Improved spectral quality for 3D MR spectroscopic imaging using a high spatial resolution acquisition strategy

Spectral quality in (1)H MR spectroscopic imaging (MRSI) of the brain is often significantly degraded in regions subject to local magnetic susceptibility variations, which results in broadened and distorted spectral lineshapes. In this report, a modified acquisition strategy for volumetric echo-planar spectroscopic imaging (3D EPSI) is presented that extends the region of the brain that can be observed. The data are sampled at higher spatial resolution, then corrected for local B(0) shifts and reconstructed such that the final spatial resolution matches that of 3D EPSI data acquired with the conventional lower spatial resolution. Comparison of in vivo data obtained at 1.5 T with these two acquisition schemes shows that the high spatial resolution acquisition provides considerable reduction of spectral linewidths in many problematic brain regions, though with a reduction in signal-to-noise ratio by a factor of approximately 1.4 to 1.6 for the matrix sizes used in this study. However, the effect of the increased noise was largely offset by the improved spectral quality, leading to an overall improvement of the metabolite image quality obtained using automated spectral analysis.     

High spatial resolution in vivo 2D (1)H magnetic resonance spectroscopic imaging of human muscles with a band-selective technique.

This report demonstrates a 2D (1)H magnetic resonance spectroscopic imaging (MRSI) technique that can address some technical difficulties often encountered in MRS studies of human muscles. A preliminary application of this whole-slice technique in human skeletal muscles demonstrates clearly noticeable differences in (1)H metabolite spectra between different human muscles. This observation illustrates the importance of multi-voxel and high spatial resolution in a heterogeneous environment. This technique is robust, can be easily implemented on a commercial MR scanner, and should prove useful for investigators in both basic and clinical (1)H MRS studies.     

High-resolution 3D MR spectroscopic imaging of the prostate at 3 T with the MLEV-PRESS sequence

A 3 T MLEV-point-resolved spectroscopy (PRESS) sequence employing optimized spectral-spatial and very selective outer-voxel suppression pulses was tested in 25 prostate cancer patients. At an echo time of 85 ms, the MLEV-PRESS sequence resulted in maximally upright inner resonances and minimal outer resonances of the citrate doublet of doublets. Magnetic resonance spectroscopic imaging (MRSI) exams performed at both 3 and 1.5 T for 10 patients demonstrated a 2.08+/-0.36-fold increase in signal-to-noise ratio (SNR) at 3 T as compared with 1.5 T for the center citrate resonances. This permitted the acquisition of MRSI data with a nominal spatial resolution of 0.16 cm3 at 3 T with similar SNR as the 0.34-cm3 data acquired at 1.5 T. Due to the twofold increase in spectral resolution at 3 T and the improved magnetic field homogeneity provided by susceptibility-matched endorectal coils, the choline resonance was better resolved from polyamine and creatine resonances as compared with 1.5 T spectra. In prostate cancer patients, the elevation of choline and the reduction of polyamines were more clearly observed at 3 T, as compared with 1.5 T MRSI. The increased SNR and corresponding spatial resolution obtainable at 3 T reduced partial volume effects and allowed improved detection of the presence and extent of abnormal metabolite levels in prostate cancer patients, as compared with 1.5 T MRSI.     

A 3D trajectory for undersampling k-space in MRSI applications

Magnetic resonance spectroscopic imaging (MRSI) is a noninvasive technique for producing spatially localized spectra. MRSI presents the important challenge of reducing the scan time while maintaining the spatial resolution. The preferred approach for this is to use time-varying readout gradients to collect the spatial and chemical-shift information. Fast, three-dimensional (3D) spatial encoded methods also reduce the scan time. Despite the existence of several new and faster 3D encoded methods, or k-space trajectories, for magnetic resonance imaging (MRI), only stack of spirals and echo planar have been studied in 3D MRSI. A novel formulation for designing fast, 3D k-space trajectory applicable to 3D MRSI is presented. This approach is simple and consists of rays expanding from the origin of k-space into a revolving sphere, collecting spectral data of all 3D spatial k-space at different times in the same scan. This article describes this new method and presents some results of its application to 3D MRSI. This technique allows some degree of undersampling; hence, it is possible to reconstruct high-quality undersampled spectroscopic imaging in order to recognize different compounds in short scan times. Additionally, the method is tested in regular 3D MRI. This proposed method can also be used for dynamic undersampled imaging.     

