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Journal articles on the topic 'Water/fat imaging'

Author: Grafiati

Published: 19 April 2023

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1

Bley, Thorsten A., Oliver Wieben, Christopher J. François, Jean H. Brittain, and Scott B. Reeder. "Fat and water magnetic resonance imaging." Journal of Magnetic Resonance Imaging 31, no. 1 (December 20, 2009): 4–18. http://dx.doi.org/10.1002/jmri.21895.

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2

Xiang, Qing-San, and Li An. "Water-fat imaging with direct phase encoding." Journal of Magnetic Resonance Imaging 7, no. 6 (November 1997): 1002–15. http://dx.doi.org/10.1002/jmri.1880070612.

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3

Ma, Jingfei. "Dixon techniques for water and fat imaging." Journal of Magnetic Resonance Imaging 28, no. 3 (September 2008): 543–58. http://dx.doi.org/10.1002/jmri.21492.

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4

Bauer, Daniel R., Xiong Wang, Jeff Vollin, Hao Xin, and Russell S. Witte. "Spectroscopic thermoacoustic imaging of water and fat composition." Applied Physics Letters 101, no. 3 (July 16, 2012): 033705. http://dx.doi.org/10.1063/1.4737414.

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5

Goldfarb, James W. "Fat-water separated delayed hyperenhanced myocardial infarct imaging." Magnetic Resonance in Medicine 60, no. 3 (September 2008): 503–9. http://dx.doi.org/10.1002/mrm.21685.

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6

Reeder, Scott B., Charles A. McKenzie, Angel R. Pineda, Huanzhou Yu, Ann Shimakawa, Anja C. Brau, Brian A. Hargreaves, Garry E. Gold, and Jean H. Brittain. "Water–fat separation with IDEAL gradient-echo imaging." Journal of Magnetic Resonance Imaging 25, no. 3 (2007): 644–52. http://dx.doi.org/10.1002/jmri.20831.

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7

Salvati, Roberto, Eric Hitti, Jean-Jacques Bellanger, Hervé Saint-Jalmes, and Giulio Gambarota. "Fat ViP MRI: Virtual Phantom Magnetic Resonance Imaging of water–fat systems." Magnetic Resonance Imaging 34, no. 5 (June 2016): 617–23. http://dx.doi.org/10.1016/j.mri.2015.12.002.

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8

SIMON, JACK H., and JERZY SZUMOWSKI. "Proton (Fat/Water) Chemical Shift Imaging in Medical Magnetic Resonance Imaging." Investigative Radiology 27, no. 10 (October 1992): 865–74. http://dx.doi.org/10.1097/00004424-199210000-00018.

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9

Wiens, Curtis N., Colin M. McCurdy, Jacob D. Willig-Onwuachi, and Charles A. McKenzie. "R2*-corrected water-fat imaging using compressed sensing and parallel imaging." Magnetic Resonance in Medicine 71, no. 2 (March 8, 2013): 608–16. http://dx.doi.org/10.1002/mrm.24699.

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10

Yu, Huanzhou, Scott B. Reeder, Ann Shimakawa, Charles A. McKenzie, and Jean H. Brittain. "Robust multipoint water-fat separation using fat likelihood analysis." Magnetic Resonance in Medicine 67, no. 4 (August 12, 2011): 1065–76. http://dx.doi.org/10.1002/mrm.23087.

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11

Weng, Dehe, Yanli Pan, Xiaodong Zhong, and Yan Zhuo. "Water–fat separation with parallel imaging based on BLADE." Magnetic Resonance Imaging 31, no. 5 (June 2013): 656–63. http://dx.doi.org/10.1016/j.mri.2012.10.018.

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12

Keller, P. J., W. W. Hunter, and P. Schmalbrock. "Multisection fat-water imaging with chemical shift selective presaturation." Radiology 164, no. 2 (August 1987): 539–41. http://dx.doi.org/10.1148/radiology.164.2.3602398.

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13

Wang, Dinghui, Nicholas R. Zwart, and James G. Pipe. "Joint water-fat separation and deblurring for spiral imaging." Magnetic Resonance in Medicine 79, no. 6 (October 5, 2017): 3218–28. http://dx.doi.org/10.1002/mrm.26950.

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14

Kaldoudi, Eleni, and Steve C. R. Williams. "Fat and water differentiation by nuclear magnetic resonance imaging." Concepts in Magnetic Resonance 4, no. 1 (January 1992): 53–71. http://dx.doi.org/10.1002/cmr.1820040104.

