Abstract #3130

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

Sebastian Mueller¹, Felix Glang¹, Klaus Scheffler^1,2, and Moritz Zaiss^1,3

¹High-field Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, ²Department of Biomedical Magnetic Resonance, Eberhard Karls University Tuebingen, Tuebingen, Germany, ³Department of Neuroradiology, University Hospital Erlangen, Erlangen, Germany

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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