Longitudinal and multi-site clinical studies create the imperative to characterize and correct technological sources of variance that limit image reproducibility in high-resolution structural MRI studies, thus facilitating precise, quantitative, platform-independent, multi-site evaluation. In this work, we investigated the effects that imaging gradient non-linearity have on reproducibility of multi-site human MRI. We applied an image distortion correction method based on spherical harmonics description of the gradients and verified the accuracy of the method using phantom data. The correction method was then applied to the brain image data from a group of subjects scanned twice at multiple sites having different 1.5 T platforms. Within-site and across-site variability of the image data was assessed by evaluating voxel-based image intensity reproducibility. The image intensity reproducibility of the human brain data was significantly improved with distortion correction, suggesting that this method may offer improved reproducibility in morphometry studies. We provide the source code for the gradient distortion algorithm together with the phantom data.

Perhaps more than any other “-omics” endeavor, the accuracy and level of detail obtained from mapping the major connection pathways in the living human brain with diffusion MRI depends on the capabilities of the imaging technology used. The current tools are remarkable; allowing the formation of an “image” of the water diffusion probability distribution in regions of complex crossing fibers at each of half a million voxels in the brain. Nonetheless our ability to map the connection pathways is limited by the image sensitivity and resolution, and also the contrast and resolution in encoding of the diffusion probability distribution. The goal of our Human Connectome Project (HCP) is to address these limiting factors by re-engineering the scanner from the ground up to optimize the high b-value, high angular resolution diffusion imaging needed for sensitive and accurate mapping of the brain’s structural connections. Our efforts were directed based on the relative contributions of each scanner component. The gradient subsection was a major focus since gradient amplitude is central to determining the diffusion contrast, the amount of T2 signal loss, and the blurring of the water PDF over the course of the diffusion time. By implementing a novel 4-port drive geometry and optimizing size and linearity for the brain, we demonstrate a whole-body sized scanner with Gmax = 300mT/m on each axis capable of the sustained duty cycle needed for diffusion imaging. The system is capable of slewing the gradient at a rate of 200 T/m/s as needed for the EPI image encoding. In order to enhance the efficiency of the diffusion sequence we implemented a FOV shifting approach to Simultaneous MultiSlice (SMS) EPI capable of unaliasing 3 slices excited simultaneously with a modest g-factor penalty allowing us to diffusion encode whole brain volumes with low TR and TE. Finally we combine the multi-slice approach with a compressive sampling reconstruction to sufficiently undersample q-space to achieve a DSI scan in less than 5 minutes. To augment this accelerated imaging approach we developed a 64-channel, tight-fitting brain array coil and show its performance benefit compared to a commercial 32-channel coils at all locations in the brain for these accelerated acquisitions. The technical challenges of developing the over-all system are discussed as well as results from SNR comparisons, ODF metrics and fiber tracking comparisons. The ultra-high gradients yielded substantial and immediate gains in the sensitivity through reduction of TE and improved signal detection and increased efficiency of the DSI or HARDI acquisition, accuracy and resolution of diffusion tractography, as defined by identification of known structure and fiber crossing.

Echo planar imaging is characterized by scanning the 2D k-space after a single excitation. Different sampling patterns have been proposed. A technically feasible method uses a sinusoidal readout gradient resulting is measured data that does not sample k-space in an equidistant manner. In order to employ a conventional 2D-FFT image reconstruction, the data have to be converted to a cartesian grid. This can be done either by interpolation or alternatively by a generalized transformation. Filtering methods are described to minimize ghosting artifact that is typical in echo planar imaging. Results both from computer simulation and from experiments will be presented. Experimental images were obtained using a 2-T whole-body research system.

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Slice-selective RF waveforms that mitigate severe B 1 ؉ inhomogeneity at 7 Tesla using parallel excitation were designed and validated in a water phantom and human studies on six subjects using a 16-element degenerate stripline array coil driven with a butler matrix to utilize the eight most favorable birdcage modes. The parallel RF waveform design applied magnitude least-squares (MLS) criteria with an optimized k-space excitation trajectory to significantly improve profile uniformity compared to conventional least-squares (LS) designs. Parallel excitation RF pulses designed to excite a uniform in-plane flip angle (FA) with slice selection in the z-direction were demonstrated and compared with conventional sinc-pulse excitation and RF shimming. In all cases, the parallel RF excitation significantly mitigated the effects of inhomogeneous B 1 ؉ on the excitation FA. The optimized parallel RF pulses for human B 1 ؉ mitigation were only 67% longer than a conventional sinc-based excitation, but significantly outperformed RF shimming. Key words: parallel excitation; slice-selective excitation; RF inhomogeneity mitigation; multidimensional RF pulse; RF coil array Slice-selective excitation plays a crucial role in MRI. With the push toward higher magnetic field strength, dramatic B 1 ϩ inhomogeneity for human imaging has become a serious issue, causing inhomogeneous flip-angle (FA) distribution in-plane for slice-selective excitations and detrimental nonuniformity for both signal-to-noise ratio (SNR) and image contrast. Several RF design approaches have been suggested to compensate for this inhomogeneity, including adiabatic pulses (1,2), RF-shimming (3-6), and spatially tailored excitation designs (7-11).For relatively mild B 1 ϩ inhomogeneity, using the low-FA approximation (12) with appropriate echo-volumnar k-space trajectories (9 -11), termed either "fast-k z " or "spokes" excitation trajectories, the within-slice FA inhomogeneity can be corrected. With these pulses, slice selection is achieved with a conventional sinc-like RF pulse during each k z traversal (a spoke), and in-plane FA inhomogeneity is mitigated by the appropriate choice of the complex-valued amplitude that modulates the RF waveform of each spoke. Nonetheless, if the transmit (Tx) B 1 ϩ field is rapidly varying with position, a large number of spokes will be required at correspondingly high k x and k y locations, rendering the RF pulse too lengthy for practical use.With the introduction of parallel excitation systems (13-16), the k-space trajectory can be undersampled significantly to accelerate the RF pulse and reduce its duration. A number of successful demonstrations of this concept have been reported (e.g., . For example, it has been demonstrated at 3T (18,21) and 4.7T (17) that a parallel RF design method using low-FA approximation with spokebased excitation trajectories can produce highly uniform slice-selective excitation with reasonable excitation durations.In this work we use spoke-based excitation in combination with magnitude least-squar...