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15

Kaldoudi, Eleni, and Steve C. R. Williams. "Fat and water differentiation by nuclear magnetic resonance imaging." Concepts in Magnetic Resonance 4, no. 2 (April 1992): 162–65. http://dx.doi.org/10.1002/cmr.1820040206.

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16

Lu, Minjie, An Jing, Gang Yin, Shiliang Jiang, Qiong Liu, Ning Ma, Tao Zhao, Xiuyu Chen, and Shihua Zhao. "MYOCARDIAL FAT DEPOSITION IN DILATED CARDIOMYOPATHY–ASSESSMENT BY USING MR WATER-FAT SEPARATION IMAGING." Heart 98, Suppl 2 (October 2012): E249.3—E250. http://dx.doi.org/10.1136/heartjnl-2012-302920q.8.

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17

Baron, Paul, Roel Deckers, Job G. Bouwman, Chris J. G. Bakker, Martijn de Greef, Max A. Viergever, Chrit T. W. Moonen, and Lambertus W. Bartels. "Influence of water and fat heterogeneity on fat‐referenced MR thermometry." Magnetic Resonance in Medicine 75, no. 3 (March 2016): 1187–97. http://dx.doi.org/10.1002/mrm.25727.

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18

Bachrata, Beata, Bernhard Strasser, Wolfgang Bogner, Albrecht Ingo Schmid, Radim Korinek, Martin Krššák, Siegfried Trattnig, and Simon Daniel Robinson. "Simultaneous Multiple Resonance Frequency imaging (SMURF): Fat‐water imaging using multi‐band principles." Magnetic Resonance in Medicine 85, no. 3 (September 27, 2020): 1379–96. http://dx.doi.org/10.1002/mrm.28519.

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19

Fellner, Claudia, Marcel Dominik Nickel, Stephan Kannengiesser, Niklas Verloh, Christian Stroszczynski, Michael Haimerl, and Lukas Luerken. "Water–Fat Separated T1 Mapping in the Liver and Correlation to Hepatic Fat Fraction." Diagnostics 13, no. 2 (January 5, 2023): 201. http://dx.doi.org/10.3390/diagnostics13020201.

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(1) Background: T1 mapping in magnetic resonance imaging (MRI) of the liver has been proposed to estimate liver function or to detect the stage of liver disease, among others. Thus far, the impact of intrahepatic fat on T1 quantification has only been sparsely discussed. Therefore, the aim of this study was to evaluate the potential of water–fat separated T1 mapping of the liver. (2) Methods: A total of 386 patients underwent MRI of the liver at 3 T. In addition to routine imaging techniques, a 3D variable flip angle (VFA) gradient echo technique combined with a two-point Dixon method was acquired to calculate T1 maps from an in-phase (T1_in) and water-only (T1_W) signal. The results were correlated with proton density fat fraction using multi-echo 3D gradient echo imaging (PDFF) and multi-echo single voxel spectroscopy (PDFF_MRS). Using T1_in and T1_W, a novel parameter FF_T1 was defined and compared with PDFF and PDFF_MRS. Furthermore, the value of retrospectively calculated T1_W (T1_W_calc) based on T1_in and PDFF was assessed. Wilcoxon test, Pearson correlation coefficient and Bland–Altman analysis were applied as statistical tools. (3) Results: T1_in was significantly shorter than T1_W and the difference of both T1 values was correlated with PDFF (R = 0.890). FF_T1 was significantly correlated with PDFF (R = 0.930) and PDFF_MRS (R = 0.922) and yielded only minor bias compared to both established PDFF methods (0.78 and 0.21). T1_W and T1_W_calc were also significantly correlated (R = 0.986). (4) Conclusion: T1_W acquired with a water–fat separated VFA technique allows to minimize the influence of fat on liver T1. Alternatively, T1_W can be estimated retrospectively from T1_in and PDFF, if a Dixon technique is not available for T1 mapping.

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20

Gerdes, Clint M., Richard Kijowski, and Scott B. Reeder. "IDEAL Imaging of the Musculoskeletal System: Robust Water–Fat Separation for Uniform Fat Suppression, Marrow Evaluation, and Cartilage Imaging." American Journal of Roentgenology 189, no. 5 (November 2007): W284—W291. http://dx.doi.org/10.2214/ajr.07.2593.

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21

Manaster, B. J. "IDEAL Imaging of the Musculoskeletal System: Robust Water–Fat Separation for Uniform Fat Suppression, Marrow Evaluation, and Cartilage Imaging." Yearbook of Diagnostic Radiology 2009 (January 2009): 85–86. http://dx.doi.org/10.1016/s0098-1672(09)79325-7.

