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Head motion is a fundamental problem in brain MRI. The problem is further compounded in diffusion tensor imaging because of long acquisition times, and the sensitivity of the tensor computation to even small misregistration. To combat motion artifacts in diffusion tensor imaging, a novel real-time prospective motion correction method was introduced using an in-bore monovision system. The system consists of a camera mounted on the head coil and a self-encoded checkerboard marker that is attached to the patient's forehead. Our experiments showed that optical prospective motion correction is more effective at removing motion artifacts compared to image-based retrospective motion correction. Statistical analysis revealed a significant improvement in similarity between diffusion data acquired at different time points when prospective correction was used compared to retrospective correction (P < 0.001). Magn Reson Med 66:366-378,

Purpose Previous studies in phantoms and animals using animal MR systems have shown promising results in using oscillating gradient spin echo (OGSE) diffusion acquisition to depict microstructure information. The OGSE approach has also been shown to be a sensitive biomarker of tumor treatment response and white matter-related diseases. Translating these studies to a human MR scanner faces multiple challenges due to the much weaker gradient system. The goals of the current study are to optimize the OGSE acquisition for a human MR system and investigate its applicability in the in vivo human brain. Methods An analytical analysis of the OGSE modulation spectrum was provided. Based on this analysis and thorough simulation experiments, the OGSE acquisition was optimized in terms of diffusion waveform shape, waveform timing, and sequence timing – to achieve higher diffusion sensitivity and better sampling of the diffusion spectrum. Results The trapezoid-cosine waveform was found to be the optimal OGSE waveform. At the three employed peak encoding frequencies of 18 Hz, 44 Hz, and 63 Hz, the waveform polarity for the least blurry sampling of the diffusion spectrum was 90+/180−, 90+/180+, and 90+/180+, respectively. For the highest diffusion to noise ratio (DNR) at 63 Hz, the b-value was 200 s/mm2 and the echo time was 116 ms. Using the optimized sequence, a frequency dependence of the measured ADCs was observed in white-matter-dominant regions such as the corpus callosum. Conclusion The obtained results demonstrate, for the first time, the potential of utilizing an OGSE acquisition for investigating microstructure information on a human MR system.

Noninvasive imaging of cerebral blood flow provides critical information to understand normal brain physiology as well as to identify and manage patients with neurological disorders. To date, the reference standard for cerebral blood flow measurements is considered to be positron emission tomography using injection of the [(15)O]-water radiotracer. Although [(15)O]-water has been used to study brain perfusion under normal and pathological conditions, it is not widely used in clinical settings due to the need for an on-site cyclotron, the invasive nature of arterial blood sampling, and experimental complexity. As an alternative, arterial spin labeling is a promising magnetic resonance imaging technique that magnetically labels arterial blood as it flows into the brain to map cerebral blood flow. As arterial spin labeling becomes more widely adopted in research and clinical settings, efforts have sought to standardize the method and validate its cerebral blood flow values against positron emission tomography-based cerebral blood flow measurements. The purpose of this work is to critically review studies that performed both [(15)O]-water positron emission tomography and arterial spin labeling to measure brain perfusion, with the aim of better understanding the accuracy and reproducibility of arterial spin labeling relative to the positron emission tomography reference standard.

Readout segmentation (RS-EPI) has been suggested as a promising variant to echo-planar imaging (EPI) for high-resolution imaging, particularly when combined with parallel imaging. This work details some of the technical aspects of diffusionweighted (DW)-RS-EPI, outlining a set of reconstruction methods and imaging parameters that can both minimize the scan time and afford high-resolution diffusion imaging with reduced distortions. These methods include an efficient generalized autocalibrating partially parallel acquisition (GRAPPA) calibration for DW-RS-EPI data without scan time penalty, together with a variant for the phase correction of partial Fourier RS-EPI data. In addition, the role of pulsatile and rigid-body brain motion in DW-RS-EPI was assessed. Corrupt DW-RS-EPI data arising from pulsatile nonlinear brain motion had a prevalence of ϳ7% and were robustly identified via k-space entropy metrics. For DW-RS-EPI data corrupted by rigid-body motion, we showed that no blind overlap was required. Although multishot echo-planar imaging (EPI) reduces blurring and geometric distortions over single-shot EPI, a shortcoming of this method for diffusion imaging is that even minuscule physiologic motion can cause nonlinear phase errors that usually result in profound ghosting artifacts. Although navigator-based nonlinear phase correction ameliorates the ghosting problem, residual nonequidistant sampling with regionally undersampled k-space still exists and requires excessive oversampling or averaging (1). While parallel imaging can also be used to accelerate k-space traversal and reduce distortions in EPI (2,3), the net acceleration for EPI is currently limited to realistic values of 3 and 4, producing images that still suffer from distortion artifacts, especially at high field strengths or higher spatial resolution.Instead of interleaving EPI trajectories along the phaseencoding dimension (k PE ) to increase k-space velocity, another variant of multishot EPI for diffusion-weighted (DW) imaging is readout-segmented EPI (RS-EPI) (4-11). In RS-EPI, adjacent 'blinds' are acquired (each accompanied with a navigator) to produce the combined k-space data that support the desired resolution along the readout dimension (k RO ). RS-EPI increases the k-space velocity compared with EPI by shortening the trajectory along k RO , thus diminishing distortions. Further distortion reduction can be achieved in RS-EPI via parallel imaging methods (7,9,10). Here, the net gain in acceleration of k-space traversal compared with standard single-shot EPI is governed by the blind width, the GRAPPA-acceleration factor, and slew rate constraints (shown in Table 1). Ignoring slew rate limitations, an RS-EPI scan theoretically offers an N/#blinds-fold distortion reduction over a conventional single-shot EPI scan.Due to its greater data consistency within the blind, in practice, DW-RS-EPI is much more manageable for motion and phase correction than interleaved DW-EPI (9). However, despite the consistency of each blind, a potential problem can ari...