Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition
9 May 2026 – 14 May 2026 · Cape Town, South Africa
507-03-007 ISMRM Abstract

Spatial-Frequency Feature Learning for Fast Amide Contrast Mapping from Sparse CEST Offsets

Primary: Contrast Mechanisms - CEST / APT / NOE
Secondary: Acquisition & Reconstruction - AI methods
507-03-007 · New Frontiers in CEST MRI · Wednesday, 13 May, 1:40 PM–3:30 PM · Meeting Room 1.40
Keywords: Deep Learning-based quantification Amide contrast map reconstruction Spatial-frequency feature learning CEST-MRI post-processing
Accepted
PEI CAI1, Ziyan Wang1, Jiawen Wang1, Huabin Zhang1,2, Shihao Zeng1, Ka Fung Henry Mak1, Lequan Yu3, Jianpan Huang 1,4,5
1Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
2Medical Imaging Centre, Department of Electronic Engineering and Information Science, University of Science and Technology of China, He Fei, China
3School of Computing and Data Science, The University of Hong Kong, Hong Kong, China
4Tam Wing Fan Neuroimaging Research Laboratory, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China
5Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
Presenting Author: Jianpan Huang

Synopsis

Motivation:
Goals:
Approach:
Results:
Full abstract & presentation

The full text, figures, and any recorded presentation for this abstract are not shown here. Log in if you are a member or registered attendee with access.

Full abstracts, figures, and presentations for Cape Town - 2026 ISMRM-ISMRT Annual Meeting and Exhibition are available to registered attendees. This content becomes freely available to the public roughly two years after the meeting.

To request or purchase access, contact the ISMRM Central Office at info@ismrm.org.

Log in

References

1. Van Zijl PC, Yadav NN. Chemical exchange saturation transfer (CEST): what is in a name and what isn't? Magnetic resonance in medicine 2011;65(4):927–948.https://doi.org/10.1002/mrm.22761 [doi]
2. Ward K, Aletras A, Balaban RS. A new class of contrast agents for MRI based on proton chemical exchange dependent saturation transfer (CEST). Journal of magnetic resonance 2000;143(1):79–87.https://doi.org/10.1006/jmre.1999.1956 [doi]
3. Togao O, Yoshiura T, Keupp J, Hiwatashi A, Yamashita K, Kikuchi K, Suzuki Y, Suzuki SO, Iwaki T, Hata N. Amide proton transfer imaging of adult diffuse gliomas: correlation with histopathological grades. Neuro-oncology 2014;16(3):441–448.https://doi.org/10.1093/neuonc/not158 [doi]
4. Zhou J, Zaiss M, Knutsson L, Sun PZ, Ahn SS, Aime S, Bachert P, Blakeley JO, Cai K, Chappell MA. Review and consensus recommendations on clinical APT‐weighted imaging approaches at 3T: application to brain tumors. Magnetic resonance in medicine 2022;88(2):546–574.https://doi.org/10.1002/mrm.29241 [doi]
5. Zaiß M, Schmitt B, Bachert P. Quantitative separation of CEST effect from magnetization transfer and spillover effects by Lorentzian-line-fit analysis of z-spectra. Journal of magnetic resonance 2011;211(2):149–155.https://doi.org/10.1016/j.jmr.2011.05.001 [doi]
6. Huang J, Lai JH, Tse KH, Cheng GW, Liu Y, Chen Z, Han X, Chen L, Xu J, Chan KW. Deep neural network based CEST and AREX processing: Application in imaging a model of Alzheimer’s disease at 3 T. Magnetic resonance in medicine 2022;87(3):1529–1545.https://doi.org/10.1002/mrm.29044 [doi]
7. Hunger L, Rajput JR, Klein K, Mennecke A, Fabian MS, Schmidt M, Glang F, Herz K, Liebig P, Nagel AM. DeepCEST 7 T: Fast and homogeneous mapping of 7 T CEST MRI parameters and their uncertainty quantification. Magnetic resonance in medicine 2023;89(4):1543–1556.https://doi.org/10.1002/mrm.29520 [doi]
8. Glang F, Deshmane A, Prokudin S, Martin F, Herz K, Lindig T, Bender B, Scheffler K, Zaiss M. DeepCEST 3T: Robust MRI parameter determination and uncertainty quantification with neural networks—application to CEST imaging of the human brain at 3T. Magnetic resonance in medicine 2020;84(1):450–466.https://doi.org/10.1002/mrm.28117 [doi]
9. Zaiss M, Deshmane A, Schuppert M, Herz K, Glang F, Ehses P, Lindig T, Bender B, Ernemann U, Scheffler K. DeepCEST: 9.4 T chemical exchange saturation transfer MRI contrast predicted from 3 T data–a proof of concept study. Magnetic resonance in medicine 2019;81(6):3901–3914.https://doi.org/10.1002/mrm.27690 [doi]
10. Chen L, Xu H, Gong T, Jin J, Lin L, Zhou Y, Huang J, Chen Z. Accelerating multipool CEST MRI of Parkinson's disease using deep learning–based Z‐spectral compressed sensing. Magnetic Resonance in Medicine 2024.https://doi.org/10.1002/mrm.30233 [doi]
11. Xiao G, Zhang X, Tang H, Huang W, Chen Y, Zhuang C, Chen B, Yang L, Chen Y, Yan G. Deep learning for dense Z-spectra reconstruction from CEST images at sparse frequency offsets. Frontiers in Neuroscience 2024;17:1323131.https://doi.org/10.3389/fnins.2023.1323131 [doi]
12. Cheema K, Han P, Lee HL, Xie Y, Christodoulou AG, Li D. Accelerated CEST imaging through deep learning quantification from reduced frequency offsets. Magnetic Resonance in Medicine 2024.https://doi.org/10.1002/mrm.30269 [doi]
13. Li Y, Xie D, Cember A, Nanga RPR, Yang H, Kumar D, Hariharan H, Bai L, Detre JA, Reddy R. Accelerating GluCEST imaging using deep learning for B0 correction. Magnetic resonance in medicine 2020;84(4):1724–1733.https://doi.org/10.1002/mrm.28289 [doi]
14. Zhu J-Y, Park T, Isola P, Efros AA. Unpaired image-to-image translation using cycle-consistent adversarial networks. 2017. p 2223–2232.https://doi.org/10.1109/iccv.2017.244 [doi]
15. Isola P, Zhu J-Y, Zhou T, Efros AA. Image-to-image translation with conditional adversarial networks. 2017. p 1125–1134.https://doi.org/10.1109/CVPR.2017.632 [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/507-03-007