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  pH mapping of brain tissue by a deep neural network trained on 9.4T CEST MRI data: pH-deepCEST

Mueller, S., Glang, F., Scheffler, K., & Zaiss, M. (2020). pH mapping of brain tissue by a deep neural network trained on 9.4T CEST MRI data: pH-deepCEST. Poster presented at 2020 ISMRM & SMRT Virtual Conference & Exhibition.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0006-D8B6-9 Version Permalink: http://hdl.handle.net/21.11116/0000-0006-D8B7-8
Genre: Poster

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 Creators:
Mueller, S1, 2, Author              
Glang, F1, 2, Author              
Scheffler, K1, 2, Author              
Zaiss, M1, 2, Author              
Affiliations:
1Department High-Field Magnetic Resonance, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497796              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: The pH value is of major importance for most physiological processes and may change due to altered metabolism in pathologies. In the present work, we exploit the inherent dependency of CEST MR data on pH with a new approach: train neural networks to map voxel-by-voxel from multi-B1+ CEST spectra to pH value. Measurements were performed in homogenate of pig brain tissue at 9.4T ultra high field. Prediction of absolute pH values was possible and predictions were stable against inhomogeneity in B1+. We hope this proof of concept might be a first small step towards high-resolution 3D pH maps in vivo.

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 Dates: 2020-08
 Publication Status: Published online
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Title: 2020 ISMRM & SMRT Virtual Conference & Exhibition
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Start-/End Date: 2020-08-08 - 2020-08-14

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Title: 2020 ISMRM & SMRT Virtual Conference & Exhibition
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 3130 Start / End Page: - Identifier: -