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Principle and clinical application of high resolution magnetic resonance diffusion imaging with multiplexed sensitivity encoding
LIU Qin  ZHOU Zhipeng 

Cite this article as: Liu Q, Zhou ZP. Principle and clinical application of high resolution magnetic resonance diffusion imaging with multiplexed sensitivity encoding[J]. Chin J Magn Reson Imaging, 2022, 13(1): 167-170. DOI:10.12015/issn.1674-8034.2022.01.040.

[Abstract] By combining conventional diffusion-weighted imaging (DWI) and multiple sensitivity encoding (MUSE) to correct random motion-induced phase variations, multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) can minimize image distortion, milder susceptibility artifacts and improve imaging quality in echo-planar imaging. Compared with traditional diffusion-weighted imaging, MUSE-DWI has improved matrix inversion conditions, better signal-to-noise ratio and higher spatial resolution. So far, the multiplexed sensitivity-encoding algorithm has improved imaging quality by integrates multiple magnetic resonance imaging (MRI) techniques and has been widely used in multiple organs. In this paper, we introduced some aspects including MUSE imaging technology, the basic principle of MUSE, multi-technology combined MUSE, clinical application of MUSE-DWI briefly.
[Keywords] magnetic resonance imaging;multiple sensitivity encoding;diffusion-weighted imaging;echo-planar imaging

LIU Qin   ZHOU Zhipeng*  

Department of Radiology, Affiliated Hospital of Guilin Medical University, Guilin 541000, China

Zhou ZP, E-mail:

Conflicts of interest   None.

Received  2021-07-22
Accepted  2021-11-09
DOI: 10.12015/issn.1674-8034.2022.01.040
Cite this article as: Liu Q, Zhou ZP. Principle and clinical application of high resolution magnetic resonance diffusion imaging with multiplexed sensitivity encoding[J]. Chin J Magn Reson Imaging, 2022, 13(1): 167-170.DOI:10.12015/issn.1674-8034.2022.01.040

