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Papageorgakis C, Firippi E, Gy B, Boutelier T, Khormi I, Al-Iedani O, Lechner-Scott J, Ramadan S, Liebig P, Schuenke P, Zaiss M, Casagranda S. CEST 2022 - Fast WASABI post-processing: Access to rapid B 0 and B 1 correction in clinical routine for CEST MRI. Magn Reson Imaging 2023:S0730-725X(23)00097-8. [PMID: 37321377 DOI: 10.1016/j.mri.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 03/20/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
CEST MRI methods, such as APT and NOE imaging reveal biomarkers with significant diagnostic potential due to their ability to access molecular tissue information. Regardless of the technique used, CEST MRI data are affected by static magnetic B0 and radiofrequency B1 field inhomogeneities that degrade their contrast. For this reason, the correction of B0 field-induced artefacts is essential, whereas accounting for B1 field inhomogeneities have shown significant improvements in image readability. In a previous work, an MRI protocol called WASABI was presented, which can map simultaneously B0 and B1 field inhomogeneities, while maintaining the same sequence and readout types as used for CEST MRI. Despite the highly satisfactory quality of B0 and B1 maps computed from the WASABI data, the post-processing method is based on an exhaustive search of a four-parameter space and an additional four-parameter non-linear model fitting step. This leads to long post-processing times that are prohibitive in clinical practice. This work provides a new method for fast post-processing of WASABI data with outstanding acceleration of the parameter estimation procedure and without compromising its stability. The resulting computational acceleration makes the WASABI technique suitable for clinical use. The stability of the method is demonstrated on phantom data and clinical 3 Tesla in vivo data.
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Affiliation(s)
| | - Eleni Firippi
- Department of Research & Innovation, Olea Medical, La Ciotat, France.
| | - Benoit Gy
- Department of Research & Innovation, Olea Medical, La Ciotat, France.
| | - Timothé Boutelier
- Department of Research & Innovation, Olea Medical, La Ciotat, France.
| | - Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, Newcastle, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia.
| | - Oun Al-Iedani
- Hunter Medical Research Institute, Newcastle, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, Newcastle, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia.
| | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, Newcastle, Australia.
| | | | - Patrick Schuenke
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Berlin, Germany.
| | - Moritz Zaiss
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
| | - Stefano Casagranda
- Department of R&D Advanced Applications, Olea Medical, La Ciotat, France.
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