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 multislice 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.

Simultaneous multislice imaging (SMS) using parallel image reconstruction has rapidly advanced to become a major imaging technique. The primary benefit is an acceleration in data acquisition that is equal to the number of simultaneously excited slices. Unlike in‐plane parallel imaging this can have only a marginal intrinsic signal‐to‐noise ratio penalty, and the full acceleration is attainable at fixed echo time, as is required for many echo planar imaging applications. Furthermore, for some implementations SMS techniques can reduce radiofrequency (RF) power deposition. In this review the current state of the art of SMS imaging is presented. In the Introduction, a historical overview is given of the history of SMS excitation in MRI. The following section on RF pulses gives both the theoretical background and practical application. The section on encoding and reconstruction shows how the collapsed multislice images can be disentangled by means of the transmitter pulse phase, gradient pulses, and most importantly using multichannel receiver coils. The relationship between classic parallel imaging techniques and SMS reconstruction methods is explored. The subsequent section describes the practical implementation, including the acquisition of reference data, and slice cross‐talk. Published applications of SMS imaging are then reviewed, and the article concludes with an outlook and perspective of SMS imaging. Magn Reson Med 75:63–81, 2016. © 2015 The Authors. Magnetic Resonance in Medicine Published by Wiley Periodicals, Inc. on behalf of International Society of Medicine in Resonance.

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 multislice 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 55:549 -556, 2006.

Current parallel imaging techniques for accelerated imaging require a fully encoded reference data set to estimate the spatial coil sensitivity information needed for reconstruction. In dynamic parallel imaging a time-interleaved acquisition scheme can be used, which eliminates the need for separately acquiring additional reference data, since the signal from directly adjacent time frames can be merged to build a set of fully encoded full-resolution reference data for coil calibration. In this work, we demonstrate that a time-interleaved sampling scheme, in combination with autocalibrated GRAPPA (referred to as TGRAPPA), allows one to easily update the coil weights for the GRAPPA algorithm dynamically, thereby improving the acquisition efficiency. This method may update coil sensitivity estimates frame by frame, thereby tracking changes in relative coil sensitivities that may occur during the data acquisition. Image acquisition time is one of the most important considerations for clinical magnetic resonance imaging. Recently, several partially parallel acquisition (PPA) strategies (1-7) have been described to speed up the acquisition time by decreasing the number of phase encoding steps by a reduction factor R. Normally, this undersampling is performed by increasing the distance between adjacent acquired k-space lines while maintaining the maximum kvalues. All PPA reconstruction algorithms require extra coil sensitivity information from an array of multiple radiofrequency receiver coils to remove the aliasing artifacts that result from undersampled k-space. Naturally, this sensitivity information is acquired in an additional reference experiment, thereby degrading the efficiency of the actual PPA experiment. In dynamic parallel imaging, a timeinterleaved acquisition scheme similar to UNFOLD (8) and TSENSE (9) may be exploited in order to obtain this sensitivity information directly from the actual accelerated dynamic imaging experiment, thereby realizing the full image acceleration. To this end, directly adjacent time frames can be merged to build a fully encoded, full-resolution reference data set, which can be used as autocalibration signals (ACS) for an improved GRAPPA (7) reconstruction. With every acquired time frame in the series a new set of ACS lines can be generated. This allows one to update the coil coefficients for the GRAPPA algorithm dynamically, thereby automatically tracking changes in relative coil sensitivities over time efficiently. In particular, this method is beneficial whenever coil sensitivity maps, as required for the SENSE algorithm, are difficult to obtain. This is the case in, for example, inhomogeneous regions with low signal-to-noise ratio (SNR) (e.g., the lung). In this work, TGRAPPA reconstructions of accelerated (reduction factor 2 to 4) real-time (nongated), free breathing cardiac studies are presented. METHODSAll experiments were performed on a Sonata 1.5-T clinical whole body scanner (Siemens Medical Solutions, Erlangen, Germany) equipped with eight independent receiver channe...

In this work a theoretical description for practical quantitative estimation of the noise enhancement in generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstructions, equivalent to the geometry (g)-factor in sensitivity encoding for fast MRI (SENSE) reconstructions, is described. The GRAPPA g-factor is derived directly from the GRAPPA reconstruction weights. The procedure presented here also allows the calculation of quantitative g-factor maps for both the uncombined and combined accelerated GRAPPA images. This enables, for example, a fast comparison between the performances of various GRAPPA reconstruction kernels or SENSE reconstructions. The applicability of this approach is validated on phantom studies and demonstrated using in vivo images for 1D and 2D parallel imaging. Magn Reson Med 62: 739 -746, 2009.