Zhu GB, Luo JW, Ouyang ZM, et al. The Assessment of Prostate Cancer Aggressiveness Using a Combination of Quantitative Diffusion-Weighted Imaging and Dynamic Contrast-Enhanced Magnetic Resonance Imaging[J]. Cancer Manag Res, 2021, 13: 5287-5295. DOI: 10.2147/CMAR.S319306.
Wang S, Bai Y, Wang MY, et al. The value of diffusion-weighted imaging of single index, double index and stretch index modelsin the differential diagnosis of orbital benign and malignant tumors[J]. Chin J Magn Reson Imaging, 2021, 12(3): 44-48. DOI: 10.12015/issn.1674-8034.2021.03.010.
Zheng CX, Li CT. The new application of MRI in diagnosis of viral encephalitis[J]. J Med Imaging, 2010, 20(2): 278-280.
An H, Ma XD, Pan ZY, et al. Qualitative and quantitative comparison of image quality between single-shot echo-planar and interleaved multi-shot echo-planar diffusion-weighted imaging in female pelvis[J]. Eur Radiol, 2020, 30(4): 1876-1884. DOI: 10.1007/s00330-019-06491-3.
Xie SM, Masokano IB, Liu WG, et al. Comparing the clinical utility of single-shot echo-planar imaging and readout-segmented echo-planar imaging in diffusion-weighted imaging of the liver at 3 tesla[J]. Eur J Radiol, 2021, 135: 109472. DOI: 10.1016/j.ejrad.2020.109472.
Chen NK, Guidon A, Chang HC, et al. A robust multi-shot scan strategy for high-resolution diffusion weighted MRI enabled by multiplexed sensitivity-encoding (MUSE)[J]. Neuroimage, 2013, 72: 41-47. DOI: 10.1016/j.neuroimage.2013.01.038.
Park J, Lee J, Lee SK, et al. Strategies for rapid reconstruction in 3D MRI with radial data acquisition: 3D fast Fourier transform vs two-step 2D filtered back-projection[J]. Sci Rep, 2020, 10(1): 13813. DOI: 10.1038/s41598-020-70698-4.
Ullah I, Nisar H, Raza H, et al. QR-decomposition based SENSE reconstruction using parallel architecture[J]. Comput Biol Med, 2018, 95: 1-12. DOI: 10.1016/j.compbiomed.2018.01.013.
Kawamura M, Tamada D, Funayama S, et al. Accelerated Acquisition of High-resolution Diffusion-weighted Imaging of the Brain with a Multi-shot Echo-planar Sequence: Deep-learning-based Denoising[J]. Magn Reson Med Sci, 2021, 20(1): 99-105. DOI: 10.2463/
Pinker K, Moy L, Sutton EJ, et al. Diffusion-Weighted Imaging With Apparent Diffusion Coefficient Mapping for Breast Cancer Detection as a Stand-Alone Parameter: Comparison With Dynamic Contrast-Enhanced and Multiparametric Magnetic Resonance Imaging[J]. Invest Radiol, 2018, 53(10): 587-595. DOI: 10.1097/RLI.0000000000000465.
Santini T, Zhao Y, Wood S, et al. In-vivo and numerical analysis of the eigenmodes produced by a multi-level Tic-Tac-Toe head transmit array for 7 Tesla MRI[J]. PLOS One, 2018, 13(11): e0206127. DOI: 10.1371/journal.pone.0206127.
Hu Y, Ikeda DM, Pittman SM, et al. Multishot Diffusion-Weighted MRI of the Breast With Multiplexed Sensitivity Encoding (MUSE) and Shot Locally Low-Rank (Shot‐LLR) Reconstructions[J]. J Magn Reson Imaging, 2020, 53(3): 807-817. DOI: 10.1002/JMRI.27383.
Luo XR, Rong K, Li XL. Research progresses of MRI based on water molecular diffusion[J]. Chin J Med Imaging Technol, 2020, 36(11): 1726-1729. DOI: 10.13929/j.issn.1003-3289.2020.11.032.
Zhang Z, Huang F, Ma XD, et al. Self-feeding MUSE: A robust method for high resolution diffusion imaging using interleaved EPI[J]. NeuroImage, 2015, 105: 552-560. DOI: 10.1016/j.neuroimage.2014.10.022.
Bilgic B, Chatnuntawech I, Manhard MK, et al. Highly accelerated multishot echo planar imaging through synergistic machine learning and joint reconstruction[J]. Magn Reson Med, 2019, 82(4): 1343-1358. DOI: 10.1002/mrm.27813.
Guhaniyogi S, Chu ML, Chang HC, et al. Motion immune diffusion imaging using augmented MUSE for high-resolution multi-shot EPI[J]. Magn Reson Med, 2016, 75(2): 639-652. DOI: 10.1002/mrm.25624.
Bruce IP, Petty C, Song AW. Simultaneous and inherent correction of B0 and eddy-current induced distortions in high-resolution diffusion MRI using reversed polarity gradients and multiplexed sensitivity encoding (RPG-MUSE)[J]. Neuroimage, 2018, 183: 985-993. DOI: 10.1016/j.neuroimage.2018.09.055.
Konar AS, Fung M, Paudyal R, et al. Diffusion-Weighted Echo Planar Imaging using MUltiplexed Sensitivity Encoding and Reverse Polarity Gradient in Head and Neck Cancer: An Initial Study[J]. Tomography, 2020, 6(2): 231-240. DOI: 10.18383/j.tom.2020.00014.
Walheim J, Gotschy A, and Kozerke S. On the limitations of partial Fourier acquisition in phase-contrast MRI of turbulent kinetic energy[J]. Magn Reson Med, 2019, 81(1): 514-523. DOI: 10.1002/mrm.27397.
