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.

The engineering of a 3T human MRI scanner equipped with 300 mT/m gradients – the strongest gradients ever built for an in vivo human MRI scanner – was a major component of the NIH Blueprint Human Connectome Project (HCP). This effort was motivated by the HCP’s goal of mapping, as completely as possible, the macroscopic structural connections of the in vivo healthy, adult human brain using diffusion tractography. Yet, the 300 mT/m gradient system is well suited to many additional types of diffusion measurements. Here, we present three initial applications of the 300mT/m gradients that fall outside the immediate scope of the HCP. These include: 1) diffusion tractography to study the anatomy of consciousness and the mechanisms of brain recovery following traumatic coma; 2) q-space measurements of axon diameter distributions in the in vivo human brain and 3) postmortem diffusion tractography as an adjunct to standard histopathological analysis. We show that the improved sensitivity and diffusion-resolution provided by the gradients is rapidly enabling human applications of techniques that were previously possible only for in vitro and animal models on small-bore scanners, thereby creating novel opportunities to map the microstructure of the human brain in health and disease.

At macroscopic scales, the human connectome is composed of anatomically distinct brain areas, the structural pathways connecting them, and their functional interactions. Successful annotation of phenotypic associations with variation in the connectome and cataloguing of neurophenotypes promise to transform our understanding of the human brain. This review provides a survey of magnetic resonance imaging-based measurements of functional and structural connectivity. We highlight emerging areas of development and inquiry, and emphasize the importance of integrating structural and functional perspectives on brain architecture.

Purpose To reduce the sensitivity of echo-planar imaging (EPI) Auto-Calibration Signal (ACS) data to patient respiration and motion in order to improve the image quality and temporal Signal-to-Noise Ratio (tSNR) of accelerated EPI time-series data. Methods ACS data for accelerated EPI are generally acquired using segmented, multi-shot EPI to distortion-match the ACS and time-series data. The ACS data are therefore typically collected over multiple TR periods, leading to increased vulnerability to motion and dynamic B0 changes. The Fast Low-angle Excitation Echo-planar Technique (FLEET) is adopted to reorder the ACS segments so that segments within any given slice are acquired consecutively in time, thereby acquiring ACS data for each slice as rapidly as possible. Results Subject breath-hold and motion phantom experiments demonstrate that artifacts in the ACS data reduce tSNR and produce tSNR discontinuities across slices in the accelerated EPI time-series data. Accelerated EPI data reconstructed using FLEET-ACS exhibit improved tSNR and increased tSNR continuity across slices. Additionally, image quality is improved dramatically when bulk motion occurs during the ACS acquisition. Conclusion FLEET-ACS provides reduced respiration and motion sensitivity in accelerated EPI, which yields higher tSNR and image quality. Benefits are demonstrated in both conventional-resolution 3T and high-resolution 7T EPI time-series data.

Anatomical MRI studies at 7T have demonstrated the ability to provide high-quality images of human tissue in vivo. However, diffusion-weighted imaging at 7T is limited by the increased level of artifact associated with standard, singleshot, echo-planar imaging, even when parallel imaging techniques such as generalized autocalibrating partially parallel acquisitions (GRAPPA) are used to reduce the effective echo spacing. Readout-segmented echo-planar imaging in conjunction with parallel imaging has the potential to reduce these artifacts by allowing a further reduction in effective echo spacing during the echo-planar imaging readout. This study demonstrates that this approach does indeed provide a substantial improvement in image quality by reducing image blurring and susceptibility-based distortions, as well as by allowing the acquisition of diffusion-weighted images with a high spatial resolution. A preliminary application of the technique to highresolution diffusion tensor imaging provided a high level of neuroanatomical detail, which should prove valuable in a wide range of applications. Magn Reson Med 64:9-14, 2010. V C 2010 Wiley-Liss, Inc. Key words: readout-segmented EPI; parallel imaging; 2D navigator; multi-shot diffusion; DTI MRI of humans at 7T can provide highly detailed anatomical brain images and perform localized functional MRI with very high spatial resolution. However, it remains a challenge to acquire good-quality diffusionweighted (DW) images at ultra-high field strengths. Single-shot echo-planar imaging (ss-EPI) is well established as the method of choice for DW imaging and therefore for diffusion tensor imaging (DTI). This is due to its low sensitivity to the motion-induced phase errors that occur during diffusion sensitization of the MR signal. However, ss-EPI is prone to artifacts related to susceptibility changes at tissue interfaces and has a limited spatial resolution due to T 2 * relaxation. Parallel imaging can be used to improve the image quality of ss-EPI acquisitions (1), but there are still significant limitations, particularly at higher field strength. Susceptibility effects and T 2 * blurring increase with field strength, and therefore parallel imaging techniques with high acceleration factors (greater than 4) are necessary to address these problems for high-resolution DW imaging and DTI (2). The shorter T 2 of brain tissue at 7T presents further difficulties by limiting the acquisition of data at long echo times (TEs). At lower field strengths, improved image quality has been demonstrated in several studies using a variety of multi-shot DW sequences, which correct for the shot-toshot, spatially varying phase errors caused by cardiac pulsation during diffusion preparation (3-6). An additional technique that can be used with nonlinear phase correction is readout-segmented echo-planar imaging (rs-EPI). Following an initial description by Robson et al. (7), the method was further developed in subsequent work to include two-dimensional (2D) navigator correction, parallel imaging, an...