• Magn Reson Med · Jan 2009

    Implementation of three-dimensional wavelet encoding spectroscopic imaging: in vivo application and method comparison.

    • Richard Young and Hacene Serrai.
    • Institute for Biodiagnostics (IBD), National Research Council, Winnipeg, MB, Canada.
    • Magn Reson Med. 2009 Jan 1; 61 (1): 6-15.

    AbstractWe have recently proposed a two-dimensional Wavelet Encoding-Spectroscopic Imaging (WE-SI) technique as an alternative to Chemical Shift Imaging (CSI), to reduce acquisition time and crossvoxel contamination in magnetic resonance spectroscopic imaging (MRSI). In this article we describe the extension of the WE-SI technique to three dimensions and its implementation on a clinical 1.5 T General Electric (GE) scanner. Phantom and in vivo studies are carried out to demonstrate the usefulness of this technique for further acquisition time reduction with low voxel contamination. In wavelet encoding, a set of dilated and translated prototype functions called wavelets are used to span a localized space by dividing it into a set of subspaces with predetermined sizes and locations. In spectroscopic imaging, this process is achieved using radiofrequency (RF) pulses with profiles resembling the wavelet shapes. Slice selective excitation and refocusing RF pulses, with single-band and dual-band profiles similar to Haar wavelets, are used in a modified PRESS sequence to acquire 3D WE-SI data. Wavelet dilation and translation are achieved by changing the strength of the localization gradients and frequency shift of the RF pulses, respectively. The desired spatial resolution in each direction sets the corresponding number of dilations (increases in the localization gradients), and consequently, the number of translations (frequency shift) of the Haar wavelets (RF pulses), which are used to collect magnetic resonance (MR) signals from the corresponding subspaces. Data acquisition time is reduced by using the minimum recovery time (TR(min)), also called effective time, when successive MR signals from adjacent subspaces are collected. Inverse wavelet transform is performed on the acquired data to produce metabolite maps. The proposed WE-SI method is compared in terms of acquisition time, pixel bleed, and signal-to-noise ratio to the CSI technique. The study outcome shows that 3D WE-SI provides accurate results while reducing both acquisition time and voxel contamination.

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