Robin M. Heidemann

Generalized autocalibrating partially parallel acquisitions (GRAPPA)

In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD‐AUTO‐SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k‐space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique. Magn Reson Med 47:1202–1210, 2002.

SMASH, SENSE, PILS, GRAPPA How to Choose the Optimal Method

Fast imaging methods and the availability of required hardware for magnetic resonance tomography (MRT) have significantly reduced acquisition times from about an hour down to several minutes or seconds. With this development over the last 20 years, magnetic resonance imaging (MRI) has become one of the most important instruments in clinical diagnosis. In recent years, the greatest progress in further increasing imaging speed has been the development of parallel MRI (pMRI). Within the last 3 years, parallel imaging methods have become commercially available, and therefore are now available for a broad clinical use. The basic feature of pMRI is a scan time reduction, applicable to nearly any available MRI method, while maintaining the contrast behavior without requiring higher gradient system performance. Because of its faster image acquisition, pMRI can in some cases even significantly improve image quality. In the last 10 years of pMRI development, several different pMRI reconstruction methods have been set up which partially differ in their philosophy, in the mode of reconstruction as well in their advantages and drawbacks with regard to a successful image reconstruction. In this review, a brief overview is given on the advantages and disadvantages of present pMRI methods in clinical applications, and examples from different daily clinical applications are shown.

Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging.

In all current parallel imaging techniques, aliasing artifacts resulting from an undersampled acquisition are removed by means of a specialized image reconstruction algorithm. In this study a new approach termed “controlled aliasing in parallel imaging results in higher acceleration” (CAIPIRINHA) is presented. This technique modifies the appearance of aliasing artifacts during the acquisition to improve the subsequent parallel image reconstruction procedure. This new parallel multi‐slice technique is more efficient compared to other multi‐slice parallel imaging concepts that use only a pure postprocessing approach. In this new approach, multiple slices of arbitrary thickness and distance are excited simultaneously with the use of multi‐band radiofrequency (RF) pulses similar to Hadamard pulses. These data are then undersampled, yielding superimposed slices that appear shifted with respect to each other. The shift of the aliased slices is controlled by modulating the phase of the individual slices in the multi‐band excitation pulse from echo to echo. We show that the reconstruction quality of the aliased slices is better using this shift. This may potentially allow one to use higher acceleration factors than are used in techniques without this excitation scheme. Additionally, slices that have essentially the same coil sensitivity profiles can be separated with this technique. Magn Reson Med 53:684–691, 2005.

High resolution diffusion-weighted imaging using readout-segmented echo-planar imaging, parallel imaging and a two-dimensional navigator-based reacquisition

Single‐shot echo‐planar imaging (EPI) is well established as the method of choice for clinical, diffusion‐weighted imaging with MRI because of its low sensitivity to the motion‐induced phase errors that occur during diffusion sensitization of the MR signal. However, the method is prone to artifacts due to susceptibility changes at tissue interfaces and has a limited spatial resolution. The introduction of parallel imaging techniques, such as GRAPPA (GeneRalized Autocalibrating Partially Parallel Acquisitions), has reduced these problems, but there are still significant limitations, particularly at higher field strengths, such as 3 Tesla (T), which are increasingly being used for routine clinical imaging. This study describes how the combination of readout‐segmented EPI and parallel imaging can be used to address these issues by generating high‐resolution, diffusion‐weighted images at 1.5T and 3T with a significant reduction in susceptibility artifact compared with the single‐shot case. The technique uses data from a 2D navigator acquisition to perform a nonlinear phase correction and to control the real‐time reacquisition of unusable data that cannot be corrected. Measurements on healthy volunteers demonstrate that this approach provides a robust correction for motion‐induced phase artifact and allows scan times that are suitable for routine clinical application. Magn Reson Med, 2009.

VD-AUTO-SMASH imaging.

Recently a self‐calibrating SMASH technique, AUTO‐SMASH, was described. This technique is based on PPA with RF coil arrays using auto‐calibration signals. In AUTO‐SMASH, important coil sensitivity information required for successful SMASH reconstruction is obtained during the actual scan using the correlation between undersampled SMASH signal data and additionally sampled calibration signals with appropriate offsets in k‐space. However, AUTO‐SMASH is susceptible to noise in the acquired data and to imperfect spatial harmonic generation in the underlying coil array. In this work, a new modified type of internal sensitivity calibration, VD‐AUTO‐SMASH, is proposed. This method uses a VD k‐space sampling approach and shows the ability to improve the image quality without significantly increasing the total scan time. This new k‐space adapted calibration approach is based on a k‐space–dependent density function. In this scheme, fully sampled low‐spatial frequency data are acquired up to a given cutoff‐spatial frequency. Above this frequency, only sparse SMASH‐type sampling is performed. On top of the VD approach, advanced fitting routines, which allow an improved extraction of coil‐weighting factors in the presence of noise, are proposed. It is shown in simulations and in vivo cardiac images that the VD approach significantly increases the potential and flexibility of rapid imaging with AUTO‐SMASH. Magn Reson Med 45:1066–1074, 2001.

