Three-dimensional T(1), T(2) and proton density mapping with inversion recovery balanced SSFP.

By combining a balanced steady-state free precession (bSSFP) readout with an initial inversion pulse, all three contrast parameters, T(1), T(2) and proton density (M(0)), may be rapidly calculated from the signal progression in time. However, here it is shown that this technique is quite sensitive to variation in the applied transmit RF (B(1)) field, leading to pronounced errors in calculated values. Two-dimensional (2D) acquisitions are taxed to accurately quantify the relaxation, as the short RF pulses required by SSFP's rapid TR contain a broad spectrum of excitation angles. A 3D excitation using a large diameter excitation coil was able to correctly quantify the parameters. While the extreme B(1) sensitivity was previously problematic and has precluded use of IR-bSSFP for relaxometry, in this work these obstacles were significantly reduced, allowing the rapid quantification of T(1), T(2) and M(0). The results may further be used to simulate image contrast from common sequences, such as a T(1)-weighted or fluid-attenuated inversion recovery (FLAIR) examination.

New methods in diffusion-weighted and diffusion tensor imaging.

Considerable strides have been made by countless individual researchers in diffusion-weighted imaging (DWI) to push DWI from an experimental tool, limited to a few institutions with specialized instrumentation, to a powerful tool used routinely for diagnostic imaging. The field of DWI constantly evolves, and progress has been made on several fronts. These developments are primarily composed of improved robustness against patient and physiologic motion, increased spatial resolution, new biophysical and tissue models, and new clinical applications for DWI. This article aims to provide a succinct overview of some of these new developments and a description of some of the major challenges associated with DWI.

Perfusion mapping with multiecho multishot parallel imaging EPI.

Echo-planar imaging (EPI) is the standard technique for dynamic susceptibility-contrast (DSC) perfusion MRI. However, EPI suffers from well-known geometric distortions, which can be reduced by increasing the k-space phase velocity. Moreover, the long echo times (TEs) used in DSC lead to signal saturation of the arterial input signal, and hence to severe quantitation errors in the hemodynamic information. Here, through the use of interleaved shot acquisition and parallel imaging (PI), rapid volumetric EPI is performed using pseudo-single-shot (ss)EPI with the effective T(*)(2) blur and susceptibility distortions of a multishot EPI sequence. The reduced readout lengths permit multiple echoes to be acquired with temporal resolution and spatial coverage similar to those obtained with a single-echo method. Multiecho readouts allow for unbiased R(*)(2) mapping to avoid incorrect estimation of tracer concentration due to signal saturation or T(1) shortening effects. Multiecho perfusion measurement also mitigates the signal-to-noise ratio (SNR) reduction that results from utilizing PI. Results from both volunteers and clinical stroke patients are presented. This acquisition scheme can aid most rapid time-series acquisitions. The use of this method for DSC addresses the problem of signal saturation and T(1) contamination while it improves image quality, and is a logical step toward better quantitative MR PWI.

Identifying systematic errors in quantitative dynamic-susceptibility contrast perfusion imaging by high-resolution multi-echo parallel EPI.

Several obstacles usually confound a straightforward perfusion analysis using dynamic-susceptibility contrast-based magnetic resonance imaging (DSC-MRI). In this work, it became possible to eliminate some of these sources of error by combining a multiple gradient-echo technique with parallel imaging (PI): first, the large dynamic range of tracer concentrations could be covered satisfactorily with multiple echo times (TE) which would otherwise result in overestimation of image magnitude in the presence of noise. Second, any bias from T(1) relaxation could be avoided by fitting to the signal magnitude of multiple TEs. Finally, with PI, a good tradeoff can be achieved between number of echoes, brain coverage, temporal resolution and spatial resolution. The latter reduces partial voluming, which could distort calculation of the arterial input function. Having ruled out these sources of error, a 4-fold overestimation of cerebral blood volume and flow remained, which was most likely due to the completely different relaxation mechanisms that are effective in arterial voxels compared with tissue. Hence, the uniform tissue-independent linear dependency of relaxation rate upon tracer concentration, which is usually assumed, must be questioned. Therefore, DSC-MRI requires knowledge of the exact dependency of transverse relaxation rate upon tracer concentration in order to calculate truly quantitative perfusion maps.