A robust algorithm for reduction of truncation artifact in chemical shift images

Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer-volume suppression saturation bands

PURPOSE

To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands.

MATERIALS AND METHODS

The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality.

RESULTS

3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality.

CONCLUSION

The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases.

Truncation artifact reduction in spectroscopic imaging using a dual-density spiral k-space trajectory

Truncation artifacts arise in magnetic resonance spectroscopic imaging (MRSI) of the human brain due to limited coverage of k-space necessitated by low SNR of metabolite signal and limited scanning time. In proton MRSI of the head, intense extra-cranial lipid signals "bleed" into brain regions, thereby contaminating signals of metabolites therein. This work presents a data acquisition strategy for reducing truncation artifact based on extended k-space coverage achieved with a dual-SNR strategy. Using the fact that the SNR in k-space increases monotonically with sampling density, dual-SNR is achieved in an efficient manner with a dual-density spiral k-space trajectory that permits a smooth transition from high density to low density. The technique is demonstrated to be effective in reducing "bleeding" of extra-cranial lipid signals while preserving the SNR of metabolites in the brain.

Extension of finite-support extrapolation using the generalized series model for MR spectroscopic imaging

In magnetic resonance (MR) imaging, limited data sampling in k-space leads to the well-known Fourier truncation artifact, which includes ringing and blurring. This problem is particularly severe for MR spectroscopic imaging, where only 16-24 points are typically acquired along each spatial dimension. Several methods have been proposed to overcome this problem by incorporating prior information in the image reconstruction. These include the generalized series (GS) model and the finite-support extrapolation method. This paper shows the connection between finite-support extrapolation and the GS model. In particular, finite-support extrapolation is a limiting case of the GS model, when the only available prior information is the support region. The support region refers to those image portions with nonzero intensities, and it can be estimated in practice as the nonbackground region of an image. By itself, the support region constitutes a rather weak constraint that may not lead to considerable resolution gain. This situation can be improved by using additional prior information, which can be incorporated systematically with the GS model. Examples of such additional prior information include intensity estimates of anatomical structures inside the support region.

Comparison of methods for reduction of lipid contamination for in vivo proton MR spectroscopic imaging of the brain

In vivo proton MR spectroscopic imaging (MRSI) of human brain is complicated by the presence of a strong signal from subcutaneous lipids, which may result in signal contamination in metabolite images obtained following Fourier-transform reconstruction. In this study, two approaches for reduction of lipid contamination--using postprocessing and additional data acquisition--are compared. The first uses extrapolation of k-space information for subcutaneous lipid, which has been applied to data obtained using conventional fully phase-encoded MRSI with circularly sampled k-space or echo-planar spectroscopic imaging (EPSI). The second uses a dual EPSI technique that combines multiple-averaged central k-space data with a single EPSI acquisition of additional information that is used for improved lipid reconstruction. Comparisons are carried out with data obtained from human brain in vivo at 1.5 T with short and medium TEs. Results demonstrate that the performance of both methods for reducing the effects of lipid contamination is similar, and that both are limited by the effects of instrumental instabilities and subject motion, which also depend on the acquisition method used.

A hybrid technique for spectroscopic imaging with reduced truncation artifact

Traditionally, Fourier spectroscopic imaging is associated with a small k-space coverage which leads to truncation artifacts such as "bleeding" and ringing in the resultant image. Because substantial truncation artifacts mainly arise from regions having intense signals, such as the subcutaneous lipid in the head, effective reduction of truncation artifacts can be achieved by obtaining an extended k-space coverage for these regions. In this paper, a hybrid technique which employs phase-encoded spectroscopic imaging (SI) to cover the central portion of the k-space and echo-planar spectroscopic imaging (EPSI) to measure the peripheral portion of the k-space is developed. EPSI, despite its inherently low SNR characteristics, provides a sufficient SNR for outer high-spatial frequency components of the aforementioned high signal regions and supplies an extended k-space coverage of these regions for the reduction of truncation artifacts. The data processing includes steps designed to remove inconsistency between the two types of data and a previously described technique for selectively retaining only outer k-space information for the high signal regions during the reconstruction. Experimental studies, in both phantoms and normal volunteers, demonstrate that the hybrid technique provides significant reduction in truncation artifacts.