Fast chemical exchange saturation transfer imaging based on PROPELLER acquisition and deep neural network reconstruction
© 2020 International Society for Magnetic Resonance in Medicine..
PURPOSE: To develop a method for fast chemical exchange saturation transfer (CEST) imaging.
METHODS: The periodically rotated overlapping parallel lines enhanced reconstruction (PROPELLER) sampling scheme was introduced to shorten the acquisition time. Deep neural network was employed to reconstruct CEST contrast images. Numerical simulation and experiments on a creatine phantom, hen egg, and in vivo tumor rat brain were performed to test the feasibility of this method.
RESULTS: The results from numerical simulation and experiments show that there is no significant difference between reference images and CEST-PROPELLER reconstructed images under an acceleration factor of 8.
CONCLUSION: Although the deep neural network is trained entirely on synthesized data, it works well on reconstructing experimental data. The proof of concept study demonstrates that the combination of the PROPELLER sampling scheme and the deep neural network enables considerable acceleration of saturated image acquisition and may find applications in CEST MRI.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:84 |
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| Enthalten in: |
Magnetic resonance in medicine - 84(2020), 6 vom: 30. Dez., Seite 3192-3205 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Guo, Chenlu [VerfasserIn] |
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| Links: |
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| Themen: |
Chemical exchange saturation transfer |
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| Anmerkungen: |
Date Completed 14.05.2021 Date Revised 14.05.2021 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1002/mrm.28376 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM311809901 |
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| 245 | 1 | 0 | |a Fast chemical exchange saturation transfer imaging based on PROPELLER acquisition and deep neural network reconstruction |
| 264 | 1 | |c 2020 | |
| 336 | |a Text |b txt |2 rdacontent | ||
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| 500 | |a Date Completed 14.05.2021 | ||
| 500 | |a Date Revised 14.05.2021 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © 2020 International Society for Magnetic Resonance in Medicine. | ||
| 520 | |a PURPOSE: To develop a method for fast chemical exchange saturation transfer (CEST) imaging | ||
| 520 | |a METHODS: The periodically rotated overlapping parallel lines enhanced reconstruction (PROPELLER) sampling scheme was introduced to shorten the acquisition time. Deep neural network was employed to reconstruct CEST contrast images. Numerical simulation and experiments on a creatine phantom, hen egg, and in vivo tumor rat brain were performed to test the feasibility of this method | ||
| 520 | |a RESULTS: The results from numerical simulation and experiments show that there is no significant difference between reference images and CEST-PROPELLER reconstructed images under an acceleration factor of 8 | ||
| 520 | |a CONCLUSION: Although the deep neural network is trained entirely on synthesized data, it works well on reconstructing experimental data. The proof of concept study demonstrates that the combination of the PROPELLER sampling scheme and the deep neural network enables considerable acceleration of saturated image acquisition and may find applications in CEST MRI | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 650 | 4 | |a PROPELLER | |
| 650 | 4 | |a chemical exchange saturation transfer | |
| 650 | 4 | |a deep neural network | |
| 700 | 1 | |a Wu, Jian |e verfasserin |4 aut | |
| 700 | 1 | |a Rosenberg, Jens T |e verfasserin |4 aut | |
| 700 | 1 | |a Roussel, Tangi |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Shuhui |e verfasserin |4 aut | |
| 700 | 1 | |a Cai, Congbo |e verfasserin |4 aut | |
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