High-resolution diffusion MRI can provide the ability to resolve small brain structures, enabling investigations of detailed white matter architecture. A major challenge for in vivo high-resolution diffusion MRI is the low signal-to-noise ratio. In this work, we combine two highly compatible methods, ultra-high field and three-dimensional multi-slab acquisition to improve the SNR of high-resolution diffusion MRI. As each kz plane is encoded using a single-shot echo planar readout, scan speeds of the proposed technique are similar to the commonly used two-dimensional diffusion MRI. In-plane parallel acceleration is applied to reduce image distortions. To reduce the sensitivity of auto-calibration signal data to subject motion and respiration, several new adaptions of the fast low angle excitation echo-planar technique (FLEET) that are suitable for 3D multi-slab echo planar imaging are proposed and evaluated. A modified reconstruction scheme is proposed for auto-calibration with the most robust method, Slice-FLEET acquisition, to make it compatible with navigator correction of motion induced phase errors. Slab boundary artefacts are corrected using the nonlinear slab profile encoding method recently proposed by our group. In vivo results demonstrate that using 7T and three-dimensional multi-slab acquisition with improved auto-calibration signal acquisition and nonlinear slab boundary artefacts correction, high-quality diffusion MRI data with ~1 mm isotropic resolution can be achieved.

Functional magnetic resonance imaging (fMRI) is an emerging tool for investigating brain activation associated with, or modulated by, deep brain stimulation (DBS). However, DBS-fMRI generally suffers from severe susceptibility to artifacts in regions near the metallic stimulation electrodes, as well as near tissue/air boundaries of the brain. These result in strong intensity and geometric distortions along the phase-encoding (PE) (i.e., blipped) direction in gradient-echo echo-planar imaging (GE-EPI). Distortion presents a major challenge to conducting reliable data analysis and in interpreting the findings. A recent study showed that the point spread function (PSF) mapping-based reverse gradient approach has a potential to correct for distortions not only in spin-echo EPI, but also in GE-EPI acquired in both the forward and reverse PE directions. In this study, we adapted that approach in order to minimize severe metal-induced susceptibility artifacts for DBS-fMRI, and to evaluate the performance of the approach in a phantom study and a large animal DBS-fMRI study. The method combines the distortion-corrected GE-EPI pair with geometrically different intensity distortions due to the opposing encoding directions. The results demonstrate that the approach can minimize susceptibility artifacts that appear around the metallic electrodes, as well as in the regions near the tissue/air boundaries in the brain. We also demonstrated that an accurate geometric correction is important in improving BOLD contrast in the group dataset, especially in regions where strong susceptibility artifacts appear.

We estimated ballistocardiogram (BCG) components in EEG signals recorded inside an MRI magnet using the electro-oculogram (EOG) signals recorded simultaneously with the EEG signals. Since the EOG signals are measured near the EEG measuring points, it is thought that the BCG components in the EOG signals resemble the BCG components in the EEG signals. To estimate the BCG components in the EEG signals, we applied the Kalman filter to the EOG and EEG signals recorded inside a 3.0 T MRI magnet. After removing the estimated BCG components from the EEG signals, we extracted the visual-evoked potentials (VEPs) from the BCG-removed EEG signals. To validate the efficacy of Kalman filtering in the BCG artifact removal, we have compared three types of VEPs of eight healthy subjects: one extracted from the raw EEG signals measured outside the magnet and the others extracted from the BCG-removed EEG signals measured inside the magnet. The BCG artifacts have been removed with Kalman filtering as well as with the conventional BCG template subtraction method for the sake of comparison. No significant difference in waveforms, latencies and amplitudes has been found between the two types of VEPs extracted from the two kinds of BCG-removed EEG signals.

One of the major concerns associated with high-performance gradients is peripheral nerve stimulation (PNS) of the subject during MRI exams. Since the installation, more than 680 volunteer subjects (patients and controls) have been scanned on a compact 3 T MRI system with high-performance gradients, capable of 80 mT m−1 gradient amplitude and 700 T m−1 s−1 slew rate simultaneously. Despite PNS concerns associated with the high-performance gradients, due to the smaller physical dimensions of the gradient coils, minimal or no PNS sensation was reported with most pulse sequences. The exception was PNS reported by only five of 252 subjects (about 2%) scanned with a specific 3D fast spin echo pulse sequence (3DFLAIR). Rather than derating the entire system performance across all pulse sequences and all gradient lobes, we addressed reported PNS effect with a simple and specific modification to the targeted lobes of the problematic pulse sequence. in addition, the PNS convolutional model was adapted to predict sequence-specific PNS threshold level and its reduction after derating. The effectiveness of the targeted pulse sequence modification was demonstrated by successfully re-scanning four of the subjects who previously reported PNS sensations without further reported PNS. The pulse sequence modification did not result in noticeable degradation of image quality or substantial increase in scan time. The results demonstrated that PNS was rarely reported on the compact 3 T, and when it was, utilizing a specific modification of the gradient waveform causing PNS was an effective strategy, rather than derating the performance of the entire gradient system.