Spectroscopic imaging display and analysis.

A system for display of magnetic resonance (MR) spectroscopic imaging (SI) data is described which provides for efficient review and analysis of the multidimensional spectroscopic and spatial data format of this technique. Features include the rapid display of spectra from selected image voxels, formation of spectroscopic images, spectral and image data processing operations, methods for correlating spectroscopic image data with high resolution 1H MR images, and hardcopy facilities. Examples are shown for 31P and 1H spectroscopic imaging studies obtained in human and rat brain.     

Automatic frequency alignment and quantitation of single resonances in multiple magnetic resonance spectra via complex principal component analysis

Several algorithms for automatic frequency alignment and quantitation of single resonances in multiple magnetic resonance (MR) spectra are investigated. First, a careful comparison between the complex principal component analysis (PCA) and the Hankel total least squares-based methods for quantifying the resonances in the spectral sets of magnetic resonance spectroscopy imaging (MRSI) spectra is presented. Afterward, we discuss a method based on complex PCA plus linear regression and a method based on cross correlation of the magnitude spectra for correcting frequency shifts of resonances in sets of MR spectra. Their advantages and limitations are demonstrated on simulated MR data sets as well as on an in vivo MRSI data set of the human brain.     

Perfusion MR imaging and proton MR spectroscopic imaging in differentiating necrotizing cerebritis from glioblastoma multiforme

We describe a lesion with the magnetic resonance imaging (MRI) characteristics of a glioblastoma mutiforme and demonstrate how perfusion MRI and proton MR spectroscopic imaging can be used to differentiate necrotizing cerebritis from what appeared to be a high-grade glioma. A 43-year-old woman presented to her physician complaining of progressive visual disturbance and headache for several weeks. Conventional MRI demonstrated a parietal peripherally enhancing mass with central necrosis and moderate to severe surrounding T2 hyperintensity, suggesting an infiltrating high-grade glioma. However, advanced imaging, including dynamic susceptibility contrast MRI (DSC MRI) and magnetic resonance spectroscopic imaging (MRSI), suggested a nonneoplastic lesion. The DSC MRI data demonstrated no hyperperfusion within the lesion and surrounding T2 signal abnormality, and the MRSI data showed overall decrease in metabolites in this region, except for lactate. Because of the aggressive appearance to the lesion and the patients' worsening symptoms, a biopsy was performed. The pathologic diagnosis was necrotizing cerebritis. After the commencement of steroid therapy, imaging findings and patient symptoms improved. This report will review the utility of advanced imaging for differentiating inflammatory from neoplastic appearing lesions on conventional imaging.     

Spectroscopic imaging of the brain with phased-array coils at 3.0 T

The goal of this study was to develop and evaluate high-resolution magnetic resonance spectroscopic imaging (MRSI) utilizing the gains in signal-to-noise ratio (SNR) provided by combining higher magnetic field with high-sensitivity phased-array (PA) coils. We investigated the maximum improvement in spatial resolution as small as 0.09 cm(3) for brain MRSI while maintaining adequate SNR and acquisition time. The use of low peak power, dual-band spectral-spatial pulses was also investigated for application to 3 T MRSI of the brain using the body coil for radiofrequency excitation and PA coils for signal reception.     

Fast nosologic imaging of the brain

Magnetic resonance spectroscopic imaging (MRSI) provides information about the spatial metabolic heterogeneity of an organ in the human body. In this way, MRSI can be used to detect tissue regions with abnormal metabolism, e.g. tumor tissue. The main drawback of MRSI in clinical practice is that the analysis of the data requires a lot of expertise from the radiologists. In this article, we present an automatic method that assigns each voxel of a spectroscopic image of the brain to a histopathological class. The method is based on Canonical Correlation Analysis (CCA), which has recently been shown to be a robust technique for tissue typing. In CCA, the spectral as well as the spatial information about the voxel is used to assign it to a class. This has advantages over other methods that only use spectral information since histopathological classes are normally covering neighbouring voxels. In this paper, a new CCA-based method is introduced in which MRSI and MR imaging information is integrated. The performance of tissue typing is compared for CCA applied to the whole MR spectra and to sets of features obtained from the spectra. Tests on simulated and in vivo MRSI data show that the new method is very accurate in terms of classification and segmentation. The results also show the advantage of combining spectroscopic and imaging data.     

