Implementation of three‐dimensional wavelet encoding spectroscopic imaging: In vivo application and method comparison

Abstract

We have recently proposed a two-dimensional Wavelet EncodingSpectroscopic 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. It is well established that by acquiring metabolic information, magnetic resonance spectroscopic imaging (MRSI) provides a unique modality to noninvasively study tissue metabolism in vivo (1-6). This technique may provide early prognostic information, which aids in better understanding of tissue metabolism, differentiating between diseased and normal tissue, improving treatment, and reducing risk to the patient. However, acquiring this metabolic information in several dimensions is time consuming, especially if the classical Chemical Shift Imaging (CSI) (7,8) technique is used.To reduce acquisition time, several Fourier-based techniques that use modified high-speed imaging sequences have been proposed (9). Although these rapid techniques, like Echo Planar Imaging (EPI) (10) and spiral imaging (11), provide metabolite information with high spatial resolution and good signal-to-noise ratio (SNR), they require complicated reconstruction methods to differentiate between...

Fast magnetic resonance spectroscopic imaging (MRSI) using wavelet encoding and parallel imaging: In vitro results

“…Wavelet encoding is described in detail elsewhere [9], [13], [17] and [18]. The major steps for encoding in MRSI outlined above are briefly summarized as follows.…”

“…As a consequence, acquisition time in WE-PI is the WE-SI acquisition time [19] reduced by the factor R. Since the WE-SI technique is generally quicker than CSI [9]; the WE-PI technique is also generally quicker than PE-PI (Fig. 1). …”

“…Recently a new MRSI technique based upon wavelet encoding spectroscopic imaging (WE-SI) has been proposed as an alternative to the standard Fourier-based CSI to reduce acquisition time and pixel bleed [9]. As detailed previously [10] and [11], this technique is derived from the discrete wavelet transform which uses dilated and translated basis functions, called wavelets, to perform a linear transformation from the spatial domain to the wavelet domain [12].…”

“…The wavelet dilations and translations are achieved by changing the localization gradient strength and by shifting the frequency of the selective RF pulses, respectively. The number of wavelet dilations, which sets the number of translations, is determined by the desired number of image voxels N [9] and [13]. Because dilations of the wavelet become increasingly spatially localized, it becomes possible to choose a set of adjacent sub-volumes to be excited without waiting a full TR.…”

“…Inverse wavelet transform is performed on the collected wavelet domain data to obtain spatial metabolic information. It has been shown that, compared to Fourier-based techniques, WE-SI may achieve a high caliber of combined qualitative and quantitative results, with minimal cross voxel contamination, and with an acquisition algorithm that does not sacrifice speed [9], [10] and [13]. It is a reliable method, since it provides accurate results with shorter acquisition time and less voxel contamination compared to the standard CSI.…”