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22

Wen, Zhifei, Scott B. Reeder, Angel R. Pineda, and Norbert J. Pelc. "Noise considerations of three-point water-fat separation imaging methods." Medical Physics 35, no. 8 (July 16, 2008): 3597–606. http://dx.doi.org/10.1118/1.2952644.

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23

Zhadanov, Sergey I., Amish H. Doshi, Puneet S. Pawha, Idoia Corcuera-Solano, and Lawrence N. Tanenbaum. "Contrast-Enhanced Dixon Fat-Water Separation Imaging of the Spine." Journal of Computer Assisted Tomography 40, no. 6 (2016): 985–90. http://dx.doi.org/10.1097/rct.0000000000000453.

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24

Yu, Huanzhou, Scott B. Reeder, Charles A. McKenzie, Anja C. S. Brau, Ann Shimakawa, Jean H. Brittain, and Norbert J. Pelc. "Single acquisition water-fat separation: Feasibility study for dynamic imaging." Magnetic Resonance in Medicine 55, no. 2 (February 2006): 413–22. http://dx.doi.org/10.1002/mrm.20771.

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25

Börnert, Peter, Jochen Keupp, Holger Eggers, and Bernd Aldefeld. "Whole-body 3D water/fat resolved continuously moving table imaging." Journal of Magnetic Resonance Imaging 25, no. 3 (2007): 660–65. http://dx.doi.org/10.1002/jmri.20861.

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26

Alanen, A., M. Komu, R. Leino, and S. Toikkanen. "MR and magnetisation transfer imaging in cirrhotic and fatty livers." Acta Radiologica 39, no. 4 (July 1998): 434–39. http://dx.doi.org/10.1080/02841859809172459.

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Purpose: To determine whether low-field MR fat/water separation and magnetisation transfer (MT) techniques are useful in studying the livers of patients with parenchymal liver diseases in vivo. Material and Methods: MR and MT imaging of the liver in 33 patients (14 with primary biliary cirrhosis, 15 with alcohol-induced liver disease, and 4 with fatty liver) was performed by means of the fat/water separation technique at 0.1 T. The relaxation time T1 and the MT contrast (MTC) parameter of liver and spleen tissue were measured, and the relative proton density fat content N(%) and MTC of the liver were calculated from the separate fat and water images. The value of N(%) was also compared with the percentage of fatty hepatocytes at histology. Results: The relaxation rate R1 of liver measured from the magnitude image, and the difference in the value of MTC measured from the water image compared with the one measured from the fat and water magnitude image, both depended linearly on the value of N(%). The value of N(%) correlated significantly with the percentage of the fatty hepatocytes. In in vivo fatty tissue, fat infiltration increased both the observed relaxation rate R1 and the measured magnetisation ratio (the steady state magnetisation Ms divided by the equilibrium magnetisation Mo, Ms/Mo) and consequently decreased the MT efficiency measured in a magnitude MR image. The amount of liver fibrosis did not correlate with the value of MTC measured after fat separation. Conclusion: Our results in studying fatty livers with MR imaging and the MT method show that the fat/water separation gives more reliable parametric results. Characterisation of liver cirrhosis by means of the MTC parameter is not reliable, even after fat separation.

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27

Yu, Huanzhou, Ann Shimakawa, Charles A. McKenzie, Ethan Brodsky, Jean H. Brittain, and Scott B. Reeder. "Multiecho water-fat separation and simultaneousR2* estimation with multifrequency fat spectrum modeling." Magnetic Resonance in Medicine 60, no. 5 (November 2008): 1122–34. http://dx.doi.org/10.1002/mrm.21737.

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28

de Vrijer, Barbra, Stephanie Giza, Craig Olmstead, Debbie Penava, Genevieve Eastabrook, Timothy Regnault, and Charles McKenzie. "O-OBS-MFM-MD-070 Imaging Fetal Subcutaneous Fat Development Using 3D Water-Fat MRI." Journal of Obstetrics and Gynaecology Canada 39, no. 5 (May 2017): 387. http://dx.doi.org/10.1016/j.jogc.2017.03.020.

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29

Peterson, Pernilla, Thobias Romu, Håkan Brorson, Olof Dahlqvist Leinhard, and Sven Månsson. "Fat quantification in skeletal muscle using multigradient-echo imaging: Comparison of fat and water references." Journal of Magnetic Resonance Imaging 43, no. 1 (June 10, 2015): 203–12. http://dx.doi.org/10.1002/jmri.24972.

