Gilbert Hangel

Mapping of brain macromolecules and their use for spectral processing of (1)H-MRSI data with an ultra-short acquisition delay at 7 T.

Long echo time (TE) MR spectroscopy (MRS) sequences are sensitive only to metabolites of low molecular weight. At shorter TE, significantly more metabolite signals are detectable, including broad signals of high-molecular-weight macromolecules (MMs). Although the presence of MM resonances can bias metabolite quantification at short TE, proper quantification of MMs is important since MMs themselves may serve as potentially valuable biomarkers for many pathologies. We have therefore developed an FID-based 2D-MR Spectroscopic Imaging (2D-MRSI) sequence to map MMs in healthy brain tissue at 7 T within a scan time of ~17 min and a repetition time of 879 ms. This 2D-MRSI technique provides MM maps over a whole slice (i.e., including cortical gray matter) at an ultra-short acquisition delay of 1.3 ms, using double inversion for efficient nulling of low-molecular-weight metabolites. The optimal sequence parameters were estimated using Bloch simulations, phantom testing, and in vivo validation. The acquired in vivo MM spectra (n=6) included nine distinct MM peaks in the range of ~0.9-3.7 ppm. The measured average MM spectrum was incorporated into the LCModel basis set and utilized for further quantification of MRSI data sets without metabolite nulling, which were acquired in five additional volunteers. The quantification results for two basis sets, one including the MMs and one without MM spectrum, were compared. Due to the high spectral resolution and full signal detection provided by the FID-MRSI sequence, we could successfully map five important brain metabolites. Most quantified metabolite signal amplitudes were significantly lower since the inclusion of MMs into the basis set corrected the overestimation of metabolite signals. The precision of fit (i.e., Cramér Rao lower bounds) remained unchanged. Our MM maps show that the overall MM contribution was higher in gray matter than in white matter. In conclusion, the acquired MM spectrum improved the accuracy of metabolite quantification and allowed the acquisition of high spatial resolution maps of five major brain metabolites and also MMs.

Lipid suppression via double inversion recovery with symmetric frequency sweep for robust 2D-GRAPPA-accelerated MRSI of the brain at 7 T.

This work presents a new approach for high‐resolution MRSI of the brain at 7 T in clinically feasible measurement times. Two major problems of MRSI are the long scan times for large matrix sizes and the possible spectral contamination by the transcranial lipid signal. We propose a combination of free induction decay (FID)‐MRSI with a short acquisition delay and acceleration via in‐plane two‐dimensional generalised autocalibrating partially parallel acquisition (2D‐GRAPPA) with adiabatic double inversion recovery (IR)‐based lipid suppression to allow robust high‐resolution MRSI. We performed Bloch simulations to evaluate the magnetisation pathways of lipids and metabolites, and compared the results with phantom measurements. Acceleration factors in the range 2–25 were tested in a phantom. Five volunteers were scanned to verify the value of our MRSI method in vivo. GRAPPA artefacts that cause fold‐in of transcranial lipids were suppressed via double IR, with a non‐selective symmetric frequency sweep. The use of long, low‐power inversion pulses (100 ms) reduced specific absorption rate requirements. The symmetric frequency sweep over both pulses provided good lipid suppression (>90%), in addition to a reduced loss in metabolite signal‐to‐noise ratio (SNR), compared with conventional IR suppression (52–70%). The metabolic mapping over the whole brain slice was not limited to a rectangular region of interest. 2D‐GRAPPA provided acceleration up to a factor of nine for in vivo FID‐MRSI without a substantial increase in g‐factors (<1.1). A 64 × 64 matrix can be acquired with a common repetition time of ~1.3 s in only 8 min without lipid artefacts caused by acceleration. Overall, we present a fast and robust MRSI method, using combined double IR fat suppression and 2D‐GRAPPA acceleration, which may be used in (pre)clinical studies of the brain at 7 T.

