A single-scan T2* mapping method based on two gradient-echo images with compensation for macroscopic field inhomogeneity

Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences

Purpose

To reduce the misbalance between compensation gradients and macroscopic field gradients, we introduce an adaptive slice‐specific z‐shimming approach for 2D spoiled multi‐echo gradient‐echoe sequences in combination with modeling of the signal decay.

Methods

Macroscopic field gradients were estimated for each slice from a fast prescan (15 seconds) and then used to calculate slice‐specific compensation moments along the echo train. The coverage of the compensated field gradients was increased by applying three positive and three negative moments. With a forward model, which considered the effect of the slice profile, the z‐shim moment, and the field gradient, R2∗ maps were estimated. The method was evaluated in phantom and in vivo measurements at 3 T and compared with a spoiled multi‐echo gradient‐echo and a global z‐shimming approach without slice‐specific compensation.

Results

The proposed method yielded higher SNR in R2∗ maps due to a broader range of compensated macroscopic field gradients compared with global z‐shimming. In global white matter, the mean interquartile range, proxy for SNR, could be decreased to 3.06 s⁻¹ with the proposed approach, compared with 3.37 s⁻¹ for global z‐shimming and 3.52 s⁻¹ for uncompensated multi‐echo gradient‐echo.

Conclusion

Adaptive slice‐specific compensation gradients between echoes substantially improved the SNR of R2∗ maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.

Improved susceptibility weighted imaging method using multi-echo acquisition

PURPOSE

To introduce novel acquisition and postprocessing approaches for susceptibility weighted imaging (SWI) to remove background field inhomogeneity artifacts in both magnitude and phase data.

METHODS

The proposed method acquires three echoes in a three-dimensional gradient echo (GRE) sequence, with a field compensation gradient (z-shim gradient) applied to the third echo. The artifacts in the magnitude data are compensated by signal estimation from all three echoes. The artifacts in phase signals are removed by modeling the background phase distortions using Gaussians. The method was applied in vivo and compared with conventional SWI.

RESULTS

The method successfully compensates for background field inhomogeneity artifacts in magnitude and phase images, and demonstrated improved SWI images. In particular, vessels in frontal lobe, which were not observed in conventional SWI, were identified in the proposed method.

CONCLUSION

The new method improves image quality in SWI by restoring signal in the frontal and temporal regions.

Setup and data analysis for functional magnetic resonance imaging of awake cat visual cortex

Functional magnetic resonance imaging (fMRI) is one of the most commonly used methods in cognitive neuroscience on humans. In recent decades, fMRI has also been used in the awake monkey experiments to localize functional brain areas and to compare the functional differences between human and monkey brains. Several procedures and paradigms have been developed to maintain proper head fixation and to perform motion control training. In this study, we extended the application of fMRI to awake cats without training, receiving a flickering checkerboard visual stimulus projected to a screen in front of them in a block-design paradigm. We found that body movement-induced non-rigid motion introduced artifacts into the functional scans, especially those around the eye and neck. To correct for these artifacts, we developed two methods: one for general experimental design, and the other for studies of whether a checkerboard task could be used as a localizer to optimize the motion-correction parameters. The results demonstrated that, with proper animal fixation and motion correction procedures, it is possible to perform fMRI experiments with untrained awake cats.