Liu Yixuan, Li Jie, Ji Hongfei, Zhuang Jie
Shanghai Yangzhi Rehabilitation Hospital Shanghai Sunshine Rehabilitation Center, College of Electronics and Information Engineering, Tongji University, Shanghai, China.
School of Psychology, Shanghai University of Sport, Shanghai, China.
Front Neurosci. 2022 May 3;16:838157. doi: 10.3389/fnins.2022.838157. eCollection 2022.
Chemical exchange saturation transfer (CEST) is one of the molecular magnetic resonance imaging (MRI) techniques that indirectly measures low-concentration metabolite or free protein signals that are difficult to detect by conventional MRI techniques. We applied CEST to Alzheimer's disease (AD) and analyzed both region of interest (ROI) and pixel dimensions. Through the analysis of the ROI dimension, we found that the content of glutamate in the brains of AD mice was higher than that of normal mice of the same age. In the pixel-dimensional analysis, we obtained a map of the distribution of glutamate in the mouse brain. According to the experimental data of this study, we designed an algorithm framework based on data migration and used Resnet neural network to classify the glutamate distribution images of AD mice, with an accuracy rate of 75.6%. We evaluate the possibility of glutamate imaging as a biomarker for AD detection for the first time, with important implications for the detection and treatment of AD.
化学交换饱和转移（CEST）是分子磁共振成像（MRI）技术之一，它间接测量传统MRI技术难以检测到的低浓度代谢物或游离蛋白质信号。我们将CEST应用于阿尔茨海默病（AD），并分析了感兴趣区域（ROI）和像素维度。通过对ROI维度的分析，我们发现AD小鼠大脑中的谷氨酸含量高于同年龄正常小鼠。在像素维度分析中，我们获得了小鼠大脑中谷氨酸分布的图谱。根据本研究的实验数据，我们设计了一种基于数据迁移的算法框架，并使用Resnet神经网络对AD小鼠的谷氨酸分布图像进行分类，准确率为75.6%。我们首次评估了谷氨酸成像作为AD检测生物标志物的可能性，这对AD的检测和治疗具有重要意义。
