SLIM: Spectral localization by imaging

Abstract

Nonspectroscopic magnetic resonance (MR) imaging often shows that a slice is composed of several compartments, each of which can be assumed to have a spatially homogeneous magnetic resonance spectrum, e.g., a limb composed of fat, muscle, bone marrow, and tumor. We show how to use structural information from such a nonspectroscopic image in order to increase the efficiency of subsequent localized spectroscopic measurements. Specifically, knowledge of the boundaries of N compartments makes it possible to reconstruct compartmental spectra from spectroscopic signals from an entire cross section with N or more different degrees of phase encoding. Experimental studies of a two-compartment phantom show that this method (SLIM) can be used to derive regional hydrogen spectra of a single slice from signals with as few as 2 phase-encoding steps, although Fourier transform chemical-shift imaging requires 64 steps to achieve a result of comparable accuracy. SLIM required only 16 phase-encoding steps to obtain accurate regional single slice spectra in a human limb with three compartments. Spectra of similar quality, obtained by Fourier transform chemical-shift imaging, required 256 to 1024 steps.

Hadamard‐encoding combined with two‐dimensional‐selective radiofrequency excitations for flexible and efficient acquisitions of multiple voxels in MR spectroscopy

“…An alternative to the presented approach is the SLIM (spectroscopic localization by imaging) method (19) and, in particular, its extension to SLOOP (spectral localization with optimal point spread function) (20,21), which identifies and applies a limited set of phase encoding steps from which spectra of arbitrarily shaped target volumes can be determined simultaneously. However, a sharp definition and homogenous coverage of the target volumes that can easily be realized with 2DRF excitations, requires many phase encoding steps which would yield considerably longer acquisition times.…”

Natural linewidth chemical shift imaging (NL‐CSI)

“…Hu et al (13) proposed SLIM reconstruction as an alternative to FT reconstruction to overcome the limitations of the FT approach and to speed up imaging time by reducing the number of phase-encoding steps. The SLIM approach exploits the structural information available from a highresolution MR image to reconstruct the spectroscopic imaging data.…”

“…This ringing causes intervoxel signal leakage and contaminates the signals from individual voxels. As noted above, Hu et al (13) developed the SLIM reconstruction technique to reduce scanning time and avoid spectral leakage caused by truncated Fourier series reconstruction. The technique is based on the principle that if the desired object is first segmented into a set of generalized homogeneous compartments, one can then derive the signal from each compartment by fitting the compartment model to the measured phase-encoded data.…”

“…It is assumed that these homogeneous compartments can be identified on a high-resolution proton image obtained from the same spatial coordinates as the spectroscopic imaging data. Hu et al (13) showed that, in principle, a set of only M (or more) phase-encoding data is sufficient to obtain spectra from M compartments of arbitrary shape. In an experiment with N phase-encoding steps and M͑M Յ N͒ homogeneous compartments in the object, they showed that mathematically this problem can be stated as a set of linear equations:…”

“…One such technique, spectral localization by imaging (SLIM), proposed by Hu et al (13), is used to improve scanning efficiency and eliminate intervoxel signal leakage. This technique uses model-based reconstruction whereby the spatial coordinates of the boundaries of several compartments of interest with arbitrary shape are determined based on a high-resolution MR image.…”