A CEST Z-spectral learning network from 3T to higher B0 field: a simulation-based preliminary study

Z-spectrum acquired under ultra-high field (> 3T) features stronger and better isolated CEST peaks than those under 3T. But from imaging aspect, 3T scanners perform better and are clinically accessible. Herein, we built a deep neural network (DNN) for predicting Z-spectrum under higher B0 from the corresponding measurement at 3T. The network was trained by 10 million Z-spectra calculated from Bloch-equation models. Simulations with various B0 shifts and noise suggested that 3T Z-spectra could be rapidly and accurately transformed to those under 7T or 9.4T. This network may help improve signal extraction and interpretation of CEST data acquired at 3T.