Coil combination of multichannel MRSI data at 7 T: MUSICAL.

The goal of this study was to evaluate a new method of combining multi‐channel 1H MRSI data by direct use of a matching imaging scan as a reference, rather than computing sensitivity maps. Seven healthy volunteers were measured on a 7‐T MR scanner using a head coil with a 32‐channel array coil for receive‐only and a volume coil for receive/transmit. The accuracy of prediction of the phase of the 1H MRSI data with a fast imaging pre‐scan was investigated with the volume coil. The array coil 1H MRSI data were combined using matching imaging data as coil combination weights. The signal‐to‐noise ratio (SNR), spectral quality, metabolic map quality and Cramér–Rao lower bounds were then compared with the data obtained by two standard methods, i.e. using sensitivity maps and the first free induction decay (FID) data point. Additional noise decorrelation was performed to further optimize the SNR gain. The new combination method improved significantly the SNR (+29%), overall spectral quality and visual appearance of metabolic maps, and lowered the Cramér–Rao lower bounds (−34%), compared with the combination method based on the first FID data point. The results were similar to those obtained by the combination method using sensitivity maps, but the new method increased the SNR slightly (+1.7%), decreased the algorithm complexity, required no reference coil and pre‐phased all spectra correctly prior to spectral processing. Noise decorrelation further increased the SNR by 13%. The proposed method is a fast, robust and simple way to improve the coil combination in 1H MRSI of the human brain at 7 T, and could be extended to other 1H MRSI techniques.

Ultra-high resolution brain metabolite mapping at 7 T by short-TR Hadamard-encoded FID-MRSI ☆

ABSTRACT MRSI in the brain at ≥7 T is a technique of great promise, but has been limited mainly by low B0/B1+‐homogeneity, specific absorption rate restrictions, long measurement times, and low spatial resolution. To overcome these limitations, we propose an ultra‐high resolution (UHR) MRSI sequence that provides a 128×128 matrix with a nominal voxel volume of 1.7×1.7×8 mm3 in a comparatively short measurement time. A clinically feasible scan time of 10–20 min is reached via a short TR of 200 ms due to an optimised free induction decay‐based acquisition with shortened water suppression as well as parallel imaging (PI) using Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA). This approach is not limited to a rectangular region of interest in the centre of the brain, but also covers cortical brain regions. Transversal pulse‐cascaded Hadamard encoding was able to further extend the coverage to 3D‐UHR‐MRSI of four slices (100×100×4 matrix size), with a measurement time of 17 min. Lipid contamination was removed during post‐processing using L2‐regularisation. Simulations, phantom and volunteer measurements were performed. The obtained single‐slice and 3D‐metabolite maps show the brain in unprecedented detail (e.g., hemispheres, ventricles, gyri, and the contrast between grey and white matter). This facilitates the use of UHR‐MRSI for clinical applications, such as measurements of the small structures and metabolic pathologic deviations found in small Multiple Sclerosis lesions. HIGHLIGHTSUltra‐high resolution MRSI (128×128 in‐plane matrix) at 7 T.Parallel imaging and short TR of 200 ms make UHR‐MRSI clinically feasible (10–20 min).Pulse‐cascaded Hadamard encoding provides 3D‐MRSI coverage.

(2 + 1)D-CAIPIRINHA accelerated MR spectroscopic imaging of the brain at 7T.

To compare a new parallel imaging (PI) method for multislice proton magnetic resonance spectroscopic imaging (1H‐MRSI), termed (2 + 1)D‐CAIPIRINHA, with two standard PI methods: 2D‐GRAPPA and 2D‐CAIPIRINHA at 7 Tesla (T).

Key clinical benefits of neuroimaging at 7 T

The growing interest in ultra-high field MRI, with more than 35.000 MR examinations already performed at 7 T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7 T is to gain higher spatial resolution in the brain compared to 3 T. Of specific clinical interest for neuro applications is the cerebral cortex at 7 T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7 T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7 T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7 T.