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30

Jaubert, Olivier, Gastão Cruz, Aurélien Bustin, Torben Schneider, Begoña Lavin, Peter Koken, Reza Hajhosseiny, et al. "Water–fat Dixon cardiac magnetic resonance fingerprinting." Magnetic Resonance in Medicine 83, no. 6 (November 18, 2019): 2107–23. http://dx.doi.org/10.1002/mrm.28070.

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31

Reeder, Scott B., Brian A. Hargreaves, Huanzhou Yu, and Jean H. Brittain. "Homodyne reconstruction and IDEAL water-fat decomposition." Magnetic Resonance in Medicine 54, no. 3 (2005): 586–93. http://dx.doi.org/10.1002/mrm.20586.

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32

Wu, Yan, Marcus Alley, Zhitao Li, Keshav Datta, Zhifei Wen, Christopher Sandino, Ali Syed, et al. "Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging." Bioengineering 9, no. 10 (October 19, 2022): 579. http://dx.doi.org/10.3390/bioengineering9100579.

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Conventional water–fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water–fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water–fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.

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33

Chang, Jerry S., Bachir Taouli, Nouha Salibi, Elizabeth M. Hecht, Deanna G. Chin, and Vivian S. Lee. "Opposed-Phase MRI for Fat Quantification in Fat-Water Phantoms with 1H MR Spectroscopy to Resolve Ambiguity of Fat or Water Dominance." American Journal of Roentgenology 187, no. 1 (July 2006): W103—W106. http://dx.doi.org/10.2214/ajr.05.0695.

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34

Borrello, Joseph A., Dorit D. Adler, and W. Richard Dunham. "MR IMAGING OF THE BREAST USING A DEDICATED BREAST COIL AND WATER-FAT IMAGING." Investigative Radiology 24, no. 12 (December 1989): S132. http://dx.doi.org/10.1097/00004424-198912000-00236.

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35

Goldfarb, James W., and Sheeba Arnold-Anteraper. "Water-fat separation imaging of the heart with standard magnetic resonance bSSFP CINE imaging." Magnetic Resonance in Medicine 71, no. 6 (July 31, 2013): 2096–104. http://dx.doi.org/10.1002/mrm.24879.

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36

Kim, Hokun, Joon-Il Choi, and Hyun-Soo Lee. "Friend or Foe: How to Suppress and Measure Fat During Abdominal Resonance Imaging?" Korean Journal of Abdominal Radiology 6, no. 1 (July 15, 2022): 22–36. http://dx.doi.org/10.52668/kjar.2022.00143.

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The suppression of fat signals in abdominal magnetic resonance imaging has become a basic and routine practice in the diagnosis of pathologic conditions of abdominal organs in clinical settings. Many fat-suppression techniques have been developed in the past several decades, with fat-quantification methods introduced in response in more recent years. Fat-suppression techniques can be divided into two categories. Chemical shift–based techniques include chemical shift selective (CHESS), water excitation, and the Dixon method. CHESS is the most commonly used fat-suppression method, nulling the fat signal using a fat-selective radiofrequency pulse with a spoiler gradient. Water excitation employs a binomial pulse that excites only the water protons. Finally, the Dixon method involves using the in-phase/out-of-phase cycling of fat and water. An inversionbased technique, known as short tau inversion recovery (STIR), uses a pre-excitation inversion pulse that inverts the spin of all tissues. By selecting the appropriate MRI inversion time such that the longitudinal magnetization of fat is zero, fat protons will not contribute to the MRI signal. Also, spectral attenuated inversion recovery (SPAIR) is a hybrid technique that combines the characteristics of both CHESS and STIR. The most precise fat-quantification technique known to date is a complex-based multipoint Dixon method, with which the protondensity fat fraction (PDFF) can be obtained. Multiple confounding factors must be well-corrected for accurate fat quantification. Radiologists should be familiar with the various fat suppression and measurement methods during MRI and be able to apply them to enhance patient care.

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37

Chebrolu, Venkata V., Catherine D. G. Hines, Huanzhou Yu, Angel R. Pineda, Ann Shimakawa, Charles A. McKenzie, Alexey Samsonov, Jean H. Brittain, and Scott B. Reeder. "Independent estimation ofT*2for water and fat for improved accuracy of fat quantification." Magnetic Resonance in Medicine 63, no. 4 (May 2010): 849–57. http://dx.doi.org/10.1002/mrm.22300.

