基于神经网络拟合的腹部化学交换饱和转移成像
收稿日期: 2021-03-30
网络出版日期: 2021-05-16
基金资助
华东师范大学“幸福之花”基金资助项目
CEST Imaging of the Abdomen with Neural Network Fitting
Received date: 2021-03-30
Online published: 2021-05-16
磁共振成像（Magnetic Resonance Imaging，MRI）化学交换饱和转移（Chemical Exchange Saturation Transfer，CEST）技术在临床诊断中展现了巨大的潜力，但在腹部成像中受到主磁场偏移量大的挑战，而且利用传统的非对称性分析法得到的酰胺质子转移（Amide Proton Transfer，APT）成像对比度受到核奥氏增强（Nuclear Overhauser Enhancement，NOE）效应的干扰.本文提出了一种基于神经网络拟合的CEST后处理方法，对每个像素采集得到的Z谱特征进行识别，不需要额外序列扫描即可得到背景参考Z谱与主磁场偏移量，用以校正和获得理想的Z谱，并进一步分离得到源自APT效应与NOE效应的信号.鸡蛋清和健康志愿者腹部成像结果显示，本文提出的基于神经网络的CEST后处理方法效果较好.
关键词： 磁共振成像（MRI）; 化学交换饱和转移（CEST）; 酰胺质子转移（APT）; 核奥氏增强（NOE）; 神经网络
王志超 , 张记磊 , 赵羽 , 华婷 , 汤光宇 , 李建奇 . 基于神经网络拟合的腹部化学交换饱和转移成像[J]. 波谱学杂志, 2022 , 39(1) : 33 -42 . DOI: 10.11938/cjmr20212903
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.
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