PSF-choice: a novel MRI method for shaping point-spread functions in phase-encoding dimensions

Improved spatial localization in magnetic resonance spectroscopic imaging with two-dimensional PSF-Choice encoding

PURPOSE

Magnetic resonance spectroscopic imaging (MRSI), under low-spatial resolution settings, often suffers signal contamination from neighboring voxels due to ringing artifacts. Spatial localization can be improved by constraining the point-spread-function (PSF). Here the effectiveness of the two-dimensional PSF-Choice technique in providing improved spatial localization for MRSI is demonstrated.

THEORY AND METHODS

The PSF-Choice technique constrains the PSF to a desired shape by manipulating the weighting of RF excitation pulse throughout phase-encode steps. Based on a Point REsolved SpectroScopy (PRESS)-type sequence, PSF-Choice encoding was implemented along two dimensions to excite a two-dimensional Gaussian profile, by replacing the usual RF excitation pulse with a train of pulses that is modified at each phase-encoding step. The method was proven mathematically, and demonstrated experimentally in phantoms containing prostate relevant metabolic compounds of choline, creatine and citrate.

RESULTS

Using a dedicated prostate-mimicking spectroscopy phantom surrounded by oil, it was found that there is significantly less signal contamination from oil for PSF-Choice encoding compared with standard phase encoding. In particular, with standard phase encoding, there was a significant difference (p = 0.014) between ratios of Choline + Creatine to Citrate for voxels well within the phantom compared to voxels within the phantom but near the boundary with oil. The ratios in boundary voxels were also significantly different (p = 0.035) from reference values obtained using the prostate phantom with no oil present. In contrast, no significant differences were found in comparisons of these ratios when encoding with PSF-Choice.

CONCLUSION

The PSF-Choice scheme applied along two dimensions produces MR spectroscopic images with substantially reduced truncation artifacts and spectral contamination.

Investigation of the PSF-choice method for reduced lipid contamination in prostate MR spectroscopic imaging

The purpose of this work was to evaluate a previously proposed approach that aims to improve the point spread function (PSF) of MR spectroscopic imaging (MRSI) to avoid corruption by lipid signal arising from neighboring voxels. Retrospective spatial filtering can be used to alter the PSF; however, this either reduces spatial resolution or requires extending the acquisition in k-space at the cost of increased imaging time. Alternatively, the method evaluated here, PSF-choice, can modify the PSF localization to reduce the contamination from adjacent lipids by conforming the signal response more closely to the desired MRSI voxel grid. This is done without increasing scan time or degrading SNR of important metabolites. PSF-choice achieves improvements in spatial localization through modifications to the radiofrequency excitation pulses. An implementation of this method is reported for MRSI of the prostate, where it is demonstrated that, in 13 of 16 pilot prostate MRSI scans, intravoxel spectral contamination from lipid was significantly reduced when using PSF-choice. Phantom studies were also performed that demonstrate, compared with MRSI with standard Fourier phase encoding, out-of-voxel signal contamination of spectra was significantly reduced in MRSI with PSF-choice.

Non-spin-echo 3D transverse hadamard encoded proton spectroscopic imaging in the human brain

A non-spin-echo multivoxel proton MR localization method based on three-dimensional transverse Hadamard spectroscopic imaging is introduced and demonstrated in a phantom and the human brain. Spatial encoding is achieved with three selective 90° radiofrequency pulses along perpendicular axes: The first two create a longitudinal ±M(Z) Hadamard order in the volume of interest. The third pulse spatially Hadamard-encodes the ±M(Z)s in the volume of interest in the third direction while bringing them to the transverse plane to be acquired immediately. The approaching-ideal point spread function of Hadamard encoding and very short acquisition delay yield signal-to-noise-ratios of 20 ± 8, 23 ± 9, and 31 ± 10 for choline, creatine, and N-acetylaspartate in the human brain at 1.5 T from 1 cm(3) voxels in 21 min. The advantages of transverse Hadamard spectroscopic imaging are that unlike gradient (Fourier) phase-encoding: (i) the volume of interest does not need to be smaller than the field of view to prevent aliasing; (ii) the number of partitions in each direction can be small, 8, 4, or even 2 at no cost in point spread function; (iii) the volume of interest does not have to be contiguous; and (iv) the voxel profile depends on the available B1 and pulse synthesis paradigm and can, therefore, at least theoretically, approach "ideal" "1" inside and "0" elsewhere.

Magnetic resonance Spectroscopy with Linear Algebraic Modeling (SLAM) for higher speed and sensitivity

Speed and signal-to-noise ratio (SNR) are critical for localized magnetic resonance spectroscopy (MRS) of low-concentration metabolites. Matching voxels to anatomical compartments a priori yields better SNR than the spectra created by summing signals from constituent chemical-shift-imaging (CSI) voxels post-acquisition. Here, a new method of localized Spectroscopy using Linear Algebraic Modeling (SLAM) is presented, that can realize this additional SNR gain. Unlike prior methods, SLAM generates spectra from C signal-generating anatomic compartments utilizing a CSI sequence wherein essentially only the C central k-space phase-encoding gradient steps with highest SNR are retained. After MRI-based compartment segmentation, the spectra are reconstructed by solving a sub-set of linear simultaneous equations from the standard CSI algorithm. SLAM is demonstrated with one-dimensional CSI surface coil phosphorus MRS in phantoms, the human leg and the heart on a 3T clinical scanner. Its SNR performance, accuracy, sensitivity to registration errors and inhomogeneity, are evaluated. Compared to one-dimensional CSI, SLAM yielded quantitatively the same results 4-times faster in 24 cardiac patients and healthy subjects. SLAM is further extended with fractional phase-encoding gradients that optimize SNR and/or minimize both inter- and intra-compartmental contamination. In proactive cardiac phosphorus MRS of six healthy subjects, both SLAM and fractional-SLAM (fSLAM) produced results indistinguishable from CSI while preserving SNR gains of 36-45% in the same scan-time. Both SLAM and fSLAM are simple to implement and reduce the minimum scan-time for CSI, which otherwise limits the translation of higher SNR achievable at higher field strengths to faster scanning.

Spatial localization in nuclear magnetic resonance spectroscopy

The ability to select a discrete region within the body for signal acquisition is a fundamental requirement of in vivo NMR spectroscopy. Ideally, it should be possible to tailor the selected volume to coincide exactly with the lesion or tissue of interest, without loss of signal from within this volume or contamination with extraneous signals. Many techniques have been developed over the past 25 years employing a combination of RF coil properties, static magnetic field gradients and pulse sequence design in an attempt to meet these goals. This review presents a comprehensive survey of these techniques, their various advantages and disadvantages, and implications for clinical applications. Particular emphasis is placed on the reliability of the techniques in terms of signal loss, contamination and the effect of nuclear relaxation and J-coupling. The survey includes techniques based on RF coil and pulse design alone, those using static magnetic field gradients, and magnetic resonance spectroscopic imaging. Although there is an emphasis on techniques currently in widespread use (PRESS, STEAM, ISIS and MRSI), the review also includes earlier techniques, in order to provide historical context, and techniques that are promising for future use in clinical and biomedical applications.