CEST Imaging of the Abdomen with Neural Network Fitting

Abstract

Chemical exchange saturation transfer (CEST) imaging shows great potential in clinical applications. However, CEST imaging is challenging in abdomen due to the large B0 shift. Meanwhile, the nuclear Overhauser enhancement (NOE) effect contaminates amide proton transfer (APT) image when using the conventional asymmetry analysis. In this paper, a CEST post-processing approach based on neural network fitting was proposed. Through recognizing the characteristics of acquired Z-spectrum, the background reference Z-spectrum and the B0offset were obtained and used to correct the acquired Z-spectrum. The APT effect and NOE effect could be calculated by subtracting the background reference Z-spectrum from the acquired Z-spectrum. The proposed CEST post-processing approach was validated by the egg white imaging and the abdomen imaging on four healthy volunteers.

Keywords

• magnetic resonance imaging (mri)
• chemical exchange saturation transfer (cest)
• amide proton transfer (apt)
• nuclear overhauser enhancement (noe)
• neural network