Short TE in vivo (1)H MR spectroscopic imaging at 1.5 T: acquisition and automated spectral analysis

Spectral analysis of short TE in vivo proton magnetic resonance spectroscopic imaging (MRSI) data are complicated by the presence of spectral overlap, low signal to noise and uncharacterized signal contributions. In this study, it is shown that an automated data analysis method can be used to generate metabolite images from MRSI data obtained from human brain at TE = 25 ms and 1.5 T when optimized pulse sequences and a priori metabolite knowledge are used. The analysis approach made use of computer simulation methods to obtain a priori spectral information of the metabolites of interest and utilized a combination of parametric spectral modeling and non-parametric signal characterization for baseline fitting. This approach was applied to data from optimized PRESS-SI and multi-slice spin-echo SI acquisitions, for which sample spectra and metabolite images are shown.     

3D sensitivity encoded ellipsoidal MR spectroscopic imaging of gliomas at 3T

Purpose

The goal of this study was to implement time efficient data acquisition and reconstruction methods for 3D magnetic resonance spectroscopic imaging (MRSI) of gliomas at a field strength of 3T using parallel imaging techniques.

Methods

The point spread functions, signal to noise ratio (SNR), spatial resolution, metabolite intensity distributions and Cho:NAA ratio of 3D ellipsoidal, 3D sensitivity encoding (SENSE) and 3D combined ellipsoidal and SENSE (e-SENSE) k-space sampling schemes were compared with conventional k-space data acquisition methods.

Results

The 3D SENSE and e-SENSE methods resulted in similar spectral patterns as the conventional MRSI methods. The Cho:NAA ratios were highly correlated (P<.05 for SENSE and P<.001 for e-SENSE) with the ellipsoidal method and all methods exhibited significantly different spectral patterns in tumor regions compared to normal appearing white matter. The geometry factors ranged between 1.2 and 1.3 for both the SENSE and e-SENSE spectra. When corrected for these factors and for differences in data acquisition times, the empirical SNRs were similar to values expected based upon theoretical grounds. The effective spatial resolution of the SENSE spectra was estimated to be same as the corresponding fully sampled k-space data, while the spectra acquired with ellipsoidal and e-SENSE k-space samplings were estimated to have a 2.36–2.47-fold loss in spatial resolution due to the differences in their point spread functions.

Conclusion

The 3D SENSE method retained the same spatial resolution as full k-space sampling but with a 4-fold reduction in scan time and an acquisition time of 9.28 min. The 3D e-SENSE method had a similar spatial resolution as the corresponding ellipsoidal sampling with a scan time of 4:36 min. Both parallel imaging methods provided clinically interpretable spectra with volumetric coverage and adequate SNR for evaluating Cho, Cr and NAA.     

Acquisition time reduction in magnetic resonance spectroscopic imaging using discrete wavelet encoding

This paper describes a new magnetic resonance spectroscopic imaging (MRSI) technique based upon the discrete wavelet transform to reduce acquisition time and cross voxel contamination. Prototype functions called wavelets are used in wavelet encoding to localize defined regions in localized space by dilations and translations. Wavelet encoding in MRSI is achieved by matching the slice selective RF pulse profiles to a set of dilated and translated wavelets. Single and dual band slice selective excitation and refocusing pulses, with profiles resembling Haar wavelets, are used in a spin-echo sequence to acquire 2D-MRSI wavelet encoding data. The 2D space region is spanned up to the desired resolution by a proportional number of dilations (increases in the localization gradients) and translations (frequency shift) of the Haar wavelets (RF pulses). Acquisition time is reduced by acquiring successive MR signals from regions of space with variable size and different locations with no requirement for a TR waiting time between acquisitions. An inverse wavelet transform is performed on the data to produce the correct spatial MR signal distribution.     