Chang HC, Guhaniyogi S, Chen NK. Interleaved diffusion-weighted improved by adaptive partial-Fourier and multiband multiplexed sensitivity-encoding reconstruction[J]. Magn Reson Med, 2015, 73(5): 1872-1884. DOI: 10.1002/mrm.25318.
Hu J, Xu B, Cao J, et al. Application value of CAIPIRINHA-VIBE with MOCO in liver magnetic resonance examination[J]. Eur J Radiol, 2021, 140: 109739. DOI: 10.1016/J.EJRAD.2021.109739.
Chang HC, Gaur P, Chou YH, et al. Interleaved EPI based fMRI improved by multiplexed sensitivity encoding (MUSE) and simultaneous multi-band imaging[J]. PLoS One, 2019, 9(12): e116378. DOI: 10.1371/journal.pone.0116378.
Mani M, Jacob M, McKinnon G, et al. SMS MUSSELS: A navigator-free reconstruction for simultaneous multi-slice-accelerated multi-shot diffusion weighted imaging[J]. Magn Reson Med, 2020, 83(1): 154-169. DOI: 10.1002/mrm.27924.
Chang HC, Sundman M, Petit L, et al. Human brain diffusion tensor imaging at submillimeter isotropic resolution on a 3Tesla clinical MRI scanner[J]. NeuroImage, 2015, 118: 667-675. DOI: 10.1016/j.neuroimage.2015.06.016.
Bruce IP, Chang HC, Petty C, et al. 3D-MB-MUSE: A robust 3D multi-slab, multi-band and multi-shot reconstruction approach for ultrahigh resolution diffusion MRI[J]. NeuroImage, 2017, 159: 46-56. DOI: 10.1016/j.neuroimage.2017.07.035.
Herbst M, Zahneisen B, Knowles B, et al. Prospective motion correction of segmented diffusion weighted EPI[J]. Magn Reson Med, 2015, 74(6): 1675-1681. DOI: 10.1002/mrm.25547.
Xie S, Zhang Z, Chang F, et al. Subcortical White Matter Changes with Normal Aging Detected by Multi-Shot High Resolution Diffusion Tensor Imaging[J]. PLoS One, 2016, 11(6): e0157533. DOI: 10.1371/journal.pone.0157533.
Song AW, Chang HC, Petty C, et al. Improved delineation of short cortical association fibers and gray/white matter boundary using whole-brain three-dimensional diffusion tensor imaging at submillimeter spatial resolution[J]. Brain Connect, 2014. 4(9): 636-640. DOI: 10.1089/brain.2014.0270.
Daimiel Naranjo I, Lo Gullo R, Morris EA, et al. High-Spatial-Resolution Multishot Multiplexed Sensitivity-encoding Diffusion-weighted Imaging for Improved Quality of Breast Images and Differentiation of Breast Lesions: A Feasibility Study[J]. Radiol Imaging Cancer, 2020, 2(3): e190076. DOI: 10.1148/rycan.2020190076.
Iima M, Honda M, Sigmund EE, et al. Diffusion MRI of the breast: Current status and future directions[J]. J Magn Reson Imaging, 2020, 52(1): 70-90. DOI: 10.1002/jmri.26908.
Baxter GC, Patterson AJ, Woitek R, et al. Improving the image quality of DWI in breast cancer: comparison of multi-shot DWI using multiplexed sensitivity encoding to conventional single-shot echo-planar imaging DWI[J]. Br J Radiol, 2020, 94(1119): 20200427. DOI: 10.1259/bjr.20200427.
Solomon E, Liberman G, Nissan N, et al. Diffusion-weighted breast MRI of malignancies with submillimeter resolution and immunity to artifacts by spatiotemporal encoding at 3T[J]. Magn Reson Med, 2020, 84(3): 1391-1403. DOI: 10.1002/mrm.28213.
Kim YY, Kim MJ, Gho SM, et al. Comparison of multiplexed sensitivity encoding and single-shot echo-planar imaging for diffusion-weighted imaging of the liver[J]. Eur J Radiol, 2020, 132: 109292. DOI: 10.1016/j.ejrad.2020.109292.
Taron J, ohannink J, Bitzer M, et al. Added value of diffusion-weighted imaging in hepatic tumors and its impact on patient management[J]. Cancer imaging, 2018, 18(1): 10. DOI: 10.1186/s40644-018-0140-1.
Chang HC, Chen GT, Chung HW, et al. Multi-shot Diffusion-Weighted MRI With Multiplexed Sensitivity Encoding (MUSE) in the Assessment of Active Inflammation in Crohn's Disease[J]. J Magn Reson Imaging, 2021. DOI: 10.1002/JMRI.27801.
Chu ML, Chang HC, Chung HW, et al. POCS-based reconstruction of multiplexed sensitivity encoded MRI (POCSMUSE): A general algorithm for reducing motion-related artifacts[J]. Magn Reson Med, 2015, 74(5): 1336-1348. DOI: 10.1002/mrm.25527.
Chu ML, Chang HC, Chung HW, et al. Free-breathing abdominal MRI improved by repeated k-t-subsampling and artifact-minimization (ReKAM)[J]. Med Phys, 2018, 45(1): 178-190. DOI: 10.1002/mp.12674.
Chen XY, Zhang Y, Cao Y, et al. A feasible study on using multiplexed sensitivity-encoding to reduce geometric distortion in diffusion-weighted echo planar imaging[J]. Magn Reson Imaging, 2018. 54: 153-159. DOI: 10.1016/j.mri.2018.08.022.

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