Controlled Aliasing in Volumetric Parallel Imaging (2D CAIPIRINHA)

The CAIPIRINHA (Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration) concept in parallel imaging has recently been introduced, which modifies the appearance of aliasing artifacts during data acquisition in order to improve the subsequent parallel imaging reconstruction procedure. This concept has been successfully applied to simultaneous multi‐slice imaging (MS CAIPIRINHA). In this work, we demonstrate that the concept of CAIPIRINHA can also be transferred to 3D imaging, where data reduction can be performed in two spatial dimensions simultaneously. In MS CAIPIRINHA, aliasing is controlled by providing individual slices with different phase cycles by means of alternating multi‐band radio frequency (RF) pulses. In contrast to MS CAIPIRINHA, 2D CAIPIRINHA does not require special RF pulses. Instead, aliasing in 2D parallel imaging can be controlled by modifying the phase encoding sampling strategy. This is done by shifting sampling positions from their normal positions in the undersampled 2D phase encoding scheme. Using this modified sampling strategy, coil sensitivity variations can be exploited more efficiently in multiple dimensions, resulting in a more robust parallel imaging reconstruction. Magn Reson Med, 2006.

How the brain tissue shapes the electric field induced by transcranial magnetic stimulation

In transcranial magnetic stimulation (TMS), knowledge of the distribution of the induced electric field is fundamental for a better understanding of the position and extent of the stimulated brain region. However, the different tissue types and the varying fibre orientation in the brain tissue result in an inhomogeneous and anisotropic conductivity distribution and distort the electric field in a non-trivial way. Here, the field induced by a figure-8 coil is characterized in detail using finite element calculations and a geometrically accurate model of an individual head combined with high-resolution diffusion-weighted imaging for conductivity mapping. It is demonstrated that the field strength is significantly enhanced when the currents run approximately perpendicular to the local gyral orientation. Importantly, the spatial distribution of this effect differs distinctly between gray matter (GM) and white matter (WM): While the field in GM is selectively enhanced at the gyral crowns and lips, high field strengths can still occur rather deep in WM. Taking the anisotropy of brain tissue into account tends to further boost this effect in WM, but not in GM. Spatial variations in the WM anisotropy affect the local field strength in a systematic way and result in localized increases of up to 40% (on average ~7% for coil orientations perpendicular to the underlying gyri). We suggest that these effects might create hot spots in WM that might contribute to the excitation of WM structures by TMS. However, our results also demonstrate the necessity of using realistic nerve models in the future to allow for more definitive conclusions.

Diffusion imaging in humans at 7T using readout-segmented EPI and GRAPPA.

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, single‐shot, 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 high‐resolution 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.

K-space and q-space: Combining ultra-high spatial and angular resolution in diffusion imaging using ZOOPPA at 7T

There is ongoing debate whether using a higher spatial resolution (sampling k-space) or a higher angular resolution (sampling q-space angles) is the better way to improve diffusion MRI (dMRI) based tractography results in living humans. In both cases, the limiting factor is the signal-to-noise ratio (SNR), due to the restricted acquisition time. One possible way to increase the spatial resolution without sacrificing either SNR or angular resolution is to move to a higher magnetic field strength. Nevertheless, dMRI has not been the preferred application for ultra-high field strength (7 T). This is because single-shot echo-planar imaging (EPI) has been the method of choice for human in vivo dMRI. EPI faces several challenges related to the use of a high resolution at high field strength, for example, distortions and image blurring. These problems can easily compromise the expected SNR gain with field strength. In the current study, we introduce an adapted EPI sequence in conjunction with a combination of ZOOmed imaging and Partially Parallel Acquisition (ZOOPPA). We demonstrate that the method can produce high quality diffusion-weighted images with high spatial and angular resolution at 7 T. We provide examples of in vivo human dMRI with isotropic resolutions of 1 mm and 800 μm. These data sets are particularly suitable for resolving complex and subtle fiber architectures, including fiber crossings in the white matter, anisotropy in the cortex and fibers entering the cortex.

Field‐of‐view limitations in parallel imaging

Parallel imaging is one of the most promising developments in recent years for the acceleration of MR acquisitions. One area of practical importance where different parallel imaging methods perform differently is the manner in which they deal with aliasing in the full‐FOV reconstructed image. It has been reported that sensitivity encoding (SENSE) reconstruction fails whenever the reconstructed FOV is smaller than the object being imaged. On the other hand, generalized autocalibrating partially parallel acquisition (GRAPPA) has been used successfully to reconstruct images with aliasing in the reconstructed FOV, as in conventional imaging. The disparate behavior of these methods can be easily demonstrated by a few simple illustrative examples. Additional in vivo examples using GRAPPA and modified SENSE (mSENSE) make this distinction clear. These experiments demonstrate that SENSE fails to reconstruct correct images when coil sensitivity maps are used that do not automatically account for the object size and therefore the aliasing in the reconstructed images. However, with the use of aliased high‐resolution coil sensitivity maps, accurate SENSE reconstructions can be generated. On the other hand, GRAPPA produces images with an aliasing appearance that is exactly as would be expected from normal nonaccelerated acquisitions. An understanding of these effects could potentially lead to fewer operator‐dependent errors, as well as a better understanding of the differences between the underlying reconstruction processes. Magn Reson Med 52:1118–1126, 2004.