Acquisition time reduction in magnetic resonance spectroscopic imaging using discrete wavelet encoding

Serrai, Haçène; Senhadji, Lotfi

doi:10.1016/j.jmr.2005.07.006

Cited by 14 publications

(47 citation statements)

References 31 publications

(46 reference statements)

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“…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.…”

Section: Theory and Methodsmentioning

confidence: 99%

“…As function of WE-SI, the equation above becomes: (13) Notice that with R = 1 (no acceleration is performed), the SNR WE-PI approaches the SNR WE-SI up to the coil factor g n .…”

Section: Signal To Noise Ratiomentioning

confidence: 99%

“…Similar to phase encoding (PE), in which an inverse Fourier transform is performed on the k-space data to obtain the input spatial function, in wavelet encoding an inverse wavelet transform is performed on the wavelet domain data (wavelet coefficients) to achieve the same task [12]. In practice, WE-SI is similar to the Hadamard technique [13] since it utilizes selective radio-frequency (RF) pulses with profiles resembling the shape of wavelets to excite the sub-volumes (by analogy to sub-spaces) of the input image FOV and acquire the corresponding magnetic resonance (MR) signals (wavelet coefficients) to fill the wavelet domain. The wavelet dilations and translations are achieved by changing the localization gradient strength and by shifting the frequency of the selective RF pulses, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Serrai

2011

Journal of Magnetic Resonance

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In previous work we have shown that wavelet encoding spectroscopic imaging (WE-SI) reduces acquisition time and voxel contamination compared to the standard Chemical Shift Imaging (CSI) also known as phase encoding (PE). In this paper, we combine the wavelet encoding method with parallel imaging (WE-PI) technique to further reduce the acquisition time by the acceleration factor R, and preserve the spatial metabolite distribution. Wavelet encoding provides results with a lower signal-to-noise ratio (SNR) than the phase encoding method. Their combination with parallel imaging, introduces an intrinsic SNR reduction. The rate of SNR reduction is slower in wavelet encoding with PI than PE with parallel imaging (PE-PI). This is due to the fact that in WE-PI, the SNR reduction is a function of the acceleration factor R and the voxel number N, whereas in PE-PI it is a function of the acceleration factor R only. Graphical abstractOne dimensional Wavelet Encoding -Parallel Imaging (WE-PI) steps for data acquisition and reconstruction (inverse wavelet transform and unfolding using coil sensitivity maps) with MR signal real part in blue and imaginary part in red. Tx is the profile of the transmitted RF pulse and Rx is the received signal for each coil, each one covering a corresponding spatial region. Highlights

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“…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.…”

Section: Theory and Methodsmentioning

confidence: 99%

“…As function of WE-SI, the equation above becomes: (13) Notice that with R = 1 (no acceleration is performed), the SNR WE-PI approaches the SNR WE-SI up to the coil factor g n .…”

Section: Signal To Noise Ratiomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Serrai

2011

Journal of Magnetic Resonance

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

Young

Serrai

2008

Magnetic Resonance in Med

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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...

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Fast data acquisition techniques in magnetic resonance spectroscopic imaging

Shankar

Chang

et al. 2019

NMR in Biomedicine

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Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal‐to‐noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k‐space. Techniques such as fast/turbo‐spin echo MRSI, echo‐planar spectroscopic imaging, and non‐Cartesian MRSI effectively cover the full k‐space in a more efficient manner per TR. On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k‐space points and employ advanced reconstruction algorithms to recreate the spatial‐spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel‐wise comparisions) with the fully sampled data. The advantages and limitations of each state‐of‐the‐art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.

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Acquisition time reduction in magnetic resonance spectroscopic imaging using discrete wavelet encoding

Cited by 14 publications

References 31 publications

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

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

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

Fast data acquisition techniques in magnetic resonance spectroscopic imaging

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