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      Using the Compressed Sensing Technique for Lumbar Vertebrae Imaging: Comparison with Conventional Parallel Imaging

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          Abstract

          Objective

          To compare conventional sensitivity encoding turbo spin-echo (SENSE-TSE) with compressed sensing plus SENSE turbo spin-echo (CS-TSE) in lumbar vertebrae magnetic resonance imaging (MRI).

          Methods

          This retrospective study of lumbar vertebrae MRI included 600 patients; 300 patients received SENSE-TSE and 300 patients received CS-TSE. The SENSE acceleration factor was 1.4 for T1WI, 1.7 for T2WI, and 1.7 for PDWI. The CS total acceleration factor was 2.4, 3.6, 4.0, and 4.0 for T1WI, T2WI, PDWI sagittal, and T2WI transverse, respectively. The image quality of each MRI sequence was evaluated objectively by the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) and subjectively on a five-point scale. Two radiologists independently reviewed the MRI sequences of the 300 patients receiving CS-TSE, and their diagnostic consistency was evaluated. The degree of intervertebral foraminal stenosis and nerve root compression was assessed using the T1WI sagittal and T2WI transverse images.

          Results

          The scan time was reduced from 7 min 28 s to 4 min 26 s with CS-TSE. The median score of nerve root image quality was 5 (p > 0.05). The diagnostic consistency using CS-TSE images between the two radiologists was high for diagnosing lumbar diseases (κ > 0.75) and for evaluating the degree of lumbar foraminal stenosis and nerve root compression (κ = 0.882). No differences between SENSE-TSE and CS-TSE were observed for sensitivity, specificity, positive predictive value, or negative predictive value.

          Conclusion

          CS-TSE has the potential for diagnosing lumbar vertebrae and disc disorders.

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          Most cited references31

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          Compressed sensing

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            SENSE: Sensitivity encoding for fast MRI

            New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementary to Fourier preparation by linear field gradients. Thus, by using multiple receiver coils in parallel scan time in Fourier imaging can be considerably reduced. The problem of image reconstruction from sensitivity encoded data is formulated in a general fashion and solved for arbitrary coil configurations and k-space sampling patterns. Special attention is given to the currently most practical case, namely, sampling a common Cartesian grid with reduced density. For this case the feasibility of the proposed methods was verified both in vitro and in vivo. Scan time was reduced to one-half using a two-coil array in brain imaging. With an array of five coils double-oblique heart images were obtained in one-third of conventional scan time. Magn Reson Med 42:952-962, 1999. Copyright 1999 Wiley-Liss, Inc.
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              Sparse MRI: The application of compressed sensing for rapid MR imaging.

              The sparsity which is implicit in MR images is exploited to significantly undersample k-space. Some MR images such as angiograms are already sparse in the pixel representation; other, more complicated images have a sparse representation in some transform domain-for example, in terms of spatial finite-differences or their wavelet coefficients. According to the recently developed mathematical theory of compressed-sensing, images with a sparse representation can be recovered from randomly undersampled k-space data, provided an appropriate nonlinear recovery scheme is used. Intuitively, artifacts due to random undersampling add as noise-like interference. In the sparse transform domain the significant coefficients stand out above the interference. A nonlinear thresholding scheme can recover the sparse coefficients, effectively recovering the image itself. In this article, practical incoherent undersampling schemes are developed and analyzed by means of their aliasing interference. Incoherence is introduced by pseudo-random variable-density undersampling of phase-encodes. The reconstruction is performed by minimizing the l(1) norm of a transformed image, subject to data fidelity constraints. Examples demonstrate improved spatial resolution and accelerated acquisition for multislice fast spin-echo brain imaging and 3D contrast enhanced angiography. (c) 2007 Wiley-Liss, Inc.
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                Author and article information

                Journal
                Curr Med Imaging
                Curr Med Imaging
                CMIM
                Current Medical Imaging
                Bentham Science Publishers
                1573-4056
                24 August 2021
                24 August 2021
                : 17
                : 8
                : 1010-1017
                Affiliations
                [1 ]Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China;
                [2 ]Department of Radiology, The First Affiliated Hospital of University of South China, Hunan, China;
                [3 ]Department of Clinical Science, Philips Healthcare, Beijing 100600, China
                Author notes
                [* ]Address correspondence to this author at the Department of Radiology, Shengjing Hospital of China Medical University, Shenyang, Liaoning, China; Tel: +86-8624-23929902; Email: cjr.panshinong@ 123456vip.163.com
                Article
                CMIM-17-1010
                10.2174/1573405617666210126155814
                8653421
                33573574
                2fe625c1-17f3-4ed0-8af8-caed97441177
                © 2021 Bentham Science Publishers

                This is an open access article licensed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International Public License (CC BY-NC 4.0) ( https://creativecommons.org/licenses/by-nc/4.0/legalcode), which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.

                History
                : 10 August 2020
                : 17 December 2020
                : 22 December 2020
                Funding
                Funded by: China
                Award ID: (No. 30871211, No. 81271538) [No. 2019-ZD-0794].
                Award Recipient : This work was financially supported by the National Natural Science Foundation of China (No. 30871211, No. 81271538) and 345 Talent Project and Natural Science Foundation of Liaoning Province [No. 2019-ZD-0794].
                Categories
                Article

                lumbar vertebrae,nerve root,magnetic resonance imaging,compressed sense,turbo spin-echo,radiofrequency (rf)

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