Image reconstruction for magnetic resonance spectroscopic imaging (MRSI) requires specialized spatial and spectral data processing methods and benefits from the use of several sources of prior information that are not commonly available, including MRI-derived tissue segmentation, morphological analysis and spectral characteristics of the observed metabolites. In addition, incorporating information obtained from MRI data can enhance the display of low-resolution metabolite images and multiparametric and regional statistical analysis methods can improve detection of altered metabolite distributions. As a result, full MRSI processing and analysis can involve multiple processing steps and several different data types. In this paper, a processing environment is described that integrates and automates these data processing and analysis functions for imaging of proton metabolite distributions in the normal human brain. The capabilities include normalization of metabolite signal intensities and transformation into a common spatial reference frame, thereby allowing the formation of a database of MR-measured human metabolite values as a function of acquisition, spatial and subject parameters. This development is carried out under the MIDAS project (Metabolite Imaging and Data Analysis System), which provides an integrated set of MRI and MRSI processing functions. It is anticipated that further development and distribution of these capabilities will facilitate more widespread use of MRSI for diagnostic imaging, encourage the development of standardized MRSI acquisition, processing and analysis methods and enable improved mapping of metabolite distributions in the human brain.

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For many clinical applications of proton MR spectroscopic imaging (MRSI) of the brain, diagnostic assessment is limited by insufficient coverage provided by single-or multislice acquisition methods as well as by the use of volume preselection methods. Additionally, traditional spectral analysis methods may limit the operator to detailed analysis of only a few selected brain regions. It is therefore highly desirable to use a fully 3D approach, combined with spectral analysis procedures that enable automated assessment of 3D metabolite distributions over the whole brain. In this study, a 3D echo-planar MRSI technique has been implemented without volume preselection to provide sufficient spatial resolution with maximum coverage of the brain. Using MRSI acquisitions in normal subjects at 1.5T and a fully automated spectral analysis procedure, an assessment of the resultant spectral quality and the extent of viable data in human brain was carried out. The analysis found that 69% of brain voxels were obtained with acceptable spectral quality at TE ‫؍‬ 135 ms, and 52% at TE ‫؍‬ For most diagnostic imaging applications it is of benefit to obtain data from a wide, 3D, tissue region; however, most MR spectroscopic imaging (MRSI) methods have been implemented as a single-or multiplane 2D acquisition. This has primarily been due to the time requirements for obtaining an additional spatial dimension by phase encoding, but also because of difficulties associated with shimming over a larger volume, water suppression, and contamination from subcutaneous lipid. An additional consideration has been the use of labor-intensive spectral analysis methods, since earlier MRSI studies have used operator-assisted spectral analysis to address difficulties associated with B 0 shifts, variable lineshapes, and separation of metabolite resonances from complex underlying baseline signals. This has frequently meant that data analysis was limited to only a few operator-selected voxels, in which case single-slice MRSI acquisition methods were generally suitable. These factors have limited MRSI studies to measurements in only a few more central brain regions, and large, vitally important, regions of the brain have been excluded from study, making poor use of the available metabolic information. An additional disadvantage of slice-selection approaches is that even some central brain structures cannot be adequately covered using a 2D image format.Volumetric MRSI using spatial phase-encoding has been used for 31 P studies in human brain (1), or 1

Spectral quality in 1 H magnetic resonance spectroscopic imaging (MRSI) critically depends on the stability of the main magnetic field. For echo-planar MRSI implemented at 3 T, temperature variation in the passive steel shims of the magnet system can lead to a significant drift in the resonance frequency. A method is presented that incorporates interleaved measurement of the instantaneous resonance frequency of a reference water signal into a volumetric MRSI sequence and allows correction for the drift during postprocessing. Key words: in vivo MR spectroscopic imaging; brain; instrumental instabilities; frequency drift; EPSI Even small instrumental instabilities can limit the data quality for MR spectroscopy and spectroscopic imaging (MRSI). For example, the small field drift of the main magnetic field, B 0 , of superconducting magnets (Ͻ0.1 ppm/hr) can result in a measurable frequency shift over the course of a MRSI acquisition that results in suboptimal water suppression, broadening of spectral lines, and loss of phase coherence (1). An additional source of instability that can occur on higher-field MRI systems, i.e., with B 0 Ն 3 T, is heating of the gradient coil former and thermally coupled passive steel shims, due to either high shim currents or strong magnetic field gradients, which can cause a change in the resonance frequency that is several-fold higher than the magnet field stability (2). An elegant solution was proposed for single-voxel spectroscopy using an interleaved, nonlocalized water reference signal to obtain a frequency estimate and applying a negative feedback in real time to the Z0 shim coil current (2). However, implementation of this interleaved nonlocalized B 0 measurement is undesirable for spectroscopic imaging of the brain, where it is also desirable to obtain a localized and phase-encoded water reference signal, which can be used for measurement and correction of local B 0 variations of the metabolite data (3). The acquisition of both localized and nonlocalized B 0 measurements and execution of the real-time B 0 correction are time consuming and would lengthen the minimum TR of the pulse sequence (2) and thus the total acquisition time.In this paper, we show that a spatially varying drift of the resonance frequency occurs during the prolonged use of strong, oscillating readout gradients for a volumetric echo-planar spectroscopic imaging (3D EPSI) pulse sequence on a 3-T magnet and present a method for detection and correction of this effect, as well as frequency shifts induced due to subject motion. METHODSA volumetric proton EPSI acquisition sequence has been implemented on a 3-T Trio system (Siemens Medical Systems, Germany) as illustrated in Fig. 1. The sequence is similar to that described earlier (4), with the incorporation of an interleaved water reference acquisition. Data were acquired in normal human brain with TR ϭ 1710 msec, TE ϭ 70 msec, and TI ϭ 198 msec for global inversionrecovery used for lipid suppression. Additional timings shown in Fig. 1 include TR wr ϭ 591 msec, t...