Magnetic Resonance Materials in Physics, Biology and Medicine

The post-processing of MR spectroscopic data requires several steps more or less easy to automate, including the phase correction and the chemical shift assignment. First, since the absolute phase is unknown, one of the difficulties the MR spectroscopist has to face is the determination of the correct phase correction. When only a few spectra have to be processed, this is usually performed manually. However, this correction needs to be automated as soon as a large number of spectra is involved, like in the case of phase coherent averaging or when the signals collected with phased array coils have to be combined. A second post-processing requirement is the frequency axis assignment. In standard mono-voxel MR spectroscopy, this can also be easily performed manually, by simply assigning a frequency value to a well-known resonance (e.g. the water or NAA resonance in the case of brain spectroscopy). However, when the correction of a frequency shift is required before averaging a large amount of spectra (due to B 0 spatial inhomogeneities in chemical shift imaging, or resulting from motion for example), this post-processing definitely needs to be performed automatically. Zero-order phase and frequency shift of a MR spectrum are linked respectively to zero-order and first-order phase variations in the corresponding free induction decay (FID) signal. One of the simplest ways to remove the phase component of a signal is to calculate the modulus of this signal: this approach is the basis of the correction technique presented here. We show that selecting the modulus of the FID allows, under certain conditions that are detailed, to automatically phase correct and frequency align the spectra. This correction technique can be for example applied to the summation of signals acquired from combined phased array coils, to phase coherent averaging and to B 0 shift correction. We demonstrate that working on the modulus of the FID signal is a simple and efficient way to both phase correct and frequency align MR spectra automatically. This approach is particularly well suited to brain proton MR spectroscopy.

We aimed to investigate the effect of $$ T_{2}^{*} $$ correction on estimation of kinetic parameters from T 1-weighted dynamic contrast enhanced (DCE) MRI data when a reference-tissue arterial input function (AIF) is used. DCE-MRI data were acquired from seven mice with 4T1 mouse mammary tumors using a double gradient echo sequence at 7 T. The AIF was estimated from a region of interest in the muscle. The extended Tofts model was used to estimate pharmacokinetic parameters in the enhancing part of the tumor, with and without $$ T_{2}^{*} $$ correction of the lesion and AIF. The parameters estimated with $$ T_{2}^{*} $$ correction of both the AIF and lesion time-intensity curve were assumed to be the reference standard. For the whole population, there was significant difference (p < 0.05) in transfer constant (K trans) between $$ T_{2}^{*} $$ corrected and not corrected methods, but not in interstitial volume fraction (v e). Individually, no significant differences were found in K trans and v e of four and six tumors, respectively, between the $$ T_{2}^{*} $$ corrected and not corrected methods. In contrast, K trans was significantly underestimated, if the $$ T_{2}^{*} $$ correction was not used, in other tumors for which the median K trans was larger than 0.4 min−1. $$ T_{2}^{*} $$ effect on tumors with high K trans may not be negligible in kinetic model analysis, even if AIF is estimated from reference tissue where the concentration of contrast agent is relatively low.

Susceptibility artifacts along the phase-encoding (PE) direction impact the activation pattern in the amygdala and may lead to systematic asymmetries. We implemented a triple-echo echo-planar imaging (EPI) sequence, acquiring opposite PE polarities along left–right PE direction in a single shot, to investigate its effects on amygdala lateralization. Twelve subjects viewed emotional faces to evoke amygdala activation. A region of interest analysis revealed that the lateralization of amygdala responses depended on the PE polarity thus representing a pure method artifact. Alternating PE with multi-echo EPI reduced the artifact. Lateralized fMRI activation in areas with magnetic field inhomogeneities need to be interpreted with caution.

The goal of the study was to determine blood T 1 and T 2 values as functions of oxygen saturation (Y), temperature (Temp) and hematocrit (Hct) at an ultrahigh MR field (11.7 T) and explore their impacts on physiological measurements, including cerebral blood flow (CBF), blood volume (CBV) and oxygenation determination. T 1 and T 2 were simultaneously measured. Temperature was adjusted from 25 to 40°C to determine Temp dependence; Hct of 0.17–0.51 to evaluate Hct dependence at 25 and 37°C; and Y of 40–100% to evaluate Y dependence at 25 and 37°C. Comparisons were made with published data obtained at different magnetic field strengths (B 0). T 1 was positively correlated with Temp, independent of Y, and negatively correlated with Hct. T 2 was negatively correlated with Temp and Hct, but positively correlated with Y, in a non-linear fashion. T 1 increased linearly with B 0, whereas T 2 decreased exponentially with B0. This study reported blood T 1 and T 2 measurements at 11.7 T for the first time. These blood relaxation data could have implications in numerous functional and physiological MRI studies at 11.7 T.

This review article gives an account of the development of the MR-encephalography (MREG) method, which started as a mere ‘Gedankenexperiment’ in 2005 and gradually developed into a method for ultrafast measurement of physiological activities in the brain. After going through different approaches covering k-space with radial, rosette, and concentric shell trajectories we have settled on a stack-of-spiral trajectory, which allows full brain coverage with (nominal) 3 mm isotropic resolution in 100 ms. The very high acceleration factor is facilitated by the near-isotropic k-space coverage, which allows high acceleration in all three spatial dimensions. The methodological section covers the basic sequence design as well as recent advances in image reconstruction including the targeted reconstruction, which allows real-time feedback applications, and—most recently—the time-domain principal component reconstruction (tPCR), which applies a principal component analysis of the acquired time domain data as a sparsifying transformation to improve reconstruction speed as well as quality. Although the BOLD-response is rather slow, the high speed acquisition of MREG allows separation of BOLD-effects from cardiac and breathing related pulsatility. The increased sensitivity enables direct detection of the dynamic variability of resting state networks as well as localization of single interictal events in epilepsy patients. A separate and highly intriguing application is aimed at the investigation of the glymphatic system by assessment of the spatiotemporal patterns of cardiac and breathing related pulsatility. MREG has been developed to push the speed limits of fMRI. Compared to multiband-EPI this allows considerably faster acquisition at the cost of reduced image quality and spatial resolution.

To assess the possible influence of third-order shim coils on the behavior of the gradient field and in gradient–magnet interactions at 7 T and above. Gradient impulse response function measurements were performed at 5 sites spanning field strengths from 7 to 11.7 T, all of them sharing the same exact whole-body gradient coil design. Mechanical fixation and boundary conditions of the gradient coil were altered in several ways at one site to study the impact of mechanical coupling with the magnet on the field perturbations. Vibrations, power deposition in the He bath, and field dynamics were characterized at 11.7 T with the third-order shim coils connected and disconnected inside the Faraday cage. For the same whole-body gradient coil design, all measurements differed greatly based on the third-order shim coil configuration (connected or not). Vibrations and gradient transfer function peaks could be affected by a factor of 2 or more, depending on the resonances. Disconnecting the third-order shim coils at 11.7 T also suppressed almost completely power deposition peaks at some frequencies. Third-order shim coil configurations can have major impact in gradient–magnet interactions with consequences on potential hardware damage, magnet heating, and image quality going beyond EPI acquisitions.