Quantification of magnetic resonance parameters plays an increasingly important role in clinical applications, such as the detection and classification of neurodegenerative diseases. The major obstacle that remains for its widespread use in clinical routine is the long scanning times. Therefore, strategies that allow for significant decreases in scan time are highly desired. Recently, the k-t principal component analysis method was introduced for dynamic cardiac imaging to accelerate data acquisition. This is done by undersampling k-t space and constraining the reconstruction of the aliased data based on the k-t Broad-use Linear Acquisition Speed-up Technique (BLAST) concept and predetermined temporal basis functions. The objective of this study was to investigate whether the k-t principal component analysis concept can be adapted to parameter quantification, specifically allowing for significant acceleration of an inversion recovery fast imaging with steady state precession (TrueFISP) acquisition. We found that three basis functions and a single training data line in central k-space were sufficient to achieve up to an 8-fold acceleration of the quantification measurement. This allows for an estimation of relaxation times T 1 and T 2 and spin density in one slice with sub-millimeter in-plane resolution, in only 6 s. Our findings demonstrate that the k-t principal component analysis method is a potential candidate to bring the acquisition time for magnetic resonance parameter mapping to a clinically acceptable level. Magn Reson Med 66:706-716,

Autocalibrated parallel MRI methods such as TSENSE or k-t SENSE have been presented for dynamic imaging studies as they are able to provide images with high temporal resolution. One key element of these techniques is the temporal averaging of the undersampled raw data to obtain an unaliased image. This image represents the temporal average (also known as direct current, DC) and is used to derive the reconstruction parameters. In this work, we show that aliasing artifacts can be introduced in the DC signal obtained from the undersampled raw data. These artifacts lead to undesired temporal filtering effects when the DC signal is used for coil sensitivity calibration or when the DC signal is subtracted from the raw data. It is demonstrated that the temporal filtering effects can be reduced significantly by filtering the DC signal. Magn Reson Med 66:192-198, 2011. V C 2011 Wiley-Liss, Inc.

Auto-calibrated k-t SENSE provides high quality reconstructions for dynamic imaging applications.

In recent years, the phased array coil technology has found more and more its way in applications at high field small animal systems. However, these coil arrays are usually based on simple loops and are mostly used in rat imaging studies only. Mouse imaging studies are limited to the use of linear arrays or volume resonators. Recently, a novel surface coil design based on the hole-slot magnetron's geometry was introduced to MRI. The hole-slot magnetron is a vacuum tube which operates e.g. as a high frequency oscillator in radar applications. It has been shown that the magnetron surface coil allows for a deeper RF penetration than a conventional coil both at 1.5 and 4 Tesla. The objective of this work was to find an optimal loop coil based on the hole-slot magnetron geometry in order to build a volume phased array for cardiac imaging with improved SNR on the centre of the sample. To achieve this goal, different magnetron loops were simulated and evaluated towards their performance. Based on these results the best performing hole-slot magnetron geometries were built and compared. In addition, the magnetron loop (referred as hole-slotted coil) with the best sensitivity was compared with conventional simple loop geometries. Furthermore, a four channel hole-slotted phased array based on the magnetron's design theory was built, evaluated and compared with a conventional four channel array. The four channel hole-slotted array shows improved RF penetration depth over the four channel array with simple loop geometry