Orientational dependence of trimethyl ammonium signal in human muscles by (1)H magnetic resonance spectroscopic imaging

(1)H magnetic resonance spectroscopic imaging (MRSI) was used to investigate the effect of orientation on spectral characteristics of trimethyl ammonium (TMA) in human muscle at rest. Four different muscles in the healthy calf were studied: soleus, gastrocnemius, tibial posterior and anterior. The data demonstrate that muscle orientation can profoundly change apparent spectral characteristics of proton metabolites. In particular, muscle orientation can cause concerted changes in the spectral pattern of TMA/methyl (tCr) and methylene (Cr2) protons of creatine for a given muscle, a switch of TMA/tCr spectral patterns among different muscles and changes in the T(2) of TMA. A significant correlation was detected between TMA/tCr peaks and the Cr2 peak splitting (r=.62, P<.001). In vivo (1)H MRSI has the potential to simultaneously evaluate the orientation of muscle fibers and biochemical changes induced by a disease process or physiological activity.     

Considerations in applying 3D PRESS H-1 brain MRSI with an eight-channel phased-array coil at 3 T

The purpose of this study was to assess the benefits of a 3 T scanner and an eight-channel phased-array head coil for acquiring three-dimensional PRESS (Point REsolved Spectral Selection) proton (H-1) magnetic resonance spectroscopic imaging (MRSI) data from the brains of volunteers and patients with brain tumors relative to previous studies that used a 1.5 T scanner and a quadrature head coil. Issues that were of concern included differences in chemical shift artifacts, line broadening due to increased susceptibility at higher field strengths, changes in relaxation times and the increased complexity of the postprocessing software due to the need for combining signals from the multichannel data. Simulated and phantom spectra showed that very selective suppression pulses with a thickness of 40 mm and an overpress factor of at least 1.2 are needed to reduce chemical shift artifact and lipid contamination at higher field strengths. Spectral data from a phantom and those from six volunteers demonstrated that the signal-to-noise ratio (SNR) in the eight-channel coil was more than 50% higher than that in the quadrature head coil. For healthy volunteers and eight patients with brain tumors, the SNR at 3 T with the eight-channel coil was on average 1.5 times higher relative to the eight-channel coil at 1.5 T in voxels from normal-appearing brains. In combination with the effect of a higher field strength, the use of the eight-channel coil was able to provide an increase in the SNR of more than 2.33 times the corresponding acquisition at 1.5 T with a quadrature head coil. This is expected to be critical for clinical applications of MRSI in patients with brain tumors because it can be used to either decrease acquisition time or improve spatial resolution.     

Correction of local B0 shifts in 3D EPSI of the human brain at 4 T

High-spatial-resolution acquisition (HR) was previously proposed for 3D echo-planar spectroscopic imaging (EPSI) in combination with a high-spatial-resolution water reference EPSI data set to minimize inhomogeneous spectral line broadening, allowing for local frequency shift (B(0) shift) correction in human brain metabolite maps at 1.5 T (Ebel A et al., Magn. Reson. Imaging 21:113-120, 2003). At a higher magnetic field strength, B(0), increased field inhomogeneities typically lead to increased line broadening. Additionally, increased susceptibility variations render shimming of the main magnetic field over the whole head more difficult. This study addressed the question whether local B(0)-shift correction still helps limit line broadening in whole-brain 3D EPSI at higher magnetic fields. The combination of HR and local B(0)-shift correction to limit line broadening was evaluated at 4 T. Similar to the results at 1.5 T, the approach provided a high yield of voxels with good spectral quality for 3D EPSI, resulting in improved brain coverage.     

Wavelet Encoding Spectroscopic Imaging in Small FOV Regime: Comparison to Chemical Shift Imaging at 3?Tesla

