569-05-002 ISMRM Abstract

Multi-center Validation of Plug'n Play 3D MRSI at 7 T Using an Online Reconstruction: A Song of ICE and FIRE

Primary: Contrast Mechanisms - Spectroscopy

Secondary: Acquisition & Reconstruction - Image Reconstruction: AI

569-05-002 · Spectroscopy and Spectroscopic Imaging: Methods · Wednesday, 13 May, 4:00 PM–4:55 PM · Digital Posters Row J

Keywords: Image Reconstruction MRSI Deep-learning-based image reconstruction Spectral quantification Online Reconstruction

Accepted

Bernhard Strasser ¹, Korbinian Eckstein¹, Lukas Hingerl¹, Aaron P Osburg¹, Hauke Fischer¹, Paul Weiser^2,3,4, Ekaterina Sazonova⁵, Antoine Klauser⁶, Ovidiu C Andronesi^2,3, Yan Li⁷, Jing Liu⁷, Amirmohammad Shamaei⁸, Barbara Dymerska⁹, Martina Callaghan⁹, Zeinab Eftekhari^10,11, Thomas B Shaw^11,12, Markus Barth^11,12, Stanislav Motyka^1,4,13, Gilbert Hangel^1,4,13, Wolfgang Bogner^1,4,13

¹High-field MR Center, Vienna, Austria

²Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, United States of America

³Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, United States of America

⁴Medical University of Vienna, Vienna, Austria

⁵Department of Electrical Engineering and Information Technology, Technical University of Vienna, Vienna, Austria

⁶Swiss Innovation Hub, Siemens Healthineers International AG, Lausanne, Switzerland

⁷Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, United States of America

⁸Department of Electrical and Software Engineering, University of Calgary, Calgary, Canada

⁹Functional Imaging Laboratory, Department of Imaging Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom

¹⁰Department of Nuclear Medicine, Royal Brisbane and Women's Hospital, Brisbane, Australia

¹¹School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia

¹²Centre for Advanced Imaging at the Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia

¹³Christian Doppler Laboratory for MR Imaging Biomarkers (BIOMAK), Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria

Presenting Author: Bernhard Strasser

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References

1. Hingerl et al. Clinical High-Resolution 3D-MR Spectroscopic Imaging of the Human Brain at 7 T. Investigative Radiology 55(4):p 239-248, April 2020. doi: 10.1097/RLI.0000000000000626 [doi]

2. Weiser et al. WALINET: A water and lipid identification convolutional neural network for nuisance signal removal in 1H MR spectroscopic imaging. Magn Reson Med. 2025;93:1430–1442. doi: https://doi.org/10.1002/mrm.30402. [doi]

3. Shamaei et al. PHIVE: A Physics-Informed Variational Encoder Enables Rapid Spectral Fitting of Brain Metabolite Mapping at 7T. medRxiv [preprint]. doi: 10.1101/2025.01.02.25319930. [doi]

4. Moser et al. Non-Cartesian GRAPPA and coil combination using interleaved calibration data – application to concentric-ring MRSI of the human brain at 7T. Magn Reson Med. 2019;82:1587–1603. doi: 10.1002/mrm.27822. [doi]

Cite this abstract

http://echo.ismrm.org/p/ISMRM2026/569-05-002