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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.

Purpose: To implement proton magnetic resonance spectroscopic imaging (1H MRSI) at 3 Tesla (3T) using an eight-channel phased-array head coil in a population of brain-tumor patients., Materials and Methods: A total of 49 MRI/MRSI examinations were performed on seven volunteers and 34 patients on a 3T GE Signa EXCITE scanner using body coil excitation and reception with an eight-channel phased-array head coil. 1H MRSI was acquired using point-resolved spectroscopy (PRESS) volume selection and three-dimensional (3D) phase encoding using a 144-msec echo time (TE)., Results: The mean choline to N-acetyl aspartate ratio (Cho/NAA) was similar within regions of normal-appearing white matter (NAWM) in volunteers (0.5 +/- 0.04) and patients (0.6 +/- 0.1, P = 0.15). This ratio was significantly higher in regions of T2-hyperintensity lesion (T2L) relative to NAWM for patients (1.4 +/- 0.7, P = 0.001). The differences between metabolite intensities in lesions and NAWM were similar, but there was an increase in SNR of 1.95 when an eight-channel head coil was used at 3T vs. previous results at 1.5T., Conclusion: The realized increase in SNR means that clinically relevant data can be obtained in five to 10 minutes at 3T and used to predict the spatial extent of tumor in a manner similar to that previously used to acquire 1.5T data in 17 minutes., (Copyright 2007 Wiley-Liss, Inc.)

Prostate MR spectroscopic imaging (MRSI) at 3T may provide two-fold higher spatial resolution over 1.5T, but this can result in longer acquisition times to cover the entire gland using conventional phase-encoding. In this study, flyback echo-planar readout trajectories were incorporated into a Malcolm Levitt's composite-pulse decoupling sequence (MLEV)-point-resolved spectroscopy sequence (PRESS) to accelerate the acquisition of large array (16 x 16 x 8), high spatial (0.154 cm(3)) resolution MRSI data by eight-fold to just 8.5 minutes. Artifact free, high-quality MRSI data was obtained in nine prostate cancer patients. Easy data reconstruction and the robustness of the flyback echo-planar encoding make this technique particularly suitable for the clinical setting. The short acquisition time provided by this method reduces the 3T prostate MRI/MRSI exam time, allows longer repetition times, and/or allows the acquisition of additional MR acquisitions within the same exam., ((c) 2007 Wiley-Liss, Inc.)

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.

3D magnetic resonance spectroscopic imaging (MRSI) has been successfully employed to extract information about brain tumor metabolism, such as cell membrane breakdown, cellular energetics, and neuronal integrity, through its ability to differentiate signals coming from choline (Cho), creatine (Cr), and N-acetyl aspartate (NAA) molecules. The additional presence of lipids within subregions of the tumor may indicate cellular membrane breakdown due to cell death. Another potential source of lipids is subcutaneous fat, which may be excited with point-resolved spectroscopy (PRESS) volume selection and aliased into the spectral field of view (FOV) due to the chemical shift artifact and the low bandwidth of the selection pulses. The purpose of our study was to employ a postprocessing method for unaliasing lipid resonances originating from in-slice subcutaneous lipids from the 3D MRSI of gliomas at 3T, using an eight-channel phased-array coil and sensitivity encoding (SENSE)., (Copyright (c) 2006 Wiley-Liss, Inc.)

This paper compares two spectral processing methods for obtaining quantitative measures from in vivo prostate spectra, evaluates their effectiveness, and discusses the necessary modifications for accurate results. A frequency domain analysis (FDA) method based on peak integration was compared with a time domain fitting (TDF) method, a model-based nonlinear least squares fitting algorithm. The accuracy of both methods at estimating the choline + creatine + polyamines to citrate ratio (CCP:C) was tested using Monte Carlo simulations, empirical phantom MRSI data and in vivo MRSI data. The paper discusses the different approaches employed to achieve the quantification of the overlapping choline, creatine and polyamine resonances. Monte Carlo simulations showed induced biases on the estimated CCP:C ratios. Both methods were successful in identifying tumor tissue, provided that the CCP:C ratio was greater than a given (normal) threshold. Both methods predicted the same voxel condition in 94% of the in vivo voxels (68 out of 72). Both TDF and FDA methods had the ability to identify malignant voxels in an artifact-free case study using the estimated CCP:C ratio. Comparing the ratios estimated by the TDF and the FDA, the methods predicted the same spectrum type in 17 out of 18 voxels of the in vivo case study (94.4%).

Magnetic resonance spectroscopic imaging (MRSI) is a powerful tool for diagnosis of many pathologic conditions. However conventional MRSI involves long scan times, in the order of 20 minutes. This work simulated an autocalibrating parallel technique based on GRAPPA algorithm for accelerating MRSI and applied it to 3 dimensional (3D) MRSI of the brain at 3 Tesla. Employing two fold undersampling in two phase-encoding directions, a four fold reduction in scantime was simulated. Metabolic parameters showed close agreement between the full and GRAPPA reconstructed spectral data.