We have recently proposed a new magnetic resonance spectroscopic imaging (MRSI) technique called wavelet encoding spectroscopic imaging (WE-SI), and described its implementation on a clinical 1.5?T scanner. This technique is proposed as an alternative to chemical shift imaging (CSI), to decrease acquisition time, and voxel contamination. The proposed method is implemented here on a clinical 3?T scanner. Phantom and in vivo studies are chosen to validate the technique at higher field, as well as to fully explore the usefulness of this technique, and find its niche of application in the chain of existing MRSI techniques. In wavelet encoding, a set of dilated and translated wavelets are used to span a localized space by dividing it into a set of sub-spaces with pre-determined sizes and locations. Due to their simple shapes, Haar wavelets are chosen. They are represented in the modified PRESS sequence by the selective excitation and refocusing radio-frequency (RF) pulses. The wavelets dilation and translation are achieved by changing the strength of the localization gradients and frequency shift of the RF pulses, respectively. Data acquisition time is reduced using the minimum recovery time when successive MR signals from adjacent sub-spaces are collected. The results obtained at 3?T confirm those obtained at 1.5?T, and demonstrate that despite the low signal-to-noise ratio, the proposed WE-SI provides accurate results and reduces both voxel contamination and acquisition time as compared to CSI. This applies especially in the small field-of-view regime where only a small number of voxels is required.     

The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification

This study investigated the value of information from both magnetic resonance imaging and magnetic resonance spectroscopic imaging (MRSI) to automated discrimination of brain tumours. The influence of imaging intensities and metabolic data was tested by comparing the use of MR spectra from MRSI, MR imaging intensities, peak integration values obtained from the MR spectra and a combination of the latter two. Three classification techniques were objectively compared: linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel as linear techniques and LS-SVM with radial basis function kernel as a nonlinear technique. Classifiers were evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic (ROC) curve (AUC) was used as a global performance measure on test data. In general, all techniques obtained a high performance when using peak integration values with or without MR imaging intensities. For example for low- versus high-grade tumours, low- versus high-grade gliomas and gliomas versus meningiomas, the mean test AUC was higher than 0.91, 0.94, and 0.99, respectively, when both MR imaging intensities and peak integration values were used. The use of metabolic data from MRSI significantly improved automated classification of brain tumour types compared to the use of MR imaging intensities solely.     

Phase-difference and spectroscopic imaging for monitoring of human brain temperature during cooling

Decrease of the human brain temperature was induced by intranasal cooling. The main purpose of this study was to compare the two magnetic resonance methods for monitoring brain temperature changes during cooling: phase-difference and magnetic resonance spectroscopic imaging (MRSI) with high spatial resolution. Ten healthy volunteers were measured. Selective brain cooling was performed through nasal cavities using saline-cooled balloon catheters. MRSI was based on a radiofrequency spoiled gradient echo sequence. The spectral information was encoded by incrementing the echo time of the subsequent eight image records. Reconstructed voxel size was 1×1×5 mm³. Relative brain temperature was computed from the positions of water spectral lines. Phase maps were obtained from the first image record of the MRSI sequence. Mild hypothermia was achieved in 15–20 min. Mean brain temperature reduction varied in the interval <−3.0; − 0.6>°C and <−2.7; − 0.7>°C as measured by the MRSI and phase-difference methods, respectively. Very good correlation was found in all locations between the temperatures measured by both techniques except in the frontal lobe. Measurements in the transversal slices were more robust to the movement artifacts than those in the sagittal planes. Good agreement was found between the MRSI and phase-difference techniques.     

An improved 1H magnetic resonance spectroscopic imaging technique for the human breast: preliminary results

The high sensitivity but poor specificity of magnetic resonance imaging for detecting breast cancer has stimulated interest in magnetic resonance spectroscopic imaging (MRSI) as a tool to improve specificity and reduce the number of benign biopsies. The challenge of applying 1H MRSI to the diagnosis of cancer in the human breast is the need for robust lipid suppression and a clinically acceptable acquisition time. We present an improved 1H MRSI technique that uses an independently optimized chemical-shift-selective for lipid suppression and weighted elliptical k-space sampling combined with a Hamming filter for improved sampling efficiency.     

Three-dimensional H spectroscopic imaging of cerebral metabolites in the rat using surface coils

Three dimensional metabolite maps of protonated metabolites were obtained using ¹H magnetic resonance spectroscopic imaging at 7 T. Surface coils were used to increase sensitivity and spatial resolution significantly over a volume coil two-dimensional acquisition. Adiabatic pulses were employed to provide homogeneous B₁ excitation and frequency selective refocusing over the volume of the rat brain. These techniques were employed to obtain three-dimensional spectroscopic imaging spectra from nominal voxel volumes of 9–30 μl from rat brain. The improved spatial resolution and sensitivity are also demonstrated with studies of focal ischemia in the rat.