MRI.

PURPOSE: A two-dimensional fat navigator (FatNav) image is proposed, designed for future use as a means of prospective motion correction of head-nodding motion. METHODS: The proposed FatNav module comprised a fat-selective excitation, followed by an accelerated echo planar imaging readout played out in one central sagittal plane. Step-wise motion experiments with different acceleration factors, blip polarity, and matrix sizes were performed. The accuracy of motion estimates derived from the FatNav data was assessed using water-based, distortion-free, spoiled-gradient echo images as the gold standard. The duration of the FatNav module was 10 ms to 20 ms. Volunteer data were acquired on a 3T system using an 8-channel radiofrequency coil. METHODS: It is shown that acceleration factors of R = 8 are feasible for FatNav data. Best results are obtained when parallel imaging calibration data is matched in terms of both geometric distortions and signal content. For head rotations up to about 15 mm and 20 degrees, mean absolute errors of the motion estimates using FatNav data were about 0.5 mm and 1 degree. CONCLUSION: FatNav is advantageous in that it leaves most of the brain water magnetization unaffected and left to the host pulse sequence. Furthermore, high acceleration factors are possible with FatNav, which reduces estimation bias and the navigator duration.