Faculty Bibliography

In radial fast spin-echo magnetic resonance imaging (MRI), a set of overlapping spokes with an inconsistent T2 weighting is acquired, which results in an averaged image contrast when employing conventional image reconstruction techniques. This work demonstrates that the problem may be overcome with the use of a dedicated reconstruction method that further allows for T2 quantification by extracting the embedded relaxation information. Thus, the proposed reconstruction method directly yields a spin-density and relaxivity map from only a single radial data set. The method is based on an inverse formulation of the problem and involves a modeling of the received MRI signal. Because the solution is found by numerical optimization, the approach exploits all data acquired. Further, it handles multicoil data and optionally allows for the incorporation of additional prior knowledge. Simulations and experimental results for a phantom and human brain in vivo demonstrate that the method yields spin-density and relaxivity maps that are neither affected by the typical artifacts from TE mixing, nor by streaking artifacts from the incomplete k-space coverage at individual echo times

The use of parallel imaging for scan time reduction in MRI faces problems with image degradation when using GRAPPA or SENSE for high acceleration factors. Although an inherent loss of SNR in parallel MRI is inevitable due to the reduced measurement time, the sensitivity to image artifacts that result from severe undersampling can be ameliorated by alternative reconstruction methods. While the introduction of GRAPPA and SENSE extended MRI reconstructions from a simple unitary transformation (Fourier transform) to the inversion of an ill-conditioned linear system, the next logical step is the use of a nonlinear inversion. Here, a respective algorithm based on a Newton-type method with appropriate regularization terms is demonstrated to improve the performance of autocalibrating parallel MRI--mainly due to a better estimation of the coil sensitivity profiles. The approach yields images with considerably reduced artifacts for high acceleration factors and/or a low number of reference lines

Rapid MR imaging using the stimulated echo acquisition mode (STEAM) technique yields single-shot images without any sensitivity to resonance offset effects. However, the absence of susceptibility-induced signal voids or geometric distortions is at the expense of a somewhat lower signal-to-noise ratio than EPI. As a consequence, the achievable spatial resolution is limited when using conventional Fourier encoding. To overcome the problem, this study combined single-shot STEAM MRI with radial encoding. This approach exploits the efficient undersampling properties of radial trajectories with use of a previously developed iterative image reconstruction method that compensates for the incomplete data by incorporating a priori knowledge. Experimental results for a phantom and human brain in vivo demonstrate that radial single-shot STEAM MRI may exceed the resolution obtainable by a comparable Cartesian acquisition by a factor of four

The finite sampling of k-space in MRI causes spurious image artifacts, known as Gibbs ringing, which result from signal truncation at the border of k-space. The effect is especially visible for acquisitions at low resolution and commonly reduced by filtering at the expense of image blurring. The present work demonstrates that the simple assumption of a piecewise-constant object can be exploited to extrapolate the data in k-space beyond the measured part. The method allows for a significant reduction of truncation artifacts without compromising resolution. The assumption translates into a total variation minimization problem, which can be solved with a nonlinear optimization algorithm. In the presence of substantial noise, a modified approach offers edge-preserving denoising by allowing for slight deviations from the measured data in addition to supplementing data. The effectiveness of these methods is demonstrated with simulations as well as experimental data for a phantom and human brain in vivo

The reconstruction of artifact-free images from radially encoded MRI acquisitions poses a difficult task for undersampled data sets, that is for a much lower number of spokes in k-space than data samples per spoke. Here, we developed an iterative reconstruction method for undersampled radial MRI which (i) is based on a nonlinear optimization, (ii) allows for the incorporation of prior knowledge with use of penalty functions, and (iii) deals with data from multiple coils. The procedure arises as a two-step mechanism which first estimates the coil profiles and then renders a final image that complies with the actual observations. Prior knowledge is introduced by penalizing edges in coil profiles and by a total variation constraint for the final image. The latter condition leads to an effective suppression of undersampling (streaking) artifacts and further adds a certain degree of denoising. Apart from simulations, experimental results for a radial spin-echo MRI sequence are presented for phantoms and human brain in vivo at 2.9 T using 24, 48, and 96 spokes with 256 data samples. In comparison to conventional reconstructions (regridding) the proposed method yielded visually improved image quality in all cases

In view of recent applications in cardiovascular and functional brain imaging, this work revisits the basic performance characteristics of spiral imaging in direct comparison to echo-planar imaging (EPI) and conventional rapid gradient-echo imaging. Using both computer simulations and experiments on phantoms and human subjects at 2.9 T, the study emphasizes single-shot applications and addresses the design of a suitable trajectory, the choice of a gridding algorithm, and the sensitivity to experimental inadequacies. As a general result, the combination of a spiral trajectory with regridding of the k-space data poses no principle obstacle for high-quality imaging. On the other hand, experimental difficulties such as gradient deviations, resonance offset contributions, and concomitant field effects cause more pronounced and even less acceptable image artifacts than usually obtained for EPI. Moreover, when ignoring parallel imaging strategies that are also applicable to EPI, improvements of image quality via reduced acquisition periods are only achievable by interleaved multishot spirals because partial Fourier sampling and rectangular fields of view (FOVs) cannot be exploited for non-Cartesian trajectories. Taken together, while spiral imaging may find its niche applications, most high-speed imaging needs are more easily served by EPI