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38

SCHICK, FRITZ, STEPHAN MILLER, ULRICH HAHN, THOMAS NÄGELE, UWE HELBER, NORBERT STAUDER, KLAUS BRECHTEL, and CLAUS D. CLAUSSEN. "Fat- and Water-Selective MR Cine Imaging of the Human Heart." Investigative Radiology 35, no. 5 (May 2000): 311–18. http://dx.doi.org/10.1097/00004424-200005000-00005.

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39

Jackson, A., S. Sheppard, R. D. Laitt, A. Kassner, and D. Moriarty. "Optic neuritis: MR imaging with combined fat- and water-suppression techniques." Radiology 206, no. 1 (January 1998): 57–63. http://dx.doi.org/10.1148/radiology.206.1.9423652.

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40

Nezafat, Maryam, Shiro Nakamori, Tamer A. Basha, Ahmed S. Fahmy, Thomas Hauser, and René M. Botnar. "Imaging sequence for joint myocardial T1 mapping and fat/water separation." Magnetic Resonance in Medicine 81, no. 1 (July 29, 2018): 486–94. http://dx.doi.org/10.1002/mrm.27390.

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41

Glover, Gary H. "Multipoint dixon technique for water and fat proton and susceptibility imaging." Journal of Magnetic Resonance Imaging 1, no. 5 (September 1991): 521–30. http://dx.doi.org/10.1002/jmri.1880010504.

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42

Farrelly, Cormac, Saurabh Shah, Amir Davarpanah, Aoife N. Keeling, and James C. Carr. "ECG-Gated Multiecho Dixon Fat-Water Separation in Cardiac MRI: Advantages Over Conventional Fat-Saturated Imaging." American Journal of Roentgenology 199, no. 1 (July 2012): W74—W83. http://dx.doi.org/10.2214/ajr.11.7759.

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43

Goldfarb, James W., Marguerite Roth, and Jing Han. "Myocardial Fat Deposition after Left Ventricular Myocardial Infarction: Assessment by Using MR Water-Fat Separation Imaging." Radiology 253, no. 1 (October 2009): 65–73. http://dx.doi.org/10.1148/radiol.2532082290.

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44

Abbott, Rebecca, Anneli Peolsson, Janne West, James M. Elliott, Ulrika Åslund, Anette Karlsson, and Olof Dahlqvist Leinhard. "The qualitative grading of muscle fat infiltration in whiplash using fat and water magnetic resonance imaging." Spine Journal 18, no. 5 (May 2018): 717–25. http://dx.doi.org/10.1016/j.spinee.2017.08.233.

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45

Liu, Chia-Ying, Alban Redheuil, Ronald Ouwerkerk, Joao A. C. Lima, and David A. Bluemke. "Myocardial fat quantification in humans: Evaluation by two-point water-fat imaging and localized proton spectroscopy." Magnetic Resonance in Medicine 63, no. 4 (April 2010): 892–901. http://dx.doi.org/10.1002/mrm.22289.

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46

Manabe, Atsutaka, Toshiyuki Miyazaki, and Hideo Toyoshima. "0.1-T human fat/water separation by SIDAC." Magnetic Resonance in Medicine 5, no. 5 (November 1987): 492–501. http://dx.doi.org/10.1002/mrm.1910050513.

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47

Wu, Hochong H., Jin Hyung Lee, and Dwight G. Nishimura. "Fat/water separation using a concentric rings trajectory." Magnetic Resonance in Medicine 61, no. 3 (December 18, 2008): 639–49. http://dx.doi.org/10.1002/mrm.21865.

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48

Johnson, Kevin M., Oliver Wieben, and Alexey A. Samsonov. "Phase-contrast velocimetry with simultaneous fat/water separation." Magnetic Resonance in Medicine 63, no. 6 (April 23, 2010): 1564–74. http://dx.doi.org/10.1002/mrm.22355.

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49

Taviani, Valentina, Diego Hernando, Christopher J. Francois, Ann Shimakawa, Karl K. Vigen, Scott K. Nagle, Mark L. Schiebler, Thomas M. Grist, and Scott B. Reeder. "Whole-heart chemical shift encoded water-fat MRI." Magnetic Resonance in Medicine 72, no. 3 (November 1, 2013): 718–25. http://dx.doi.org/10.1002/mrm.24982.

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50

Marty, Benjamin, and Pierre G. Carlier. "MR fingerprinting for water T1 and fat fraction quantification in fat infiltrated skeletal muscles." Magnetic Resonance in Medicine 83, no. 2 (September 10, 2019): 621–34. http://dx.doi.org/10.1002/mrm.27960.

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