Quantitative evaluation of prospective motion correction in healthy subjects at 7T MRI

PURPOSE

Quantitative assessment of prospective motion correction (PMC) capability at 7T MRI for compliant healthy subjects to improve high-resolution images in the absence of intentional motion.

METHODS

Twenty-one healthy subjects were imaged at 7 T. They were asked not to move, to consider only unintentional motion. An in-bore optical tracking system was used to monitor head motion and consequently update the imaging volume. For all subjects, high-resolution T₁ (3D-MPRAGE), T₂ (2D turbo spin echo), proton density (2D turbo spin echo), and T2∗ (2D gradient echo) weighted images were acquired with and without PMC. The images were evaluated through subjective and objective analysis.

RESULTS

Subjective evaluation overall has shown a statistically significant improvement (5.5%) in terms of image quality with PMC ON. In a separate evaluation of every contrast, three of the four contrasts (T₁ , T₂ , and proton density) have shown a statistically significant improvement (9.62%, 9.85%, and 9.26%), whereas the fourth one ( T2∗ ) has shown improvement, although not statistically significant. In the evaluation with objective metrics, average edge strength has shown an overall improvement of 6% with PMC ON, which was statistically significant; and gradient entropy has shown an overall improvement of 2%, which did not reach statistical significance.

CONCLUSION

Based on subjective assessment, PMC improved image quality in high-resolution images of healthy compliant subjects in the absence of intentional motion for all contrasts except T2∗ , in which no significant differences were observed. Quantitative metrics showed an overall trend for an improvement with PMC, but not all differences were significant.

Model-based iterative reconstruction for single-shot EPI at 7T

PURPOSE

To describe a model-based reconstruction strategy for single-shot echo planar imaging (EPI) that intrinsically accounts for k-space nonuniformity, Nyquist ghosting, and geometric distortions during rather than before or after image reconstruction.

METHODS

Ramp sampling and inhomogeneous B0 field-induced distortion cause the EPI samples to lie on a non-Cartesian grid, thus requiring the nonuniform fast Fourier transform. Additionally, a 2D Nyquist ghost phase correction without the need for extra navigator acquisition is included in the proposed reconstruction. Coil compression is also incorporated to reduce the computational load. The proposed method is applied to phantom and human brain MRI data.

RESULTS

The results demonstrate that Nyquist ghosting and geometric distortions are reduced by the proposed reconstruction. The proposed 2D phase correction is superior to a conventional 1D correction. The reductions of both artifacts lead to improved temporal signal-to-noise ratio (tSNR). The virtual coil results suggest that the processing time can be reduced by up to 75%, with a mean tSNR loss of only 3.2% when using 8-virtual instead of 32-physical coils for twofold undersampled data.

CONCLUSION

The proposed reconstruction improves the quality (ghosting, geometry, and tSNR) of EPI without requiring calibration data for Nyquist ghost correction. Magn Reson Med 78:2250-2264, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Motion correction in MRI of the brain

Subject motion in MRI is a relevant problem in the daily clinical routine as well as in scientific studies. Since the beginning of clinical use of MRI, many research groups have developed methods to suppress or correct motion artefacts. This review focuses on rigid body motion correction of head and brain MRI and its application in diagnosis and research. It explains the sources and types of motion and related artefacts, classifies and describes existing techniques for motion detection, compensation and correction and lists established and experimental approaches. Retrospective motion correction modifies the MR image data during the reconstruction, while prospective motion correction performs an adaptive update of the data acquisition. Differences, benefits and drawbacks of different motion correction methods are discussed.