Patch-Based Super-Resolution of MR Spectroscopic Images: Application to Multiple Sclerosis

Purpose: Magnetic resonance spectroscopic imaging (MRSI) provides complementary information to conventional magnetic resonance imaging. Acquiring high resolution MRSI is time consuming and requires complex reconstruction techniques. Methods: In this paper, a patch-based super-resolution method is presented to increase the spatial resolution of metabolite maps computed from MRSI. The proposed method uses high resolution anatomical MR images (T1-weighted and Fluid-attenuated inversion recovery) to regularize the super-resolution process. The accuracy of the method is validated against conventional interpolation techniques using a phantom, as well as simulated and in vivo acquired human brain images of multiple sclerosis subjects. Results: The method preserves tissue contrast and structural information, and matches well with the trend of acquired high resolution MRSI. Conclusions: These results suggest that the method has potential for clinically relevant neuroimaging applications.

Simultaneous mapping of metabolites and individual macromolecular components via ultra-short acquisition delay 1H MRSI in the brain at 7T

Short‐echo‐time proton MR spectra at 7T feature nine to 10 distinct macromolecule (MM) resonances that overlap with the signals of metabolites. Typically, a metabolite‐nulled in vivo MM spectrum is included in the quantification`s prior knowledge to provide unbiased metabolite quantification. However, this MM model may fail if MMs are pathologically altered. In addition, information about the individual MM peaks is lost. In this study, we aimed to create an improved MM model by parameterization of the in vivo MM spectrum into individual components, and to use this new model to quantify free induction decay MR spectroscopic imaging (FID‐MRSI) data.

Ultrashort‐TE stimulated echo acquisition mode (STEAM) improves the quantification of lipids and fatty acid chain unsaturation in the human liver at 7 T

Ultrahigh‐field, whole‐body MR systems increase the signal‐to‐noise ratio (SNR) and improve the spectral resolution. Sequences with a short TE allow fast signal acquisition with low signal loss as a result of spin–spin relaxation. This is of particular importance in the liver for the precise quantification of the hepatocellular content of lipids (HCL). In this study, we introduce a spoiler Gradient‐switching Ultrashort STimulated Echo AcqUisition (GUSTEAU) sequence, which is a modified version of a stimulated echo acquisition mode (STEAM) sequence, with a minimum TE of 6 ms. With the high spectral resolution at 7 T, the efficient elimination of water sidebands and the post‐processing suppression of the water signal, we estimated the composition of fatty acids (FAs) via the detection of the olefinic lipid resonance and calculated the unsaturation index (UI) of hepatic FAs. The performance of the GUSTEAU sequence for the assessment of UI was validated against oil samples and provided excellent results in agreement with the data reported in the literature. When measuring HCL with GUSTEAU in 10 healthy volunteers, there was a high correlation between the results obtained at 7 and 3 T (R2 = 0.961). The test–retest measurements yielded low coefficients of variation for HCL (4 ± 3%) and UI (11 ± 8%) when measured with the GUSTEAU sequence at 7 T. A negative correlation was found between UI and HCL (n = 10; p < 0.033). The ultrashort TE MRS sequence (GUSTEAU; TE = 6 ms) provided high repeatability for the assessment of HCL. The improved spectral resolution at 7 T with the elimination of water sidebands and the offline water subtraction also enabled an assessment of the unsaturation of FAs. This all highlights the potential use of this MRS acquisition scheme for studies of hepatic lipid composition in vivo. Copyright

Density-weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T: DW-CONCEPT for High Resolution Brain MRSI at 7T

Full‐slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k‐space filtering, but this prolongs scan times and reduces the signal‐to‐noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR‐efficiency further. In this study, we propose an SNR‐efficient spatial‐spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming‐weighted k‐space, thus termed density‐weighted‐CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR.